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Information technologies have a significant impact on digital development and the advancement of all spheres of life and business. Mobile applications have become a significant resource for raising awareness and using different areas of services. Many institutions have digitized their services, and cultural institutions are increasingly digitally present. This paper presents an application developed for iOS and Android devices that helps tourists in Belgrade, Serbia to explore the city ’s museums.

Data warehouse systems (DWSs) are widespread in business organizations, but their usage in education is lower compared with others sectors. The experiences of DWSs usage in complex business organizations can be applied in education organizations, too. Pandemic challenges forced the faculties to change the paradigms of education and to make full transition towards online learning. In order to evaluate the teaching-learning process and to compare its outcomes within traditional and remote settings data from different sources would be analyzed. In the paper we present a pilot project of a DWS for monitoring the students' accomplishment of course requirements in the lecturing process, both within the traditional and distance learning environment. We present: the data sources, data Extraction/Transform/Load process, database schema of DWS, and examples of reporting functions for data analysis processes.

As part of preventative maintenance and start-up activities, electrical test equipment is brought into an Electrically Safe Work Boundary to perform testing to confirm the functionality of the system and critical components. When the test equipment is performing the test, a voltage or current is applied to the electrical equipment, thus destroying an electrically safe work condition. This paper will evaluate the potential sources of power that test equipment can supply to equipment, determine which test sets could be considered hazardous, and how qualified workers can protect themselves from these hazards.

The Occupational Safety and Health Administration (OSHA) uses the term “employee in charge” 12 times in their regulations. The National Fire Protection Association (NFPA) Standard for Electrical Safety in the Workplace, 70E® uses the terms “employee” or “person in charge” 28 times. The National Electrical Safety Code (NESC) uses the term seven times. The term is important in all three documents, yet none of them define it. This paper offers an analysis of the use of the term in these documents, and details why that role is critical to safe work practices on or near electrical conductors and circuit parts, with particular focus on its function in high voltage work.

One of the challenges faced by employers and workers is determining the appropriate rating of arc flash personal protective equipment (PPE) when an engineering calculation has not been performed. Some standards include tables to assist the user in selecting arc flash PPE for specific equipment types and voltage ranges. However, to use these and similar tabular methods requires the user to determine the fault current and the fault clearing time. Determining these values is at best difficult for the electrical worker, and in some circumstances, all but impossible. This paper discusses a proposed simplified table method to determine the required arc flash PPE requirements based on a constant-energy boundary, and alternatives considered in the process of creating the proposed table. The method requires identification of readily available electrical system characteristics in addition to the nominal voltage and equipment type to use the table. The method does not require the user to calculate the available fault current or determine fault clearing times. The method also addresses the effect of electrode configuration on the incident energy introduced in IEEE 1584™-2018 Guide for Performing Arc-Flash Hazard Calculations and low arcing current, which are currently unaccounted for in the tables commonly used today.

Standards developed by the National Fire Protection Association (NFPA) are a very important source of information for electrical safety programs and safe electrical installations for a very large number of individuals and organizations. They are widely used by many countries around the world. NFPA 70®, National Electrical Code®, (or NEC®), and NFPA 70E®, Standard for Electrical Safety in the Workplace® are two more commonly known examples, although there are many others. NFPA has a well-established process for the development of new standards and for periodic review and revision of existing ones. Understanding this standards development and revision process is important to everyone involved with electrical safety. It follows a defined set of rules and regulations that moves the standards through the process, and that also encourages participation from members of the public. Most people are not aware of what this process is, or that it encourages public participation. The process is open to anyone and the more involvement from affected individuals, the better the resulting standards. Everyone has their own knowledge, experiences and expertise. All are valuable and should be included in the process. The objective of this paper is to increase a person's knowledge of the process, including explaining how anyone can get involved and encouraging them to do so.

The electrical industry has greatly evolved over the past several decades. Originally, there was no such thing as a “safety culture”. Now, hundreds of the industry's leading minds show up annually for a full week to learn, listen, and exchange ideas for stopping electrical incidents and injuries in the workplace. Under normal operations, most companies have adopted the “Safety First” mantra. In 2020, the world was faced with something it had never seen before; a modern-day pandemic. This completely changed the way that we here in the United States were able to conduct business. When circumstances change so rapidly even on a day to day basis and people's businesses and the ability to support their families are put on the line, is safety still first? In this paper, we will discuss the struggles of operating a business and keeping employees as safe as possible during the 2020 SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) (COVID-19) Pandemic. We linked with other professionals and centers of excellence from around the world in the electrical sector to advance our mission of a Safety-First culture. The innovations required involved human performance best practices to overcome these substantial barriers to everyday work tasks. The US Department of Homeland Security deemed the Energy Sector as critically essential. They stated, “The U.S. energy infrastructure fuels the economy of the 21st century. Without a stable energy supply, health and welfare are threatened, and the U.S. economy cannot function [1].” The electrical industry could not shut down in this crisis. Our industry needed to adapt, in real-time, to the environments they were in. Engineers, technicians, and electricians dealt daily with this new hazard that they could not see, interestingly not unlike electricity. The ongoing respect for electricity that our employees have always had, along with the ability to adapt quickly in innovative ways made it possible to still provide this essential work to keep the country moving.

