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Cardiotocography (CTG) is a clinical procedure that is used to track and gauge the severity of fetal distress. Although CTG is the most often used equipment to monitor and assess the health of the fetus, the high rate of false positive results due to visual interpretation significantly contributes to needless surgical delivery or delayed intervention. In this study, a novel approach is introduced where both printing CTG paper is digitized and a machine learning approach is employed to detect the abnormality in the digitized CTG signal. Image processing-based preprocessing steps are employed to make the printing of CTG paper more convenient to extract the CTG signal. Various signal-processing techniques are used to calibrate the extracted CTG signal. Then, Empirical Mode Decomposition (EMD) is used to decompose the CTG signal into its frequency components and instantaneous frequency and spectral entropy features are extracted. After feature normalization and feature selection with ReliefF algorithm, support vector machines (SVM) is used for the classification of the normal and abnormal classes. A novel dataset is used in the experimental works and various performance evaluation metrics are used for the evaluation of the achievement of the proposed method. 10-fold cross-validation-based experiments show that the proposed method is quite efficient in abnormality detection in printing CTG papers where an average accuracy score of around 90.0% is produced.

The robotic wearable exoskeletons have been developed due to various advantages offered by these devices. These advantages are manifested by integrating the human and a robot into one system under the user's control, which motivated researchers to develop different exoskeletons through years. However, several advances in exoskeleton; still, dealing with the various technical challenges in designing these impressive devices is inevitably. This paper aims to introduce informative resources and quick guidance of various technical challenges as such information is critical for exoskeleton development. The constructive discussion is intended to encourage researchers, innovators and academia to be aware of these challenges. Finally, the contemporary research gaps with various challenges have been highlighted, which remain to be solved as well as some future directions in this field that will have far-reaching effects on developing exoskeletons.

We demonstrate power-scaling of nonlinear frequency conversion in fibres via dispersive wave generation using higher order modes. By pumping in the LP0,m modes at 1030 nm we show wavelength selectability between 550 and 800 nm with pulse energies up to tens of nJ.

In the past two decades, there has been a consider-able increase in use of computer-based exams. Currently there is a lack of comprehensive understanding about equivalence between paper-based and computer-based exams in engineering and computing education. This study utilised a systematic literature review (using PRISMA) to synthesise the literature regarding paper and computer-based testing in engineering and computing education between 2010-2020 (inclusive). The research database that was used was Scopus. Publications were first screened by title, abstract and keywords. This was followed by screening the full text of each publication. Twenty-four papers were included in the final analysis. Outcomes demonstrated no clear result regarding equivalency between computer-based and paper-based exams. Similarly, many studies reported that students preferred computer-based exams, but this was not ubiquitous. Educators should consider these factors when considering transitioning from paper to computer-based testing.

For extra-high-voltage high-temperature superconducting (HTS) cables, not only high electrical insulation performance but also low dielectric loss is required. Therefore, we focus on a porous synthetic paper with lower dielectric loss, e.g., Tyvek polyethylene nonwoven fabric, than that of polypropylene laminated paper (PPLP), which has been used for a conventional HTS cable insulation system. In this paper, we compare partial discharge inception characteristics for different liquid nitrogen/synthetic paper composite insulation systems. The partial discharge inception electric field strength in the composite insulation system depends on the electric field strength in the porous area of synthetic paper.

Theodolite is a framework for benchmarking the scalability of cloud-native applications. It automates deployment and monitoring of a cloud-native application for different load intensities and provisioned cloud resources and assesses whether specified service level objectives (SLOs) are fulfilled. Provided as a Kubernetes Operator, Theodolite allows defining, sharing, and archiving benchmarks and experiment configurations in declarative files. We demonstrate Theodolite’s benchmarking method and show how researchers and cloud engineers can execute existing scalability benchmarks or define new ones with Theodolite.

Theodolite is a framework for benchmarking the scalability of cloud-native applications. It automates deployment and monitoring of a cloud-native application for different load intensities and provisioned cloud resources and assesses whether specified service level objectives (SLOs) are fulfilled. Provided as a Kubernetes Operator, Theodolite allows defining, sharing, and archiving benchmarks and experiment configurations in declarative files. We demonstrate Theodolite’s benchmarking method and show how researchers and cloud engineers can execute existing scalability benchmarks or define new ones with Theodolite.

In this paper, we work on analyzing old paper advertisement (Ad). An Ad usually contains various types of textual and non-textual objects, which may also be in different orientations. We attempt to detect such objects from an early Indian-print paper Ad database comprising 1500 Ad images. The past major object detectors did not perform well on this database. We propose a deep reinforcement learning-based orientation-aware object detector. Our system learns by itself where to look and what to look of an Ad image. Therefore, it can bypass the impeding zone due to degraded image quality. To find the looking spot, we come up with a foveal transformation. In reinforcement learning, we present a scheme for shaping an internal reward with a top-up. For oriented object detection, we also propose a generic loss function. Our system obtained encouraging results from the experiments performed on the Ad database.

