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An emerging alternative to conventional Augmented Reality (AR) glasses designs, Beaming displays promise slim AR glasses free from challenging design trade-offs, including battery-related limits or computational budget-related issues. These beaming displays remove active components such as batteries and electronics from AR glasses and move them to a projector that projects images to a user from a distance (1-2 meters), where users wear only passive optical eyepieces. However, earlier implementations of these displays delivered poor resolutions (7 cycles per degree) without any optical focus cues and were introduced with a bulky form-factor eyepiece (50 mm thick). This paper introduces a new milestone for beaming displays, which we call HoloBeam. In this new design, a custom holographic projector populates a micro-volume located at some distance (1-2 meters) with multiple planes of images. Users view magnified copies of these images from this small volume with the help of an eyepiece that is either a Holographic Optical Element (HOE) or a set of lenses. Our HoloBeam prototypes demonstrate the thinnest AR glasses to date with a submillimeter thickness (e.g., HOE film is only 120 um thick). In addition, HoloBeam prototypes demonstrate near retinal resolutions (24 cycles per degree) with a 70 degrees-wide field of view., Comment: 15 pages, 18 Figures, 1 Table, 1 Listing

In this work, Schottky diodes based on amorphous indium-gallium-zinc-oxide (IGZO) were fabricated on cellulose microfiber paper substrate. Silver lines used as the Schottky barrier were printed, in parallel to thermally evaporated Cr/Au ohmic contact, using a dispense printer. The morphological and electrical characteristics of the devices are presented. The fabricated diodes exhibited rectification ratios ranging from 3.4 to 34.9 at ±1V with ON voltages that range from 1.1V to 1.4 V, for device lengths (Ag to Au distance) from 145 µm to 894 µm. The diodes were characterized in a temperature range between 25°C and 80°C. They showed a decrease of the ON current when increasing temperature, which is mainly attributed to the change of the cellulose microstructure. Indeed, an opposite of the ON current behavior was registered when the diode was realized on a polyimide substrate. The realized flexible paper-based diodes offer a potential promising choice for printed environmental-friendly electronics.

The single-mode bosonic channel is addressed with classical interference in the modulation and with side information at the transmitter. This model can viewed as the quantum counterpart of the classical random-parameter Gaussian channel. Based on Costa's writing-on-dirty-paper result (1983), the effect of the channel parameter can be canceled even when the decoder has no side information, and regardless of the input power constraint. For both homodyne and heterodyne detection with a coherent-state protocol, the model reduces to a classical channel with either real or complex-valued Gaussian noise. Thereby, by applying Costa's dirty paper coding strategy, we observe that the effect of the classical interference can be canceled for those channels as well. Then, we consider the bosonic channel with joint detection, for which the classical results do not apply, and derive a dirty-paper coding lower bound. Furthermore, considering the special case of a pure-loss bosonic channel, we demonstrate that the optimal coefficient for dirty paper coding is not necessarily the MMSE estimator coefficient as in the classical setting.

Ultraviolet (UV) irradiation was used as a tool Kraft paper. Using measurements of the DP as a function of irradiation time, a theoretical model was used to predict the local value of DP in the surface layer of the paper. After characterization of their mechanical properties, selected samples were exposed to oil flows mimicking ONAN, OFAF and reclamation conditions. The presence of a surface layer of low D Pled to significant surface roughening under high rates of oil flow,but no significant erosion. The findings indicate that the DP value at the surface is more critical than the average (or measured) D Pin determining the extent of oil flow related damage.

The time-to-failure for oil-impregnated paper (OIP) insulation is governed by two primary aging mechanisms: electrical and thermal. The electrical life can be represented as an Inverse Power Law, where lifetime is inversely proportional to applied electric field. The process of thermal aging on the other hand is established by Arrhenius Law, which relates the rate of aging exponentially to temperature. Due to thermal aging, the structure of insulation is altered owing to chemical changes like oxidation, polymerization, and cellulose degradation. For life estimation of a service-aged high-pressure gas filled (HPGF) cables, electrical endurance tests are normally performed at controlled voltage levels to estimate the time to breakdown. However, it is equally necessary to investigate how thermal aging influence changes in the electrical life of insulation. Therefore, in this paper, firstly short-term ramped stress tests are carried out on elevated thermal aged OIP samples extracted from already field-aged HPGF to find a rough estimate of breakdown voltages at different temperatures. Then, long-term electro-thermal step stress tests are performed on the samples to establish a correlation of temperature on the electrical life of the OIP insulation. The long-term stress tests produce reliable breakdown statistics and Maximum Likelihood Estimation of Inverse Power Law fitted on 2-parameter Weibull distributed breakdown data indicate a reduction of model parameter, n from 13.61 to 7.38 with an increase in temperature from 45 to 75 °C and a constant shape factor, beta of 1.50. The dissipation factor, tandelta related to the aging also shows an increase with temperature across a wide frequency range and is inversely proportional to the breakdown voltage.