This paper looks at the process and problems the authors encountered when developing and standardizing PPE levels and task-specific risk assessments for a multinational company that operates large facilities with complex electrical systems around the world. The obstacles of synchronizing a coherent electrical safety program with national standards, international test methods and certification processes and even different language for arc flash/electric arc/electrical arc were resolved to provide consistent requirements that met a corporate NFPA 70E/OSHA 1910.269 program adapted to EU and other international norms. These risk assessment learnings will provide an extremely effective tool for minimizing risk and protecting workers, when applied correctly. For this to happen, personnel of all levels need to have a clear understanding of the company's expectations when it comes to assessing risk and selecting PPE for a given task. The company can accomplish this by standardizing PPE criteria and risk assessments for common tasks on a given piece of equipment. Doing so requires a significant amount of upfront and ongoing work, but will greatly reduce the chance of errors in common tasks and provide a template for future risk assessments.

Troubleshooting, testing, and tuning are words synonymous with energized work due to infeasibility (NFPA 70E 130.2(A)(2)). As such, the hazards associated with troubleshooting are often assumed to be a fact of life one must accept. These hazards are even often overlooked while performing such work. Energized troubleshooting presents significant added challenges to safe work, as it represents the knowledge-based mode, often with error precursors built in when the non-working equipment is holding up production. This paper examines the troubleshooting subject with suggestions on safer troubleshooting work methods for existing installations along with design considerations that follow the hierarchy of controls to reduce the hazards for new and modified installations.

We proposed a deep reinforcement learning (DRL) based approach to reconfigure the multicast sessions in an elastic optical network (EON) adaptively. Simulation results demonstrate that our proposal maintains the optimality of light-trees with less reconfigurations and reduces blocking probability.

In order to automate the task of correcting handwritten subjective answers, we envision a system that reads such answers and grades them. In this project, we have created a mobile application to achieve this task. We have used the RAKE algorithm to extract key-phrases, which are then embedded using Word2vec model and compared using Word Mover's Distance. Our created model achieved almost human like evaluation accuracy. We have also provided accessibility features to the users with the aim of making this application a one-stop solution to automatic evaluation of handwritten subjective answers.

Wireless communications via reconfigurable intelligent surfaces (RIS) are envisioned to offer unprecedented spectral efficiency gains by smartly inducing phase shifts on the impinging electromagnetic waves at the RIS to reconfigure the underlying propagation environment. This work investigates a multi-user downlink communication system in which the access point, equipped with multiple antennas, serves its associated single-antenna users equipments (UE) with the help of RIS. The proposal is a leakage-based design in which the transmit precoding, the power allocation, and the phase shifts of the RIS, are designed to maximize the minimum signal-to-Ieakage-plus-noise power ratio (SLNR) of the UEs subject to the constraint on the power budget of the access point. The merits of the SLNR-based approach are highlighted, e.g., reduced complexity, and simulation results show that the RIS-aided design can achieve massive MIMO gains with much fewer number of active antennas in the access point as compared to conventional relaying.

Sentiment analysis and opinion mining have developed significantly throughout the last decades. This study aims to assess, amongst many other aspects, people's feelings, opinions, and emotions of someone or something. This review's principal objective is to automatically assess the direction of the review and contrast this with the evaluation made by the reviewers. This will allow scientists to categorize and evaluate reviews cross-sectionally and encourage a scientific article's overall evaluation more critically. An EM-VC ensemble approach has been proposed for analyzing the reviews. This approach uses POS to achieve a syntactic sentence structure. With dictionaries, this syntactic structure enables the semantic orientation of the analysis via the scoring algorithm to be determined. To test the proposed approach's efficiency and performance about the baseline method, some tests have been performed using typical performance metrics like precision, accuracy, F1-score, and recall. The findings reveal that improvements are achieved in binary classification, ternary classification, & five-point classification compared to the existing HS-SVM method. Still, it provides a slight improvement in accuracy in the context of multiclass classification compared to others.

