Reviewerly/exHarmony huggingface dataset:
Design of Self Adaptive Fuzzy Sliding Mode Controller for Robot Manipulators

This paper intends to design and develop an adaptive fuzzy sliding mode controller (SMC) for robotic manipulator. Since it is not viable to pair the SMC operations with the system model every time, this paper adopts a Fuzzy Inference System (FIS) to replace the system model. It effectively achieves the experimentation in two phases. Accordingly, in the first phase, it attains the accurate features of the system model based on varied samples to characterize the robotic manipulator. In the second stage, it represents the derived fuzzy rules based on adaptive fuzzy membership functions. Moreover, it establishes the self-adaptiveness using Grey Wolf Optimization (GWO) to attain the adaptive fuzzy membership functions. The analysis distinguishes the efficiency of the adopted technique with the optimal investigational scheme and the traditional schemes such as SMC, Fuzzy SMC (FSMC) and GWO-SMC. Moreover, the comparative analysis is also performed by including the noise and validates the effectiveness of the proposed and conventional models. Index Terms : Sliding Mode Control, Robot manipulators, Controller, Noise.
SGAT: Shuffle and graph attention based Siamese networks for visual tracking

Siamese-based trackers have achieved excellent performance and attracted extensive attention, which regard the tracking task as a similarity learning between the target template and search regions. However, most Siamese-based trackers do not effectively exploit correlations of the spatial and channel-wise information to represent targets. Meanwhile, the cross-correlation is a linear matching method and neglects the structured and part-level information. In this paper, we propose a novel tracking algorithm for feature extraction of target templates and search region images. Based on convolutional neural networks and shuffle attention, the tracking algorithm computes the similarity between the template and a search region through a graph attention matching. The proposed tracking algorithm exploits the correlations between the spatial and channel-wise information to highlight the target region. Moreover, the graph matching can greatly alleviate the influences of appearance variations such as partial occlusions. Extensive experiments demonstrate that the proposed tracking algorithm achieves excellent tracking results on multiple challenging benchmarks. Compared with other state-of-the-art methods, the proposed tracking algorithm achieves excellent tracking performance.
RESEARCH AND IMPLEMENTATION OF A SPEAKER-DEPENDENT SPEECH RECOGNITION ALGORITHM

The goal of this research to realize the control humanoid type prosthetic movement used for speech recognition principles.Also, the basic principles of speaker-dependent speech recognition algorithms are introduced, a speaker-dependent speech recognition algorithm in the implementation process of an upper machine is described, and the feature template library of voice command is established.Ultimately, this information was used to test the performance of a speech recognition system.Experimental results show that this method could detect blinks at high accuracy signals and obtain an eigenvector, which achieved the goal of accurate prosthetic limb movement control.
User Behavior Prediction Based on DCGAN: The Case of Sina Weibo

&lt;p&gt;E-commerce marketing forces are taking advantage of microblogs to deliver their advertisements to promote product information. The success of product information diffusion in microblog depends greatly on user behaviors -- browsing, commenting and reposting. In this paper, we divide user behaviors of Sina Weibo into four types corresponding to four different colors, and propose a method to predict user behavior based on DCGAN (Deep Convolutional Generative Adversarial Nets). By analyzing a real Sina Weibo dataset, the experimental results show that the prediction accuracy of the four types of user behaviors reaches more than 80%, which proves that our method is feasible and effective, and also can help companies succeed in their product advertisements.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;
In-Depth Case Study on Artificial Neural Network Weights Optimization Using Meta-Heuristic and Heuristic Algorithmic Approach

The Meta-heuristic and Heuristic algorithms that have been introduced for deep neural network optimization is in this paper. Artificial Intelligence, and also the most used Deep Learning methods are all growing in popularity these days, thus we need faster optimization strategies for finding the results of future activities. Neural Network Optimization with Particle Swarm Optimization, Backpropagation (BP), Resilient Propagation (Rprop), and Genetic Algorithm (GA) is used for numerical analysis of different datasets and comparing each other to find out which algorithms work better for finding optimal solutions by reducing training loss. Genetic algorithm and also bio-inspired Particle Swarm Optimization is introduced in this paper. Besides, Resilient Propagation and Conventional Backpropagation algorithms which are application-specific algorithms have also been introduced. Meta-heuristic algorithms GA and PSO are a higher-level formula and problem-independent technique that may be used to a diverse number of challenges. The characteristic of Heuristic algorithms has extremely specific features that vary depending on the problem. The conventional Backpropagation (BP) based optimization, the Particle Swarm Optimization methodology, and Resilient Propagation (Rprop) are all fully presented, and how to apply these procedures in Artificial Deep Neural networks Optimization is also thoroughly described. Applied numerical simulation over several datasets proves that the Meta-heuristic algorithm Particle Swarm Optimization and also Genetic Algorithm performs better than the conventional heuristic algorithm like Backpropagation and Resilient Propagation.
From Rekhta to rekhta.org