Inclusion and accessibility in visualization research have gained increasing attention in recent years. However, many challenges still remain to be solved on the road toward a more inclusive, shared-experience-driven visualization design and evaluation process. In this position paper, we discuss challenges and speculate about potential solutions, based on related work, our own research, as well as personal experiences. The goal of this paper is to start discussions on the role of accessibility and inclusion in visualization design and evaluation., Comment: 8 pages, IEEE VIS BELIV 2022 workshop, preprint

Memory corruption bugs continue to plague lowlevel systems software, generally written in unsafe programming languages. In order to detect and protect against such exploits, many pre- and post-deployment techniques exist. In this position paper, we propose and motivate the need for a hybrid approach for the protection against memory safety vulnerabilities, combining techniques that can identify the presence (and absence) of vulnerabilities pre-deployment with those that can detect and mitigate such vulnerabilities post-deployment. Our proposed hybrid approach involves three layers: hardware runtime protection provided by capability hardware, software runtime protection provided by compiler instrumentation, and static analysis provided by bounded model checking and symbolic execution. The key aspect of the proposed hybrid approach is that the protection offered is greater than the sum of its parts – the expense of postdeployment runtime checks is potentially reduced via information obtained during pre-deployment analysis. During pre-deployment analysis, static checking can be guided by runtime information.

International audience; This paper presents the design and characterisation of an antenna on a paper-based substrate. The antenna is designed on a nanocellulose foil optimised with a highly conductive ink based on silver nanoparticles. The electrical and dielectric properties of the materials were characterised prior to the antenna simulation. The antenna is designed to operate at the ISM 868 MHz frequency band and has a maximum gain of +1.7 dBi. Its development is part of the first step in the implementation of a flexible battery-free geolocation tag, remotely powered by UHF Energy sources in the European RFID spectrum between 865.6 MHz and 867.6 MHz. An accurate characterisation procedure was carried out and the results show good agreement with the simulations.

The use of vegetable oil (natural ester) in electrical devices like power transformers is increasing due to their high biodegradability and better safety. The lifespan of power trans- formers is mainly defined by cellulose insulation condition, which usually works together with dielectric oil as electrical insulation and also as mechanical winding protector and compactor. That is why the aim and results of this research shows us not only the dielectric parameters evolution, but also the relationship between the mechanical factors and the moisture content of thermal accelerated ageing processes, with commercial vegetable oil, of Kraft paper and Diamond Dotted Paper (DDP). These are two of the most common insulating materials in electric power transformers. In addition, the new tests have been done by a different method of paper ageing analysis. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement Nº 823969 - BIOTRAFO.

The deterioration of the insulation in the windings of power transformers affects their lifespan. A commercial insulated Continuously Transposed Conductor (CTC) was studied experimentally, numerically and analytically. The purpose was to understand the mechanisms governing the mechanical failure of the insulating paper, and to achieve a criterion for predicting failure under different conditions. Samples of that insulated CTC were extracted from a coil and aged at 150∘C for different durations inside vessels filled with naphthenic oil. Then the degree of polymerisation and tensile, compressive and shear mechanical properties of the insulation were measured/estimated. Aged insulated CTC samples were subjected to three-point bending tests, producing deformations compatible with a short circuit, and the fractures in the insulation were analysed. The bending test over a CTC sample was simulated by means of a FEM Program. The Norris failure model, applicable to a lamina, was adapted to the studied insulation materials. The predictions of that failure criterion agreed with experimental observations.

With increasing demands on capacity and height- ened user density, it is imperative to propose approaches that exploit and utilise all possible degrees of freedom (DoF) of a MIMO system. This directly translates to increased channel estimation accuracy. With this motivation, in this paper, a novel MIMO antenna array system with a receiver of N antennas that includes a joint estimation of Direction-of-Arrival (DOA) and Direction-of-Departure (DOD) of the desired user in the presence of other multiple access users, is presented. This is achieved by using the concept of the “Manifold Extender” which increases the dimensionality of the observation space of the received vector- signals, and thus increases the DoF from N to N Next where Next is the extended dimension. The performance of the receiver is evaluated against the existing spatial-only and virtual receivers by computer simulation studies.