This position paper proposes CsPI (Cybersecurity Performance Index) as a new way to evaluate the cyber security investment decisions and measure the progresses and effects of the investments and projects. In a conventional way, cyber security budgets are usually evaluated by the return on investment (ROI), which has some undesirable side effects. Since we don't ask for return on investment for other similar expenses (like IT or capital), why should we use ROI for cybersecurity? Here, we propose to adopt a well-established technique in the project management field called "earned value" to the field of cyber security. Specifically, what we propose is to measure the progress of cybersecurity expenses against a plan. The plan should include protection, detect, respond, recover goals that cybersecurity expenses (people, process, technology) attempt to meet – and this has to take into account business objectives and threat/vulnerabilities. Similar to the "Cost Performance Index" or "Schedule Performance Index" in Earned Value, we can define "Cybersecurity Performance Index" (CsPI). The main idea is to show how well current cybersecurity expenses are performing against a plan. At the end, future research directions are presented.

The large software applications of today provide abstractions of the real-life systems that they support. A digital model of the system, and of the changes that occur within, are being maintained and updated, as triggered by real-life events. Morphologically, such applications contain several distinct architectural entities: databases holding the state, central components describing how the system reacts to external events and mechanisms through which the user can view the current state and issue new commands. Each of these entities may use distinct paradigms and employ different technologies. A production-ready software application ends up assembling a relatively high technology stack and provides the final abstractions for both the problem and its solution. In this paper we propose a short-circuit for the long chain of technologies that are usually employed in large, production-ready software applications. The resulting architecture is a distributed, message-based system which behaves as a hybrid between a database and a runtime environment. The system operates with persistent and live entities, encapsulating both state and operations and therefore easily assimilated with OOP classes.

The reduction of production waste impact started to be an important subject in the context of industrial development. In the last years the authorities became to be interested in the reduction of impacts generated by the large amount of waste, by recycling or reuse in processes. In this context, the present study is developed to help decision makers to take the best decision regarding the management of production waste from paper manufacturing so as to mitigate its impacts. According to the results obtained after an analysis of the production waste conducted in the Life Cycle Analysis (LCA) framework, the recycling of this type of waste can reduce considerable the impact on the environment and human health by reducing tree cutting and increasing the absorption capacity of CO 2 from the environment.

This paper takes a view on the Quality-of-Experience (QoE) perspective of Cyber-Physical System (CpS) applications involving users. We provide an overview of characteristics of CPS applications, their relation to QoE and implications for assessing QoE of such systems. Furthermore, we incorporate eudaimonic aspects such as meaningfulness and personal growth that need to be considered in order to grasp the strongly multi-dimensional aspects of QoE in this context.

We present a timing-valve mechanism on a paper-based device to conduct competitive ELISA procedures. The device consists of multiple channels, where timing-valves regulate each individual liquid flow, to automate sequential steps. The timing-valve is achieved using surfactants to dissolve the hydrophobic barriers and to allow fluid to pass through in a timed duration. Imidacloprid (small molecule pesticide) is tested in our proposed device, while the results validate a simplified fluidic manipulation procedure and permits only single-step application of the sample solution for on-site detection.

One of the rising stresses of human life is over prosperity and wellbeing. Undeniably, prosperity and sustenance are one of the huge pieces of life. As such, mechanical progressions to help overhaul and even development prosperity care is key. In this Paper, We will look at changed framework dependent on a couple past assessment work done by significant scientists. By the strategies for that, we can orchestrate the right food as demonstrated by our lifestyle.

We develop and commercialize autonomous machines, such as logistic robots and self-driving cars, around the globe. A critical challenge to our—and any—autonomous machine is accurate and efficient localization under resource constraints, which has fueled specialized localization accelerators recently. Prior acceleration efforts are point solutions in that they each specialize for a specific localization algorithm. In real-world commercial deployments, however, autonomous machines routinely operate under different environments and no single localization algorithm fits all the environments. Simply stacking together point solutions not only leads to cost and power budget overrun, but also results in an overly complicated software stack.This paper demonstrates our new software-hardware co-designed framework for autonomous machine localization, which adapts to different operating scenarios by fusing fundamental algorithmic primitives. Through characterizing the software framework, we identify ideal acceleration candidates that contribute significantly to the end-to-end latency and/or latency variation. We show how to co-design a hardware accelerator to systematically exploit the parallelisms, locality, and common building blocks inherent in the localization framework. We build, deploy, and evaluate an FPGA prototype on our next-generation self-driving cars. To demonstrate the flexibility of our framework, we also instantiate another FPGA prototype targeting drones, which represent mobile autonomous machines. We achieve about $2 \times$ speedup and $4 \times$ energy reduction compared to widely-deployed, optimized implementations on general-purpose platforms.

