Reviewerly/exHarmony huggingface dataset:
Multi-Agent System Applications in Health Care: A Survey

Earlier, medical systems were suffering from many issues. The issues are mostly observed due to inadequate medical practitioners, poor medical infrastructure, manually operated healthcare systems and improper coordination between each and every aspects of healthcare system. Most of the medical reports and records are based on paper and pen, which is difficult to manage and maintain and also raise a question of reliability. So, situation needs a change in the existing system. Keeping that need of change in mind, the concept of multi-agent system was introduced in healthcare system. Multi-agent systems are considered as the best and most appropriate technology that can be applied to fulfill the need required in healthcare system. In multi-agent system, the agents are representing and acting on behalf of users and owners with very difficult goals and motivations. The agents cooperate, coordinate and negotiate with each other in the same way that we cooperate, coordinate and negotiate with other people in day-to-day life and consequently can be used as the best technology to solve the problem arrived in medical healthcare system. This chapter focuses mainly about architecture, planning, implementation and application of multi-agent system in healthcare domain. Categories and Subject Descriptors General and reference: Surveys and overviews—multi-agent system (MAS), artificial intelligence, healthcare domain.
3d Dual-Stream Convolutional Neural Networks with Simple Recurrent Unit Network: A New Framework for Action Recognition

Human action recognition is a supervised process of labeling an entire video image sequence with action labels in computer vision fields. Different from the recognition of static images, this process also needs to learn the contact information between video frames, such as the timing characteristics that reflect the changes of actions in the video. In existing deep learning methods, due to the size of the convolution kernel, the models use a small number of consecutive frames as input and trains to assign feature vectors to short sequences instead of the entire sequence. Therefore, even if the learned features contain time information, their evolution over time will be completely ignored. In this work, we propose a dual-stream deep fusion framework that can fully utilize the long-term information of a video. We preprocess the video into static frames and optical flow graphs and input them into a three-dimensional convolutional neural network to obtain the spatiotemporal feature stream with time series. Then, the spatiotemporal feature stream is input into a simple recurrent unit network to learn the long-term sequence features of the time dimension. Finally, SoftMax classifier is used for feature classification. We tested our model on the classic action recognition UCF-101 and HMDB-51 data sets, and our model achieved better performance than existing methods.
Human Implicit Intention Inference Based on Gaze Information

Abstract: In artificial intelligence, correct intention inference is conducive to the natural and effective interaction between humans and robots. This paper proposes a gaze-based implicit intention inference model. Firstly, we extract the gaze coordinates from the eye movement data and obtain the gaze center coordinates through clustering. Then the visual gaze center coordinates are registered with the object center coordinates in the scene map to complete the recognition of the human gaze object sequence Finally, the sequence of objects being watched is matched with a set of trained single intention models. Through the matching score, the implicit intention behind the sequence of human gaze objects is inferred. The experimental results show that in the case of interference, the accuracy of implicit intention inference is more than 93%, which ensures the reliability of implicit intention inference of restricted people in human-robot interaction.
Self-education of adolescent schoolchildren as a socio-pedagogical necessity

In modern conditions, the question of the need for self-education of students remains relevant. Today it is impossible to find a single sphere of human activity that is not associated with the generally recognized spiritual and material values of society as a whole and of each person. In this regard, the purpose of the article is to consider the need to build pedagogical systems for the actualization of the student's self-education, which are set by the emerging trends of humanization, differentiation of the environmental friendliness of social processes, elevating the function of education in the structure of educational processes and causing the need for a new reading of the concept of education as a synthesis of the processes of learning and learning, upbringing and self-education, development and self-development, maturation and socialization of the individual.
Pay-Per-Byte for Block Reward: A Revised Incentive Mechanism in Bitcoin

Since Satoshi Nakamoto introduced Bitcoin in 2009, there have been around more than 1600 other cryptocurrencies in the market [1]. However, only a handful of them can be compared with bitcoin as it still rules the cryptocurrency market. There are two types of incentives provided by Bitcoin for miners, namely Block Reward and Transaction Fees. For every miner, the block reward matters more than the latter one. Miners being the creator of the block and having received block reward have the moral obligation towards the system to give their best and to not be greedy while mining. However, it is found that around a quarter of the mined blocks until the start of 2017 are empty blocks and other blocks are also merely half-full from their allowed capacity. Thus, this work proposes a cerebral change in the block reward system. Being derived from pay-per-piece wage system, this revised mechanism imposes a policy of contributing best to the system on miners. This work comprises of theoretical discussion and experiment results analysis of the system with future extensions. Every Satoshi (smallest unit of bitcoin) being a scarce asset, miners should be rewarded in proportion to their better intentions towards the system.
METHODOLOGICAL SUPPORT IN IMPLEMENTATION OF PROGRAM FOR UNIVERSAL COMPETENCIES FORMATION AMONG COLLEGE STUDENTS IN LEISURE ACTIVITIES

