Reviewerly/exHarmony huggingface dataset:
Network Fault Diagnosis of Embedded System Based on Topology Constraint and Data Mining

Maintaining the safe and efficient operation of network technology is an important development task of the computer industry. Topology constraint can optimize and combine the tracking results and select the target objects with better tracking performance to obtain the final tracking results and determine the target scale changes. Data mining technology can reduce the number of combinations to be detected, reduce the workload, and improve the timeliness and accuracy of the process of mining alarm association rules. Therefore, based on the summary and analysis of previous research results, this paper studied the network fault diagnosis of the embedded system method based on topology constraint and data mining. Firstly, a fault diagnosis topology model was established by constructing a topology search algorithm, which eliminated the filtering of association rules without topology relationship; the association rule-based data mining model was analyzed through the collection of network alarm data; the model algorithm was applied to the simulation experiment of network fault diagnosis of the embedded system and achieved good results. The results show that correcting rage of retrieval varies from 0.65 to 090 under different window sizes; the running time of the proposed method drops from 310 s to 35 s during 1–8 step/s of the sliding step, while the node degree ranges from 8 to 14 and diagnostic accuracy ranges from 0.97 to 0.94; the remaining alarm number increases from 0.5 to 3.5 threshold value, while the regular association number distributed in an interval of 40 to 140. The algorithm in this paper provides a reference for further research on network fault diagnosis of the embedded system.
Full-Body Interaction in a Remote Context: Adapting a Dance Piece to a Browser-Based Installation

This paper describes the process of adapting a dance piece to an interactive installation. To cope with COVID-19 restrictions, the installation runs on a browser, allowing for remote access, and is based on camera tracking of movement. We describe the adaptation of the dramaturgy, with a primary focus on translating the interaction design aspects from the performance to the browser-based installation. We invited five users to test our working prototype, and we report on their feedback. This paper offers insights on how to adapt a dance piece to an interactive browser-based installation. We also highlight the benefits of using machine learning for motion capture in this context. Finally, we identify the potential of using interaction design with sound for embodied perception.
Development of an Educational and Research Poultry Laboratory with Remote Access

Training of specialists is the most important stage of technological renewal of the agricultural industry in Russia. The introduction of remote access technologies in the learning process serves as a response to the growth of digitalization of production and allows for the implementation of distance learning programs. Poultry laboratories and experimental farms with remote access are currently unavailable for educational and research purposes. The solution may be to create a model laboratory of digital poultry farming. (Research purpose) The research purpose is in studying and systematization of the domestic and foreign experience in creating laboratories with remote access paying attention to the possibility of its application by specialists for the development of a poultry laboratory with remote access. (Materials and methods) The article reviews the documentary studies of the current state of remote access technologies. Authors conducted search experiments and analyzed the obtained data. (Results and discussion) The laboratories of a technical orientation with remote access are widely represented in Russia and abroad, whose experience can be partially used. They provided links to existing laboratories and materials on their development. At the first stage, it was proposed to use low-budget schemes for organizing remote access based on video surveillance systems and microcontrollers. A simple way to organize remote access is video surveillance with the placement of instrument screens in the field of view of the camera. The Smart Home technology can be used to organize two-way remote access. The article presents the results of an experiment using microcontrollers as a local server with information output to a remote server. (Conclusions) Poultry breeding laboratories with remote access are promising in the study of specialties: private animal husbandry, agricultural mechanization, electrical engineering, veterinary medicine and zoopsychology, they expand the opportunities of remote students.
Effect of optimization framework on rigid and non-rigid multimodal image registration

The process of transforming or aligning two images is known as image registration.In the present era, image registration is one of the most popular transformation tools in case of, for example, satellite as well as medical imaging analysis.Images captured by difference devices that can be processed under same registration model are called multimodal images.In this work, we present a multimodal image registration framework, upon which ant colony optimization (ACO) and flower pollination algorithms (FPA), which are two meta heuristics algorithms, are applied in order to improve the performance of a proposed rigid and non-rigid multimodal registration framework and decrease its processing time.The results of the ACO and FPA based framework were compared against particle swarm optimization and Genetic algorithm-based framework's results and seem to be promising.
Application of Blockchain in KYC Compliance

The current process of Know Your Customer (KYC) used by banks is time-consuming, expensive, and redundant in practice. A Thomson Reuters Research states that while banks globally spend around 60 million USD on an average, this number may go up to 500 million USD for some banks [1]. Hence, to improve the efficiency of this process, the use of a blockchain-based mechanism is suggested. The use of smart contracts also provides scope for adding features that cannot be achieved by the current process. The paper majorly discusses the advantages and disadvantages of using blockchain for performing KYC processes.
The Effectiveness of Kahoot! in Improving Understanding of Scientific Works in the Distance Learning