This paper is the first to provide a thorough system design overview along with the fusion methods selection criteria of a real-world cooperative autonomous driving system, named Infrastructure-Augmented Autonomous Driving or IAAD. We present an in-depth introduction of the IAAD hardware and software on both road-side and vehicle-side computing and communication platforms. We extensively characterize the IAAD system in the context of real-world deployment scenarios and observe that the network condition that fluctuates along the road is currently the main technical roadblock for cooperative autonomous driving. To address this challenge, we propose new fusion methods, dubbed "inter-frame fusion" and "planning fusion" to complement the current state-of-the-art "intra-frame fusion". We demonstrate that each fusion method has its own benefit and constraint.

We often point to the relative increase in the amount and sophistication of evaluations of visualization systems versus the earliest days of the field as evidence that we are maturing as a field. I am not so convinced. In particular, I feel that evaluations of visualizations, as they are ordinarily performed in the field or asked for by reviewers, fail to tell us very much that is useful or transferable about visualization systems, regardless of the statistical rigor or ecological validity of the evaluation. Through a series of thought experiments, I show how our current conceptions of visualization evaluations can be incomplete, capricious, or useless for the goal of furthering the field, more in line with the “heroic age” of medical science than the rigorous evidence-based field we might aspire to be. I conclude by suggesting that our models for designing evaluations, and our priorities as a field, should be revisited.

The exchange of academic marks between HEIs (Higher Education Institutions) is mandatory in every student mobility programs (i.e. the EU Erasmus Program) but that process remains to present date with insufficient technological support and the absence of a comprehensive reference model that allows the integration of potential technological solutions for the exchange of academic data with existing Academic Information Systems seems to limit greatly the possibility of adopting solutions of this type referred to in the existing literature. This work addresses this issue, conducting an initial bibliographic review aimed at the identification of the fundamental requirements of such an architecture as well as explores some of the technologies that are showing potential for usage in the safe exchange of academic results between partner HEIs, with particular interest in blockchain technology applied in an educational context. info:eu-repo/semantics/publishedVersion

The modern HPC scientific software ecosystem is instrumental to the practice of science. However, software can only fulfill that role if it is readily usable. In this position paper, we discuss usability in the context of scientific software development, how usability engineering can be incorporated into current practice, and how software engineering research can help satisfy that objective.

In HVDC converter transformers, the potential DC component in electric stresses imposed on valve windings would unfavorably cause space charge accumulation inside oil-paper insulation. Insulation degradation and aging may have great effects on space charge behaviors in oil-paper insulation. This paper focuses on the effect of the low molecular weight (LMA) and the moisture on space charge phenomenon in oil impregnated-paper insulation. Pulsed electro-acoustic (PEA) technique was used in this study to measure space charge behaviors in 400 $\mu$ m thick, dry and moist single-layer paper sample impregnated in mineral oil prepared with different amounts of formic acid. The measurements were carried out at $30 ^ { \circ } \mathrm { C }$ under a field strength of 20 kV/mm. It was found that LMA greatly strengthens the homo charge accumulation. The combination of LMA and moisture results in even more active space charge accumulations. In dry samples, the existence of LMA causes slower charge decaying rate. However, the introduction of the moisture accelerates the charge dissipation.

This paper focuses on the potential and practice of alternative forms of assessment to the conventional written exam. Readers will be interested in issues such as why would a staff member want to replace the written exam and how can I be sure that the replacement is equally effective at capturing student attainment. The paper summarises a trial at the University of Sheffield where the written exam was replaced by a computer quiz which was marked automatically.

International audience; The design of a dipole antenna printed on a paper substrate is presented in this paper. The antenna which integrates a compact balun is devoted for dual-band 2.4/5 GHz WLAN applications. The antenna is based on a double-side printed multilayer paper substrate and is fed with a coaxial cable for the testing. The simulated results of the whole structure are also presented in detail and compared with the measured performances.

Space charge is a major issue that hinders the development of HVDC polymeric cables. On the other hand, HVDC cables with polypropylene laminated paper (PPLP) insulation has been in operation for a long time with a good record. In the present paper, the electrical performance of PPLP insulation has been studied to understand the reasons for its excellent characteristics. It has been found that the charge accumulated at the interface between PP and Kraft paper plays a key role in determining electrical performance of PPLP insulation. The formation of the interfacial charge results in an optimal electric field distribution for PPLP insulation system as well as a small and electric field independent conductivity.

