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© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., [EN] This paper gathers experiences and results from several demonstration projects in the field of grid integration of electric vehicles. The analyzed research projects are selected among research institutes and universities that are part of the European Energy Research Alliance Joint Program on Smart Grids. The paper provides an overview of recent trends in the field of electric vehicles integration issues and then dives deeper into specific aspects of each project. Twelve research projects are presented in general terms, while detailed information can be retrieved from the references and the websites. Although each project has its focus, a common element that can be devised is that the charging process can be technically controlled based on different interests and algorithms, but its role in the market is still under development. Particular focus is always given to the behavior of the user, which ultimately determines the possible level of flexibility that the electric vehicle can provide to the grid.

[EN] Generalized Spatial Modulation (GSM) is a trans-mission technique used in wireless communications in which only part of the transmitter antennas are activated during each time signaling period. A low complexity Sphere Decoding (SD) algorithm to achieve maximum likelihood (ML) detection has recently been proposed by using subproblem partitions, sorting preprocessing and radius updating. However, the ordering method has a serious limitation when the number of activated antennas is equal to the number of received antennas. Therefore, alternative sorting methods are studied in the present paper. In addition, the computational cost of the ML algorithm can be high when the system sizes increases. In this paper a suboptimal version is proposed where only the first L SD subproblems are carried out. The results show that the proposed algorithm achieves near optimal performance at lower computational cost than ML algorithms.

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., [EN] This paper gathers experiences and results from several demonstration projects in the field of grid integration of electric vehicles. The analyzed research projects are selected among research institutes and universities that are part of the European Energy Research Alliance Joint Program on Smart Grids. The paper provides an overview of recent trends in the field of electric vehicles integration issues and then dives deeper into specific aspects of each project. Twelve research projects are presented in general terms, while detailed information can be retrieved from the references and the websites. Although each project has its focus, a common element that can be devised is that the charging process can be technically controlled based on different interests and algorithms, but its role in the market is still under development. Particular focus is always given to the behavior of the user, which ultimately determines the possible level of flexibility that the electric vehicle can provide to the grid.

[EN] Generalized Spatial Modulation (GSM) is a trans-mission technique used in wireless communications in which only part of the transmitter antennas are activated during each time signaling period. A low complexity Sphere Decoding (SD) algorithm to achieve maximum likelihood (ML) detection has recently been proposed by using subproblem partitions, sorting preprocessing and radius updating. However, the ordering method has a serious limitation when the number of activated antennas is equal to the number of received antennas. Therefore, alternative sorting methods are studied in the present paper. In addition, the computational cost of the ML algorithm can be high when the system sizes increases. In this paper a suboptimal version is proposed where only the first L SD subproblems are carried out. The results show that the proposed algorithm achieves near optimal performance at lower computational cost than ML algorithms.

[EN] True, the scientific community still has a lot to investigate on how to get 5G to have a satisfactory journey in the development of standards. However, it is now that we must begin to glimpse the future of mobile technology, it is time to imagine what 6G will be. This paper offers a realistic view of what this technology might be. In this case, the experience of one of the most important groups in Europe dedicated to the mobile communication systems design, the iTEAM research institute, is combined with the one of the world's leading manufacturers of femtocells, Casa Systems. From the belief that the deployment of SG will come from homes, this paper analyzes the new use cases of the 6G, as well as the three technological pillars of this future technology.

[EN] Generalized Spatial Modulation (GSM) is a trans-mission technique used in wireless communications in which only part of the transmitter antennas are activated during each time signaling period. A low complexity Sphere Decoding (SD) algorithm to achieve maximum likelihood (ML) detection has recently been proposed by using subproblem partitions, sorting preprocessing and radius updating. However, the ordering method has a serious limitation when the number of activated antennas is equal to the number of received antennas. Therefore, alternative sorting methods are studied in the present paper. In addition, the computational cost of the ML algorithm can be high when the system sizes increases. In this paper a suboptimal version is proposed where only the first L SD subproblems are carried out. The results show that the proposed algorithm achieves near optimal performance at lower computational cost than ML algorithms.

[EN] True, the scientific community still has a lot to investigate on how to get 5G to have a satisfactory journey in the development of standards. However, it is now that we must begin to glimpse the future of mobile technology, it is time to imagine what 6G will be. This paper offers a realistic view of what this technology might be. In this case, the experience of one of the most important groups in Europe dedicated to the mobile communication systems design, the iTEAM research institute, is combined with the one of the world's leading manufacturers of femtocells, Casa Systems. From the belief that the deployment of SG will come from homes, this paper analyzes the new use cases of the 6G, as well as the three technological pillars of this future technology.

[EN] True, the scientific community still has a lot to investigate on how to get 5G to have a satisfactory journey in the development of standards. However, it is now that we must begin to glimpse the future of mobile technology, it is time to imagine what 6G will be. This paper offers a realistic view of what this technology might be. In this case, the experience of one of the most important groups in Europe dedicated to the mobile communication systems design, the iTEAM research institute, is combined with the one of the world's leading manufacturers of femtocells, Casa Systems. From the belief that the deployment of SG will come from homes, this paper analyzes the new use cases of the 6G, as well as the three technological pillars of this future technology.

[EN] The objective of this paper is to demonstrate how inline combline filters can be designed to implement transmission zeros in the filter transfer function. Following the design procedure described in this paper, up to N-1 transmission zeros can be implemented with a filter of order N. In addition to theory, comparisons between simulated and measured results are also presented. The agreement between simulation and measurements is indeed good, thereby fully validating the new combline filter topology, and the proposed design technique.

[EN] The objective of this paper is to demonstrate how inline combline filters can be designed to implement transmission zeros in the filter transfer function. Following the design procedure described in this paper, up to N-1 transmission zeros can be implemented with a filter of order N. In addition to theory, comparisons between simulated and measured results are also presented. The agreement between simulation and measurements is indeed good, thereby fully validating the new combline filter topology, and the proposed design technique.

[EN] Electric Vehicles (EVs) have gained increased attention courtesy their potential to mitigate environmental issues associated with transportation. To integrate EVs in transportation and power networks, it is essential to properly perform the siting and sizing of charging stations. In particular, this task is more challenging for users that have more rigid schedules such as taxi drivers. This paper proposes a coordinated siting and sizing methodology for electric taxi (ET) charging stations considering both transportation and power system constraints. The case of Quito, Ecuador has been analyzed. The results indicate the optimal placement of the ET charging stations and the number of charging spots to be installed.

[EN] In this paper, we present a self-training-based framework for glaucoma grading using OCT B-scans under the presence of domain shift. Particularly, the proposed two-step learning methodology resorts to pseudo-labels generated during the first step to augment the training dataset on the target domain, which is then used to train the final target model. This allows transferring knowledge-domain from the unlabeled data. Additionally, we propose a novel glaucoma-specific backbone which introduces residual and attention modules via skip-connections to refine the embedding features of the latent space. By doing this, our model is capable of improving state-of-the-art from a quantitative and interpretability perspective. The reported results demonstrate that the proposed learning strategy can boost the performance of the model on the target dataset without incurring in additional annotation steps, by using only labels from the source examples. Our model consistently outperforms the baseline by 1¿3% across different metrics and bridges the gap with respect to training the model on the labeled target data.

[Otros] Neuropsychological assessment has been traditionally made through paper-and-pencil batteries which usually are time-consuming, decontextualized, and nonecological. These abilities play a critical role in education since they are very related to learning capacity, academic achievement, social functioning, as well as the inhibition of maladaptive behaviors. Meanwhile, serious games are being used in education and psychology to achieve assessments without these limitations, including neuropsychological assessments. While traditional tests can be analyzed with classical statistics, a large number of variables can be extracted from serious games, the analysis of which can be more complex. Machine learning can handle this large amount of information and find patterns that allow us to recognize behaviors. This study aimed to investigate whether machine learning could be used to improve predictive validity in applying a serious game for neuropsychological assessment. Results were based on 60 subjects, including 42 cognitive activities. The validation process showed best results on attention, memory, planning, and cognitive flexibility, achieving accuracies higher or equal to 0.8 and Cohen¿s Kappas higher than 0.55, which implies that the Virtual Serious Game could be a valid tool to perform a neuropsychological evaluation along with traditional tests.