Best Paper Award ​© 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., The Web has a collection of over 150 million tables, which as a whole represents an invaluable source of semi-structured knowledge. Such tables are commonly referred to as Web tables, and are considerably easier to leverage in automated processes than completely unstructured, free-format text. Understanding the semantics of Web tables is important since they are used in various applications like knowledge base augmentation, information retrieval or natural language interfaces for databases. The task of understanding the semantics of a given Web table is known as Web table annotation. In recent years, it has been tackled through methods where the table is enriched using existing knowledge bases containing valuable information on the domain at hand, its entities and their mutual relationships. In this paper, we present two novel and unsupervised Web table annotation methods, which leverage the context of the tables to better capture their semantics. Our first method is lookup-based and exploits text similarity to find reference entities in the knowledge base. The second method uses distributional vector representations – a.k.a. embeddings – of the Web tables to elicit their context and disambiguate their semantics. Experiments show that our proposed approach outperforms the state of the art in Web table annotation by up to 18%. Another contribution of this work is a manually corrected version of one of the popular gold standard datasets, Limaye, with annotations from DBpedia. Our dataset and code are publicly available.

Best Paper Award ​© 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., The Web has a collection of over 150 million tables, which as a whole represents an invaluable source of semi-structured knowledge. Such tables are commonly referred to as Web tables, and are considerably easier to leverage in automated processes than completely unstructured, free-format text. Understanding the semantics of Web tables is important since they are used in various applications like knowledge base augmentation, information retrieval or natural language interfaces for databases. The task of understanding the semantics of a given Web table is known as Web table annotation. In recent years, it has been tackled through methods where the table is enriched using existing knowledge bases containing valuable information on the domain at hand, its entities and their mutual relationships. In this paper, we present two novel and unsupervised Web table annotation methods, which leverage the context of the tables to better capture their semantics. Our first method is lookup-based and exploits text similarity to find reference entities in the knowledge base. The second method uses distributional vector representations – a.k.a. embeddings – of the Web tables to elicit their context and disambiguate their semantics. Experiments show that our proposed approach outperforms the state of the art in Web table annotation by up to 18%. Another contribution of this work is a manually corrected version of one of the popular gold standard datasets, Limaye, with annotations from DBpedia. Our dataset and code are publicly available.

With the increasing popularity of optimization algorithms in electromagnetic engineering, it is clear that mixed-variable design problems prevail. This paper shows that the Cross-Entropy (CE) optimization method is intrinsically versatile to handle these and other types of problems. We provide implementation details of two antenna examples optimized by the CE method to demonstrate its elegance and efficiency.

© 2018 IEEE. During the secure boot process for a trusted execution environment, the processor must provide a chain of certificates to the remote client demonstrating that their secure container was established as specified. This certificate chain is rooted at the hardware manufacturer who is responsible for constructing chips according to the correct specification and provisioning them with key material. We consider a semi-honest manufacturer who is assumed to construct chips correctly, but may attempt to obtain knowledge of client private keys during the process. Using the RISC-V Rocket chip architecture as a base, we design, document, and implement an attested execution processor that does not require secure non-volatile memory, nor a private key explicitly assigned by the manufacturer. Instead, the processor derives its cryptographic identity from manufacturing variation measured by a Physical Unclonable Function (PUF). Software executed by a bootloader built into the processor transforms the PUF output into an elliptic curve key pair. The (re)generated private key is used to sign trusted portions of the boot image, and is immediately destroyed. The platform can therefore provide attestations about its state to remote clients. Reliability and security of PUF keys are ensured through the use of a trapdoor computational fuzzy extractor. We present detailed evaluation results for secure boot and attestation by a client of a Rocket chip implementation on a Xilinx Zynq 7000 FPGA.

In this paper, we study the sum rate maximization for a multiple-input multiple-output (MIMO) system with successive zero-forcing dirty-paper coding (SZFDPC) and per-antenna power constraint (PAPC). Although SZFDPC is a low-complexity alternative to the optimal dirty paper coding, efficient algorithms to compute its sum rate are still open problems especially under practical PAPC. The existing solution to the considered problem is computationally inefficient due to employing high-complexity interior-point method. In this study, we propose two novel low-complexity approaches to this important problem. More specifically, the first algorithm achieves the optimal solution by transforming the original problem in the broadcast channel into an equivalent problem in the multiple access channel, then the resulting problem is solved by alternating optimization together with successive convex approximation. We also derive a suboptimal solution based on machine learning to which simple linear regressions are applicable. The approaches are analyzed and validated extensively to demonstrate their superiors over the existing approach.

In this paper, we study the sum rate maximization for a multiple-input multiple-output (MIMO) system with successive zero-forcing dirty-paper coding (SZFDPC) and per-antenna power constraint (PAPC). Although SZFDPC is a low-complexity alternative to the optimal dirty paper coding, efficient algorithms to compute its sum rate are still open problems especially under practical PAPC. The existing solution to the considered problem is computationally inefficient due to employing high-complexity interior-point method. In this study, we propose two novel low-complexity approaches to this important problem. More specifically, the first algorithm achieves the optimal solution by transforming the original problem in the broadcast channel into an equivalent problem in the multiple access channel, then the resulting problem is solved by alternating optimization together with successive convex approximation. We also derive a suboptimal solution based on machine learning to which simple linear regressions are applicable. The approaches are analyzed and validated extensively to demonstrate their superiors over the existing approach.