Passing through the stages of oral, manuscript, and print technology, Urdu literature has now entered the digital sphere, transforming the contours of the Urdu literary culture and the public sphere not only by revolutionizing its reach but also by redefining its identity and ethos. In the process, Urdu has been salvaged from the ravages of communal politics that crept into its fold as a side-effect of print culture and was further amplified under the heightened nationalist fervour during the anti-colonial politics and the subsequent Partition of the nation. This chapter undertakes a close examination of the digitization work being carried out by the Rekhta Foundation-owned website https://www.rekhta.org" xmlns:xlink="https://www.w3.org/1999/xlink">rekhta.org to examine the ways in which digital technology is transforming Urdu literary and public sphere. The study employs qualitative research method involving document review, interviews, and personal observation of the Rekhta Foundation office, workspace, and their digitization process.
Synthesizing the Attributes of Computer-Based Error Analysis for ESL and EFL Learning: A Scoping Review

An error analysis (EA) is the process of determining the incidence, nature, causes, and consequences of unsuccessful language acquisition. Traditional EA for English as a second language/English as a foreign language technique lacks an orderly investigation due to human errors. Consequently, computer-based error analysis (CBEA) was introduced into EA in linguistics to achieve accuracy and instant analysis. Although many studies have concluded that CBEA holds numerous strengths, other studies have found that CBEA has certain limitations. However, the strengths and limitations of the CBEA were not clearly synthesized and outlined. Accordingly, this review aims to explore the strengths and limitations of CBEA to provide areas for improvement of computer applications toward an efficient EA procedure. This work also aims to synthesize the strengths and limitations of CBEA mentioned in a variety of articles into a single review to sustain its efficiency and serve as a guide for teachers to benefit from the strengths and gain awareness of CBEA’s limitations. Stakeholders can access broader perspectives on developing application software capable of addressing the deficiencies in EA. By doing so, we can sustain CBEA’s efficiency for the benefit of all. For this purpose, Arksey and O’Malley’s procedure of a scoping review and the PRISMA framework were adopted to guide the filtering and selection of relevant previous studies. Sixty-two articles were selected through the processes of identification, screening, eligibility, and inclusion. Although the findings showed six strengths and seven limitations of CBEA, CBEA can only perform the diagnostic part of EA. Human intervention is still required to perform the prognostic part to accomplish an efficient EA.
Using Written Synchronous Chat to Enhance Student Engagement and Learning in EFL Online Classrooms

Teaching online has become a widely implemented strategy in different educational institutes, particularly after the outbreak of the covid-19 pandemic.Nevertheless, online learning might render students' role passive unless innovative strategies are implemented.Instructors of online classes need strategies that would enhance students' engagement and interaction.Experimenting with various online learning platforms, such as Microsoft Teams, has opened the door for new learning tools to keep students engaged.One of these tools is the Chat box that exists in most of the applications used to deliver classes online.The purpose of this study was to examine students' perceptions of using the Chat box to write their answers and receive instant feedback in an EFL synchronous online classroom in a university branch in Lebanon.After being asked to use the Chat box for at least two times in their EFL classrooms, fifty-one students filled a questionnaire that was designed to assess their views about its usefulness and importance.Generally, the results revealed that more than half of the participants find it important to write in the Chat box and receive feedback from their instructor.Most of the participating students agreed that the Chat box allows them to go back to check their answers, to copy the links shared in class, and to learn from their friends' ideas and mistakes.Many respondents consider themselves more motivated to write in the Chat box than to speak and more eager to participate in class.Hence, this method could constitute a tool for instructors to identify students' level of engagement and to enhance their interaction levels.Asking students to write their answers in the chat box in an EFL synchronous online classroom, followed by an instant feedback, is likely to improve students' engagement and learning.
Two level obstacles avoidance method for manned aircrafts

Flight guidance is the process of building a flight route for an aircraft from A to B that avoids all obstacles, both physical like mountains, clouds, and virtual such as Air Defense Identification Zones (ADIZ), conflicted territories, etc. In this paper, we propose a 2-level obstacles avoidance method that optimizes not only the length of the flight route but also direction changes and off-planned-route segments.
COACHING ACTIVITY AND ITS PRACTICAL SIGNIFICANCE IN THE PEDAGOGICAL PROCESS

The article analyzes the peculiarities of coaching as pedagogical technology. That activity is presented in the context of a coach?s internship. Pedagogical science is the key to the development of modern society, which implies that the education system must be transformed in line with the changes of time. Coaching as a pedagogical technology ensures the learner's personal growth based on planning his own strategy. Therefore, the use of coaching as a pedagogical technology is relevant and in demand in modern schools, as it reveals the maximum potential of all learners and helps them develop cognitive-metacognitive abilities. The coach creates conditions for self-development by guiding the learners' educational needs, goals and potential opportunities.
Study on island ecosystem health assessment based on remediation projects