Image classification is a major application domain for conventional deep learning (DL). Quantum machine learning (QML) has the potential to revolutionize image classification. In any typical DL-based image classification, we use convolutional neural network (CNN) to extract features from the image and multi-layer perceptron network (MLP) to create the actual decision boundaries. On one hand, QML models can be useful in both of these tasks. Convolution with parameterized quantum circuits (Quanvolution) can extract rich features from the images. On the other hand, quantum neural network (QNN) models can create complex decision boundaries. Therefore, Quanvolution and QNN can be used to create an end-to-end QML model for image classification. Alternatively, we can extract image features separately using classical dimension reduction techniques such as, Principal Components Analysis (PCA) or Convolutional Autoencoder (CAE) and use the extracted features to train a QNN. We review two proposals on quantum-classical hybrid ML models for image classification namely, Quanvolutional Neural Network and dimension reduction using a classical algorithm followed by QNN. Particularly, we make a case for trainable filters in Quanvolution and CAE-based feature extraction for image datasets (instead of dimension reduction using linear transformations such as, PCA). We discuss various design choices, potential opportunities, and drawbacks of these models. We also release a Python-based framework to create and explore these hybrid models with a variety of design choices.

The formulation of good academic paper titles in English is challenging for intermediate English authors (particularly students). This is because such authors are not aware of the type of titles that are generally in use. We aim to realize a support system for formulating more effective English titles for intermediate English and beginner authors. This study develops an extractive title generation system that formulates titles from keywords extracted from an abstract. Moreover, we realize a title evaluation model that can evaluate the appropriateness of paper titles. We train the model with titles of top-conference papers by using BERT. This paper describes the training data, implementation, and experimental results. The results show that our evaluation model can identify top-conference titles more effectively than intermediate English and beginner students., 6 pages, 3 figures, 4 tables, 2 algorithms

Our understanding of COVID-19 pandemic epidemiology has many gaps, with many challenges arising on a global scale. This paper looks at the problem at a smaller geographical scale, the extent of the campus of a large organization. Equipped with an asymptomatic testing program and rough location data from the campus wireless network, we make the case that epidemiological models may be informed from this new source of data, which offers fidelity at the temporal resolution of seconds and spatial resolution of a Wi-Fi cell size, in particular for the tasks of pinpointing clusters of cases and contexts of infection transmission. We sketch the design of a system that fuses the two foregoing information streams and explain how the result can be incorporated into standard epidemiological models of communicable disease, both for better parameter estimation in elementary models, as well as for providing spatial inputs into more sophisticated models. We conclude with logistical and privacy considerations we have encountered in an associated ongoing study, to inform similar efforts at other organizations.

The amount of scholarly data has been increasing dramatically over the last years. For newcomers to a particular science domain (e.g., IR, physics, NLP) it is often difficult to spot larger trends and to position the latest research in the context of prior scientific achievements and breakthroughs. Similarly, researchers in the history of science are interested in tools that allow them to analyze and visualize changes in particular scientific domains. Temporal summarization and related methods should be then useful for making sense of large volumes of scientific discourse data aggregated over time. We demonstrate a novel approach to analyze the collections of research papers published over longer time periods to provide a high-level overview of important semantic changes that occurred over the progress of time. Our approach is based on comparing word semantic representations over time and aims to support users in a better understanding of large domain-focused archives of scholarly publications. As an example dataset we use the ACL Anthology Reference Corpus that spans from 1979 to 2015 and contains 22,878 scholarly articles., Comment: 4 pages, JCDL-2021

The uneven utilisation of modes of transport has a big impact on traffic in transport pathway infrastrutures. For motor vehicles for instance, this situation explains rapid road deterioration and the large amounts of money invested in maintenance and development due to overuse. There are many approaches to managing this problem; however, the impact of individual users in infrastructural maintenance is mostly ignored. In this position paper, we hypothesise that important changes torwards a more efficient use of the transport network start with its users and their behavioural changes. To this end, we introduce our vision on how to employ data driven, intelligent agent-based modelling, incorporating human factors aspects, as a toolset to understand travellers and to stimulate behavioural changes. The aim is to achieve better balanced and integrated mobility usage within the transport network. The idea is explored with a few guided questions, and a methodology is proposed. We employ 1) cognitive work analysis to investigate the reasons for travellers' mode choice; 2) computational intelligence to extract and represent knowledge from related datasets; 3) agent-based modelling to represent the real-world and to observe both individual and emergent behaviours. Future directions to adapt our methodology to alternative smart mobility projects are also discussed.