In this paper, we study the sum rate maximization for a multiple-input multiple-output (MIMO) system with successive zero-forcing dirty-paper coding (SZFDPC) and per-antenna power constraint (PAPC). Although SZFDPC is a low-complexity alternative to the optimal dirty paper coding, efficient algorithms to compute its sum rate are still open problems especially under practical PAPC. The existing solution to the considered problem is computationally inefficient due to employing high-complexity interior-point method. In this study, we propose two novel low-complexity approaches to this important problem. More specifically, the first algorithm achieves the optimal solution by transforming the original problem in the broadcast channel into an equivalent problem in the multiple access channel, then the resulting problem is solved by alternating optimization together with successive convex approximation. We also derive a suboptimal solution based on machine learning to which simple linear regressions are applicable. The approaches are analyzed and validated extensively to demonstrate their superiors over the existing approach.

Intelligent reflecting surfaces (IRSs) have received considerable attention from the wireless communications research community recently. In particular, as low-cost passive devices, IRSs enable the control of the wireless propagation environment, which is not possible in conventional wireless networks. To take full advantage of such IRS-assisted communication systems, both the beamformer at the access point (AP) and the phase shifts at the IRS need to be optimally designed. However, thus far, the optimal design is not well understood. In this paper, a point-to-point IRS-assisted multiple-input single-output (MISO) communication system is investigated. The beamformer at the AP and the IRS phase shifts are jointly optimized to maximize the spectral efficiency. Two efficient algorithms exploiting fixed point iteration and manifold optimization techniques, respectively, are developed for solving the resulting non-convex optimization problem. The proposed algorithms not only achieve a higher spectral efficiency but also lead to a lower computational complexity than the state-of-the-art approach. Simulation results reveal that deploying large-scale IRSs in wireless systems is more efficient than increasing the antenna array size at the AP for enhancing both the spectral and the energy efficiency. © 2019 IEEE.

Intelligent reflecting surfaces (IRSs) have received considerable attention from the wireless communications research community recently. In particular, as low-cost passive devices, IRSs enable the control of the wireless propagation environment, which is not possible in conventional wireless networks. To take full advantage of such IRS-assisted communication systems, both the beamformer at the access point (AP) and the phase shifts at the IRS need to be optimally designed. However, thus far, the optimal design is not well understood. In this paper, a point-to-point IRS-assisted multiple-input single-output (MISO) communication system is investigated. The beamformer at the AP and the IRS phase shifts are jointly optimized to maximize the spectral efficiency. Two efficient algorithms exploiting fixed point iteration and manifold optimization techniques, respectively, are developed for solving the resulting non-convex optimization problem. The proposed algorithms not only achieve a higher spectral efficiency but also lead to a lower computational complexity than the state-of-the-art approach. Simulation results reveal that deploying large-scale IRSs in wireless systems is more efficient than increasing the antenna array size at the AP for enhancing both the spectral and the energy efficiency. © 2019 IEEE.

Gamification is one of the trends in education that is best suited to the current learning environment. Putra BINGO is a transformative assessment tool that uses gamification techniques. This research starts by elaborating the concept of Putra BINGO and its implementation using traditional method with pen and paper. The feedbacks gathered from the implementation are analyzed and applied to develop a multiplayer educational online game using Unity Game Engine. This paper describes details of the development for its two components; the database and the digital online game. Putra Bingo is available on PC and Android devices. It required additional plugins such as Photon Networking to handle game communication between multiple players. This is crucial to accommodate its test case application as an alternative assessment for teamwork skills using Rubrics and questionnaires. Further research will be conducted to enhance its functionality and user experience after the initial development of the digital online version is completed.

Gamification is one of the trends in education that is best suited to the current learning environment. Putra BINGO is a transformative assessment tool that uses gamification techniques. This research starts by elaborating the concept of Putra BINGO and its implementation using traditional method with pen and paper. The feedbacks gathered from the implementation are analyzed and applied to develop a multiplayer educational online game using Unity Game Engine. This paper describes details of the development for its two components; the database and the digital online game. Putra Bingo is available on PC and Android devices. It required additional plugins such as Photon Networking to handle game communication between multiple players. This is crucial to accommodate its test case application as an alternative assessment for teamwork skills using Rubrics and questionnaires. Further research will be conducted to enhance its functionality and user experience after the initial development of the digital online version is completed.

This White Paper follows the first one produced in 2017 by the IEEE Symbiotic Autonomous Systems Initiative (SAS)1 , extending it to address updated technologies and cover additional topics due to the evolution of science and technology. Additional white papers will follow because this is an area in continuous development. The first examples of symbioses are already available in a number of areas, and even now, these are impacting our economic system and way of life. The IEEE SAS Initiative takes a 360° view based on technology and standardization—the foundation of IEEE—and invites all interested constituencies to contribute complementary point of views, including economic, regulatory, and sociocultural perspectives. The transformation fostered by technology evolution in all paths of life requires planning and education by current and future players. Another goal of the initiative is to consider the future of education, given that these symbioses transform its meaning, making it both shared and distributed. In this respect, the aims of this White Paper are to further develop the ideas presented in the first white paper: (1) to highlight impacts that are clearly identifiable today, and (2) to indicate emerging issues, thus providing a starting point to those involved in making public policy to understand the technical fundamentals, their evolution and their potential implications. Note that this White Paper is intended to be self-contained, without requiring the reader to read the previous white paper.

