Reviewerly/exHarmony huggingface dataset:
Implementation and Evaluation of Advantage Actor-Critic Algorithm on a Desktop Computer with a Multi-Core CPU

In this paper, the implementation and evaluation of the Advantage Actor-Critic (A2C) algorithm, one of the most important Deep Reinforcement Learning schemes, is performed. The objective is to determine the behavior of the algorithm on a desktop computer with a multi-core CPU, establishing its behavior, performance, and resource consumption for embedded applications. This algorithm makes use of multiple agents on parallel instances of the environment so that each agent adds knowledge to the system, which is weighted by a value of Advantage that evaluates its interaction in the environment. This assessment is performed on OpenAI's CartPole-v0 playground, so the results are comparable and easily reproducible. The results show a high performance of the algorithm for different instances with fixed-length segments of experience, which allows us to think of successful use on more resource-constrained hardware platforms.
Skin Hunger: A Telematic Installation

Skin Hunger is a web-based interactive system for telematic installation and performance that plays on the zoom-style video-chat that has become ubiquitous during the COVID-19 pandemic. Participants in the telematic installation can reach across the webcam screens to virtually ‘touch’ one another. By touching or moving together, participants create virtual organisms and sounds that emerge and evolve from participant relation and interaction, making the intangible connection tangible and giving it life. Skin Hunger explores a new way of enabling embodied joint music making and movement over a distance.
An Example of using Simulators in Basic Electromagnetics Education

In recent years, the period of taking liberal arts subjects and specialized subjects at universities has been mixed over four years, and wedge-shaped education that incorporates specialized subjects into the curriculum has become widespread. Students need to study specialized subjects such as electromagnetics from an early stage. Some ingenuity is required to facilitate the education of electromagnetics in the wedge-shaped curriculum, and the author thinks that visualization of electromagnetic fields by simulation has a high educational effect as one of them. This paper introduces an example of using an electromagnetic simulation application in electromagnetics education. The explained theory and the properties of electric and magnetic fields were confirmed through visualization with a simulator. A questionnaire survey was conducted, and it was found that the use of simulation is effective in promoting understanding.
Advanced Reverse Image Search and Profile Creation using Machine Learning

The Reverse image search is most widely used image search engine due to its extensive database that contains billions of images uploaded over the web. It is best to use the image search when your aim is to find identical images against your queried image. The reverse image search by image is idle option for people getting down similar images in different quality, size, or formats. This online facility leads us to explore image search results with a single click. A convolutional neural network is a type of artificial neural network used for image processing.
English Language Teaching at Kindergarten: What Happens in The Classroom

This study aims to describe the English teaching and learning process for young learners in kindergarten. It used the descriptive qualitative research method. An observation checklist and field notes were used as the instruments to collect the data. The observation covers aspects of language teaching activities such as the students’ role, the teacher’s role, classroom management strategy, approach, technique, materials, tasks, language used, teacher-student interaction, and students’ participation. This study suggested that the English teaching and learning process at Pertiwi Kindergarten can be considered sufficient. It has satisfactorily met 62% of the aspects measured. Some of the highlights of this study are that the TPR method and songs are highly recommended as teaching techniques. Moreover, understanding the characteristics of the young learners is very important for the success of the teaching and learning activities.
Prospects for the use of remote technologies in the course of graduation design

This article discusses topical issues on the possibilities of distance education when conducting diploma design and subsequent diploma defense in technical schools and colleges. Deﬁnitions of such terms as distance education and distance educational technologies are given. The principles of structuring the material in distance learning, psychological features of contacts between teachers and students in the conditions of distance learning, the application of distance education technologies and distance learning models used today are also considered. The method of calculating the strategy by the teacher in the remote preparation of the diploma project for students is also considered. In addition, several models of distance learning are identiﬁed when considering the process of preparing a diploma project by students, namely: a consulting model, a “case technology” model, a model of regulated self-learning. The eﬀectiveness of these models is revealed in the aspect of their application in distance learning at the stage of diploma design and diploma defense by students. Distance learning technologies are a good help in the work of the teaching staﬀ of any educational institution, because they allow students to quickly and with a high degree of quality to provide all the necessary information in a form convenient for them, as well as to exercise eﬀective control over its assimilation by the student.
Analysis on Text Summarization