The Covid-19 virus pandemic that has hit the world since two years ago has changed the education system rapidly and extremely, mainly in the process of teaching and learning activities. All learning activities turn into distance learning. This research tries to study the students of Semarang Polymarine in the Commercial and Port Shipping Management Study Program who take an Indonesian language course. It has two main objectives. The first is to improve the students' ability to write scientific papers on distance learning. The second one is to find out the effectiveness of using Kahoot! to improve the ability to write scientific papers on distance learning. This is a classroom action research that consists of two cycles each research stage to identify and view the implementation of the Kahoot! in the learning process. Each cycle is divided into four stages of research. They are planning, implementation, observation, and reflection. This research uses three techniques in data collection, namely observation, interviews, and documentation. The results show that there is an increase in the students’ learning outcomes which can be seen from the post-test scores. The use of Kahoot! can also be said as successful, because the students’ learning outcomes have reached 75% of the students’ being tested
Sistem Informasi Akuntansi Simpan Pinjam Pada Sinar Kalimantan Dengan Metode Pengembangan Waterfall

&#x0D; &#x0D; &#x0D; &#x0D; Sinar Kalimantan Cooperative is a community service cooperative in savings and loans. Based on the analysis that has been done, the Sinar Kalimantan Cooperative still recaps each per each cash-in and cash-out data transactions that come from notes and then copy them to Ms. Excel to be used as financial statements. Processing data like this requires effort and a long time, errors in data processing that have an impact on the quality of information in financial statements. Therefore, the purpose of writing this Final Project is to design and build a web-based savings and loan accounting information system at the Sinar Kalimantan Cooperative using the waterfall model as a software development method consisting of analysis of software requirements, design, program code creation and testing. Data collection techniques used consisted of observation, interviews and literature study. This system is built to provide facilities for two users, namely the Chairman and the Cashier. Chairman can manage employee (user) data, access loan reports, loan list reports, installment reports, savings reports, general journal reports, general ledger reports, balance sheet reports, cash receipts reports, cash disbursements reports and cash flow report. The cashier can manage account data, customer data, deposit data, deposit withdrawal data, loan data, installment data and expense (cost) data and access loan reports, loan list reports, installment reports and savings reports. The savings and loan accounting information system that was built is expected to help improve the performance of savings and loan data processing at the Sinar Kalimantan Cooperative.&#x0D; &#x0D; &#x0D; &#x0D;
The Application of A Contextual Approach in Indonesian Learning About Writing Exposition Text

Indonesian language learning can not be separated from the methods of approach in the delivery of materials in this case one of the approaches used is contextual approach. The implementation of this approach must have inhibitory factors and supporting factors. The purpose of this research was to find out how the implementation of the application, inhibitory factors and supporting factors contextual approach in learning Indonesian text material exposition students Class X IPA 3 SMA 1 Negeri Kinali. This type of research is descriptive qualitative. Data collection by conducting observations of teachers, students and classes, interviews and documentation. The subjects of this study were Indonesian language teachers and X IPA 3 grade students. Data validity technique is triangulation of sources by means of data suppression obtained. Based on the results of research conducted by researchers to teachers and students of Grade X IPA 3 SMA 1 Negeri Kinali. That the implementation of contextual approach is implemented ideally this has been proven by the existence of research interviews to teachers, students and monitoring carried out when the teaching and learning process takes place and the supporting factors are enthusiastic learners in following the learning, as well as adequate facilities and pre-facilities and inhibitory factors are lack of time and lack of materials delivered.
Sistem Informasi Layanan Pengaduan Masalah Pegawai Berbasis Android

Services provided by an organizational unit or people who work in that organization and employees in other units are known as internal services. The use of web applications for problem complaints services at the Secretariat General of DPD RI is still considered less flexible because the activities of employees and officials within the Secretariat General of DPD RI are mobile and rarely in the room. This research aims to design a mobile-based problem complaint information system by applying the waterfall system development methodology. System requirements analysis was conducted by interviewing two informants with more than two years of service and observing the current system. The study results stated that the problem complaint information system managed to display the things that were expected from the entire menu after being tested using the black-box method. After testing, it is hoped that a mobile-based problem complaint information system can be developed by adding features that support and measure the performance of employees or officials.
The Effectiveness of Mathematical Learning Based on WhatsApp Groups Assisted by LKPD and Student’s Motivation