Replications are rare in visualization research, but if they were more common, it is not unreasonable to believe that they would show a similar rate of unreproducible results as in the psychological and social sciences. While a replication crisis in visualization research would be a helpful wake-up call, examining and correcting the underlying problems in many studies is ultimately more productive.In this paper, we survey the state of replication in visualization research. We examine six threats to the validity of studies in visualization and suggest ways to address them. Finally, we describe possible models for publishing replications that satisfy the novelty criterion that can keep replications from being accepted.

Machine learning (ML) components are increasingly adopted in many automated systems. Their ability to learn and work with novel input/incomplete knowledge and their generalization capabilities make them highly desirable solutions for complex problems. This has motivated the inclusion of ML techniques/components in products for many industrial domains including automotive systems. Such systems are safety-critical systems since their failure may cause death or injury to humans. Therefore, their safety must be ensured before they are used in their operational environment. However, existing safety standards and Verification and Validation (V&V) techniques do not properly address the special characteristics of ML-based components such as non-determinism, non-transparency, instability. This position paper presents the authors' view on the safety of automotive systems incorporating ML-based components, and it is intended to motivate and sketch a research agenda for extending a safety standard, namely ISO 26262, to address challenges posed by incorporating ML-based components in automotive systems.

In the era of emerging Smart Built Environments (SBEs), a smart house, unlike regular houses with static "components", consists of numerous interconnected and often actuated devices, capable of executing tasks independent of user supervision. Living in such a SBE, where for example, the furniture can rearrange itself, and the doors open and close of their own volition, may be difficult and unpredictable. Furthermore, cyber-security attacks and intrusion could allow attackers to assume control of the SBE, damage its components and to potentially harm its inhabitants. Such novel characteristics of SBEs present developers with several unique challenges with regards to implementing the needed safety and security measures and protocols that go along with them. With such environments, therefore, there is a need for a system that is capable of monitoring user activities in real-time, identifying the safety and security hazards to users in their immediate local context, warning users of these hazards, and perhaps even taking preventative and mitigative action against the hazards that it identified. In this paper, we survey some of these challenges and explore the design and implementation of a system designed around the safety and security of SBE inhabitants. We propose an approach to modeling SBE safety that combines the three laws of robotics and the swarm behavior model. We also present a preliminary prototype and discuss a case study.

There has been an increase in the interest in blockchain technologies. While the most popular application of this technology is in the cryptocurrency sector in the developed world, recent studies have shown that they hold promise toward deployment in many sectors such as digital contracts and healthcare in the developing world. This article discusses the various use cases of the blockchain technology, particularly from the point of view of developing countries in general and for India in particular.

Artificial Intelligence (AI), and digital technology in general, has the potential to transform healthcare in every setting, and even more in the developing world, where the current healthcare system simply cannot scale to the growing masses, often in more remote locations. Digital technology— mobile phones, remote sensing, and the Internet—can help improve quality of healthcare delivery, reduce cost of healthcare systems, and improve accessibility. However, in addition to AI, there is the need for an appropriate business model for solving healthcare problems. Digital technologies also have the potential to deliver preventative care, focusing on wellness, in addition to personalized disease treatment. In that context, mobile health platforms are more versatile because they can monitor events at a finer granularity and are often used by “healthy” individuals to track their daily fitness-centric activities. Further, molecular data is available at unprecedented levels and encompass different aspects of the “being”, be in genomic, epigenomic, proteomic, or metagenomic datasets, in other words offering a holistic view of the individual. This can then be integrated with fine-grained physiological signals obtained through wearables. Thus, there are volumes of datasets that need to be annotated, often in multiple formats, offering a multi-dimensional view of the healthy or diseased human. In fact, the human reference genome should have multiple representations based on the race, ethnicity, and the general well-being of the human. This calls for monitoring healthy people at scale, not just diseased people so we get a better understanding of the “ground truth” for the healthy human being. Overall, AI can therefore be thought of as augmented intelligence that can leverage both better observational and interventional capabilities for delivering precision healthcare and augmented monitoring capabilities to the masses at scale.

Improper Input Validation (IIV) is a software vulnerability that occurs when a system does not safely handle input data. Even though IIV is easy to detect and fix, it still commonly happens in practice. In this paper, we study to what extent developers can detect IIV and investigate underlying reasons. This knowledge is essential to better understand how to support developers in creating secure software systems. We conduct an online experiment with 146 participants, of which 105 report at least three years of professional software development experience. Our results show that the existence of a visible attack scenario facilitates the detection of IIV vulnerabilities and that a significant portion of developers who did not find the vulnerability initially could identify it when warned about its existence. Yet, a total of 60 participants could not detect the vulnerability even after the warning. Other factors, such as the frequency with which the participants perform code reviews, influence the detection of IIV. Preprint: https://arxiv.org/abs/2102.06251. Data and materials: https://doi.org/10.5281/zenodo.3996696.

