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A systematic method for designing reconfigurable compact multiple-input multiple-output (MIMO) antennas is described. This method is based on the analysis of a general loaded N - port structure in beamspace domain and is use-ful in optimizing various compact MIMO antennas for next-generation wireless communication. In this method, multiple streams of symbols are mapped onto a set of orthogonal far-field radiation patterns. Then by finding the required loads, the desired radiation patterns can be excited to transmit symbols. Leveraging this method, in this paper, we focus on two MIMO antenna configurations, including single-radio-frequency (RF) electronically steerable parasitic array radiator (ESPAR) and multi-RF compact antenna, and provide efficient optimization methods to find the optimal MIMO antenna design with load values. Simulation results show that by using the proposed method, the single-RF ESPAR can significantly improve the energy efficiency (EE) while achieving close spectral efficiency (SE) when compared with conventional MIMO antennas. In addition for the multi-RF compact antenna, the mutual coupling can be efficiently suppressed by generating orthogonal radiation patterns at multiple ports and the resulting SE can achieve the channel capacity bound. © 2023 IEEE.

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.

Reconstructing simplicial signals, e.g., signals defined on nodes, edges, triangles, etc., of a network, from (partial) noisy observation is of interest in water/traffic flow estimation or currency exchange markets. Typically, this concerns solving a regularised problem w.r.t. the l2 norm of the divergence or the curl of the signal, i.e., the netflows at nodes and in triangles. Realworld simplicial signals are intrinsically divergence- or curl-free, which makes l2 regularizers inapplicable. To overcome this, we develop a simplicial trend filter (STF) by regularising the total divergence and the curl via their l1 norm. By tuning two scalars, the STF can reduce independently the divergence and curl much more than smooth filtering, leading to a better reconstructed signal. The SFT is a convex problem and can be solved by fast iterative algorithms. We apply the SFT to interpolation and denoising tasks in forex and music/artist transition recordings and show its superior performance to alternatives., 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. Funding Information: Emails: m.yang-2, e.isufi-1@tudelft.nl. This work is supported by the TU Delft AI Labs Programme., Multimedia Computing

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.

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.

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.

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.

This short paper presents an architectural overview of an agent-based framework called iv4XR for automated testing that is currently under development by an H2020 project with the same name. The framework’s intended main use case of is testing the family of Extended Reality (XR) based systems (e.g. 3D games, VR sytems, AR systems), though the approach can indeed be adapted to target other types of interactive systems. The framework is unique in that it is an agent-based system. Agents are inherently reactive, and therefore are arguably a natural match to deal with interactive systems. Moreover, it is also a natural vessel for mounting and combining different AI capabilities, e.g. reasoning, navigation, and learning.

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.

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.

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.

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.

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 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.

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)

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.

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

Traveling-wave tube amplifiers (TWTAs) are common power amplifiers in satellite communications. Saturation and warping effects caused by the nonlinearity make constellation shaping a non-trivial task, when nonlinear amplifiers are involved in the channel. Constellation shaping optimizes geometry and probability of occurrence of constellation points to maximize the mutual information. This paper newly introduces constellation shaping using neural networks to satellite communications by showing its benefits on channels with TWTAs. We study how the TWTA nonlinearity impacts learned constellations both in terms of geometry and point probability of occurrence. The peak-power constraint introduced by TWTA saturation leads to a decreased impact of probabilistic shaping compared to geometric shaping which is illustrated using mutual information curves and displayed constellations. The tuning of the input backoff (IBO) of the TWTA causes an additional trade-off between transmit power at the cost of more severe nonlinear effects. This paper makes a new contribution by training IBO and transmit constellation jointly for TWTAs. By displaying constellations at different IBOs the interdependency of constellation shaping and IBO optimization is motivated. Total degradation analysis on mutual information curves resulting from the cross-entropy loss of the autoencoder illustrates the impact of joint IBO training and constellation shaping. A study of coded bit error rate performance and comparison to conventional constellations with memoryless predistortion emphasizes the effectiveness of training IBO and constellation jointly using autoencoders.

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

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.

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.

This feasibility study deals with Air to Ground (ATG) communications between a 5G type Terrestrial Mobile Communication Network (TMCN) and an User Equipment (UE) installed onboard a passenger aircraft in approach to an airport. The network model is based on real gNodeB (gNB) deployment data and optimized for serving terrestrial UEs. The evaluation concerns a scenario in which the passenger aircraft is supported by a remote operator via an ATG link to assist its safe landing. To mitigate the interference expected to arise in ATG communications, the aircraft is assumed to be equipped with an Active Electronically Scanned Array (AESA). The simulation results discussed in this paper address the Signal to Interference power Ratio (SIR), link availability, and handover process during ATG communications along representative approach trajectories for different AESA configurations and levels of support by the TMCN. It is shown that SIR above 30 dB and link availability upto 97.7% can be achieved by using an 8 x 8 AESA at the aircraft when the network provides support in the form of dedicated radio resources. It is observed that the frequency of handovers increases with improving link quality.