[EN] Design education and practice are continuously evolving. Educational institutions must include intellectual complexities and new curriculum to support good design education. The design education future emerges multidisciplinary knowledge, teaching innovation and employment necessities. This paper describes a methodology centered in product validation with industrial design students. Focusing on discovering the student experience during the project execution, in addition to observing closely the female design student's perception on the methodology and process developed. The academic project was the design of a novel tool board. The students developed the proposed project in a period of eight weeks. Sixteen students participated as a sample of this research. The methodology consisted of eight phases that spanned from project brief to project conclusion, introducing two phases focused on validation exercises for the elements created to reach the solution of the tool board. During the end of the two evaluation phases, two surveys were applied asking for information on his previous experience during his design education and three elements that assessment the design methodology implementation: utility, novelty, and relevance. Using multiple choice and Likert scale answers the students answered the surveys. The survey's findings revealed relevant information on the project implementation focused on evaluation phases during the product design. The results revealed how students reflected on their previous experience developing projects, and how the design tool board integrate important phases like validation. Also, the students evaluated with a positive value the utility, novelty, and relevance of the developed project. However, the most important finding was the female perception comparing male students. The female assessment of novelty and relevance increased during project implementation, highlighting novelty as a perceived element to a greater range than men. This

[EN] In this paper, we present a self-training-based framework for glaucoma grading using OCT B-scans under the presence of domain shift. Particularly, the proposed two-step learning methodology resorts to pseudo-labels generated during the first step to augment the training dataset on the target domain, which is then used to train the final target model. This allows transferring knowledge-domain from the unlabeled data. Additionally, we propose a novel glaucoma-specific backbone which introduces residual and attention modules via skip-connections to refine the embedding features of the latent space. By doing this, our model is capable of improving state-of-the-art from a quantitative and interpretability perspective. The reported results demonstrate that the proposed learning strategy can boost the performance of the model on the target dataset without incurring in additional annotation steps, by using only labels from the source examples. Our model consistently outperforms the baseline by 1¿3% across different metrics and bridges the gap with respect to training the model on the labeled target data.

[EN] Design education and practice are continuously evolving. Educational institutions must include intellectual complexities and new curriculum to support good design education. The design education future emerges multidisciplinary knowledge, teaching innovation and employment necessities. This paper describes a methodology centered in product validation with industrial design students. Focusing on discovering the student experience during the project execution, in addition to observing closely the female design student's perception on the methodology and process developed. The academic project was the design of a novel tool board. The students developed the proposed project in a period of eight weeks. Sixteen students participated as a sample of this research. The methodology consisted of eight phases that spanned from project brief to project conclusion, introducing two phases focused on validation exercises for the elements created to reach the solution of the tool board. During the end of the two evaluation phases, two surveys were applied asking for information on his previous experience during his design education and three elements that assessment the design methodology implementation: utility, novelty, and relevance. Using multiple choice and Likert scale answers the students answered the surveys. The survey's findings revealed relevant information on the project implementation focused on evaluation phases during the product design. The results revealed how students reflected on their previous experience developing projects, and how the design tool board integrate important phases like validation. Also, the students evaluated with a positive value the utility, novelty, and relevance of the developed project. However, the most important finding was the female perception comparing male students. The female assessment of novelty and relevance increased during project implementation, highlighting novelty as a perceived element to a greater range than men. This

[Otros] Neuropsychological assessment has been traditionally made through paper-and-pencil batteries which usually are time-consuming, decontextualized, and nonecological. These abilities play a critical role in education since they are very related to learning capacity, academic achievement, social functioning, as well as the inhibition of maladaptive behaviors. Meanwhile, serious games are being used in education and psychology to achieve assessments without these limitations, including neuropsychological assessments. While traditional tests can be analyzed with classical statistics, a large number of variables can be extracted from serious games, the analysis of which can be more complex. Machine learning can handle this large amount of information and find patterns that allow us to recognize behaviors. This study aimed to investigate whether machine learning could be used to improve predictive validity in applying a serious game for neuropsychological assessment. Results were based on 60 subjects, including 42 cognitive activities. The validation process showed best results on attention, memory, planning, and cognitive flexibility, achieving accuracies higher or equal to 0.8 and Cohen¿s Kappas higher than 0.55, which implies that the Virtual Serious Game could be a valid tool to perform a neuropsychological evaluation along with traditional tests.

© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., Handwritten text recognition of Bengali is a difficult task because of complex character shapes due to the presence of modified/compound characters as well as zone-wise writing styles of different individuals. Most of the research published so far on Bengali handwriting recognition deals with either isolated character recognition or isolated word recognition, and just a few papers have researched on recognition of continuous handwritten Bengali. In this paper we present a research on continuous handwritten Bengali. We follow a classical line-based recognition approach with a system based on hidden Markov models and n-gram language models. These models are trained with automatic methods from annotated data. We research both on the maximum likelihood approach and the minimum error phone approach for training the optical models. We also research on the use of word-based language models and characterbased language models. This last approach allow us to deal with the out-of-vocabulary word problem in the test when the training set is of limited size. From the experiments we obtained encouraging results.

© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., Handwritten text recognition of Bengali is a difficult task because of complex character shapes due to the presence of modified/compound characters as well as zone-wise writing styles of different individuals. Most of the research published so far on Bengali handwriting recognition deals with either isolated character recognition or isolated word recognition, and just a few papers have researched on recognition of continuous handwritten Bengali. In this paper we present a research on continuous handwritten Bengali. We follow a classical line-based recognition approach with a system based on hidden Markov models and n-gram language models. These models are trained with automatic methods from annotated data. We research both on the maximum likelihood approach and the minimum error phone approach for training the optical models. We also research on the use of word-based language models and characterbased language models. This last approach allow us to deal with the out-of-vocabulary word problem in the test when the training set is of limited size. From the experiments we obtained encouraging results.

© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., Handwritten text recognition of Bengali is a difficult task because of complex character shapes due to the presence of modified/compound characters as well as zone-wise writing styles of different individuals. Most of the research published so far on Bengali handwriting recognition deals with either isolated character recognition or isolated word recognition, and just a few papers have researched on recognition of continuous handwritten Bengali. In this paper we present a research on continuous handwritten Bengali. We follow a classical line-based recognition approach with a system based on hidden Markov models and n-gram language models. These models are trained with automatic methods from annotated data. We research both on the maximum likelihood approach and the minimum error phone approach for training the optical models. We also research on the use of word-based language models and characterbased language models. This last approach allow us to deal with the out-of-vocabulary word problem in the test when the training set is of limited size. From the experiments we obtained encouraging results.

© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., This paper shows part of the work carried out to develop parallel versions of the SLICOT routines for model reduction of stable systems. In particular, the routines that have been parallelised are those based on the solution of Lyapunov equations. The goal is to be able to work with larger unreduced models and also to obtain better performance in the reduction process. New routines have been developed using standard libraries to improve portability and efficiency. A preliminary version was released previously by the authors, which achieved high performance. However, accuracy improvements have been necessary in order to make the new routines similar to the sequential ones in this aspect. Routines presented in this paper preserve good performance obtained by the previous parallel implementation while maintaining high accuracy of sequential SLICOT routines.

© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., This paper describes the research work in the context of the CLUVIEM project towards achieving migrat- able, self-managed virtual elastic clusters on hybrid Cloud infrastructures. These virtual clusters can span across on- premises and public Cloud infrastructures thus leveraging hybrid Cloud platforms. They are elastic since working nodes are automatically provisioned and relinquished to dynamically adapt the capacity of the virtual cluster (in terms of number of nodes) according to the current workload. They are self- managed since the elasticity rules are managed via the head node without requiring any external software entity for mon- itoring and deciding when to scale in and out. Finally, they are migratable since they consider both application migration, via application checkpointing, and infrastructure migration, by cloning infrastructures across multi-Clouds. These features introduce unprecedented flexibility for cost-effective cluster- based computing with minimal impact for cluster users. The paper summarises the current state of developments and future roads to achieve this vision.

© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., This paper shows part of the work carried out to develop parallel versions of the SLICOT routines for model reduction of stable systems. In particular, the routines that have been parallelised are those based on the solution of Lyapunov equations. The goal is to be able to work with larger unreduced models and also to obtain better performance in the reduction process. New routines have been developed using standard libraries to improve portability and efficiency. A preliminary version was released previously by the authors, which achieved high performance. However, accuracy improvements have been necessary in order to make the new routines similar to the sequential ones in this aspect. Routines presented in this paper preserve good performance obtained by the previous parallel implementation while maintaining high accuracy of sequential SLICOT routines.

© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., This paper describes the research work in the context of the CLUVIEM project towards achieving migrat- able, self-managed virtual elastic clusters on hybrid Cloud infrastructures. These virtual clusters can span across on- premises and public Cloud infrastructures thus leveraging hybrid Cloud platforms. They are elastic since working nodes are automatically provisioned and relinquished to dynamically adapt the capacity of the virtual cluster (in terms of number of nodes) according to the current workload. They are self- managed since the elasticity rules are managed via the head node without requiring any external software entity for mon- itoring and deciding when to scale in and out. Finally, they are migratable since they consider both application migration, via application checkpointing, and infrastructure migration, by cloning infrastructures across multi-Clouds. These features introduce unprecedented flexibility for cost-effective cluster- based computing with minimal impact for cluster users. The paper summarises the current state of developments and future roads to achieve this vision.