Reconfigurable intelligent surface (RIS)-assisted communications is one of the promising candidates for next generation wireless networks by controlling the propagation environment dynamically. In this study, a channel modeling strategy for RIS-assisted wireless networks is introduced in sub-6 GHz bands by considering both far-field and near-field behaviours in transmission. We also proposed an open-source physical channel simulator for sub-6 GHz bands where operating frequency, propagation environment, terminal locations, RIS location and size can be adjusted. It is demonstrated via extensive computer simulations that an improved achievable rate performance is obtained in the presence of RISs for both near-field and far-field conditions., NA

Multi-level modeling (MLM) as part of object-oriented modeling aims at fully utilizing the expressive power of multiple abstraction levels. While these levels where initially used to define domain-specific modeling languages, i.e. for linguistic purposes, the MLM community has long argued that there is much more to gain by tapping into ontological abstraction levels. While MLM is a rather specialized research field, there are now quite a number of different proposals. There is thus an opportunity to develop a uniform core of MLM that then possibly can become part of a standard and be taken up by the larger modeling community.

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 toward oxidation based on the stable viscosity and low acidity measurements of vegetable oils throughout the ageing duration even with the presence of oxygen. The AC breakdown voltages of vegetable oils can still comply with the recommended limit of new vegetable oil set by ASTM 6781 even after subjected to ageing. In general most of properties of vegetable oils are comparable with mineral oil.

For nearly four decades 2-furfural (2-FAL) in transformer oil has been used as a chemical marker to indicate the ageing state of transformer paper insulation. Nevertheless, it has always been a challenge to define an acceptable limit for 2-FAL due to issues related to non-uniform temperature distribution in transformers, stability of 2-FAL in oil and its partitioning between liquid and solid insulation. Therefore, transformer users try to combine the laboratory findings, the operational experience and post-mortem analyses together for predicting ageing state of paper insulation through 2-FAL content in oil. Due to increase in the use of ester liquids in transformers, there is a need to investigate the ability to use 2-FAL as a paper ageing indicator for ester based insulation systems. Laboratory ageing studies have shown that 2-FAL is indeed generated in ester based insulation systems. However, there is a lack of understanding related to the partitioning of 2-FAL in ester based insulation systems. This paper studies the partitioning of 2-FAL in synthetic ester based insulation systems and compares to that in mineral oil based insulation systems with the focus on the effect of paper type and water content in paper. Under the investigated conditions the synthetic ester had higher partitioning coefficients (ratio between the 2-FAL content in oil and paper) than the mineral oil. Partitioning coefficients in both oil types decreased with the increase of the water content in paper. However, change in paper type did not significantly affect the partitioning coefficients in this study.

The Panama Papers is a collection of 11.5 million leaked records that contain information for more than 214,488 offshore entities. This collection is growing rapidly as more leaked records become available online. In this paper, we present a work in progress on a web browser plugin that detects company names from the Panama Papers and alerts the user by means of unobtrusive visual cues. We matched a random sample of company names from the Public Works and Government Services Canada registry against the Panama Papers using three different string matching techniques. Monge-Elkan is found to provide the best matching results but at increased computational cost. Levenshtein-based approach is found to provide the best tradeoff between matching and computational cost, while Jacquard index like approach is found to be less sensitive to slight textual change.

Among all infections, urinary tract infections (UTI) are one of the most common. Nowadays the procedures to analyze urine and consequently detect UTI are often painful and time-consuming. Recent studies about microfluidic paper-based devices have developed the interest of researchers due their outstanding characteristics. In this paper is presented a novel design for a microfluidic paper-based device for screening and analysis of multiple biomarkers from urine samples on diapers. The device consists on a set of eight layers. It was designed based on the previous attempts to improve and overcome some problems detected as the continuous entrance of fluids, the possibility of contamination and the invalidity of results due to communication between different reagent pads. One approach was create a self-locking mechanism that closes the sample inlet in approximately four minutes solving the first two problems. Furthermore, is important that comfort is guaranteed, hence a device with a total thickness of 5,3 mm is presented. This device can keep the results for eight hours and can be used as a low-cost and more effective alternative than conventional methods being a strategy with potential for the diagnostic and analysis of biological samples in the future improving healthcare., This research is mainly supported by Norsk Regionalt Forskningsfond Oslofjordfondet Prosjekt: Touchsensor for enklere og raskere urinprøvetaking og analyse (proj. no: 234972). The support from Regionale Forksningfond Oslofjordfondet forprosjekt (proj. no. 249017, 255893 and 260586) and Forprosjekt – VRIBEDRIFT Vestfold (proj. no. 252173) is also acknowledged. We are also thankful to the funds from National Natural Science Foundation of China (grant no. 61550110253 and 61650410655), Chongqing Research Program of Basic Research and Frontier Technology (nos. cstc2016jcyjA2161, cstc2015jcyjA20023), Science and Technology Research Program of Chongqing Education Commission (no. KJ1600604) and Chongqing Innovation Team of Colleges and Universities (no. CXTDX201601025)., info:eu-repo/semantics/publishedVersion