&lt;p&gt;&lt;em&gt;This research is a quasi-experimental research that aims to determine whether online learning based on WhatsApp Group with LKPD assistance is more effective than with-based online learning WhatsApp Group without the assistance of LKPD in terms of student learning motivation towards mathematics learning outcomes of class VII students at SMP Negeri 3 Jetis. The data analysis technique used t-test, prerequisite test in the form of normality test and homogeneity test, Mann-Whitney test, and Kruskal Wallis test. The result of this study is that online learning based on WhatsApp Group with the assistance of LKPD is as effective as online learning based on WhatsApp Group without the assistance of LKPD and the mathematics learning outcomes of students with high motivation are better than students with moderate and low motivation.&lt;/em&gt;&lt;/p&gt;
Management Of Reading Community Pelosok Bumi In Karawang Regency

Aims to describe planning, organizing, and supervising reading community. The concept of George Robert Terry (2007:31) "Management as a typical process, carried out to determine and achieve the goals that have been set by the use of human resources and other resources." Qualitative research approach. Data collection techniques are observation, interviews, and documentation. The research subjects were one manager, one volunteer, and two residents student of reading community Pelosok Bumi, Karawang. Analysis of the research obtained there are four stages in the management begins with the identification of learning needs in the planning stage. Organizing is done by grouping the teaching staff into study groups. The implementation started on Saturday. The media, the strategies and methods used were returned to the volunteers. Supervision is carried out by going directly into the study group and immediately after the implementation there is a learning evaluation meeting. Suggestions Institutions can add volunteers so that the learning situation can be conducive.Keywords: Management, Reading Community
Neutrino Oscillations: Solar

The Standard Model of particle physics is an amazingly successful theory describing the fundamental particles and forces of nature. This text, written for a two-semester graduate course on the Standard Model, develops a practical understanding of the theoretical concepts it's built upon, to prepare students to enter research. The author takes a historical approach to demonstrate to students the process of discovery which is often overlooked in other textbooks, presenting quantum field theory and symmetries as the necessary tools for describing and understanding the Standard Model. He develops these tools using a basic understanding of quantum mechanics and classical field theory, such as Maxwell's electrodynamics, before discussing the important role that Noether's theorem and conserved charges play in the theory. Worked examples feature throughout the text, while homework exercises are included for the first five parts, with solutions available online for instructors. Inspired by the author's own teaching experience, suggestions for independent research topics have been provided for the second-half of the course, which students can then present to the rest of the class.
A weight Jackknife approach utilizing linear model based-estimators for clustered data

Small number of clusters combined with cluster level heterogeneity poses a great challenge for the data analysis. We have published a weighted Jackknife approach to address this issue applying weighted cluster means as the basic estimators. The current study proposes a new version of the weighted delete-one-cluster Jackknife analytic framework, which employs Ordinary Least Squares or Generalized Least Squares estimators as the fundamentals. Algorithms for computing estimated variances of the study estimators have also been derived. Wald test statistics can be further obtained, and the statistical comparison in the outcome means of two conditions is determined using the cluster permutation procedure. The simulation studies show that the proposed framework produces estimates with higher precision and improved power for statistical hypothesis testing compared to other methods.
A Cortical Learning Machine for Learning Real-Valued and Ranked Data

The cortical learning machine (CLM) introduced in [1-3] is a low-order computational model of the neocortex. It has the real-time, photogragraphic, unsupervised, and hierarchical learning capabilities, which existing learning machines such as the multilayer perceptron and convolutional neural network do not have. The CLM is a network of processing units (PUs) each comprising novel computational models of dendrites (for encoding), synapses (for storing code covariance matrices), spiking/nonspiking somas (for evaluating empirical probabilities and generating spikes), and unsupervised/supervised Hebbian learning schemes. In this paper, the masking matrix in the CLM in [1-3] is generalized to enable the CLM to learn ranked and real-valued data in the form of the binary numbers and unary (thermometer) codes. The general masking matrix assigns weights to the bits in the binary and unary code to reflect their relative significances. Numerical examples are provided to illustrate that a single PU with the general masking matrix is a pattern recognizer with an efficacy comparable to those of leading statistical and machine learning methods, showing the potential of CLMs with multiple PUs especially in consideration of the aforementioned capabilities of the CLM.
A Temporal Case-Based Reasoning Platform Relying on a Fuzzy Vector Spaces Object-Oriented Model and a Method to Design Knowledge Bases and Decision Support Systems in Multiple Domains