In recent years, with the economic development, the island is gradually becoming a new highland for leisure tourism and economic development, and human activities on the island are becoming increasingly intensive. However, the increase in human activities has also accelerated the destruction of the island's ecological environment, and the health status of the island ecosystem has declined sharply. Therefore, it is urgent to repair the island's ecological environment in the form of human intervention. In this study, the health changes of the island ecosystem are compared before and after the implementation of the Dongmen Island ecological restoration project to examine how the island ecosystem is affected by human activity. We choose the project of ecological restoration of Dongmen Island in Xiangshan County as the research area, the PSR model as a framework, the entropy weight method as an evaluation method, and 36 indicators such as social economy, environmental pollution, ecological status, island landscape, land use, social impact, and public awareness as factors to evaluate. The results show that the comprehensive assessment score of Dongmen Island ecosystem health assessment before the implementation of the remediation and restoration project is 0.7871, the mid-term implementation score is 0.8930, and the post-implementation score is 0.9419. After the implementation of the remediation and restoration project, the island ecosystem health evaluation index has increased significantly. It shows that the implementation of the Dongmen Island ecological protection and restoration project has greatly improved the Dongmen Island ecosystem, and the ecosystem and economic operation are developing in a benign direction. The implementation of the Dongmen Island ecological protection and restoration project has achieved certain results.
Metadata on open access books in BASE

BASE (Bielefeld Academic Search Engine) is one of the world's largest search engines for academic documents on the web, with references to around 310 million documents.Cross-system metadata communication and standardization are fundamental prerequisites for the development of BASE and comparable information systems.The presentation focuses on the metadata of open access books and book chapters in BASE, whose share of the total index has increased significantly in recent years, and illustrates the challenge of further dissemination of open access book metadata.
PRACTICAL TRAINING OF STUDENTS - A MOTIVATING FACTOR FOR PSYCHOSOCIAL MUTUAL AID IN A DIGITAL ENVIRONMENT

PRACTICAL TRAINING OF STUDENTS - A MOTIVATING FACTOR FOR PSYCHOSOCIAL MUTUAL AID IN A DIGITAL ENVIRONMENT
Studying the attitude of young teachers to distance education

The problem of research. The COVID-19 pandemic provoked a sudden transition to distance learning, which was uneven and exerted serious psychological pressure on teachers, and therefore it seems important to assess the attitude of teachers to distance learning, especially those whose work experience ranged from 1 to 3 years. Materials and research methods. The purpose of the study was to identify the attitude of young school teachers to distance learning. The peculiarity of the study was that it compared two periods: March 2020, as the period of an emergency transition to distance learning, and December 2021, when it was already possible to talk about some psychological adaptation of teachers to this form of work. An anonymous survey was conducted among young school teachers who took non-core advanced training courses at the Udmurt State University. The study period is April-December 2021. 79 respondents took part in the survey. Results and discussion. The study showed that satisfaction with the transition to distance learning is low and averages 2.35 points. Oddly enough, the increase in the volume of work was in last place. A greater role was played by the psychological factor – internal resistance to this form of work. A year later, young teachers already admit the idea of the possibility of switching to such a format of education, which, of course, is connected with the experience that they received during the lockdown period. 76.6% noted that they lacked the prompting of those who often work remotely to quickly adapt to new conditions. It was found that teachers whose work experience at school was one year, according to their own observations, adapted to drastic changes much faster than their colleagues, whose work experience was three years. Findings. The results of the study allow us to formulate a number of conclusions. Firstly, it can be assumed that the higher the experience of working at school, the more difficult it was for the teacher to adapt to new conditions. Secondly, as the results of the study show, the low satisfaction of teachers with the educational process in a remote format is associated to a greater extent with a psychological factor. Thirdly, the technical equipment of schools and households at the time of the emergency transition to distance learning was uneven, which affected the effectiveness and satisfaction. Fourthly, the organization of advanced training, the exchange of experience, master classes and creative workshops would allow young teachers to quickly adapt to new conditions.
INTERNATIONAL SOFTWARE DEVELOPMENT PROJECT STUDY MODULE IMPLEMENTED IN VIRTUAL TEAMS IN COOPERATION WITH WORKING LIFE