With the recent development of the Virtual Reality (VR) industry, the increasing number of VR users pushes the demand for the massive production of immersive and expressive VR scenes in related industries. However, creating expressive VR scenes involves the reasonable organization of various digital content to express a coherent and logical theme, which is time-consuming and labor-intensive. In recent years, Large Language Models (LLMs) such as ChatGPT 3.5 and generative models such as stable diffusion have emerged as powerful tools for comprehending natural language and generating digital contents such as text, code, images, and 3D objects. In this paper, we have explored how we can generate VR scenes from text by incorporating LLMs and various generative models into an automated system. To achieve this, we first identify the possible limitations of LLMs for an automated system and propose a systematic framework to mitigate them. Subsequently, we developed Text2VRScene, a VR scene generation system, based on our proposed framework with well-designed prompts. To validate the effectiveness of our proposed framework and the designed prompts, we carry out a series of test cases. The results show that the proposed framework contributes to improving the reliability of the system and the quality of the generated VR scenes. The results also illustrate the promising performance of the Text2VRScene in generating satisfying VR scenes with a clear theme regularized by our well-designed prompts. This paper ends with a discussion about the limitations of the current system and the potential of developing similar generation systems based on our framework. © 2024 IEEE.

This paper presents a thorough review of the evolution of Stacked Complementary Field-Effect transistors (CFET), including earlier work and recent demonstrations. The study outlines the challenges encountered during the fabrication process, such as insulator formation between active layers, deep ion implantation for bottom devices, selective contact between top and bottom transistors, and the layout of stacked transistors. Additionally, this paper explores the potential extension of the CFET technology and its integration with emerging device structures and advanced materials, such as 2D transistors. By analyzing these possibilities, this study sheds light on the potential for further advancements and applications of the CFET technology. © 2024 IEEE.

Neural Radiance Fields (NeRF) have shown impressive capabilities for photorealistic novel view synthesis when trained on dense inputs. However when trained on sparse inputs NeRF typically encounters issues of incorrect density or color predictions mainly due to insufficient coverage of the scene causing partial and sparse supervision thus leading to significant performance degradation. While existing works mainly consider ray-level consistency to construct 2D learning regularization based on rendered color depth or semantics on image planes in this paper we propose a novel approach that models 3D spatial field consistency to improve NeRF's performance with sparse inputs. Specifically we first adopt a voxel-based ray sampling strategy to ensure that the sampled rays intersect with a certain voxel in 3D space. We then randomly sample additional points within the voxel and apply a Transformer to infer the properties of other points on each ray which are then incorporated into the volume rendering. By backpropagating through the rendering loss we enhance the consistency among neighboring points. Additionally we propose to use a contrastive loss on the encoder output of the Transformer to further improve consistency within each voxel. Experiments demonstrate that our method yields significant improvement over different radiance fields in the sparse inputs setting and achieves comparable performance with current works. The project page for this paper is available at https://zhongyingji.github.io/CVT-xRF.

This paper adopts a methodology to assess and rank the severity of the most frequent disturbances, 3 types in particular, that occur in the Mexican Interconnected System (MIS) when wind power plants (WPPs) are integrated. This is done by combining three stability indices from which an overall performance measure can be derived. In this way, it is possible to assess the severity of the disturbances such as generation tripping, line tripping and disconnection of loads. The indices under consideration include measures such as maximum amplitude, speed variation, and the Lyapunov exponent. For ranking the severity, a general index value is used. To confirm the effectiveness and performance of the proposed methodology, this paper investigates the 190-bus and 46-generator MIS equipped with an 8% of wind generation to quantitatively evaluate the severity of disturbances, resulting in 66% of unstable disturbances which are associated with the disconnection of loads.

A balance optimization method has been employed to determine the quantity of toxic emissions particularly in emissions to air, fresh water, sea water and industrial soil, in production process of polymer and paper based RFID tags. We have developed a low profile antenna design for passive UHF RFID tags using both polymer and paper substrate with copper and aluminum for the antenna trace. Comparative analysis of toxic emissions during production process of polymer and paper based RFID antennas have been discussed in this paper. Our results show that paper based RFID antennas yield lower organic emissions to the environment while considerably higher inorganic emissions to the air. The results also depict that air is highly affected with the toxic emissions compared to fresh water, sea water and industrial soil., QC 20221004

This paper presents a hybrid wearable bio-sensing system, which combines traditional small-area low-power and high-performance System-on-Chip (SoC), flexible paper substrate and cost-effective Printed Electronics. Differential bio-signals are measured, digitized, stored and transmitted by the SoC. The total area of the chip is 1.5 × 3.0 mm2. This enables the miniaturization of the wearable system. The electrodes and interconnects are inkjet printed on paper substrate and the performance is verified in in-vivo tests. The quality of electrocardiogram signal sensed by printed electrodes is comparable with commercial electrodes, with noise level slightly increased. The paper-based inkjet printed system is flexible, light and thin, which makes the final system comfortable for end-users. The hybrid bio-sensing system offers a potential solution to the next generation wearable healthcare technology., QC 20130121

High voltage impulses in electrical power systems are mainly caused by lightning strikes and switching operations. The dielectric properties of a particular insulation at the instant of interaction with a high voltage impulse would determine the level of the degradation of the electrical insulation caused by the high voltage impulse. In this work, the effect of high voltage impulses on the partial discharge (PD) parameters was investigated. The investigation was done in test samples consisting of a cavity deliberately introduced between oil-impregnated papers used in power transformer bushings. The measurement results presented in this paper show that high voltage impulses can have a large impact on the behavior of the PD parameters if the test sample is aged by partial discharges, but a smaller impact when the test sample is unaged., QC 20121115