Now a days due to the development in color printing technology the rate of counterfeit notes production and distribution is increasing. This is a massive problem, faced by almost all the countries. It affects the economy, sine it compromises the security of the real economy. Such counterfeit currencies are used to fuel nefarious motives, usually involving terrorist activities. According to the research, developing countries like India have been impacted by this very negatively. Even after the steps taken in 2016 to remove the counterfeits, by executing the demonetization of 500 and 1000 rupees bank notes in India the counterfeits of the new notes have begun circulating. This is due to the highly advanced technology adopted by the counterfeiters which makes the tracking of these counterfeit notes hard. This has become a very critical issue and the negative impact due to the counterfeit currency keeps rising. The only one solution for this problem for a common man is to detect the fake currency, by using the fake currency detector machine. These machines are used in banks and large scale business, but for a small business or for a common man these machines are not affordable. This paper gives the complete methodology of fake note detector machine, which is affordable even for a common man. By implementing the applications of image processing techniques we can find out whether the currency notes are fake or not. Image processing technique consists of a number of operations that can be performed on an image, some of which include image segmentation, edge detection, gray scale conversion etc. The proposed system will have advantages like simplicity, reliability and costs less.

The papers in this special section were presented at the Optical Fiber Communications Conference (OFC) 2020, which took place in March 2020 in San Diego, CA.

Nowadays, there is a rapidly increasing number of conferences and journals in computer science that make a lot of challenges for researchers to find an appropriate venue to submit their scientific work. There is a need for a recommendation system that can support researchers for a better process of paper submission. In this paper, we present an efficient approach for building such a recommendation model by using embedding methods, Global Vector (GloVe) 1 created by Pennington et al. [1] and FastText 2 proposed by Facebook [2], Convolutional Neural Network (CNN) [3], and LSTM. The experimental results show that the combination of CNNs and FastText, CNN + FastText, can achieve the best performance in terms of the Top 1 Accuracy compared with other techniques, including the S2RSCS model, as presented in [4]. Moreover, the performance by using GloVe or FastText is much better, faster, and more stable than S2RSCS in most cases.

The assignment of reviewers to papers is one of the most important and challenging tasks in organizing scientific conferences. Its accuracy has a direct impact on the quality and the fairness of the review process. The accuracy of the automatic assignment depends on both the assignment algorithm and the way similarity factors between papers and reviewers are calculated. This paper proposes an architecture and a working model of a software tool for accuracy evaluation of the calculated similarity factors between papers and reviewers. It has been used over a hundred times and proved to be very useful for evaluation and comparative analysis of existing methods of describing papers and reviewers' competences.

With the advances in information technologies, different research areas are emerging day by day and thousands of research papers are published in these fields. Papers are not presented to users grouped according to their topics. Therefore, it is getting harder and harder for people to access research papers in their field of interest. To facilitate this search process, a paper classification system is proposed in this study to categorize papers on similar topics. A different approach from the studies presented for classification so far has been proposed. This system is a complex system created by combining Word2vec, network modeling and community discovery. With the Word2vec method, which has attracted great attention recently, paper similarities have been found, a network based on similarity rates has been created and papers have been clustered with the community discovery algorithm. As a result of the application with the proposed system, a success of 89% has been achieved. As can be seen from the results, this approach presented for an important classification problem will provide great convenience to people. It will enable fast and efficient access to papers.

In this paper, we present a plug and play Rock-Paper-Scissors game set that utilizes CNN-based static hand gesture recognition and a Markov chain-based bot. Each game round, the camera output is fed to the neural network and the hand gesture result is compared to the current Markov chain state. We utilize a CNN trained with a dataset containing rock-paperscissors hand gestures and unwanted inputs, and a multi-state Markov chain. Automated tests confirm the bot prediction capabilities and practical tests verify the precision of static hand gesture recognition. Tests against a verification dataset reveal a recognition accuracy of 97.4%.

The rapid advance in science and technology is made possible by research conduct and breakthroughs in a wide range of fields, which have resulted in a large number of academic papers. Searching through the enormous literature to find relevant information of one's research interest has become an increasingly important yet challenging problem for many researchers. Most existing methods for academic paper recommendation are based on the analysis of paper contents and only meet with limited success. We propose a novel method based on heterogeneous information networks for academic paper recommendation, referred to as HNPR. This method considers the citation relationship between papers, the collaboration relationship between authors, and the research area information of papers to construct two types of heterogeneous information networks. In such networks, a random walk-based strategy is used to simulate natural sentences for the discovery of relevance between two papers according to a mature natural language processing model. Extensive experimental results using real data in public digital libraries show that HNPR significantly improves the accuracy of academic paper recommendation in comparison with traditional content-based recommendation methods.