This paper presents a study on the effect of beating on the physical and mechanical properties of untreated kenaf based insulation paper for application in transformers. The paper was developed based on kenaf bast fibers through soda pulping process. The pulps were subjected to beating process up to 9000 revolutions where the thickness, density and tensile index of paper were measured. It is found that the tensile index and the density of the paper increases while the thickness of the paper decreases with beating revolutions.

This paper presents a study on the effect of beating on the physical and mechanical properties of untreated kenaf based insulation paper for application in transformers. The paper was developed based on kenaf bast fibers through soda pulping process. The pulps were subjected to beating process up to 9000 revolutions where the thickness, density and tensile index of paper were measured. It is found that the tensile index and the density of the paper increases while the thickness of the paper decreases with beating revolutions.

Blockchain technology has become almost as famous for incidents involving security breaches as for its innovative potential. We shed light on the prevalence and nature of these incidents through a database structured using the STIX format. Apart from OPSEC-related incidents, we find that the nature of many incidents is specific to blockchain technology. Two categories stand out: smart contracts, and techno-economic protocol incentives. For smart contracts, we propose to use recent advances in software testing to find flaws before deployment. For protocols, we propose the PRESTO framework that allows us to compare different protocols within a five-dimensional framework.

Blockchain technology has become almost as famous for incidents involving security breaches as for its innovative potential. We shed light on the prevalence and nature of these incidents through a database structured using the STIX format. Apart from OPSEC-related incidents, we find that the nature of many incidents is specific to blockchain technology. Two categories stand out: smart contracts, and techno-economic protocol incentives. For smart contracts, we propose to use recent advances in software testing to find flaws before deployment. For protocols, we propose the PRESTO framework that allows us to compare different protocols within a five-dimensional framework.

A dual band antenna is inkjet-printed and then folded as part of a paper unmanned aerial vehicle (UAV). The patterns of the antenna are reproduced on a standard photo paper substrate using an off the shelf inkjet printer. Readily available cartridges with nanoparticle silver conductive ink are employed. A single-layer planar antenna is fed by coplanar waveguide (CPW). The geometry of the radiating element consists of a semicircle with a centered square slot. In order to examine the effect of bending on performance, the antenna is tested unfolded and then folded when integrated onto the airplane. Two configurations of the folded antenna on the plane are analyzed. The aim is to investigate the feasibility of fabricating foldable antennas for paper airplanes using low-cost inkjet printing techniques. The antenna operates at the existing 2.4 GHz and 5.2 GHz WLAN bands. Finite different time domain simulations compare well with measurement.

Recently there has been a renewed interest for probabilistic timing analysis (PTA) and probabilistic task scheduling (PTS). Despite the number of works in both fields, the link between them is weak: works on the latter build upon a series of assumptions on the probabilistic behavior of each task - or instances (jobs) of it - that have not been shown how to be fulfilled by PTA. This paper makes a first step towards covering this gap with emphasis on providing the right meaning of pWCET estimate as understood by both PTA and PTS. We show that the main issue related to ensuring that PTS assumptions on pWCET estimates are captured by PTA relates to the dependencies among tasks, and even jobs of a given task. Both change the scope of applicability of pWCET estimates provided by PTA and hence, their use by PTS., This work has been partially supported by the Spanish Ministry of Science and Innovation under grant TIN2015-65316-P. Jaume Abella has been partially supported by the Ministry of Economy and Competitiveness under Ramon y Cajal fellowship number RYC-2013-14717. Carles Hernández is jointly funded by the Spanish Ministry of Economy and Competitiveness and FEDER funds through grant TIN2014-60404-JIN., Peer Reviewed, Postprint (author's final draft)

Vegetable oils are being considered as potential alternatives to mineral oil, due to their better environmental performance and for their high fire point. Although these liquids have been used in distribution transformer, it is still a significant step to adopt vegetable oils in power transformer due to high cost and high level of safety and reliability required in service for these units. Vegetable oils such as Palm oil (PO), Corn oil (CO), and Rice Bran oils (RBO) offer suitable alternative for mineral oil. It is anticipated that most of the un-aged oil could satisfy the minimum requirement for dielectric insulation liquids in transformer. However, since transformers in service could be subjected to heat and multiple environmental parameters, the oil could be subjected to ageing. The chemical properties of the oil may change and its performance could be affected by the presence of ageing-by-products such as moisture and acids. Therefore, considering the application of new dielectric insulation liquids such as PO, CO and RBO in transformer, it is crucial to first examine its ageing performances at laboratory level. This paper focused on the effect of ageing on the electrical and physicochemical properties of PO, CO, and RBO. Sealed ageing experiments were set at 90°C for 30 days, 90 days and 180 days. Before the ageing process, the samples were dried in a vacuum oven at pressure less than 0.8kP at 85°C for 48 hours in order to remove the moisture content in the oils. Then the oils were impregnated with the Kraft paper and continue to age for selected duration time. The electrical properties (relative permittivity, dielectric losses, resistivity and breakdown strength), mechanical properties (viscosity and tensile strength) and chemical properties (moisture and acidity) of the oils were measured throughout the ageing periods. It can be concluded that the laboratory accelerated thermal ageing experiment reveals that all vegetable oils in this study are resistant towa