[EN] This paper presents a compact multimode antenna for GPS applications, where multiple modes are excited in order to achieve radiation pattern diversity. Based on the Characteristic Mode Analysis of a rectangular plate of 80 mm x 54 mm, a practical implementation of the excitation network is presented.

[EN] Multi-element antenna beam steering in free-licence higher frequency bands is one of the crucial features of 5G networks enabling better tracking of the users. In this paper, we present an experimental microwave photonics transmission system operating at 26 GHz where beamforming is fully realized in the optical domain. The system is designed to be deployed as a part of the mobile fronthaul network with an optical fiber span of 15 km. As a proof of concept, a planar 3-element antenna array has been developed and radiation patterns were measured in an anechoic chamber with high agreement between experimental and simulation results

[EN] This paper investigates integrated radio-over-fiber and radio-over-free-space optic links in a passive optical network architecture for ubiquitous wireless coverage. Two optical millimeter-wave generation techniques, namely optical heterodyning and optical modulator-based up-conversion are used. In the first configuration, simulation results are achieved for transmission of 20-40 Gb/s 4-PAM over the 60 GHz heterodyned hybrid link. In the second configuration, transmission of 20 MHz 4-QAM over the up-converted 25 GHz hybrid system is examined. System performance evaluation and practical feasibility is carried out in terms of the received optical powers, bit error rates, eye diagrams, error vector magnitude and constellation diagrams.

[EN] The growth of the Internet worldwide has been fuelled by the development of the National Research and Education Networks (NRENs), i.e., networks of academic and educational institutions. In Africa the establishment of NRENs is more recent. In this paper we analyse the readiness of African NRENs to be part of The Things Network (TTN), a network of IoT gateways that has fostered the growth of IoT in Europe by adopting a community network model. We analyse RTT and packet loss toward the nearest TTN network server, in African countries where RIPE Atlas (RIPE - Réseaux IP Européens, French for ¿European IP Networks) probes are hosted both in academic and commercial networks. Our conclusion is that NRENs and commercial ISPs are on an equal foot in hosting TTN gateways in most countries we considered.

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., [EN] This paper investigates an optical transmission architecture of a passive optical network (PON), which is compatible with the millimeter-wave radio-over-fiber and free-space optics systems (RoF-FSO) under weak-to-strong atmospheric turbulence (AT) regimes to enable seamless connectivity as part of next-generation broadband wireless access networks. We first analyze and evaluate in simulation the transmission performance of the integrated system at 40 GHz for 10 Gb/s N-pulse amplitude modulation (N-PAM) with N = 2, 4. Link performance shows that, 4-PAM outperforms 2-PAM in terms of tolerance to the combined impairment of fiber chromatic dispersion and AT. We then experimentally demonstrate the proof-of-concept integrated RoF-FSO-PON at 25 GHz using 20 MHz M-quadrature amplitude modulation (M-QAM) signals with M = 4, 16, 64. We show that, for QAM with a higher-order M, the link performance is being more affected by the combined impairments.

[EN] The Internet of Things (IoT) enables to connect the physical world to digital business processes (BP). By using the IoT, a BP can, e.g.: 1) take into account real-world data to take more informed business decisions, and 2) automate and/or improve BP tasks. To achieve these benefits, the integration of IoT and BPs needs to be successful. The first step to this end is to support the modeling of IoT-enhanced BPs. Although numerous researchers have studied this subject, it is unclear what is the current state of the art in terms of current modeling solutions and gaps. In this work, we carry out a Systematic Mapping Study (SMS) to find out how current solutions are modelling IoT into business processes. After studying 600 papers, we identified and analyzed in depth a total of 36 different solutions. In addition, we report on some important issues that should be addressed in the near future, such as, for instance the lack of standardization.

[EN] The use of Convolutional Neural Networks (CNN) has experienced a huge rise over the last recent years and its popularity has increased exponentially, mainly due to its application both for image recognition and certain applications related to artificial intelligence. The new applications of CNN request computing demands that are difficult to address by conventional processors. As a consequence, accelerators ¿both prototypes and commercial products¿ focusing on CNN computation have been proposed. Among these accelerators, those based on systolic arrays have acquired a special relevance; some examples are the Google¿s TPU and Eyeriss. Current research has focused on regular squared systolic arrays and most existing work assumes that there is enough memory bandwidth to feed the systolic array with input data. In this paper we explore the design of non-squared systolic arrays and address the impact of the memory bandwidth from a performance perspective. This work makes two main contributions. First, we found that some workloads with non-squared arrays achieve similar performance to systolic arrays twice as large, which can translate in area and/or energy benefits. Second, we present a performance comparison varying the main memory bandwidth for current DRAM devices. The analysis reveals that main memory bandwidth has a great impact on performance and that the decision of which technology use is key for the system performance. For the 64x64 array size it is necessary to use HBM2 memory to avoid the slowdown that would introduce cheaper technologies (e.g. DDR5 and DDR4).

[EN] The importance of Millimeter Waves (mmW) band for the Fifth Generation (5G) of mobile and wireless communications has motivated a lot of work in mmW channel modelling. In this paper, we assess the use of the light physics modelling of a game engine to calculate the propagation losses at mmW band in an indoor scenario. With that aim, we propose a model that we refer to as Light Intensity Model (LIM), in which a detailed 3D scenario is created in a game engine, radio transmitters and receivers are replaced by light sources and detectors, and the received light intensities are translated to received radio signal power through a translation function which is the key of the model. The results obtained corroborate the validity of the assessed approach to model propagation losses in indoor scenarios

[EN] This paper presents a compact multimode antenna for GPS applications, where multiple modes are excited in order to achieve radiation pattern diversity. Based on the Characteristic Mode Analysis of a rectangular plate of 80 mm x 54 mm, a practical implementation of the excitation network is presented.

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., [EN] This paper investigates an optical transmission architecture of a passive optical network (PON), which is compatible with the millimeter-wave radio-over-fiber and free-space optics systems (RoF-FSO) under weak-to-strong atmospheric turbulence (AT) regimes to enable seamless connectivity as part of next-generation broadband wireless access networks. We first analyze and evaluate in simulation the transmission performance of the integrated system at 40 GHz for 10 Gb/s N-pulse amplitude modulation (N-PAM) with N = 2, 4. Link performance shows that, 4-PAM outperforms 2-PAM in terms of tolerance to the combined impairment of fiber chromatic dispersion and AT. We then experimentally demonstrate the proof-of-concept integrated RoF-FSO-PON at 25 GHz using 20 MHz M-quadrature amplitude modulation (M-QAM) signals with M = 4, 16, 64. We show that, for QAM with a higher-order M, the link performance is being more affected by the combined impairments.

[EN] This paper investigates integrated radio-over-fiber and radio-over-free-space optic links in a passive optical network architecture for ubiquitous wireless coverage. Two optical millimeter-wave generation techniques, namely optical heterodyning and optical modulator-based up-conversion are used. In the first configuration, simulation results are achieved for transmission of 20-40 Gb/s 4-PAM over the 60 GHz heterodyned hybrid link. In the second configuration, transmission of 20 MHz 4-QAM over the up-converted 25 GHz hybrid system is examined. System performance evaluation and practical feasibility is carried out in terms of the received optical powers, bit error rates, eye diagrams, error vector magnitude and constellation diagrams.

[EN] The Internet of Things (IoT) enables to connect the physical world to digital business processes (BP). By using the IoT, a BP can, e.g.: 1) take into account real-world data to take more informed business decisions, and 2) automate and/or improve BP tasks. To achieve these benefits, the integration of IoT and BPs needs to be successful. The first step to this end is to support the modeling of IoT-enhanced BPs. Although numerous researchers have studied this subject, it is unclear what is the current state of the art in terms of current modeling solutions and gaps. In this work, we carry out a Systematic Mapping Study (SMS) to find out how current solutions are modelling IoT into business processes. After studying 600 papers, we identified and analyzed in depth a total of 36 different solutions. In addition, we report on some important issues that should be addressed in the near future, such as, for instance the lack of standardization.

[EN] The growth of the Internet worldwide has been fuelled by the development of the National Research and Education Networks (NRENs), i.e., networks of academic and educational institutions. In Africa the establishment of NRENs is more recent. In this paper we analyse the readiness of African NRENs to be part of The Things Network (TTN), a network of IoT gateways that has fostered the growth of IoT in Europe by adopting a community network model. We analyse RTT and packet loss toward the nearest TTN network server, in African countries where RIPE Atlas (RIPE - Réseaux IP Européens, French for ¿European IP Networks) probes are hosted both in academic and commercial networks. Our conclusion is that NRENs and commercial ISPs are on an equal foot in hosting TTN gateways in most countries we considered.