This work presents an experimental study of second mode positive streamers propagating along mineral oilpaper interfaces. A point-plane arrangement immersed in mineral oil with the paper inclined 60 degrees to the plane electrode is used to create the liquid-solid interface. Kraft paper and a kraft fibril paper, made from cellulosic micro and nano fibrils, with higher density and lower surface roughness are used as the solid materials. High speed shadowgraphy and charge recordings are used to compare the propagation of second mode positive streamers along the mineral oil-kraft paper and mineral oil-kraft fibril paper. Streamers creeping along the mineral oil-kraft paper interface propagate mainly into the liquid, with one or two main filaments. In comparison, the streamers propagating along the kraft fibril paper show a strong reduction of the branching; these streamers consist of a single filament that propagates exactly on the solid surface. Streamers along the kraft fibril paper also have longer propagation time than for the case with kraft paper. Mutual electrostatic shielding between filaments is observed for the streamers creeping on the kraft paper. An electrostatic analysis of the influence of permittivity, density and surface roughness of the solid in the electrical properties of the streamer filaments is also performed.

Microfluidic engineering technology has been widely used for implementing lab-on-chip (LOC) type point of care (POC) devices since its origins in the 1990s. LOC devices offer some distinct advantages such as the possibility of reducing the quantity of valuable samples or reagents needed and the shortening of the detection times, both of which result from their compact structure [1]. Paper-based microfluidic devices, which are regarded as a low-cost alternative to conventional POC diagnostics tools, have also been popularly studied in the last few decades, and a huge number of advantages have been explored, such as low-cost, mass production, disposability, being equipment free etc. [2] However, some disadvantages or limitations are also apparent, such as issues with the control of flow rate, multiplexed detection on the same device footprint and further reduction of size [2]. As a result, 3D microfluidic paper analytical devices, as an alternative solution, have been proposed in recent years, which enable distribution of fluids in both lateral and vertical directions.

Development of dependable multi-/many-core systems requires assurance that the system is operable in a range of conditions, subjected to both functional and non-functional requirements. To achieve this, tools need to be implemented that can enable exploration of design options and be able to detect deficiencies earlier to avoid costly system re-design. In this work we discuss the challenges of design of multi-core realtime systems with timing assurance and discuss what are the requirements for modelling, testing and analysis tools. Digital Twin-based predictive modelling and fast design space evaluation are studied that work toward addressing these challenges.

The Plenary Session begins with welcome remarks and introduction from the Conference Chair, Kevin Zhang, followed by the Technical Program Chair, Makoto Ikeda, providing an overview of ISSCC 2021. The Plenary Sessions (1A and 1B) will feature four distinguished keynote speakers. In line with the Conference theme “Integrated Intelligence is the Future of Systems,” the plenary presentations will address important innovation trends that are paving the path forward in this emerging era of Integrated Intelligence. This year, with the virtual format, an Awards Ceremony video will be posted that recognizes major technical and professional accomplishments presented by the IEEE, Solid-State-Circuits Society (SSCS), and ISSCC.

In this paper the experimental results of a compact low-power rectenna in paper substrate, designed to operate in the Wi-Fi band, are presented. The complete prototype, based on an annular slot antenna and a single-diode rectifier, features a weight of 1.5 grams and shows an RF-to-dc conversion efficiency in the design band of about 40 % for a -10 dBm available input power, of about 28 % at -15 dBm, and in the range [10, 22] % at -20 dBm, corresponding to an output DC voltage in the order of 320, 240 and 60 mV respectively. Additionally, the rectenna features an efficiency higher then 7 % in the whole band 1.8-2.7 dBm for a power density estimated around 3 μW/cm2.