This article describes the research results and students' experiences from the International Software Development project study module implemented as a hybrid model in the spring of 2022.The University of Applied Sciences Western Switzerland (HES-SO) organized the study course, and students from Haaga-Helia University of Applied Sciences (Haaga-Helia), Finland, also participated in it.Due to the COVID-19 crisis, educational institutions were forced to adapt to distance education quickly, affecting teaching and studying in many ways.Paradoxically, however, this distance learning requirement has created innovative opportunities for collaboration.New hybrid pedagogical approaches have been tested, leading to further "physical" learning spaces.The primary purpose of this International Software Development project study course shared by HES-SO and Haaga-Helia students was to enable them to participate in a real working-life cooperation project during their studies.An essential perspective in the cooperation was also to increase the students' international collaboration skills.During the study period, a survey was also conducted to better understand how the students' computer science skills developed in different areas during the course.
DIGITAL RESOURCES TO ENHANCE EMPLOYABILITY FOR STUDENTS OF INDUSTRIAL CONSTRUCTION IN THE INDUSTRIAL ENGINEERING MASTER’S DEGREE

DIGITAL RESOURCES TO ENHANCE EMPLOYABILITY FOR STUDENTS OF INDUSTRIAL CONSTRUCTION IN THE INDUSTRIAL ENGINEERING MASTER’S DEGREE
A QUATERNION-DRIVEN DEEP LEARNING-BASED NOVEL APPROACH FOR MOBILE AND LOCOMOTIVE ROBOT PATH PLANNING AND MOTION PREDICTION

In this study, I address the locomotive-robot dilemma in movement task sequences.Our method combines geometric motion planning and locomotion prediction using quaternions and deep learning architecture.This is comparable to human motion prediction.I begin by developing a collision-avoidance-based motion planning method.Then, using transformer deep learning, I anticipate robot locomotion.I used simulation to demonstrate my findings.
What Our Eyes Can Tell Us About Our Social and Affective Brain?

Abstract The eyes are windows to the soul. This phrase present in the common sense popularly expresses that it is possible to deeply understand people’s minds just by how their eyes behave. This assumption is not that far from reality. Analyzing the eyes of subjects, researchers have answered questions of how people think, remember, pay attention, recognize each other, and many other theoretical and empirical ones. Recently, with the advancement of research in social and affective neuroscience, researchers are starting to look at human interactions and how the individuals’ eyes can relate to their behaviors and cognitive functions in social contexts. To measure individuals’ gaze, a machinery specialized in recording eye movements and pupillary diameter changes is used: a device known as an eye tracker.
Contrasting Explain-ML with Interpretability Machine Learning Tools in Light of Interactive Machine Learning Principles

The way Complex Machine Learning (ML) models generate their results is not fully understood, including by very knowledgeable users. If users cannot interpret or trust the predictions generated by the model, they will not use them. Furthermore, the human role is often not properly considered in the development of ML systems. In this article, we present the design, implementation and evaluation of Explain-ML, an Interactive Machine Learning (IML) system for Explainable Machine Learning that follows the principles of Human-Centered Machine Learning (HCML). We assess the user experience with the Explain-ML interpretability strategies, contrasting them with the analysis of how other IML tools address the IML principles. To do so, we have conducted an analysis of the results of the evaluation of Explain-ML with potential users in light of principles for IML systems design and a systematic inspection of three other tools – Rulematrix, Explanation Explorer and ATMSeer – using the Semiotic Inspection Method (SIM). Our results generated positive indicators regarding Explain-ML and the process that guided its development. Our analyses also highlighted aspects of the IML principles that are relevant from the users’ perspective. By contrasting the results with Explain-ML and SIM inspections of the other tools we were able to identify common interpretability strategies. We believe that the results reported in this work contribute to the understanding and consolidation of the IML principles, ultimately advancing the knowledge in HCML.
Interactive Learning Tool Using a Neural Network Algorithm for Speech-Delayed Child

Interactive Learning Tool using a Neural Network Algorithm for Speech-Delayed Child is a system that was developed mainly for speech-delayed children that utilized a multi-sensory approach and interactive learning technique in assessing the speech disorder. Phonology was focused as the content of the learning tool the lessons are based on the consonant-acquisition chart which contains the rules and system for speech sound production. Speech recognition was implemented to analyze, recognized, and matched the child’s speech to the exact word in the lesson. The system’s functionality is internet based and Google’s voice recognition is implemented to carry out the matching process. Neural Network Algorithm methodology is used to calculate the child’s test result. The application software is developed using HTML, Java, and PHP as the main programming language and Android Studio with Android Developer Tools as the working environment. It uses mySQL in managing its database The software is developed for the android operating system, with the version starting which stored the child’s information and results. The set of lessons is categorized by age namely: AGES 3-4, AGES 4-5, AGES 5-6, and AGES 6-7. Each category has a unique set of lessons categorized by: syllables with 67 lessons, words with 57 lessons, and phrases which contains 26 lessons. When the user finishes all the lessons prepared the system will generate the result, and the submit button transfers the data result into the teachers’ record in a separate system installed on a desktop/laptop computer.