[EN] Multi-element antenna beam steering in free-licence higher frequency bands is one of the crucial features of 5G networks enabling better tracking of the users. In this paper, we present an experimental microwave photonics transmission system operating at 26 GHz where beamforming is fully realized in the optical domain. The system is designed to be deployed as a part of the mobile fronthaul network with an optical fiber span of 15 km. As a proof of concept, a planar 3-element antenna array has been developed and radiation patterns were measured in an anechoic chamber with high agreement between experimental and simulation results

[EN] A dual circularly-polarized slot-array antenna fed by a Groove Gap Waveguide (GGW) and operating in the KaBand is presented in this paper. A simple mechanism is proposed to switch the polarization, from RHCP to LHCP, and viceversa. The lid of the antenna has two pieces: one fixed and one sliding. The fixed piece hosts T-shaped slots, and the sliding block is in charge of adjusting the offset of the perpendicular grooves with respect to the longitudinal slots. Preliminary results show an axial ratio below 1.5 dB for both, RHCP and LHCP, within a bandwidth of 1 GHz centered at 30 GHz.

[EN] This contribution presents a low-loss mechanical phase shifter in gap-waveguide technology. The phase shifter is aimed at ground terminals for Ka-band satellite on-the-move applications. The use of the gap-waveguide technology allows to divide the device into two main blocks distributed in two levels: a lower-rotatable block, in charge of the power distribution and the phase shifting; and an upper-fixed block with the output waveguides. In this paper, the lower and upper blocks are designed using Groove-gap waveguides (GGW), and Ridge-gap waveguides, respectively, connected to each other by coupling slots. Results show a good performance within the operating frequency band in terms of the phase shift between consecutive output ports (suitable for array feeding), and the return loss level at the input port.

[EN] A T-shaped slot-array antenna fed through a Groove Gap Waveguide (GGW) is presented in this paper. The array antenna operates at 30 GHz. The way the slots are excited, along with the T-shape on its lid allows a compact single-layer architecture. A uniform linear array of 12 elements is designed to demonstrate the viability of this concept for high-efficient singlelayer slot-array antennas. Preliminary results show a frequency bandwidth of 1 GHz with input reflection coefficient better than ¿12 dB. In addition, being a full-metal antenna, the expected efficiency is high. It is worth stressing the good polarization purity achieved, being below 1.5 dB within the band of interest.

[EN] In this paper we present a new method to compute singular integrals and nearly singular integrals in the context of boundary integral equations for electromagnetism. In particular the method is well suited for integral equations of the second kind. The method consist of splitting the integral in two parts, one regular, which is computed via adaptive integration, and another singular and local (with very small support of the integrand) which is computed using asymptotic expansion. This method can be applied to any second kind integral equation arising in CEM, like MFIE, Charge-Current integral equation, Non Resonant Charge Current Integral Equation (NRCCIE),...

[EN] A preliminary numerical magnetic field study of a wireless power transfer system composed of two interconnected source loops is addressed in this paper. The key feature of this study is to propose a new configuration capable of maintaining a uniform magnetic field density between the two loops. Furthermore, it has been shown that the Theory of Characteristic Modes is a helpful tool for investigating the near field of the magnetically-coupled loops.

[EN] In this paper, a new design of a reconfigurable antenna is proposed. The antenna structure is using two PIN diodes for switching between two radiation patterns (directional and bidirectional) and a SPDT switch to achieve good impedance matching. The simulated results show a good impedance matching, with S11 below -10 dB using the SPDT switch configuration. In addition, the far-field directivity for both configurations is around 5 dB.

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., [EN] The monitoring of water level in the agriculture irrigation channels is essential to control the opening gates of these channels. In this way, WSNs (Wireless Sensor Networks) have high relevance to obtain this kind of data. In this paper, we propose a sensor to measure the depth changes in irrigation channels to control the gates opening. It is connected to an Adafruit Feather HUZZAH based on ESP8266, which allows us to build a mobile edge computing system. The developed sensor is based on two coils. Sinus-wave powers the first one, and the second is induced. The coils are winding over a polyvinyl chloride (PVC) that has high resistance for corrosion and low price. Besides, we use copper wire as a conductive metal. We test two different configurations of coils. P1 has five spires for the powered coil (PC) and ten spires for the induced coil (IC). On the other hand, P2 has 40 spires for the PC and 80 spires for the IC. The two prototypes were coiled in one layer. Then, both sensors are tested using a glass bottle where the water column increased with the target to obtain the information of the depth. In both prototypes, the difference of voltage between the maximum and minimum studied depths is more or less the same, 4.46V for P1 and 4.44V for P2. Nevertheless, during the stabilization test, the P1 showed better adaptation for the turbulences than the P2. The P1 shows an oscillation of 0.48V, where the P2 has a maximum fluctuation of 3.2V.

[EN] The use of Convolutional Neural Networks (CNN) has experienced a huge rise over the last recent years and its popularity has increased exponentially, mainly due to its application both for image recognition and certain applications related to artificial intelligence. The new applications of CNN request computing demands that are difficult to address by conventional processors. As a consequence, accelerators ¿both prototypes and commercial products¿ focusing on CNN computation have been proposed. Among these accelerators, those based on systolic arrays have acquired a special relevance; some examples are the Google¿s TPU and Eyeriss. Current research has focused on regular squared systolic arrays and most existing work assumes that there is enough memory bandwidth to feed the systolic array with input data. In this paper we explore the design of non-squared systolic arrays and address the impact of the memory bandwidth from a performance perspective. This work makes two main contributions. First, we found that some workloads with non-squared arrays achieve similar performance to systolic arrays twice as large, which can translate in area and/or energy benefits. Second, we present a performance comparison varying the main memory bandwidth for current DRAM devices. The analysis reveals that main memory bandwidth has a great impact on performance and that the decision of which technology use is key for the system performance. For the 64x64 array size it is necessary to use HBM2 memory to avoid the slowdown that would introduce cheaper technologies (e.g. DDR5 and DDR4).

[EN] The growth of the Internet worldwide has been fuelled by the development of the National Research and Education Networks (NRENs), i.e., networks of academic and educational institutions. In Africa the establishment of NRENs is more recent. In this paper we analyse the readiness of African NRENs to be part of The Things Network (TTN), a network of IoT gateways that has fostered the growth of IoT in Europe by adopting a community network model. We analyse RTT and packet loss toward the nearest TTN network server, in African countries where RIPE Atlas (RIPE - Réseaux IP Européens, French for ¿European IP Networks) probes are hosted both in academic and commercial networks. Our conclusion is that NRENs and commercial ISPs are on an equal foot in hosting TTN gateways in most countries we considered.

[EN] The Internet of Things (IoT) enables to connect the physical world to digital business processes (BP). By using the IoT, a BP can, e.g.: 1) take into account real-world data to take more informed business decisions, and 2) automate and/or improve BP tasks. To achieve these benefits, the integration of IoT and BPs needs to be successful. The first step to this end is to support the modeling of IoT-enhanced BPs. Although numerous researchers have studied this subject, it is unclear what is the current state of the art in terms of current modeling solutions and gaps. In this work, we carry out a Systematic Mapping Study (SMS) to find out how current solutions are modelling IoT into business processes. After studying 600 papers, we identified and analyzed in depth a total of 36 different solutions. In addition, we report on some important issues that should be addressed in the near future, such as, for instance the lack of standardization.

[EN] The importance of Millimeter Waves (mmW) band for the Fifth Generation (5G) of mobile and wireless communications has motivated a lot of work in mmW channel modelling. In this paper, we assess the use of the light physics modelling of a game engine to calculate the propagation losses at mmW band in an indoor scenario. With that aim, we propose a model that we refer to as Light Intensity Model (LIM), in which a detailed 3D scenario is created in a game engine, radio transmitters and receivers are replaced by light sources and detectors, and the received light intensities are translated to received radio signal power through a translation function which is the key of the model. The results obtained corroborate the validity of the assessed approach to model propagation losses in indoor scenarios

[EN] The importance of Millimeter Waves (mmW) band for the Fifth Generation (5G) of mobile and wireless communications has motivated a lot of work in mmW channel modelling. In this paper, we assess the use of the light physics modelling of a game engine to calculate the propagation losses at mmW band in an indoor scenario. With that aim, we propose a model that we refer to as Light Intensity Model (LIM), in which a detailed 3D scenario is created in a game engine, radio transmitters and receivers are replaced by light sources and detectors, and the received light intensities are translated to received radio signal power through a translation function which is the key of the model. The results obtained corroborate the validity of the assessed approach to model propagation losses in indoor scenarios

[EN] A T-shaped slot-array antenna fed through a Groove Gap Waveguide (GGW) is presented in this paper. The array antenna operates at 30 GHz. The way the slots are excited, along with the T-shape on its lid allows a compact single-layer architecture. A uniform linear array of 12 elements is designed to demonstrate the viability of this concept for high-efficient singlelayer slot-array antennas. Preliminary results show a frequency bandwidth of 1 GHz with input reflection coefficient better than ¿12 dB. In addition, being a full-metal antenna, the expected efficiency is high. It is worth stressing the good polarization purity achieved, being below 1.5 dB within the band of interest.