Vegetable oils are being considered as potential alternatives to mineral oil, due to their better environmental performance and for their high fire point. Although these liquids have been used in distribution transformer, it is still a significant step to adopt vegetable oils in power transformer due to high cost and high level of safety and reliability required in service for these units. Vegetable oils such as Palm oil (PO), Corn oil (CO), and Rice Bran oils (RBO) offer suitable alternative for mineral oil. It is anticipated that most of the un-aged oil could satisfy the minimum requirement for dielectric insulation liquids in transformer. However, since transformers in service could be subjected to heat and multiple environmental parameters, the oil could be subjected to ageing. The chemical properties of the oil may change and its performance could be affected by the presence of ageing-by-products such as moisture and acids. Therefore, considering the application of new dielectric insulation liquids such as PO, CO and RBO in transformer, it is crucial to first examine its ageing performances at laboratory level. This paper focused on the effect of ageing on the electrical and physicochemical properties of PO, CO, and RBO. Sealed ageing experiments were set at 90°C for 30 days, 90 days and 180 days. Before the ageing process, the samples were dried in a vacuum oven at pressure less than 0.8kP at 85°C for 48 hours in order to remove the moisture content in the oils. Then the oils were impregnated with the Kraft paper and continue to age for selected duration time. The electrical properties (relative permittivity, dielectric losses, resistivity and breakdown strength), mechanical properties (viscosity and tensile strength) and chemical properties (moisture and acidity) of the oils were measured throughout the ageing periods. It can be concluded that the laboratory accelerated thermal ageing experiment reveals that all vegetable oils in this study are resistant towa

Condition assessment of power components such as power transformers and their bushings depends on the interpretation of data obtained from the monitoring systems. Various defects in their insulation would behave differently under electrical stresses. Surface discharge on the oil-paper interface is one of the defects which can be responsible for the failure of those components. Power system transients can impose stresses on the insulation of the power transformers and their bushings. This study investigates the effect of transients such as lightning impulses on the surface discharge characteristics of oil-impregnated paper. Two configurations, needle and rod (IEC-b), are used here. Two distinctive situations occur on paper due to these different configurations. The corresponding effect is shown in the form of variation in the partial discharge numbers and phase-resolved patterns. In the needle electrode configuration, the paper remains un-aged and the applied impulses cause a prompt change in the total number of discharges which decays fast. However, with the rod electrode, the paper gets carbonized and the applied impulses cause a decrease in the total number of discharges. The influence of moisture content in oil-impregnated paper was also studied. For this case, the total number of discharges considerably increase after applying impulse., QC 20160405

This paper proposes a method for exploring technical phrase frames by extracting word n-grams that match our information needs and interests from research paper titles. Technical phrase frames, the outcome of our method, are phrases with wildcards that may be substituted for any technical term. Our method, first of all, extracts word trigrams from research paper titles and constructs a co-occurrence graph of the trigrams. Even by simply applying Page Rank algorithm to the co-occurrence graph, we obtain the trigrams that can be regarded as technical key phrases at the higher ranks in terms of Page Rank score. In contrast, our method assigns weights to the edges of the co-occurrence graph based on Jaccard similarity between trigrams and then apply weighted Page Rank algorithm. Consequently, we obtain widely different but more interesting results. While the top-ranked trigrams obtained by unweighted Page Rank have just a self-contained meaning, those obtained by our method are technical phrase frames, i.e., A word sequence that forms a complete technical phrase only after putting a technical word (or words) before or/and after it. We claim that our method is a useful tool for discovering important phrase logical patterns, which can expand query keywords for improving information retrieval performance and can also work as candidate phrasings in technical writing to make our research papers attractive., 29th IEEE International Conference on Advanced Information Networking and Applications Workshops, WAINA 2015; Gwangju; South Korea; 25 March 2015 through 27 March 2015, 2015 IEEE 29th International Conference on Advanced Information Networking and Applications Workshops (WAINA), 7096236; 2015

People often need help when filling out paper forms, because they do not fully understand the meaning of form fields. Commonly adopted solutions are referring to the form filling instructions or consulting other people. However, they are either inefficient or inconvenient. In this paper, we propose a situation-aware and interactive system, named Interact Form, to help people fill out paper forms. First, it provides an easy-to-use tool to build the knowledge offline about any given form. The knowledge includes the instruction and examples of each form field, and the constraints between fields. Then, when people are filling out a paper form, with the equipped video camera, the system can determine the field-grained position of the pen and provide text or audio instructions based on the user's form filling situations. When a pre-defined constraint is possibly going to be violated, the provided pen will send out an alert by vibration, and an explanation of the alert will also be given at the same time. We evaluate Interact Form with 60 paper form filling activities on 10 real-world paper forms, and the results show the usability of the system.

In the increasingly dynamic realities of today's software systems, it is no longer feasible to always expect human developers to react to changing environments and changing conditions immediately. Instead, software systems need to be self-aware and autonomously adapt their behavior according to their experiences gathered from their environment. Current research provides role-based modeling as a promising approach to handle the adaptivity and self-awareness within a software system. There are established role-based systems e.g., for application development, persistence, and so on. However, these are isolated approaches using the role-based model on their specific layer and mapping to existing non-role-based layers. We present a global runtime model covering the whole stack of a software system to maintain a global view of the current system state and model the interdependencies between the layers. This facilitates building holistic role-based software systems using the role concept on every single layer to exploit its full potential, particularly adaptivity and self-awareness.