Abstract: As we enter the 21st century, with the advent of mobile phones and access to information stores, we seem to be surrounded by more information, less time, or the ability to process it. The creation of automated summaries was a clever human solution to this complex problem. However, the application of this solution was very complicated. In fact, there are a number of problems that need to be addressed before the promises of an automated text can be fully realized. Basically, it is necessary to understand how people summarize the text and build a system based on that. However, people are different in their thinking and interpretation that it is difficult to make a "gold standard" summary in which product summaries will be tested. In this paper, we will discuss the basic concepts of this article by providing the most appropriate definitions, characterization, types and two different methods of automatic text abstraction: extraction and extraction. Special attention is given to the method of extraction. It consists of selecting sentences and paragraphs that are important in the original text and combining them into a short form. It is mentally simple and easy to use
Conservation Laws

This advanced undergraduate physics textbook presents an accessible treatment of classical mechanics using plain language and clear examples. While comprehensive, the book can be tailored to a one-semester course. An early introduction of the Lagrangian and Hamiltonian formalisms gives students an opportunity to utilize these important techniques in the easily visualized context of classical mechanics. The inclusion of 321 simple in-chapter exercises, 82 worked examples, 550 more challenging end-of-chapter problems, and 65 computational projects reinforce students' understanding of key physical concepts and give instructors freedom to choose from a wide variety of assessment and support materials. This new edition has been reorganized. Numerous sections were rewritten. New problems, a chapter on fluid dynamics, and brief optional studies of advanced topics such as general relativity and orbital mechanics have been incorporated. Online resources include a solutions manual for instructors, lecture slides, and a set of student-oriented video lectures.
'Intel Acat' Assistive Platform for Arabic Speaking Disabled People: a Complete Integration.

The Intel Assistive Context-Aware Toolkit (ACAT) is the highly configurable platform used by Dr. Stephen Hawking to communicate with his environment. After being released freely to the public, we, at the Embedded Systems Laboratory - UBMA, have been working on integrating the Arabic language on the different packages of the platform in order to make it accessible for disabled people from Arabic countries and decrease their communication limitations.This subproject concerns the Arabic Text-to-speech engine implementation and comes as a final step toward the full integration of the Arabic language into Intel ACAT assistive platform.The text to speech conversions was integrated by implementing a mapping between the Arabic words and their phonetic spelling using Microsoft Text-To-Speech Synthesis on Intel ACAT modules and extensions. A full compilation was then executed and tested gathering all the modules and the features of the platform.Over this final integration step (which is freely accessible and open sourced for the public), people with severe disabilities from Arabic-speaking countries will have fully access to all the features of the ACAT platform and will be able communicate and interact easily with their computers.The Arabic language Text-to-speech engine integration on 'Intel ACAT' Assistive Platform is the final milestone of our project toward making the platform fully accessible for Arabic-Speaking users and comes after our previous integrations of the Arabic language into the keyboard, the intelligent predictive text engine and all panels and interfaces of the platform.
An adaptive randomized and secured approach against adversarial attacks

With the rising trends and use of machine learning algorithms for classification and regression tasks, deep learning has been widely accepted in the Cyber and as well as non-Cyber Domain. Recent researches have shown that machine learning classifiers such as Deep Neural Networks (DNN) can be used to improve the detection against adversarial samples as well as to detect malware in the cyber security domain. However, a recent study in deep learning has found that DNN classifiers are highly vulnerable and can be evaded simply by either performing small modifications in the training model or training data. The work proposed a randomized defensive mechanism with the use of generative adversarial networks to construct more adversaries and then defend against them. Interestingly, we encountered some open challenges highlighting common difficulties faced by defensive mechanisms. We provide a general overview of adversarial attacks and proposed an Adaptive Randomized Algorithm to enhance the robustness of models. Moreover, this work aimed to ensure the security and transferability of deep learning classifiers.
Image Distortion Analysis in Stego Images Using LSB

One of the most pressing matters at hand of today’s communication networks is privacy. Privacy is essential where information to be transmitted to the desired target without being intercepted by third parties or bringing them in a way that they cannot understand. Lossless text encryption technique for gray scale or RGB images using least significant bit (LSB) is the most commonly used method to hide data. LSB technique is preferred as it is difficult to draw a distinction between the cover object and stego object if few LSB bits of the cover object are replaced. However, image distortion is a major issue which needs critical investigation as it can change the original image. This paper proposes an algorithm to embed text in RGB images and also evaluate the distortion in image at various bit positions. Simulation results suggest that distortion in the image is least at 8th-bit and most at 1st-bit position.
Design of Online Auxiliary System for Action Teaching Based on Reinforcement