[EN] This contribution presents a low-loss mechanical phase shifter in gap-waveguide technology. The phase shifter is aimed at ground terminals for Ka-band satellite on-the-move applications. The use of the gap-waveguide technology allows to divide the device into two main blocks distributed in two levels: a lower-rotatable block, in charge of the power distribution and the phase shifting; and an upper-fixed block with the output waveguides. In this paper, the lower and upper blocks are designed using Groove-gap waveguides (GGW), and Ridge-gap waveguides, respectively, connected to each other by coupling slots. Results show a good performance within the operating frequency band in terms of the phase shift between consecutive output ports (suitable for array feeding), and the return loss level at the input port.

[EN] In this paper, a new design of a reconfigurable antenna is proposed. The antenna structure is using two PIN diodes for switching between two radiation patterns (directional and bidirectional) and a SPDT switch to achieve good impedance matching. The simulated results show a good impedance matching, with S11 below -10 dB using the SPDT switch configuration. In addition, the far-field directivity for both configurations is around 5 dB.

[EN] A preliminary numerical magnetic field study of a wireless power transfer system composed of two interconnected source loops is addressed in this paper. The key feature of this study is to propose a new configuration capable of maintaining a uniform magnetic field density between the two loops. Furthermore, it has been shown that the Theory of Characteristic Modes is a helpful tool for investigating the near field of the magnetically-coupled loops.

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., [EN] The monitoring of water level in the agriculture irrigation channels is essential to control the opening gates of these channels. In this way, WSNs (Wireless Sensor Networks) have high relevance to obtain this kind of data. In this paper, we propose a sensor to measure the depth changes in irrigation channels to control the gates opening. It is connected to an Adafruit Feather HUZZAH based on ESP8266, which allows us to build a mobile edge computing system. The developed sensor is based on two coils. Sinus-wave powers the first one, and the second is induced. The coils are winding over a polyvinyl chloride (PVC) that has high resistance for corrosion and low price. Besides, we use copper wire as a conductive metal. We test two different configurations of coils. P1 has five spires for the powered coil (PC) and ten spires for the induced coil (IC). On the other hand, P2 has 40 spires for the PC and 80 spires for the IC. The two prototypes were coiled in one layer. Then, both sensors are tested using a glass bottle where the water column increased with the target to obtain the information of the depth. In both prototypes, the difference of voltage between the maximum and minimum studied depths is more or less the same, 4.46V for P1 and 4.44V for P2. Nevertheless, during the stabilization test, the P1 showed better adaptation for the turbulences than the P2. The P1 shows an oscillation of 0.48V, where the P2 has a maximum fluctuation of 3.2V.

[EN] A dual circularly-polarized slot-array antenna fed by a Groove Gap Waveguide (GGW) and operating in the KaBand is presented in this paper. A simple mechanism is proposed to switch the polarization, from RHCP to LHCP, and viceversa. The lid of the antenna has two pieces: one fixed and one sliding. The fixed piece hosts T-shaped slots, and the sliding block is in charge of adjusting the offset of the perpendicular grooves with respect to the longitudinal slots. Preliminary results show an axial ratio below 1.5 dB for both, RHCP and LHCP, within a bandwidth of 1 GHz centered at 30 GHz.

[EN] Independently of any electrical contact, running electronic devices such as smartphones, smart watches, RFID tags etc., is now attainable over small and large distances through Wireless Power Transfer technology. Although, designing systems maintaining appreciable power transfer efficiency still not always achievable. Using two parallel loops, the Theory of Characteristic Modes provides physical insight into the power transfer efficiency. Furthermore, to reach straightforward maximization of the modal power transfer efficiency, the focus of this paper is analyzing the impact of the separation distance and the overlapping between the two antennas on the characteristic modes and their contribution in the total efficiency of the power. The study considers different positions and frequencies of the two parallel antennas.

[EN] In this paper we present a new method to compute singular integrals and nearly singular integrals in the context of boundary integral equations for electromagnetism. In particular the method is well suited for integral equations of the second kind. The method consist of splitting the integral in two parts, one regular, which is computed via adaptive integration, and another singular and local (with very small support of the integrand) which is computed using asymptotic expansion. This method can be applied to any second kind integral equation arising in CEM, like MFIE, Charge-Current integral equation, Non Resonant Charge Current Integral Equation (NRCCIE),...

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., [EN] The monitoring of water level in the agriculture irrigation channels is essential to control the opening gates of these channels. In this way, WSNs (Wireless Sensor Networks) have high relevance to obtain this kind of data. In this paper, we propose a sensor to measure the depth changes in irrigation channels to control the gates opening. It is connected to an Adafruit Feather HUZZAH based on ESP8266, which allows us to build a mobile edge computing system. The developed sensor is based on two coils. Sinus-wave powers the first one, and the second is induced. The coils are winding over a polyvinyl chloride (PVC) that has high resistance for corrosion and low price. Besides, we use copper wire as a conductive metal. We test two different configurations of coils. P1 has five spires for the powered coil (PC) and ten spires for the induced coil (IC). On the other hand, P2 has 40 spires for the PC and 80 spires for the IC. The two prototypes were coiled in one layer. Then, both sensors are tested using a glass bottle where the water column increased with the target to obtain the information of the depth. In both prototypes, the difference of voltage between the maximum and minimum studied depths is more or less the same, 4.46V for P1 and 4.44V for P2. Nevertheless, during the stabilization test, the P1 showed better adaptation for the turbulences than the P2. The P1 shows an oscillation of 0.48V, where the P2 has a maximum fluctuation of 3.2V.

In mathematical expression recognition, symbol classification is a crucial step. Numerous approaches for recognizing handwritten math symbols have been published, but most of them are either an online approach or a hybrid approach. There is an absence of a study focused on offline features for handwritten math symbol recognition. Furthermore, many papers provide results difficult to compare. In this paper we assess the performance of several well-known offline features for this task. We also test a novel set of features based on polar histograms and the vertical repositioning method for feature extraction. Finally, we report and analyze the results of several experiments using recurrent neural networks on a large public database of online handwritten math expressions. The combination of online and offline features significantly improved the recognition rate.

In mathematical expression recognition, symbol classification is a crucial step. Numerous approaches for recognizing handwritten math symbols have been published, but most of them are either an online approach or a hybrid approach. There is an absence of a study focused on offline features for handwritten math symbol recognition. Furthermore, many papers provide results difficult to compare. In this paper we assess the performance of several well-known offline features for this task. We also test a novel set of features based on polar histograms and the vertical repositioning method for feature extraction. Finally, we report and analyze the results of several experiments using recurrent neural networks on a large public database of online handwritten math expressions. The combination of online and offline features significantly improved the recognition rate.

© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works, This paper describes experiences that combine digital peer production with digital ink affordances. Rather than preparing papers to obtain a summative final mark, students work over the course of the term producing different small learning resources such as short engineering problems, reasoning or synthesis where the lecturer acts as manager and supervisor. Teacher intervention is carried out using digital ink over each individual student production being possible to share the results throughout a public or group repository and in class offering a pro-active argument about preventing common mistakes. In order to enhance students programming skills important efforts are oriented to produce learning objects in the form of Java applets. It has the additional advantage of fostering collaborative knowledge construction because any object serves to the whole group as learning material as soon as it is already produced and validated. Qualitative and quantitative results show both an overall satisfaction from students participating in the experiences, and better results in the common written exams, when compared to the other groups following the traditional method.

The increasing interest of online learning is unquestionable nowadays, with MOOCs being taken by thousands of students. However, for online learning to go mainstream it is necessary that professors perceive that the effort required to prepare and manage an online course is manageable. Today, a myriad of inexpensive tools and services can be used to produce and manage online courses with unprecedented ease and without distressing the professor. For that, this paper proposes an architecture based on Cloud services that simplifies the process of managing an online course, from delivering on-demand fully customized remote laboratories to communication automation for student engagement and feedback gathering. This approach has been applied to produce, distribute and manage an Online Course on Cloud Computing with Amazon Web Services. The paper describes the methodology, tools and results of this experience to point out that it is possible to deliver online courses with automatically provisioned labs, with minimal management overhead, while still providing a high quality learning experience to a worldwide audience.

In mathematical expression recognition, symbol classification is a crucial step. Numerous approaches for recognizing handwritten math symbols have been published, but most of them are either an online approach or a hybrid approach. There is an absence of a study focused on offline features for handwritten math symbol recognition. Furthermore, many papers provide results difficult to compare. In this paper we assess the performance of several well-known offline features for this task. We also test a novel set of features based on polar histograms and the vertical repositioning method for feature extraction. Finally, we report and analyze the results of several experiments using recurrent neural networks on a large public database of online handwritten math expressions. The combination of online and offline features significantly improved the recognition rate.