According to the Canadian Science Publishing, there are approximately 2.5 million scientific papers published each year. The huge volume of publications can be contributed to a substantial increase in the total number of academic journals, including the increasing number of predatory or fake scientific journals, which yield high volumes of poor-quality research work. The effect of this scenario is that there is an obsolete jungle of journals to flip through in searching for high-quality and relevant references for researchers, ranging from the ones who simply look for citations to cite or latest development and knowledge in a specific scientific area of study. In solving this problem, we propose a unique, elegant research paper recommender. Besides considering the topics and contents of related publications, our recommender also examines the peer reviews, authority, and popularity of each publication to ensure its quality. Conducted empirical study shows that our recommender outperforms existing research paper recommenders and contributes to the design of searching relevant publications.

1 The aim of the present work is to assess similarities between papers used in a collection of 215 lithographs by Henri Matisse. It combines the use of an anisotropic multiscale analysis built upon the hyperbolic wavelet transform to compute distances between textures, with the fact that four textures of the same print were digitized, corresponding to four different (recto/verso and top/side) views. A permutation algorithm is devised showing the importance of reordering the four views to achieve a meaningful comparison across the papers, thus suggesting possibly different artistic intentions in some prints.

In the context of papers used in the graphic arts, including silver gelatin, inkjet, and wove papers, prior work has studied measures of texture similarity for purposes of classifying such papers. The majority of prior work has been based on classical image processing approaches such as Fourier, wavelet, and fractal analysis. In this work, recent advances in deep learning are used to develop a texture similarity approach for measuring paper texture similarity. Since the available datasets generally lack labels, the convolutional neural network is trained using triplet loss to minimize the feature distance of tiles from the same image while simultaneously maximizing the feature distance of tiles drawn from different images. The approach is tested on three paper texture image databases considered in prior works and the results suggest the proposed approach achieves state-of-the-art performance.

Anti-counterfeiting technique is a research hotspot in information security domain. Common techniques are usually based on artificial physical cloneable feature which is forgeable. In this paper, we proposed an anti-counterfeit method based on microscopic translucent texture of paper (MTTP). MTTP is image of internal fiber pattern of paper (IFPP) captured by microscope under translucent light source. The IFPP has property of uniqueness and randomness, and the fiber scale of IFPP is at sub-micron or micron level. Then the IFPP is unable to be forged. Furthermore, fiber texture in IFPP is stable under disturbances (including illumination intensity change and surface damage), which guarantees the stability of the MTTP. Experiment results show that the authentication accuracy achieve 100% in our dataset (totally 13,4550 pairs of MTTPs) and the false reject rate achieves the order of magnitude of 10-136 in ideal condition and 10-59 even in condition of illumination change or surface damage. Above results indicate that our method has rather high security and reliability.

This conceptual paper argues that perceived usefulness, perceived ease of use, and attitude are insufficient in explaining online health information seeking patterns among women. Building on the technology acceptance model, this paper presents socio-economic status/income as a direct influence on the attitude that web users have towards searching for health-related information on the internet. This newly added socio-demographic construct offers an understanding of how social factors can determine attitude towards online health information-seeking behavior. The paper conceptualizes socioeconomic status as another factor that has a direct influence attitude, thus influencing women's decision to use or not to use online health-related content. This study highlights the implications of the positive attitude of women towards online health-related content which sometimes does not translate into the actual use of online health-related information. Thus, by introducing income as a limiting or motivating factor, it helps to explain how the affordability of access to the internet might explain why women have a positive attitude towards the internet through their perceptions of its usefulness and ease of use and yet decide not to utilize it.

Oil-paper insulation bears AC/DC composite voltage in converter transformers. However, the AC/DC space charge behavior is still not clear, which will result in electric field distortion, material aging and even insulation failure. In this work, the space charge distribution of oil-paper under the AC/DC composite voltage with the AC/DC ratio of 1:1, 1:3, 1:5, and 1:7, is studied by pulse electroacoustic (PEA) method, respectively. It was found that as DC component increases, the accumulated charge near the electrode decreases, while the interior charge increases. It suggests that DC stress mainly influences the amount and the depth of space charge accumulation. AC component has a relatively significant impact on the injection and extraction behavior of space charge near the electrode. Furthermore, AC/DC composite voltage enhances the migration of space charge compared with that under DC voltage. This research contributes to the further understanding of the space charge characteristics of oil-paper under AC/DC composite voltage, which will benefit the safe and stable operation of converter transformers.