In the increasingly dynamic realities of today's software systems, it is no longer feasible to always expect human developers to react to changing environments and changing conditions immediately. Instead, software systems need to be self-aware and autonomously adapt their behavior according to their experiences gathered from their environment. Current research provides role-based modeling as a promising approach to handle the adaptivity and self-awareness within a software system. There are established role-based systems e.g., for application development, persistence, and so on. However, these are isolated approaches using the role-based model on their specific layer and mapping to existing non-role-based layers. We present a global runtime model covering the whole stack of a software system to maintain a global view of the current system state and model the interdependencies between the layers. This facilitates building holistic role-based software systems using the role concept on every single layer to exploit its full potential, particularly adaptivity and self-awareness.

In the increasingly dynamic realities of today's software systems, it is no longer feasible to always expect human developers to react to changing environments and changing conditions immediately. Instead, software systems need to be self-aware and autonomously adapt their behavior according to their experiences gathered from their environment. Current research provides role-based modeling as a promising approach to handle the adaptivity and self-awareness within a software system. There are established role-based systems e.g., for application development, persistence, and so on. However, these are isolated approaches using the role-based model on their specific layer and mapping to existing non-role-based layers. We present a global runtime model covering the whole stack of a software system to maintain a global view of the current system state and model the interdependencies between the layers. This facilitates building holistic role-based software systems using the role concept on every single layer to exploit its full potential, particularly adaptivity and self-awareness.

In the increasingly dynamic realities of today's software systems, it is no longer feasible to always expect human developers to react to changing environments and changing conditions immediately. Instead, software systems need to be self-aware and autonomously adapt their behavior according to their experiences gathered from their environment. Current research provides role-based modeling as a promising approach to handle the adaptivity and self-awareness within a software system. There are established role-based systems e.g., for application development, persistence, and so on. However, these are isolated approaches using the role-based model on their specific layer and mapping to existing non-role-based layers. We present a global runtime model covering the whole stack of a software system to maintain a global view of the current system state and model the interdependencies between the layers. This facilitates building holistic role-based software systems using the role concept on every single layer to exploit its full potential, particularly adaptivity and self-awareness.

In this paper, we study path planning algorithms of resource constrained mobile agents in unknown cluttered environments, which include but are not limited to various terrestrial missions e.g., search and rescue missions by drones in jungles, and space missions e.g., navigation of rovers on the Moon. In particular, we focus our attention on artificial potential field (APF) based methods, in which the target is attractive while the obstacles are repulsive to the mobile agent. In this paper, we propose two major updates to the classical APF algorithm which significantly improve the performance of path planning using APF. First, we propose to improve an existing classical method that replaces the gradient descent optimization of the potential field cost function on a continuous domain with a combinatorial optimization on a set of predefined points (called bacteria points) around the agent's current location. Our proposition includes an adaptive hyperparameter that changes the value of the potential function associated to each bacteria point based on the current environmental measurements. Our proposed solution improves the navigation performance in terms of convergence to the target at the expense of minimal increase in computational complexity. Second, we propose an improved potential field cost function of the bacteria points by introducing a new branching cost function which further improves the navigation performance. The algorithms were tested on a set of Monte Carlo simulation trials where the environment changes for each trial. Our simulation results show 25% lower navigation time and around 300% higher success rate compared to the conventional potential field method, and we present future directions for research., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Signal Processing Systems

IEEE SA White Paper, The security aspects of V2V communications in UAS addressed by IEEE P1920.2 are delineated in this paper. Those include the architecture of communication interfaces, authentication of V2V parties, cryptographic key management, and zero trust architecture.

The 2nd workshop on Datasets for Developing Intelligent XR Applications (DATA4XR) aims to address the challenges of public datasets and reproducibility in Extended Reality, also known as XR (Augmented Reality, Virtual Reality, and Mixed Reality) research. The workshop brings together experts to discuss the availability, privacy concerns, and ethics related to open-sourcing the datasets used in XR research for algorithm training and user behavior analysis. By examining the ethical, moral, and privacy concerns and categorizing open-source datasets for XR, the workshop expects to advance XR research by incorporating artificial intelligence and defining a research agenda for XR in open science. In addition, the workshop focuses on involving the Human-Computer Interaction (HCI) community in exploring its role in the future of XR research. We invite submissions of technical papers, position papers, and research papers on topics related to XR and open science.

So far, the relationship between open science and software engineering expertise has largely focused on the open release of software engineering research insights and reproducible artifacts, in the form of open-access papers, open data, and open-source tools and libraries. In this position paper, we draw attention to another perspective: scientific insight itself is a complex and collaborative artifact under continuous development and in need of continuous quality assurance, and as such, has many parallels to software artifacts. Considering current calls for more open, collaborative and reproducible science; increasing demands for public accountability on matters of scientific integrity and credibility; methodological challenges coming with transdisciplinary science; political and communication tensions when scientific insight on societally relevant topics is to be translated to policy; and struggles to incentivize and reward academics who truly want to move into these directions beyond traditional publishing habits and cultures, we make the parallels between the emerging open science requirements and concepts already well-known in (open-source) software engineering research more explicit. We argue that the societal impact of software engineering expertise can reach far beyond the software engineering research community, and call upon the community members to proactively help driving the necessary systems and cultural changes towards more open and accountable research., Multimedia Computing