The increasing interest of online learning is unquestionable nowadays, with MOOCs being taken by thousands of students. However, for online learning to go mainstream it is necessary that professors perceive that the effort required to prepare and manage an online course is manageable. Today, a myriad of inexpensive tools and services can be used to produce and manage online courses with unprecedented ease and without distressing the professor. For that, this paper proposes an architecture based on Cloud services that simplifies the process of managing an online course, from delivering on-demand fully customized remote laboratories to communication automation for student engagement and feedback gathering. This approach has been applied to produce, distribute and manage an Online Course on Cloud Computing with Amazon Web Services. The paper describes the methodology, tools and results of this experience to point out that it is possible to deliver online courses with automatically provisioned labs, with minimal management overhead, while still providing a high quality learning experience to a worldwide audience.

© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works, This paper describes experiences that combine digital peer production with digital ink affordances. Rather than preparing papers to obtain a summative final mark, students work over the course of the term producing different small learning resources such as short engineering problems, reasoning or synthesis where the lecturer acts as manager and supervisor. Teacher intervention is carried out using digital ink over each individual student production being possible to share the results throughout a public or group repository and in class offering a pro-active argument about preventing common mistakes. In order to enhance students programming skills important efforts are oriented to produce learning objects in the form of Java applets. It has the additional advantage of fostering collaborative knowledge construction because any object serves to the whole group as learning material as soon as it is already produced and validated. Qualitative and quantitative results show both an overall satisfaction from students participating in the experiences, and better results in the common written exams, when compared to the other groups following the traditional method.

[EN] Personal audio systems aim to create listening (or bright) and quiet (or dark) zones in a room using an array of loudspeakers. For this purpose, many algorithms have been presented in the literature, being Weighted Pressure Matching (wPM) one of the most versatile. The main strength of wPM is that it can render a target soundfield in the listening zone while having control over the mean acoustic potential energy in the quiet zone. In this paper, we propose a variation of wPM such that it can provide control not only over the mean energy, but also over the spatial energy differences, obtaining a more uniform soundfield in the dark zone. The new algorithm is called wPM with Total Variation (wPM-TV), where TV is a tool used in the field of Graph Signal Processing (GSP). Firstly, we propose a graph representation of the control microphones of the dark zone and secondly, we use the wPM-TV algorithm to provide spatial control over that zone. Simulations show the good performance of the proposed algorithm and its versatility to obtain a more uniform distribution of the acoustic potential energy in the dark zone at the cost of slightly increasing the mean square reproduction error in the bright zone.

[EN] Personal audio systems aim to create listening (or bright) and quiet (or dark) zones in a room using an array of loudspeakers. For this purpose, many algorithms have been presented in the literature, being Weighted Pressure Matching (wPM) one of the most versatile. The main strength of wPM is that it can render a target soundfield in the listening zone while having control over the mean acoustic potential energy in the quiet zone. In this paper, we propose a variation of wPM such that it can provide control not only over the mean energy, but also over the spatial energy differences, obtaining a more uniform soundfield in the dark zone. The new algorithm is called wPM with Total Variation (wPM-TV), where TV is a tool used in the field of Graph Signal Processing (GSP). Firstly, we propose a graph representation of the control microphones of the dark zone and secondly, we use the wPM-TV algorithm to provide spatial control over that zone. Simulations show the good performance of the proposed algorithm and its versatility to obtain a more uniform distribution of the acoustic potential energy in the dark zone at the cost of slightly increasing the mean square reproduction error in the bright zone.

[EN] Control flow monitoring using a watchdog processor is a well-known technique to increase the dependability of a microprocessor system. Most approaches embed reference signatures for the watchdog processor into the processor instruction stream. These signatures contain the information required to detect control flow errors during program execution by the main processor. This paper proposes an architecture that offers both fault-tolerance and dynamic cache locking combined. This combination is achieved taking advantage of the fact that watchdog processor signatures are inserted along the program code. Then cache locking information is incorporated into these signatures. And also the required circuitry to inform the cache controller whether to lock or not the instructions fetched by the main processor is added into the watchdog processor. With this approach both fault-tolerant and real-time features are supported by the same hardware, therefore saving room on the silicon die or FPGA size. Results from experiments show that in most cases this approach reaches the same performance than previous, hardware-costly proposals.

[EN] Monitoring the execution of real-time systems has many advantages, it is not only useful to understand the behaviour of an application but also to find unfulfilled timing constraints in an implementation. However, real-time operating systems usually do not include the tracing tools to observe the behaviour during the execution. This paper presents the art2kitekt runtime monitoring tool, used to measure and to visualise the temporal characteristics of a real-time application. To demonstrate the functionality of the tool, the behaviour of an RTEMS-based application running over a Xilinx Zynq UltraScale+ is observed.

[EN] Cardiac function deterioration of heart failure patients is frequently manifested by the occurrence of decompensation events. One relevant step to adequately prevent cardiovascular status degradation is to predict decompensation episodes in order to allow preventive medical interventions.In this paper we introduce a methodology with the goal of finding onsets of worsening progressions from multiple physiological parameters which may have predictive value in decompensation events. The best performance was obtained for the model composed by only two features using a telemonitoring dataset (myHeart) with 41 patients. Results were achieved by applying leave-one-subject-out validation and correspond to a geometric mean of 83.67%. The obtained performance suggests that the methodology has the potential to be used in decision support solutions and assist in the prevention of this public health burden.

[EN] The use of precision agriculture and the Internet of Things has improved the efficiency of many cultures. Nevertheless, there are a few low-cost options to monitor soil moisture. Moreover, those options depend on the specific characteristics of the soil. In this paper, we attempt to find a sensor, based on mutual inductance, that could be used for more than one sort of soil. We study three prototypes, one of them with casing. The sensors are powered with a voltage of 10 peak to peak volts. One of the soils has a high content of organic matter and sand while the other is rich in sand and silt. The best prototype for the soil with high levels of organic matter has 10 turns on the powered coil and 5 on the induced coil. The best frequency for this sensor is 1340 kHz. For the soil with a significant quantity of silt, the best prototype has 80 turns on the powered coil and 40 on the induced coil. The frequency at which this sensor works best is 229 kHz, which happens to be its peak frequency. With those characteristics regressions lines with R2 values higher than 0.75 can be modeled

[EN] This paper presents a new method for fraud detection in credit cards based on exploiting the dynamics of the card transactions. We hypothesize different behavior models in the use of the card between legitimate clients and fraudsters that are registered in the sequential pattern that follows the transactions. The method considers analyses in subspaces defined by two or three variables recorded in the transactions. From these subspaces, several dynamic features, such as transaction velocity and acceleration, are estimated as input vectors for a classification process. Linear and quadratic discriminant analysis and random forest are implemented as single classifiers. All the single classification results obtained for each of the subspaces are late fused to obtain an overall result using alpha integration algorithm. The proposed method was evaluated using a subset of real data with a very low fraud to legitimate transaction ratio. We demonstrated that the temporal dependence of card transactions exploited in different subspaces and fused to give an overall result improves the detection accuracy of fraud detection in credit cards.

[EN] The sewerage is a critical infrastructure in cities because of the drainage of the urban runoff and the evacuation of the wastewater. Two types of sewerage, separated sewerage and combined sewerage, can be differentiated. In this paper, we show the application of a level sensor and a rain sensor for monitoring the separated sewerage. The level sensor is used for knowing if there is a critical level of water in the sewerage. The rain sensor is used to know if it is raining. The combination of this information allows the identification of three scenarios. These scenarios are normal situation, low drainage and illicit discharge/blockages in the pipeline. In addition, we study the use of sensors and mathematical models for monitoring the velocity of the wastewater. We concluded that the use of mathematical models is a good option for monitoring the velocity. Because with exception of the thermal sensors the other types of sensors show important gaps. The velocity is used to estimate the flow that is dumping in the water bodies. We use an ESP32 board program with Arduino IDE for data collection and sending the data to a server on the same network via Wi-Fi. The server is a computer that processes the data. We present the programming code and the ports that should be used for transmitting the data from Arduino to computer server.

[EN] With the aging of the car park in big cities, together with the fact that the number of users of private vehicles is increasing, the quality of air (QoA) in large cities has been worryingly reduced. Therefore, it is becoming increasingly necessary to implement new monitoring infrastructures to improve our smart cities. Therefore, in this paper, we present a collaborative Long Range (LoRa)-based sensor network for pollution monitoring in smart cities. The system is based on geo-located nodes capable of measuring the temperature, relative humidity and concentration of CO2 in urban environments. The system also takes into account the subjective opinions of citizens. By using the collected data and considering the restrictions policies of the city, the system in able to send the required orders to panels and traffic signs to control de traffic circulation. Finally, the citizens can be advised to avoid going to too polluted areas. The system has been testes in a real environment with very interesting results.