Knowledge bases in complex domains must take into account many attributes describing numerous objects that are themselves components of complex objects. Temporal case-based reasoning (TCBR) requires comparing the structural evolution of component objects and their states (attribute values) at different levels of granularity. This paper provides some significant contributions to computer science. It extends a fuzzy vector space object-oriented model and method (FVSOOMM) to present a new platform and a method guideline capable of designing objects and attributes that represent timepoint knowledge objects. It shows how temporal case-based reasoning can use distances between temporal fuzzy vector functions to compare these knowledge objects’ evolution. It describes examples of interfaces that have been implemented on this new platform. These include an expert’s interface that describes a knowledge class diagram; a practitioner’s interface that instantiates domain objects and their attribute constraints; and an end-user interface to input attribute values of the real cases stored in a domain case database. This paper illustrates resultant knowledge bases in different domains, with examples of pulmonary embolism diagnosis in medicine and decision making in French municipal territorial recomposition. The paper concludes with the current limitations of the proposed model, its future perspectives and possible platform enhancements.
Graph Neural Network Research at AWS AI

In the course of just a few years, Graph Neural Networks (GNNs) have emerged as the prominent supervised learning approach that brings the power of deep representation learning to graph and relational data. An ever-growing body of research has shown that GNNs achieve state-of-the-art performance for problems such as link prediction, fraud detection, target-ligand binding activity prediction, knowledge-graph completion, and product recommendations. As a result, GNNs are quickly moving from the realm of academic research involving small graphs to powering commercial applications and very large graphs. This talk will provide an overview of some of the research that AWS AI has been doing to facilitate this transition, which includes developing the Deep Graph Library (DGL)-an open source framework for writing and training GNN-based models, improving the computational efficiency and scaling of GNN model training for extremely large graphs, developing novel GNN-based solutions for different applications, and making it easy for developers to train and use GNN models by integrating graph-based ML techniques in graph databases.
Can We Learn to Hear Multi-metrically?

While certain strands of music-cogition studies suggest that we can only entrain to one metric stratum at a time, I contend that not only can we entrain to two or simultaneously, but that certain musicking practices (particularly from African and the African diaspora) require that one do so. This essay explores some scaffolded introductory activities for learning to do so through stepping, clapping, and singing.
Euler and RK4 Algorithms Based Implementation of Autonomous Chaotic Generator

Chaotic systems plays a vital role in the field of security, data hiding and steganography. FPGA implementation makes more advantageous compared to analog one. Different chaotic systems like chaos generator and nondeterministic number generator used for security purpose and key generation were successfully realized in FPGA. In this paper, FPGA implementation of Pandey-Baghel-Singh chaotic system (PBSCS) using Euler and RK4 numerical algorithms is presented. Pandey-Baghel-Singh chaotic system were obtained using numerical differential solution and numerically modelled in Verilog with the environment of Xilinx Vivado 2017.3 design suite. The design is verified using experimental setup with the help of interfacing to PC and FPGA family of Artix-7 Nexys 4 DDR and Basys3. Performance of the FPGA based chaotic generator using Euler and RK4 algorithm are analyzed using 1 GB data sets with the maximum operating frequency achieved up to 359.71 MHz.
Introduction

Nowadays, one of the most important applications of intelligent systems are expert systems for decision making, these kinds of systems can provide experts with a tool for expert systems.
Adaptive Algorithms for Knowledge Acquisition Over Complex Networks

Knowledge acquisitionKnowledge acquisition over complex networks is a process of identifying nodes (knowledge sources) that possess the required knowledge. Despite substantial research on knowledge management, it remains a challenge to effectively acquire distributed knowledge from a few entities within a network of interrelated knowledge sources.
Sign Language Detector using cloud

Abstract: Peoples who are deaf/dumb use Sign language to convey their message to normal people. Sign language detector using cloud provides us an innovative, user friendly way of interaction with the computer which is more familiar to human beings. Sign language detector has a wide area of application including human machine interaction, sign language, immersive game technology etc. By keeping in mind, the similarities of human hand shape with four fingers and one thumb, this paper aims to present a real time system for sign language detector on the basis of detection of some meaningful shape-based features like orientation, center of mass (centroid), status of fingers, thumb in terms of raised or folded fingers of hand and their respective location in image. The approach introduced in this paper is totally depending on the shape parameters of the hand gesture. It does not consider any other means of hand gesture recognition like skin color, texture because these image-based features are extremely variant to different light conditions and other influences. To implement this approach, we have utilized a simple web cam which is working on 20 fps with 7 mega pixel intensity. Keywords: Sign language detector, cloud