This paper considers fusion of dimension-reduced estimates in a decentralized sensor network. The benefits of a decentralized sensor network include modularity, robustness and flexibility. Moreover, since preprocessed data is exchanged between the agents it allows for reduced communication. Nevertheless, in certain applications the communication load is required to be reduced even further. One way to decrease the communication load is to exchange dimension-reduced estimates instead of full estimates. Previous work on this topic assumes global availability of covariance matrices, an assumption which is not realistic in decentralized applications. Hence, in this paper we consider the problem of deriving dimension-reduced estimates using only local information. The proposed solution is based on an estimate of the information common to the network. This common information estimate is computed locally at each agent by fusion of all information that is either received or transmitted by that agent. It is shown how the common information estimate is utilized for fusion of dimension-reduced estimates using two well-known fusion methods: the Kalman fuser which is optimal under the assumption of uncorrelated estimates, and covariance intersection. One main theoretical result is that the common information estimate allows for a decorrelation procedure such that uncorrelated estimates can be maintained. This property is crucial to be able to use the Kalman fuser without double counting of information. A numerical comparison suggests that the performance degradation of using the common information estimate, compared to having local access to the actual covariance matrices computed by other agents, is relatively small., Funding: Industry Excellence Center LINK-SIC - Swedish Governmental Agency for Innovation Systems (VINNOVA); Saab AB

Stock investment is a low barrier but high-risk approach of investing, which requires lots of knowledge and experience for investors in order to earn money. The work in this paper enables investors who do not meet the above conditions to still make accurate investment actions with the predicted output given by the model. In this paper, ten years of historical data of Amazon was used to train the LSTM model, then different candidates of model architecture were attempted to test out the optimal one for predicting the stock close price of Amazon and evaluated. It was observed in the result that the model with more neurons in each hidden layers and less LSTM layers and Dense layers showed a higher accuracy and a more stable forecast. In the other hand, the numbers of historical data memorized did matter. The less memory days could result in a smaller mean absolute percentage error. © 2023 IEEE.

This paper considers fusion of dimension-reduced estimates in a decentralized sensor network. The benefits of a decentralized sensor network include modularity, robustness and flexibility. Moreover, since preprocessed data is exchanged between the agents it allows for reduced communication. Nevertheless, in certain applications the communication load is required to be reduced even further. One way to decrease the communication load is to exchange dimension-reduced estimates instead of full estimates. Previous work on this topic assumes global availability of covariance matrices, an assumption which is not realistic in decentralized applications. Hence, in this paper we consider the problem of deriving dimension-reduced estimates using only local information. The proposed solution is based on an estimate of the information common to the network. This common information estimate is computed locally at each agent by fusion of all information that is either received or transmitted by that agent. It is shown how the common information estimate is utilized for fusion of dimension-reduced estimates using two well-known fusion methods: the Kalman fuser which is optimal under the assumption of uncorrelated estimates, and covariance intersection. One main theoretical result is that the common information estimate allows for a decorrelation procedure such that uncorrelated estimates can be maintained. This property is crucial to be able to use the Kalman fuser without double counting of information. A numerical comparison suggests that the performance degradation of using the common information estimate, compared to having local access to the actual covariance matrices computed by other agents, is relatively small., Funding: Industry Excellence Center LINK-SIC - Swedish Governmental Agency for Innovation Systems (VINNOVA); Saab AB

This paper considers fusion of dimension-reduced estimates in a decentralized sensor network. The benefits of a decentralized sensor network include modularity, robustness and flexibility. Moreover, since preprocessed data is exchanged between the agents it allows for reduced communication. Nevertheless, in certain applications the communication load is required to be reduced even further. One way to decrease the communication load is to exchange dimension-reduced estimates instead of full estimates. Previous work on this topic assumes global availability of covariance matrices, an assumption which is not realistic in decentralized applications. Hence, in this paper we consider the problem of deriving dimension-reduced estimates using only local information. The proposed solution is based on an estimate of the information common to the network. This common information estimate is computed locally at each agent by fusion of all information that is either received or transmitted by that agent. It is shown how the common information estimate is utilized for fusion of dimension-reduced estimates using two well-known fusion methods: the Kalman fuser which is optimal under the assumption of uncorrelated estimates, and covariance intersection. One main theoretical result is that the common information estimate allows for a decorrelation procedure such that uncorrelated estimates can be maintained. This property is crucial to be able to use the Kalman fuser without double counting of information. A numerical comparison suggests that the performance degradation of using the common information estimate, compared to having local access to the actual covariance matrices computed by other agents, is relatively small., Funding: Industry Excellence Center LINK-SIC - Swedish Governmental Agency for Innovation Systems (VINNOVA); Saab AB