[EN] The illegal dumpings in sewerage can cause problems in the Wastewater treatment plants. In this paper, we propose a system for detecting these illegal dumpings. We use conductivity sensor for detecting the change in the conductivity of water. Because this change may be due to a dump. The system is based on two coils, a coil is powered by a sinus-wave and induced the other coil. To prevent damaged for water in the copper we encapsulate the coils in a PVC tube. These coils are connected to flyport to send the values and generate alarms. We test with different configurations of coils with encapsulation of 3 and 1 mm. In the different prototypes tested have been seen that with the 3 mm encapsulation no significant differences are observed. The better prototypes are based on 40 spires of the powered coil and 80 spires in the induced coil. The best difference between samples of 0 and 40 g/l of table salt are in the prototype when the spires are distributed in 1 layer (6.06 V). Another prototype test with the same number of turns but distributed in 4 layers has a difference of 4.10 V. But during the verification phase we verified that this last prototype presents a relative error of 2.54% compared to 6.55% of the prototype distributed in a layer

[EN] The monitoring of industry processes can optimize the use of resources and improve its efficiency. In dairy farms, several parameters from the processes must be monitored. This paper proposes the design of a monitoring system for a farm that produces dairy products and jams. Several similar studies are analysed. Based on this, and on the farm characteristics, a novel design is developed. The principal benefits of the system are also exposed.

[EN] This paper aims to build a fuzzy system by means of genetic programming, which is used to extract the relevant function for each rule consequent through symbolic regression. The employed TSK fuzzy system is complemented with a variational Bayesian Gaussian mixture clustering method, which identifies the domain partition, simultaneously specifying the number of rules as well as the parameters in the fuzzy sets. The genetic programming approach is accompanied with an orthogonal least square algorithm, to extract robust rule consequent functions for the fuzzy system. The proposed model is validated with a synthetic surface, and then with real data from a gas turbine compressor map case, which is compared with an adaptive neuro-fuzzy inference system model. The results have demonstrated the efficacy of the proposed approach for modelling system with small data or bifurcating dynamics, where the analytical equations are not available, such as those in a typical industrial setting.

[EN] An optimization procedure for the design of miniaturized substrate integrated quasi-lumped filters based on aggressive space mapping techniques is presented in this paper. A gradient-descent approach based on a lossy coarse model is employed. Thus, a 3-pole bandpass filter response centered at 10 GHz is designed, manufactured and measured, showing the validity of the technique even if strong dependencies between the different electrical and physical parameters are present.

[EN] Electric Vehicles (EVs) are growing attention fortheir higher efficiency and less-polluting specifications. However,a massive introduction of EVs could lead to several issues inpower systems. Several authors have proposed various smartcharging approaches. But, these approaches could not be ap-propriately implemented without knowing the charging behaviorof the EV customers. Thus, this paper proposes an EV chargingload prediction for the particular case of Quito, Ecuador. Thisforecasting is performed based on data obtained from a GPSsystem and on statistical methods.

This paper analyzes the feasibility of using a simple diffraction model to compute the blocking of the human body to millimeter wave radio frequencies in indoor environments. The model makes a set of approximations that are evaluated to determine the applicability limits of such simplified approach, in particular for the human body blockage case. The work presented here: (1) describes briefly the mathematical support that is used to model the concealment using the Knife-Edge model, (2) identifies the potential simplifications applicable to the mathematical model implementation that allow a 3D geometric human body to be modelled with simple 2D shapes, (3) characterizes the polarization influence on the mm-wave blocking for such simplified human body models.

Aerial base stations have been recently considered in the deployment of wireless networks. Finding the optimal position for one or multiple aerial base stations is a complex problem tackled by several works. However, just a few works consider the mobility of the users which makes necessary an online optimization to follow the changes in the scenario where the optimization is performed. This paper deals with the online optimization of an aerial base station placement considering different types of users mobility and three algorithms: a Q-learning technique, a Gradient-based solution and a Greedy-search solution. Our objective is to minimize in an urban environment the path loss of the user at street level with the highest path loss. Simulation results show that the performance of the three methods is similar when a high number of users move randomly and uniformly around the scenario under test. Nevertheless, in some situations when the number of users is reduced or when the users move together in a similar direction, both Gradient and Greedy algorithms present a significantly better performance than the Q-learning method.

Wireless Body Area Networks (WBANs) have increased the attention of the research community for the next generation wireless medical devices. Among others, Wireless Capsule Endoscopy (WCE) aims to transmit better quality images. For this, the Ultra Wideband (UWB) frequency band is becoming a good alternative to currently allocated frequencies for in-body networks, allowing higher data rate and having a low power transmission. Common channel characterization in WBANs are performed in frequency domain, i.e., analyzing the received power as a function of frequency. Nevertheless, indepth studies in delay domain analyzing the impulse response of the channel are barely considered in current literature. In this paper, an initial study in delay domain, i.e., the Power Delay Profile (PDP) characteristics, is performed. Moreover, a comparison between the channel response in frequency and delay domain is performed. This work gives an insightful view of the impulse response of the channel for in-body to on-body communications. For that, an extensive campaign of phantom measurements and software simulations are conducted.

Localization for Wireless Capsule Endoscopy (WCE) in the Ultra-Wideband frequency band is a very active field of investigation due to its potential advantages in future endoscopy applications. Received Signal Strength (RSS) based localization is commonly preferred due to its simplicity. Previous studies on Ultra-Wideband (UWB) RSS-based localization showed that the localization accuracy depends on the average ranging error related to the selected combination of receivers, which not always is the one experiencing the highest level of received power. In this paper the tendency of the localization error is further investigated through supplementary software simulations and previously conducted laboratory measurements. Two-dimensional (2D) and three-dimensional (3D) positioning are performed and the trend of the localization error compared in both cases. Results shows that the distribution of the selected path loss values, corresponding to the receivers used for localization, around the in-body position to estimate also affects the localization accuracy.

[EN] Optical coherence tomography (OCT) is an important imaging modality that is used frequently to monitor the state of retinal layers both in humans and animals. Automated OCT analysis in rodents is an important method to study the possible toxic effect of treatments before the test in humans. In this paper, an automatic method to detect the most significant retinal layers in rat OCT images is presented. This algorithm is based on an encoder-decoder fully convolutional network (FCN) architecture combined with a robust method of post-processing. After the validation, it was demonstrated that the proposed method outperforms the commercial Insight image segmentation software. We obtained results (averaged absolute distance error) in the test set for the training database of 2.52±0.80 µm. In the predictions done by the method, in a different database (only used for testing), we also achieve the promising results of 4.45 ± 3.02 µm.

[EN] The sewerage is a critical infrastructure in cities because of the drainage of the urban runoff and the evacuation of the wastewater. Two types of sewerage, separated sewerage and combined sewerage, can be differentiated. In this paper, we show the application of a level sensor and a rain sensor for monitoring the separated sewerage. The level sensor is used for knowing if there is a critical level of water in the sewerage. The rain sensor is used to know if it is raining. The combination of this information allows the identification of three scenarios. These scenarios are normal situation, low drainage and illicit discharge/blockages in the pipeline. In addition, we study the use of sensors and mathematical models for monitoring the velocity of the wastewater. We concluded that the use of mathematical models is a good option for monitoring the velocity. Because with exception of the thermal sensors the other types of sensors show important gaps. The velocity is used to estimate the flow that is dumping in the water bodies. We use an ESP32 board program with Arduino IDE for data collection and sending the data to a server on the same network via Wi-Fi. The server is a computer that processes the data. We present the programming code and the ports that should be used for transmitting the data from Arduino to computer server.

[EN] Forest fires are one of the main environmental problems in the entire Mediterranean basin. In a context where low power and long-range networks (LPWAN) are increasingly common to the rise of Internet of Things (IoT) architecture, the interest in providing solutions to monitor scenarios and fire prevention based on these technologies is huge. This paper presents a low cost Long Range (LoRa) based network able to evaluate level of fire risk and the presence of a forest fire. The system is composed by a LoRa node and a set of sensors to measure the temperature, relative humidity, wind speed and CO2. The evaluation algorithm is based on the 30- 30-30 rule. Through website the users can see the parameters measured by nodes in real time. The system has been tested in a real environment and the results show that it is possible to cover a circular area of 1.1km or radius.

[EN] Cardiac function deterioration of heart failure patients is frequently manifested by the occurrence of decompensation events. One relevant step to adequately prevent cardiovascular status degradation is to predict decompensation episodes in order to allow preventive medical interventions.In this paper we introduce a methodology with the goal of finding onsets of worsening progressions from multiple physiological parameters which may have predictive value in decompensation events. The best performance was obtained for the model composed by only two features using a telemonitoring dataset (myHeart) with 41 patients. Results were achieved by applying leave-one-subject-out validation and correspond to a geometric mean of 83.67%. The obtained performance suggests that the methodology has the potential to be used in decision support solutions and assist in the prevention of this public health burden.