Through the combination of artificial intelligence technology and distributed technology, this paper puts forward a design scheme of Taijiquan action teaching online assistant system based on deep learning, which can be applied to Taijiquan teaching, broadcast gymnastics, fitness action and other fields, and provide intelligent action coach for users in the environment of no guidance. The platform adopts the front-end and back-end separation development, and uses the distributed and cluster technology to solve the problems of high concurrency and availability. Through tensorflow.js framework, the platform can identify, analyze and guide actions in real time on the front end, which can avoid privacy leakage and server overload in the front and back end data interaction. Through the scoring and comparison algorithm, users can constantly correct their actions in the process of using, and achieve the positive feedback effect of action learning.
Application of personally-oriented learning technologies in the study of general professional disciplines

The intellectual and spiritual development of the student’s personality is a priority task of the modern educational process. The purpose of modern education is to create an environment in the classroom for children with diﬀerent abilities, aimed at the realization of creative potential. At the same time, the value of the child’s personality is a determining factor. Currently, special attention is paid to pedagogical technologies, by implementing which the teacher does not oﬀerready-made information to students, but organizes and coordinates the educational process, directing educational activities in the right direction, fully taking into account the individual abilities of students. That is why student-centered pedagogical technologies are of great importance in the modern educational process. This article analyzes the concept of pedagogical technology, gives its various deﬁnitions, analyzes the features of student-centered pedagogical technologies, considers such student-oriented pedagogical technologies as collaborative learning and multi-level learning. The teaching methods used by teachers in the framework of the implementation of these pedagogical technologies are presented. The application of personality-oriented technologies in the study of general professional disciplines of secondary vocational education, in particular, binary game lessons, technologies of multi-level education, is considered. Particular attention is paid to the methods of assessing the educational achievements of students.
Complex conundrum

It is often stated that the human brain is the most complex object in the universe, but is it more complex than, say, Earth's biosphere? And how can this complexity be measured?
Teaching Hand Expression

A staff survey regarding hand-expression education revealed that hand expression was not being taught consistently to breastfeeding parents in the early postpartum period.
Accelerated Reference Frames

This advanced undergraduate physics textbook presents an accessible treatment of classical mechanics using plain language and clear examples. While comprehensive, the book can be tailored to a one-semester course. An early introduction of the Lagrangian and Hamiltonian formalisms gives students an opportunity to utilize these important techniques in the easily visualized context of classical mechanics. The inclusion of 321 simple in-chapter exercises, 82 worked examples, 550 more challenging end-of-chapter problems, and 65 computational projects reinforce students' understanding of key physical concepts and give instructors freedom to choose from a wide variety of assessment and support materials. This new edition has been reorganized. Numerous sections were rewritten. New problems, a chapter on fluid dynamics, and brief optional studies of advanced topics such as general relativity and orbital mechanics have been incorporated. Online resources include a solutions manual for instructors, lecture slides, and a set of student-oriented video lectures.
A Brief Review of Introductory Concepts

This advanced undergraduate physics textbook presents an accessible treatment of classical mechanics using plain language and clear examples. While comprehensive, the book can be tailored to a one-semester course. An early introduction of the Lagrangian and Hamiltonian formalisms gives students an opportunity to utilize these important techniques in the easily visualized context of classical mechanics. The inclusion of 321 simple in-chapter exercises, 82 worked examples, 550 more challenging end-of-chapter problems, and 65 computational projects reinforce students' understanding of key physical concepts and give instructors freedom to choose from a wide variety of assessment and support materials. This new edition has been reorganized. Numerous sections were rewritten. New problems, a chapter on fluid dynamics, and brief optional studies of advanced topics such as general relativity and orbital mechanics have been incorporated. Online resources include a solutions manual for instructors, lecture slides, and a set of student-oriented video lectures.
REAL TIME AGE AND GENDER CLASSIFIER

Gender is still a prominent element of our personalities. It also plays an important role in our social lives. Artificial intelligence age forecasts have applications in a variety of disciplines, including smart human-machine interface development, health, cosmetics, and electronic commerce, among others. The ability to estimate people's sex and age from their face photographs is a current and active research topic. The researchers proposed a number of solutions to the problem, but the criteria and actual results are still insufficient. This paper proposes a statistical pattern recognition strategy to solve this challenge. In the proposed method, a Deep Learning technique called Convolutional Neural Network (ConvNet / CNN) is employed to extract features. CNN takes input images and assigns a value to distinct characteristics / elements of the image (learnable weights and biases) and can distinguish between them. Other classification techniques require far more pre-processing than ConvNet. While the filters are created by hand using simple methods, ConvNets can be trained to learn these filters and features. Face photos of individuals were trained with convolutional neural networks in this study, and age and sex were accurately predicted with a high rate of success. There are around 20,000 photos with age and gender. Poses, facial expressions, lighting, occlusion, and resolution are all represented in the photos.
Mine Safety Monitoring and Early Warning System Based on 5G Network Technology

