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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.