The recognition of the development stage of creepage discharge of oil-paper insulation under AC-DC combined voltage is the basis of fault monitoring and diagnosis of converter transformers, and there are few related studies. In this paper, the AC-DC combined voltage with a ratio of 1:1 was used to study the development stage recognition method of creepage discharge of oil-paper insulation under the cylinder-plate electrode structure. Firstly, the pulse current method was used to collect the discharge signals in the process of creepage discharge development. Finally, based on the online sequential extreme learning machine (OS-ELM), the above characteristic parameters were used to recognize the development stage of oilpaper insulation creepage discharge. The research results show that when the size of the sample training set in the OS-ELM algorithm is closed to the number of hidden layer neurons, higher recognition accuracy can be obtained, and the type of activation function has less influence on it. Based on the OS-ELM algorithm, the developmental stage of the creepage discharge is recognized. The development process of the creepage discharge is recognized as four stages, which is the same as the trend of the characteristic parameters of the whole creepage discharge development process, and the recognition accuracy is 91.4%. The algorithm has fast rate, high accuracy and batch training data characteristics, which can be widely used in the field of online monitoring and evaluation of electrical equipment status.

The new type of coronavirus COVID-19 virus was first detected in Wuhan-China. A COVID-19 certified patient is characterized by fever, fatigue, and dry cough. The coronavirus (COVID-19) epidemic is spreading worldwide. In this review paper, a database of X-ray, CT-Scan images from patients with common bacterial pneumonia, confirmed Covid-19 infection, and common cases, were used to automatically detect Coronavirus infection. The purpose of the study was to evaluate the effectiveness of COVID-19 acquisition. During the COVID-19 scenario, the number of infected cases rises in huge number globally. Due to this fact, a vital decision had been taken by medical experts and infected patients to adopt various medical facilities within a reasonable amount of time.

We consider the problem of communicating over a channel that randomly "tears" the message block into small pieces of different sizes and shuffles them. For the binary torn-paper channel with block length $n$ and pieces of length ${\rm Geometric}(p_n)$, we characterize the capacity as $C = e^{-\alpha}$, where $\alpha = \lim_{n\to\infty} p_n \log n$. Our results show that the case of ${\rm Geometric}(p_n)$-length fragments and the case of deterministic length-$(1/p_n)$ fragments are qualitatively different and, surprisingly, the capacity of the former is larger. Intuitively, this is due to the fact that, in the random fragments case, large fragments are sometimes observed, which boosts the capacity.

For transformers in service, aging markers from cellulose in oil such as furans, water, methanol and acids are measured for diagnostic purposes. The content of these indicators, measured in oil, may therefore vary with load, temperature, solid and liquid insulation aging, as well as marker stability and evaporative loss. Correction factors estimating the level of the aging marker to a reference temperature would make the diagnostic more relevant. In this study, correction factors for temperature differences have been estimated for different aging markers in insulation systems impregnated with either mineral oil or synthetic ester. In the case of mineral oil based systems, we observe correction factors for water, methanol and furans in line with previously reported findings. On the other hand, for the synthetic ester system, novel correction factors for water and methanol are suggested while for furans, no temperature dependence was observed.

Distributed smart and connected community applications of the present and future will continuously sense perishable data on which they make decisions. We say the data are perishable when they represent information sensed at a past point in time, possibly at a distant part of the distributed application, and for which the ground truth could have since changed. This paper discusses actions the sensing source, the network, and the controller can take to make the best possible decisions given that we know only a delayed version of the truth. Some of these actions to preserve freshness of data are based on known real-time techniques such as Time Sensitive Networking. To these we add Information Theory applied on a message-by-message basis and cross-layer coordination between content and network handling. Both the unexpectedness (surprisal) and timeliness (freshness) properties of perishable information can be encoded using a Shannon information entropy framework. Examples of smart community systems of the future for which these concepts are relevant are given.

In this work, a large area, low cost and flexible polymer/paper-based double touch mode capacitive pressure sensor is demonstrated. Garage fabrication processes are used which only require cutting, taping and assembly of aluminum (Al) coated polyimide (PI) foil, PI tape and double-sided scotch tape. The presented pressure sensor operates in different pressure regions i.e. normal (0 to 7.5 kPa), transition (7.5 to 14.24 kPa), linear (14.24 to 54.9 kPa) and saturation (above 54.9 kPa). The advantages of the demonstrated double touch mode capacitive pressure sensors are low temperature drift, long linear range, high pressure sensitivity, precise pressure measurement and large die area. The linear output along with a high sensitivity range (14.24 to 54.9 kPa pressure range) of the sensor are utilized to wirelessly control the movement of a robotic arm with precise rotation and tilt movement capabilities.