Nondestructive analysis of historical materials, such as paper, is vital in the elucidation of history and culture. This is because it is possible to elucidate the background of a book’s origin using information obtained from other sources, such as paper making methods and paper’s fiber composition. Herein, we propose a patch classification method for Japanese paper kozo using EfficientNet-B0. We integrate the results classified using patch images to estimate the origin of the kozo fiber in the entire paper. Consequently, the average success rate of our method was 93.1 % for two classifications and 87.5 % for four classifications of the production areas of kozo. In addition, the classification accuracy for the entire paper was evaluated from the patch image obtained after classification using the reconstructed image in which the position was rearranged on the original image. As a result, the classification of four production areas of kozo, from which the entire macro image was made, could be classified in all macro images, although the number of experiments was limited. In the future, we will investigate a multi-scale technique to consider the fiber continuity between patches in macro images reconstructed from patch images.

The paper mill is one of the major industries of India. The various processes that are present in paper mill are not simple to model and control because of presence of nonlinearities and the dead time. The present work is focused on a prime section of a paper mill that is the headbox. The regulation of its consistency is a major concern. In this paper, first of all, the FOPDT model of the head box consistency dynamics is approximated as a polynomial model using the Pade approximation and hence control system is designed for it. The Simulated Annealing (SA) technique is used for the performance optimization of this control system. MATLAB software has been used to obtain all simulation results.

Biometric observation using portable and wearable sensors is transforming health monitoring since patients can now have their conditions frequently checked outside the hospital setting. However, modern biosensors mostly use the standard printed circuit board substrate, which is physically incompatible with irregular-surface applications. The need for a flexible, low-cost and high-resolution monitoring device for observing elderly patient mobility out of hospital settings is the motivation driving this research. The following paper is a characterization of an experimental inkjet-printed sensor that circumvents the problem of rigidity by using a highly flexible substrate while also benefiting from low fabrication costs, low power usage, and environmental friendliness. The sensor is a 4 × 4 grid of Aluminum-doped Zinc Oxide nodes inkjet-printed on paper-based substrates. The tests performed show nodes are capable of responding to applied pressures of over 540 PSI. Notably, they exhibit sensitivity to heat and humidity without shielding measures, making it more useful for physical therapy. Power usage of the device is shown to be as low as 5 μW. Silver nanoparticle ink was chosen as electrical routing between the Zinc Oxide and data collection scheme. The analog signal is connected through ELVIS II+ analog pins, where a MATLAB script retrieves and stores the data for visual analysis. The cost of printing a single pressure node of this sensor is estimated to be $0.01. These conditions make it a monetarily attractive pressure sensing and mapping option for human impact monitoring applications.

Which are the segmentation algorithms proposed during 2018-2019 in CVPR that have CNN architecture?’ Answering this question involves identifying and analyzing the deep learning architecture diagrams from several research papers. Retrieving such information poses significant challenge as most of the existing academic search engines are primarily based on only the text content. In this paper, we introduce Diag2Graph, an end-to-end framework for parsing deep learning diagram-figures, that enables powerful search and retrieval of architectural details in research papers. Our proposed approach automatically localizes figures from research papers, classifies them, and analyses the content of the diagram-figures. The key steps in analyzing the Figure content is the extraction of the different components data and finding their structural relation. Finally, the extracted components and their relations are represented in the form of a deep knowledge graph. A thorough evaluation on a real-word annotated dataset has been done to demonstrate the efficacy of our approach.

The process of drawing theoretically infinite drawings on infinite paper sheets is normal for many industries. Ordinary today used techniques exploited for relatively short drawings (size A0 or similar) are useless for this problem. The proposed paper presents a solution of a flatbed plotter for drawing long (theoretically infinite) drawings. The problems with paper shifting and rotation as well paper corrugation are solved using specific optical sensor and the appropriate software.

Conventional wisdom states that Network-on-Chip router area grows quadratically with the channel width, and this perception has fundamentally shaped the assumptions of thousands of NoC papers that have been written to date, and many chip designs. However, this assumption is not entirely true. Simple analysis and empirical data from this paper shows that, in modern standard cell technology, a router’s standard cell logic area actually grows only linearly; it is solely the wire routing area that grows quadratically.If we think of a NoC as a standalone block as is done in standard hierarchical VLSI design, then the overall area growth is indeed quadratic. But this approach either vastly under-utilizes logic area, or, in designs that match wire and logic area, leads to small network links. At the same time, many standard non-NoC logic blocks like processors or accelerator blocks typically use the standard cell logic area but need only a fraction of available wiring resources.We propose an alternative approach, NoC Symbiosis, in which router logic and the node logic it services are jointly placed together. The router absorbs excess wiring resources from the node logic, and the node logic absorbs excess standard cell area from the router. Current-day automatic place and route (APR) tools already automatically distribute the router logic across the node logic, in order to provide enough space for the wiring resources. With this approach, future SoC’s can leverage vastly larger amounts of wiring bandwidth than ever before, or alternatively, reduce the area overhead of existing routers.We describe how we first encountered this phenomena, perform experiments to demonstrate its behavior, and provide design tips to help teams realize the potential of NoC Symbiosis.