With the continuous development of industry, the demand for various minerals is also increasing. However, restricted by factors such as environment and equipment, mining safety problems continue to occur. Therefore, research on mine monitoring and early warning has been put on the agenda. The maturity of 5G technology provides technical support for current monitoring and early warning. This article first summarizes the research status of mine safety monitoring system, and combines the advantages of 5G technology to analyze the feasibility of the mine safety detection and EWS based on 5G network technology studied in this article. Afterwards, the functional modules of the mine safety monitoring and EWS were designed in detail. This article systematically expounds the Newton iterative method and other seismic source location methods. Research shows that the mine safety monitoring and EWS based on 5G network technology studied in this article has higher accuracy in monitoring data and positioning personnel.
Research on Methodology of Symmetry Optimization with Backpropagation

Machine learning is a promising technology, which is widely employed to structure a rather accurate physical system. ML-assisted application in the field of elementary particle becomes a hot-topic in both academics and industries. Electroweak interactions in the context of Standard Model is heavily depend on the Higgs mechanism. When spontaneous symmetry breaking happens, the challenge is to find a way to describe the theory behind it. In order to address this challenge, this paper investigates the breaking of global and local −U(1) symmetry and provides a pathway to compute the optimization process of nature system with gradient descent. Initially, this paper introduces Lagrangian to describe the status of a physical system which provides the initial data set. Then, this paper constructs symmetries and discovers the Higgs mass, which relates to the breaking of U(1) symmetry. Furthermore, trained network can be used to illustrate the loss function and give both learning rate and feature of the physical system.
Kinematics

This advanced undergraduate physics textbook presents an accessible treatment of classical mechanics using plain language and clear examples. While comprehensive, the book can be tailored to a one-semester course. An early introduction of the Lagrangian and Hamiltonian formalisms gives students an opportunity to utilize these important techniques in the easily visualized context of classical mechanics. The inclusion of 321 simple in-chapter exercises, 82 worked examples, 550 more challenging end-of-chapter problems, and 65 computational projects reinforce students' understanding of key physical concepts and give instructors freedom to choose from a wide variety of assessment and support materials. This new edition has been reorganized. Numerous sections were rewritten. New problems, a chapter on fluid dynamics, and brief optional studies of advanced topics such as general relativity and orbital mechanics have been incorporated. Online resources include a solutions manual for instructors, lecture slides, and a set of student-oriented video lectures.
High Dimensional Data Visualization Analysis Based on Unsupervised Laplacian Score

With the rapid development of big data technology and information visualization technology, the concept of data visualization is constantly evolving and developing. As one of the classic high-dimensional data visualization methods, the parallel coordinate axis has excellent plane geometric characteristics. However, as the amount of data increases and the dimension of the data feature increases, the number of polylines on the finite plane of the parallel coordinate graph also increases. The crossing and occlusion of lines lead to serious visual redundancy and clutter. This project uses the feature distribution and feature axis arrangement on the parallel axis as the research entry point, and uses two unsupervised feature selection methods (Laplacian Score and SVD-Entropy) to re-arrange the features on the PCP axis to improve parallelism. Phenomena such as data disorder and clutter on the coordinate axis. Furthermore, we proposed a plane geometry optimization CLS algorithm by combining two unsupervised feature selection algorithms and the PCP axis radius coverage calculation method. The proposed algorithm conforms to people's perception characteristics of information and plane space representation, and can help people more quickly analyze and understand data.
Blockchain Based Framework for Securing Students’ Records

Blockchain Based Framework for Securing Students’ Records by Omega Sarjiyus * , Israel Isaiah Department of Computer Science, Adamawa State University, Mubi Nigeria * Author to whom correspondence should be addressed. Journal of Engineering Research and Sciences, Volume 1, Issue 6, Page # 45-54, 2022; DOI: 10.55708/js0106006 Keywords: Blockchain, Encryption, Framework, Records, Security Received: 02