We consider the possibilities of leisure activities in universal competencies formation of future teachers. Presented detailed methodological support for the implementation of the author's program “Crossroad” for students in the pedagogical college is relevant due to the need for effective formation of universal competencies among students in the competently organized professionally-oriented leisure. The idea of the “Crossroad” program is to integrate several directions (“Spiritual Spring”, “Life in Art”, “I give my heart to children”, “Laboratory of Interactive Technologies”) that contribute to the innovative and creative development of the individual. Each of these directions is disclosed in detail and methodically developed, the specifics of the forms, methods and means of education and upbringing used in this process are revealed. Emphasized activity of the interactive technologies laboratory provides high-quality training in the most popular and promising areas of the socio-pedagogical sphere of the region due to the new content of education and new learning technologies. It is necessary to use a portfolio as the most pragmatic and personalized form for the correct assessment of individual achievements and universal competencies of a college student.
A Differential Privacy Approach to Preserve GWAS Data Sharing based on A Game Theoretic Perspective

Genome-wide association studies (GWAS) aim to find the significant genetic variants for common complex disease.However, genotype data has privacy information such as disease status and identity, which make data sharing and research difficult.Differential privacy is widely used in the privacy protection of data sharing.The current differential privacy approach in GWAS pays no attention to raw data but to statistical data, and doesn't achieve equilibrium between utility and privacy, so that data sharing is hindered and it hampers the development of genomics.To share data more securely, we propose a differential privacy preserving approach of data sharing for GWAS, and achieve the equilibrium between privacy and data utility.Firstly, a reasonable disturbance interval for the genotype is calculated based on the expected utility.Secondly, based on the interval, we get the Nash equilibrium point between utility and privacy.Finally, based on the equilibrium point, the original genotype matrix is perturbed with differential privacy, and the corresponding random genotype matrix is obtained.We theoretically and experimentally show that the method satisfies expected privacy protection and utility.This method provides engineering guidance for protecting GWAS data privacy.
An Investigation of Paralysis Attack Using Machine Learning Approach

Many people in today’s world suffer from paralysis and most of the paralytic patients are dependent on caretakers. As a result, many survivors have lost some of their abilities that are required to perform daily tasks. Paralysis is a condition in which there is impairment of one or more muscles in the body. In order to assist these patients, fingers of the hand play a major role. The main aim is to achieve light weight; comfortable gloves which can allow finger movement that has lost strength or nerve control. The soft hand glove could be used as an assistance to help the patient grip, pick up and lift objects. Using this glove, the patient gradually starts to restore the functionality of his hand. In our literature survey found some papers that use various types of methods using machine learning algorithms to assist paralyzed patients to address the challenges toward its research directions.
A Distributed Computation Marketplace over Blockchain

We describe a Blockchain-based, peer-to-peer network of distributed computers solving arbitrary, strictly- defined problems for a financial incentive in the form of a cryptographic currency. The computational problems are signed and posted to the blockchain in a contract describing the minimal computational unit (MCU) of the problem, the price per MCU, a method for joining the results of different Solvers, and a test for the validity of a solution.The Solver will transmit the solutions to the Bidder off the blockchain to avoid any space-complexity issues and eliminate the potential for network flooding with bogus or trivial solutions. The Bidder will transmit the Solver a signature for a payout transaction upon validation. A solution for a single MCU is used as a handshake between Bidders and Solvers, and for each following solution message, the Solver will increase the number of MCUs on a logarithmic scale. A Bidder can delegate the validation and signing process to Validators who place a significant monetary stake for this privilege and are rewarded by the network with a dynamic fee correlating to the number of open contracts. Once the Bidder receives a satisfactory amount of work, they can close the contract by submitting a signed message to the blockchain.
Quantification of the Effects of Aerosols and Clouds on Solar Energy Over China Using Wrf-Chem