The increasing number of research papers from Indonesia and the higher the need to manage large amounts of documents, including memory capacity and the availability of time to manage research documents, keyphrase can provide a picture representing a text document. Thus, the management of documents in large quantities will become easier to prepare and find a collection of documents. For this reason, proper and correct keyphrase extraction can assist in managing paper documents. This study tried to compare three extraction methods using unsupervised graph-based techniques, including TextRank, TopicRank, and PositionRank. We compare the extraction results with the keyphrase made by the authors of the paper to see the three method’s performance. From the results of our research, we found that the method TextRank Providing the highest performance compared to other methods using the ROUGE test with average Recall, Precision, and F1-Score are 0.558, 0.71, and 0.225. However, the extracted phrases are longer compared to others. The performance of TopicRank, although it does not provide higher results with TextRank, the extracted keyphrase is more compact than TextRank and PositionRank methods.

Oil-paper insulation high-voltage bushings are one of the most important power equipment in substations, and their insulation status is critical to the safety and the stabilization of the power system operation. During the production and operation, the bushing may be dampened because of the insufficient drying and impregnation or the intrusion of external moisture, which leads to the deterioration of oil paper insulation and threatens the reliability of bushing. Due to the special insulation structure of the bushing capacitor core, the distribution of moisture inside the bushing is usually non-uniform, especially when the moisture is intruded from the external environment. In this paper, a numerical simulation model of dual-unit laminated oil-paper and 110kV capacitor bushing is established. Then the frequency domain dielectric spectrum (FDS) characteristics of oil-paper insulation with different non-uniform moisture distribution are obtained by simulation. Different types of non-uniform moisture distribution include: non-uniform moisture distribution in different directions of the bushing, and different degrees of non-uniform moisture distribution. When the non-uniform moisture distribution of bushing is along the axial direction, different degrees of non-uniformity of moisture distribution have little effect on the FDS results; when the non-uniform moisture distribution of bushing is along the radial direction, the $\text{tan}\delta-f$ curve shows a clear dielectric loss peak, the characteristics of which are closely related to the degree of non-uniformity of the moisture distribution. Partial damping at the outermost side of the bushing or the end screen are more common in practice, and the FDS results of these two different types of damped bushing show different characteristic. This paper carried out a comprehensive FDS simulation study of different types of non-uniform dampened oil-paper insulation, which is of great significance for the evaluation of the insulation status of the oil-paper bushing.

In recent years, the volume of research papers has become enormous. Therefore, it is difficult for researchers to select their required papers. To lighten this problem, a method of describing abstracts called "Structured Abstract" is used in the fields of physiology and medicine. This paper proposes a method that extracts sentences matching with each heading of Structured Abstract. Specifically, SciBERT and BioBERT, which are specialized in the science and technology fields, are used in the method. The effectiveness of the proposed method is evaluated by comparing automatically generated abstracts and human-written abstracts.

The paper adopts Actor-Network Theory (ANT) endorsed by sociologists Callon, Mitchell and Latour to reveal how the Chicago School of economics has utilized big data and policies based on abstract quantitative analysis of big data to ‘measure’ the livelihood of urban poor who remain outside the regulation of modern state authority in post-colonial nations. Specifically, by studying contemporary Morocco and the policies targeting eradication of informal human settlements to eradicate poverty in urban cities, the paper utilizes Callon and Mitchell’s theory of Economization to understand how big data plays a transforming role in framing and the politics of metrology- which have become critical for the re-alignment of state and market power. International organizations and Hayekian economic experts have relied on abstract big data analysis to import results from one country to another, thereby producing ‘policy experts’ on poverty and development with little recognition of the contingent socioeconomic realities of countries in the global south. Consequently, the paper dwells on three of the given topics for the workshop covering socioeconomic implications of big data, the consequent urban planning focused on urban poor’s living settlements and the role of academic economics and the free market in re-instating state power.

This system is controlled by STM32 single-chip microcomputer. FDC2214 capacitance sensor detects different capacitance values between plates, and can accurately detect the number of paper between plates A and B. With STM32F407ZGT6 microcontroller as the core processor, data processing is carried out through the least square method of fitting the slope, eliminating the influence of parasitic capacitance on the data, improving the detection accuracy, collecting stable data of different paper Numbers between the plates in advance, generating samples and self-training and learning. When the effective data is collected, the system will find the sample value with the highest similarity of characteristic values through KNN proximity algorithm between the sample data, determine the number of detected papers, and display them on the serial port screen, at the same time, the buzzer will emit sound.