This paper considers fusion of dimension-reduced estimates in a decentralized sensor network. The benefits of a decentralized sensor network include modularity, robustness and flexibility. Moreover, since preprocessed data is exchanged between the agents it allows for reduced communication. Nevertheless, in certain applications the communication load is required to be reduced even further. One way to decrease the communication load is to exchange dimension-reduced estimates instead of full estimates. Previous work on this topic assumes global availability of covariance matrices, an assumption which is not realistic in decentralized applications. Hence, in this paper we consider the problem of deriving dimension-reduced estimates using only local information. The proposed solution is based on an estimate of the information common to the network. This common information estimate is computed locally at each agent by fusion of all information that is either received or transmitted by that agent. It is shown how the common information estimate is utilized for fusion of dimension-reduced estimates using two well-known fusion methods: the Kalman fuser which is optimal under the assumption of uncorrelated estimates, and covariance intersection. One main theoretical result is that the common information estimate allows for a decorrelation procedure such that uncorrelated estimates can be maintained. This property is crucial to be able to use the Kalman fuser without double counting of information. A numerical comparison suggests that the performance degradation of using the common information estimate, compared to having local access to the actual covariance matrices computed by other agents, is relatively small., Funding: Industry Excellence Center LINK-SIC - Swedish Governmental Agency for Innovation Systems (VINNOVA); Saab AB

We propose a new blind watermarking algorithm for three-dimensional (3D) printed objects that has applications in metadata embedding, robotic grasping, counterfeit prevention, and crime investigation. Our method can be used on fused deposition modeling (FDM) 3D printers and works by modifying the printed layer thickness on small patches of the surface of an object. These patches can be applied to multiple regions of the object, thereby making it resistant to various attacks such as cropping, local deformation, local surface degradation, or printing errors. The novelties of our method are the use of the thickness of printed layers as a one-dimensional carrier signal to embed data, the minimization of distortion by only modifying the layers locally, and one-shot detection using a common paper scanner. To correct encoding or decoding errors, our method combines multiple patches and uses a two-dimensional (2D) parity check to estimate the error probability of each bit to obtain a higher correction rate than a naive majority vote. The parity bits included in the patches have a double purpose because, in addition to error detection, they are also used to identify the orientation of the patches. In our experiments, we successfully embedded a watermark into flat surfaces of 3D objects with various filament colors using a standard FDM 3D printer, extracted it using a common 2D paper scanner and evaluated the sensitivity to surface degradation and signal amplitude.

This paper proposes a novel method for generating arbitrary stereoscopic view from multiple omni directional image sequences. Although conventional methods for arbitrary view generation with an image-based rendering approach can create binocular views, positions and directions of viewpoints for stereoscopic vision are limited to a small range. In this research, we attempt to generate arbitrary stereoscopic views from omni directional image sequences that are captured in various multiple paths. To generate a high-quality stereoscopic view from a number of images captured at various viewpoints, appropriate ray information needs to be selected. In this paper, appropriate ray information is selected from a number of omni directional images using a penalty function expressed as ray similarity. In experiments, we show the validity of this penalty function by generating stereoscopic view from multiple real image sequences., ICPR 2010 : 20th International Conference on Pattern Recognition , Aug 23-26, 2010 , Istanbul, Turkey

In this paper, a barge-in free spoken dialogue system using sound field control and microphone array is proposed. In the conventional spoken dialogue system using an acoustic echo canceller, it is indispensable to estimate and update the room transfer function, especially when the transfer function is changed by various interferences. However the estimation process for the transfer function prevents the user from speaking freely and simultaneously with speech responses from the system. In order to resolve the problem, we have already proposed a barge-in free spoken dialogue system that controls a sound field using multiple loudspeakers. In this paper, a microphone array for acquisition of user's speech is newly introduced in the previously proposed system. By introducing the microphone array, we can reduce the number of loudspeakers to be required in the system, and make the interface for spoken dialogue system more robust against the change of room transfer functions., ICASSP2003: IEEE International Conference on Acoustics, Speech, and Signal Processing, April 6-10, 2003, Hong Kong, China.

This paper describes a new blind signal separation method using the directivity patterns of a microphone array. In this method, to deal with the arriving lags among each microphone, the inverses of the mixing matrices are calculated in the frequency domain so that the separated signals are mutually independent. Since the calculations are carried out in each frequency independently, the following problems arise: (1) permutation of each sound source, (2) arbitrariness of each source gain. In this paper, we propose a new solution that directivity patterns are explicitly used to estimate each sound source direction. As the results of signal separation experiments, it is shown that the proposed method improves the SNR of degraded speech by about 16 dB under non-reverberant condition. Also, the proposed method improves the SNR by 8.7 dB when the reverberation time is 184 ms, and by 5.1 dB when the reverberation time is 322 ms, ICASSP2000: IEEE International Conference on Acoustics, Speech, and Signal Processing, June 5-9, 2000, Istanbul, Turkey.

Deals with the recognition of distant talking speech and, particularly, with the simultaneous recognition of multiple sound sources. A problem that must be solved in the recognition of distant talking speech is talker localization. In some approaches, the talker is localized by using short- and long-term power. The 3-D Viterbi search based method proposed by Yamada et al.(1998), integrates talker localization and speech recognition. This method provides high recognition rates but its application is restricted to the presence of one talker. In order to deal with multiple talkers, we extended the 3-D Viterbi search method to a 3-D N-best search method enabling the recognition of multiple sound sources. The paper describes our baseline 3-D N-best search-based system and two additional techniques, namely, a likelihood normalization technique and a path distance-based clustering technique. The paper also describes experiments carried out in order to evaluate the performance of the system, ICASSP2001: IEEE International Conference on Acoustics, Speech and Signal Processing, May 7-11, 2001, Salt Lake City, Utah, US.