The promotion of renewable energy as a substitute for fossil fuels is the key solution to achieve the goals established during the United Nations Climate Change Conference in Glasgow (COP26) based on which member countries agreed to phase down coal power and achieve net-zero carbon emissions. Among various renewable energy sources, solar energy is an attractive option that will have a significant effect on the future energy supply and energy use. Therefore, we selected the period of 2016–2020 during which the aerosol concentration gradually decreased due to strict pollutant control measures to evaluate solar energy simulations based on the Weather Research Forecast-Chemistry (WRF-Chem) model. We also analyzed the contributions of the aerosol direct effect (ADE), aerosol indirect effect (AIE), and cloud radiation effect (CRE) to solar energy trends by conducting sensitivity experiments. The results show that the WRF-Chem model performs well for the 2 m temperature (T 2 ), cloud fraction, PM 2.5 , solar energy trends during 2016–2020. There are regional and seasonal differences in the contributions of ADE, AIE, and CRE to solar energy trends, with a decrease in ADE contributions and an increase in CRE contributions from north to south in China, and the AIE contribution being relatively slight. On an annual scale, ADE is the main contributor to the increase in solar energy trends in the Beijing-Tianjin-Hebei (89%) and Fenwei Plains (83.9%) from 2016 to 2020, which is related to the horizontal distribution of PM 2.5 . In the Yangtze River Delta and other regions, ADE and CRE contributed equally to the increase in solar energy trends, about 40%. In the Pearl River Delta and Sichuan Basin, the contribution of CRE is larger than that of AIE and ADE, the Pearl River Delta region is the largest contributor of CRE to the annual solar energy trends among the five major urban agglomerations, with a contribution of 78.4%, and Sichuan basin is the only region where CRE has a negative contribution to the annual solar energy trends (-59.1%). On the seasonal scale, the contribution of CRE is dominant except for the greater positive contribution of ADE to the solar energy trends in spring, summer, and autumn in Beijing-Tianjin-Hebei and in autumn in Fenwei Plain.
Design Protection in the Nordic Countries: The Past, the Present and Maybe the Future

The Nordic countries adopted similar Designs Acts in the 1970s and these Acts remained in place until the European Union (EU)-harmonized design regime took over in the early 2000s. This chapter first describes the background to the pan-Nordic Acts and then moves on to point out how they generally failed to live up to the expectations of the legislators in providing a tailor made protection system for the ‘modern’ functional (‘Scandinavian’) designs that had emerged from the 1950s. Next, the chapter turns to the current protection in the Nordic countries under the EU regime. It is shown how designers in some of the Nordic countries have more or less abandoned the national system based on the national Design Acts and instead have turned to the EU Design Regulation. It is also argued that the national (Danish) courts are becoming better at following the guidance from the Court of Justice of the European Union and are coming out of the shadows of the pan-Nordic Acts and into the harmonized EU-based design system. The final part uses the Nordic experiences to reflect on the recommendations in the recent Evaluation of EU Legislation on Design Protection.
Quantization Methods for Stochastic Differential Equations

In this paper we provide an introduction to quantization with applications in quantitative finance.We start with a review of vector quantization (VQ), a method originally devised for lossy signal compression. The basics of VQ are presented and applied to probability distributions.
SemanticStyleGAN: Generative Image Inpainting Using Style-Based Generator

Image inpainting, a task of reconstructing missing or corrupted image regions, has a great potential to advance the fields of image editing and computational photography. Despite being a difficult problem, the researchers have made headway into the field thanks to the progress in representation learning with very deep convolutional neural networks and the successes in generation of realistic images by using Generative Adversarial Networks (GANs). To avoid the problems of generating blurry and distorted regions as well adding artefacts, a new model for image inpainting is proposed in this paper. The GAN-based architecture incorporates two frameworks, the model for semantic image inpainting and the models for style transfer, which have been pointed out to be successful in previous research. Our model was evaluated on the Flickr-Faces-HQ dataset. The results are promising and point out that using a combination of various GAN-based technologies could improve the performance on the task of image inpainting. Directions for future research are also discussed.
Design Of Home-based Elderly Care System Based On Internet of Things Technology

At present, the problem of population aging in China is becoming more and more serious, and the problems faced by the pension model under the traditional model are becoming more and more serious. How to solve these problems through Internet of things technology, meet the diversified and intelligent needs of the elderly, and provide convenient home-based elderly care services for the elderly has become a common concern of the whole society. This paper makes full use of sensors and video detection technology to establish a home intelligent elderly care system to realize the real-time collection, reception, storage, query and display of home environment, heart rate, blood oxygen, body temperature and signs of the elderly, and whether the elderly fall. The results show that the design has high accuracy and real-time, and is a low-cost and practical home intelligent elderly care scheme.
Building a Global Content Provider Network at Scale

This tutorial covers scaling the backbone network of a global content provider. Key constraints on network growth are classified and scaling strategies discussed. Optimizations and architecture changes for higher scale are presented.
Support Vector Machines

This chapter studies binary classification from a non-statistical viewpoint. For data that are linearly separable, the perceptron algorithm is presented first. It is followed by an optimization program, known as the hard support vector machine (SVM), consisting in maximizing the margin. For data that are not exactly linearly separable, this optimization program is relaxed into soft SVM. Finally, for data that are linearly separable only after applying a feature map, the representer theorem is used to validate the so-called kernel trick.
A Simulation and Machine Learning Informed Diagnosis of the Severe Accidents