Conventional electronic components are non-foldable and non-flexible with complex and expensive fabrication processes. Considering the recent interest in foldable electronics, we report a foldable, eco-friendly, low-cost, highly sensitive, and stable microfluidic paper-based capacitive droplet $(\mu$ PCD) sensor. The sensor is fabricated using readily available materials (filter paper and copper tape) through a simplistic, easy-go- designed, and low-cost bench-top fabrication process. The design of the capacitive sensor is based on a parallel plate capacitor attained by direct deposition of copper tape on filter paper. The filter paper serves as a dielectric. Very small quantities $(\mu$ Ls) of liquid can easily flow through filter paper due to micro-pores in it. The $10 \times 10$ mm sensor can detect water droplets as small as $10 \mu \mathrm{L}$ with sensitivity $3 \pm 0.5$ pF$/ 1 \mu \mathrm{L}$. The sensor response is insensitive to bending as tested by measuring the capacitance response at different bending radius from 0 to 7mm. The sensor responds accurately and repeatedly for different volumes of water droplets at different bending radius. Foldability of the sensor makes it suitable for the environment with different geometries, shapes, and dimensions like industry, body parts, and objects for liquid detection.

According to the Canadian Science Publishing, there are approximately 2.5 million scientific papers published each year. The huge volume of publications can be contributed to a substantial increase in the total number of academic journals, including the increasing number of predatory or fake scientific journals, which yield high volumes of poor-quality research work. The effect of this scenario is that there is an obsolete jungle of journals to flip through in searching for high-quality and relevant references for researchers, ranging from the ones who simply look for citations to cite or latest development and knowledge in a specific scientific area of study. Querying existing web search engines and research paper archived websites is not the solution to the problem, since they are m-equipped to suggest high quality publications to meet the users’ information needs. In solving this problem, we propose an elegant research paper recommender, which is unique compared with existing ones, since besides considering the topics and contents of related publications, it also examines the authority and popularity of each publication to ensure its quality. Conducted empirical study shows that our recommender outperforms existing research paper recommenders and contributes to the design of searching relevant publications.

At present, the oil-paper insulation structure is mainly composed of traditional mineral oil and cellulose insulation paper. The hots pot of future research is to select better insulation oil to improve the overall insulation life of the system. Compared with traditional mineral insulation oil, gas to liquid(GTL) oil made from base oil refined by natural gas liquefaction technology by Fischer-Tropsch(FT) method are characterized by high oxidative stability and low sulfur content. In this paper, the space charge accumulation, distribution and attenuation characteristics of oil-impregnated paper composed of GTL oil and traditional mineral oil were studied. The space trap energy level and trap density distribution of two oil-impregnated papers were obtained according to isothermal decay current(IDC) method. The experimental results show that in the voltage-on stage, traditional mineral oil-impregnated paper is more prone to charge injection and the injection speed is faster. In the voltage-off stage, the traditional mineral oil-impregnated paper attenuates the charge faster, and the GTL oil-impregnated paper has more residual charge. Moreover, the trap level of GTL oil-impregnated paper is deeper than that of traditional mineral oil-impregnated paper.

Plastic bags have been introduced in the middle of 19th decade and it's received a huge popularity amongst the consumers and retailers. Around the world, numerous plastic plants are manufacturing tons of plastic bags which are very commonly used by the society because of its comfort, cheapness and handiness. But the adverse impact of plastic is certainly not highlighted or not openly debated in a serious tone. The negative impact of the plastic in the environment made many counties to ban it due to public concern. Specifically, in Agri dominant countries, such as Bangladesh, India, Pakistan, South Africa, etc., the government has taking stringent efforts towards the prevention of single ended plastic. Since, plastic bags are not bio-degradable, the only way to get rid of them is to burn up which discharges the toxic fumes into atmosphere. Dumping of plastics at the soil will also results in degradation of soil quality and makes it as an unfit to the agriculture. The domestic animals will take the plastic papers as food which will lead to their death. An ultimate solution to the above said problem is the replacement of paper bags, in the place of plastic bags. The cost, ease, availability and load carrying capacity are the main factors restricting the use of paper bags among the public. Only Few manufactures are available in the field and due to the cost of machineries, complexity of production, availability of raw materials, man power and electricity demand results in higher cost which becomes as a barrier among the common man in the adoption of paper bags. In this paper, a cost effective, portable, solar powered paper-bag making machine is proposed to produce paper-bags. The proposed design will minimize the usage of plastic bags and assist in the motto of a clean and safe society. The machine is capable of handling different sizes and textures of the paper. It also has the provision to control the speed of production and monitor the quality of the output. The bags are tested for standard conditions and were found to have enough strength to replace 20-micron plastic bags.