[EN] Monitoring the execution of real-time systems has many advantages, it is not only useful to understand the behaviour of an application but also to find unfulfilled timing constraints in an implementation. However, real-time operating systems usually do not include the tracing tools to observe the behaviour during the execution. This paper presents the art2kitekt runtime monitoring tool, used to measure and to visualise the temporal characteristics of a real-time application. To demonstrate the functionality of the tool, the behaviour of an RTEMS-based application running over a Xilinx Zynq UltraScale+ is observed.

[EN] Control flow monitoring using a watchdog processor is a well-known technique to increase the dependability of a microprocessor system. Most approaches embed reference signatures for the watchdog processor into the processor instruction stream. These signatures contain the information required to detect control flow errors during program execution by the main processor. This paper proposes an architecture that offers both fault-tolerance and dynamic cache locking combined. This combination is achieved taking advantage of the fact that watchdog processor signatures are inserted along the program code. Then cache locking information is incorporated into these signatures. And also the required circuitry to inform the cache controller whether to lock or not the instructions fetched by the main processor is added into the watchdog processor. With this approach both fault-tolerant and real-time features are supported by the same hardware, therefore saving room on the silicon die or FPGA size. Results from experiments show that in most cases this approach reaches the same performance than previous, hardware-costly proposals.

[EN] The use of precision agriculture and the Internet of Things has improved the efficiency of many cultures. Nevertheless, there are a few low-cost options to monitor soil moisture. Moreover, those options depend on the specific characteristics of the soil. In this paper, we attempt to find a sensor, based on mutual inductance, that could be used for more than one sort of soil. We study three prototypes, one of them with casing. The sensors are powered with a voltage of 10 peak to peak volts. One of the soils has a high content of organic matter and sand while the other is rich in sand and silt. The best prototype for the soil with high levels of organic matter has 10 turns on the powered coil and 5 on the induced coil. The best frequency for this sensor is 1340 kHz. For the soil with a significant quantity of silt, the best prototype has 80 turns on the powered coil and 40 on the induced coil. The frequency at which this sensor works best is 229 kHz, which happens to be its peak frequency. With those characteristics regressions lines with R2 values higher than 0.75 can be modeled

[EN] With the aging of the car park in big cities, together with the fact that the number of users of private vehicles is increasing, the quality of air (QoA) in large cities has been worryingly reduced. Therefore, it is becoming increasingly necessary to implement new monitoring infrastructures to improve our smart cities. Therefore, in this paper, we present a collaborative Long Range (LoRa)-based sensor network for pollution monitoring in smart cities. The system is based on geo-located nodes capable of measuring the temperature, relative humidity and concentration of CO2 in urban environments. The system also takes into account the subjective opinions of citizens. By using the collected data and considering the restrictions policies of the city, the system in able to send the required orders to panels and traffic signs to control de traffic circulation. Finally, the citizens can be advised to avoid going to too polluted areas. The system has been testes in a real environment with very interesting results.

[EN] This paper presents a new method for fraud detection in credit cards based on exploiting the dynamics of the card transactions. We hypothesize different behavior models in the use of the card between legitimate clients and fraudsters that are registered in the sequential pattern that follows the transactions. The method considers analyses in subspaces defined by two or three variables recorded in the transactions. From these subspaces, several dynamic features, such as transaction velocity and acceleration, are estimated as input vectors for a classification process. Linear and quadratic discriminant analysis and random forest are implemented as single classifiers. All the single classification results obtained for each of the subspaces are late fused to obtain an overall result using alpha integration algorithm. The proposed method was evaluated using a subset of real data with a very low fraud to legitimate transaction ratio. We demonstrated that the temporal dependence of card transactions exploited in different subspaces and fused to give an overall result improves the detection accuracy of fraud detection in credit cards.

[EN] The illegal dumpings in sewerage can cause problems in the Wastewater treatment plants. In this paper, we propose a system for detecting these illegal dumpings. We use conductivity sensor for detecting the change in the conductivity of water. Because this change may be due to a dump. The system is based on two coils, a coil is powered by a sinus-wave and induced the other coil. To prevent damaged for water in the copper we encapsulate the coils in a PVC tube. These coils are connected to flyport to send the values and generate alarms. We test with different configurations of coils with encapsulation of 3 and 1 mm. In the different prototypes tested have been seen that with the 3 mm encapsulation no significant differences are observed. The better prototypes are based on 40 spires of the powered coil and 80 spires in the induced coil. The best difference between samples of 0 and 40 g/l of table salt are in the prototype when the spires are distributed in 1 layer (6.06 V). Another prototype test with the same number of turns but distributed in 4 layers has a difference of 4.10 V. But during the verification phase we verified that this last prototype presents a relative error of 2.54% compared to 6.55% of the prototype distributed in a layer

[EN] The monitoring of industry processes can optimize the use of resources and improve its efficiency. In dairy farms, several parameters from the processes must be monitored. This paper proposes the design of a monitoring system for a farm that produces dairy products and jams. Several similar studies are analysed. Based on this, and on the farm characteristics, a novel design is developed. The principal benefits of the system are also exposed.

[EN] An optimization procedure for the design of miniaturized substrate integrated quasi-lumped filters based on aggressive space mapping techniques is presented in this paper. A gradient-descent approach based on a lossy coarse model is employed. Thus, a 3-pole bandpass filter response centered at 10 GHz is designed, manufactured and measured, showing the validity of the technique even if strong dependencies between the different electrical and physical parameters are present.

[EN] This paper aims to build a fuzzy system by means of genetic programming, which is used to extract the relevant function for each rule consequent through symbolic regression. The employed TSK fuzzy system is complemented with a variational Bayesian Gaussian mixture clustering method, which identifies the domain partition, simultaneously specifying the number of rules as well as the parameters in the fuzzy sets. The genetic programming approach is accompanied with an orthogonal least square algorithm, to extract robust rule consequent functions for the fuzzy system. The proposed model is validated with a synthetic surface, and then with real data from a gas turbine compressor map case, which is compared with an adaptive neuro-fuzzy inference system model. The results have demonstrated the efficacy of the proposed approach for modelling system with small data or bifurcating dynamics, where the analytical equations are not available, such as those in a typical industrial setting.

[EN] Control flow monitoring using a watchdog processor is a well-known technique to increase the dependability of a microprocessor system. Most approaches embed reference signatures for the watchdog processor into the processor instruction stream. These signatures contain the information required to detect control flow errors during program execution by the main processor. This paper proposes an architecture that offers both fault-tolerance and dynamic cache locking combined. This combination is achieved taking advantage of the fact that watchdog processor signatures are inserted along the program code. Then cache locking information is incorporated into these signatures. And also the required circuitry to inform the cache controller whether to lock or not the instructions fetched by the main processor is added into the watchdog processor. With this approach both fault-tolerant and real-time features are supported by the same hardware, therefore saving room on the silicon die or FPGA size. Results from experiments show that in most cases this approach reaches the same performance than previous, hardware-costly proposals.

[EN] The sewerage is a critical infrastructure in cities because of the drainage of the urban runoff and the evacuation of the wastewater. Two types of sewerage, separated sewerage and combined sewerage, can be differentiated. In this paper, we show the application of a level sensor and a rain sensor for monitoring the separated sewerage. The level sensor is used for knowing if there is a critical level of water in the sewerage. The rain sensor is used to know if it is raining. The combination of this information allows the identification of three scenarios. These scenarios are normal situation, low drainage and illicit discharge/blockages in the pipeline. In addition, we study the use of sensors and mathematical models for monitoring the velocity of the wastewater. We concluded that the use of mathematical models is a good option for monitoring the velocity. Because with exception of the thermal sensors the other types of sensors show important gaps. The velocity is used to estimate the flow that is dumping in the water bodies. We use an ESP32 board program with Arduino IDE for data collection and sending the data to a server on the same network via Wi-Fi. The server is a computer that processes the data. We present the programming code and the ports that should be used for transmitting the data from Arduino to computer server.

[EN] Cardiac function deterioration of heart failure patients is frequently manifested by the occurrence of decompensation events. One relevant step to adequately prevent cardiovascular status degradation is to predict decompensation episodes in order to allow preventive medical interventions.In this paper we introduce a methodology with the goal of finding onsets of worsening progressions from multiple physiological parameters which may have predictive value in decompensation events. The best performance was obtained for the model composed by only two features using a telemonitoring dataset (myHeart) with 41 patients. Results were achieved by applying leave-one-subject-out validation and correspond to a geometric mean of 83.67%. The obtained performance suggests that the methodology has the potential to be used in decision support solutions and assist in the prevention of this public health burden.