Highlights- A simulation and machine learning informed model (SMLIM) is proposed- Training and test data are generated by MELCOR simulations- Station Black Out scenario in the Fukushima Daiich Unit 1 is chosen- The model has four features with drywell pressure as a target variable- LSTM network model is used for forecasting and regression in time series- SMLIM is used for the diagnosis of the accident progression and the validity of measurement
Modeling and Integrating Interactions Involving the CYP450 Enzyme System in a Multi-Terminology Server: Contribution to Information Extraction from a Clinical Data Warehouse

Introduction: The cytochrome P450 (CYP450) enzyme system is involved in the metabolism of certain drugs and is responsible for most drug interactions. Detecting these interactions will allow for better predictability in therapeutic response. Therefore, computerized solutions can represent a valuable help for clinicians in their tasks of detection.Objective: The objective of this study is to provide an open access structured date-source of interactions involving the CYP450 enzyme system. These interactions are aimed to be integrated in the cross-lingual multi-terminology server HeTOP (Health Terminologies and Ontologies Portal), to support the query processing of the clinical data warehouse (CDW) EDSaN (Entrepôt de Données de Santé Normand).Material and methods: A selection and curation of drug components (DCs) that share a relationship with the CYP450 system was performed from several international data sources. The DCs were linked according to the type of relationship which can be substrate, inhibitor, or inducer. These relationships were then integrated into the HeTOP server and a semantic query was performed on the CDW.ResultsA total of 776 DCs are associated by a new interaction relationship, by 14 enzymes. These are CYP450 1A2, 2A6, 2B6, 2C8, 2C9, 2C18, 2C19, 2D6, 2E1, 3A4, 3A7, 11B1,11B2 mitochondrial and P-glycoprotein, constituting a total of 2,088 relationships. 233,006 queries were processed. Moreover, they showed that in our university hospital, the most frequent concurrent prescription that could cause a cytochromic interaction is Bisoprolol with Amiodarone by enzymatic inhibition for 2,493 patients.DiscussionThe queries submitted to the CDW EDSaN allowed to highlight the most prescribed molecules simultaneously and potentially responsible for cytochromic interactions. In the future, it would be interesting to evaluate the real clinical impact.Conclusion: The HeTOP server contains a non-negligible number of relationships between drug components and CYP450 from multiple reference sources. These data allow us to query our Clinical Data Warehouse to highlight these cytochromic interactions.
Dynamic Crossover in Metallic Glass Melt Detected by Nmr

The structure and dynamics of melts have critical influence on the glass formation and solidification of crystals, which attracts broad interest to clarify the underlying mechanisms. In this paper, the quadrupolar spin-lattice relaxation rates of 63 Cu and 65 Cu nuclei in a Au 50 Cu 25.5 Ag 7.5 Si 17 metallic glass melt are studied by using a home-designed high-precision high-temperature NMR equipment. The relaxation rates follow the Arrhenius behavior at high temperatures above 870 K, but become non-Arrhenius at low temperatures, which indicates a non-Arrhenius dynamical crossover. The crossover temperature T A is about 2.3 times of the glass-transition temperature ( T g =378 K). Based on the analysis of Knight shift and magnetic relaxation rates, Cu and Si atoms are found to tend to form stronger covalent-like bonds below T A . Such an increase in bonding strength may be responsible for the observed sluggish dynamics.
Eye-Controlled Wheelchair Improves Quality-of-Life on Paraplegic Patients in Home-Care Setting: A Case Study

A powered wheelchair is usually controlled with a joystick, but there are other input devices that can be used if the user lacks either coordination or the use of their hands or fingers. This study purposed to evaluate the impact after using the eye-controlled wheelchair in short term. Two elderly female subjects who suffer from stroke and spinal cord injury were recruited from a local old folks home-care. Both of them were manual wheelchair bounded and needs the assistance of their caregivers to wheel them around their home-care. Subjects’ QoL after the eye-controlled usage was assessed using a self-designed questionnaire. The data were collected and analyzed descriptively. The collected data was interpreted as such to show the subjects’ QoL progress during the 8 weeks of data collection. As in the fourth week, the QoL scores were: subject A (21/32) and subject B (22/32). In contrast, the QoL score increased from the 4th week to the 8th week. In the 8th week, the scores were: subject A (30/32) and subject B (29/32). Interpretation: The final week scores denoted that the subject’s QoL has increased as in contrast to Week 1 scores with Subject A with 9 scores difference and Subject B with 7 scores difference. There was visible QoL score improvement in both subjects comparatively. In conclusion, this study achieved the study aim which is to evaluate the impact after using the eye-controlled wheelchair in short term.