Reviewerly/exHarmony huggingface dataset:
Philosophical discourse of cognitive meanings of education

The article considers education as a system that plays an important role in the development of the whole society. An attempt is made to systematize the main characteristic features of the education system, as well as its teaching methods in each historical period of the development of civilization. Thus, the models of an educated person, characteristic of each historical stage, are determined. Within the framework of the topic under study, the modern education system is also considered, the main principles of which are openness, continuity, humanization, its national orientation. However, it should be noted that in modern realities, given the spread of the pandemic caused by the coronovirus infection, the education system has undergone significant changes. It was transformed into a new distance learning format, while retaining its content and essence. In the process of adapting education to the new prevailing conditions, both positive and negative aspects of this transition are identified.
Transcompiler CNN-GMN Based Cross Language Clone Detection and Algorithm Recognition

Abstract: Software replication stemming from code reutilization introduces complexities in software maintenance. While deep learning-driven clone detection tools abound, they predominantly cater to singular programming languages. Concurrently, the task of identifying algorithms within program code remains challenging due to the absence of metadata, rendering the selection process intricate. This research seeks to establish synergies between these disparate domains by advancing innovative methodologies. The study delves into the unexplored domain of harnessing data augmentation, particularly leveraging transcompiler-based techniques, to enhance the discernment of code clones across different programming languages. Drawing upon the insights derived from transcompilers, this investigation applies data augmentation through source-to-source translation, exemplified by the Transcoder. This method extends the applicability of single-language models, such as the Graph Matching Network (GMN), to encompass cross-language detection. Concurrently, a program code classification model is introduced, leveraging Convolutional Neural Networks (CNNs) to discern algorithms based on structural features (SFs). These SFs are extracted from program codes and subsequently transformed into a one-hot binary matrix. The CNN model undergoes meticulous fine-tuning, optimizing its structural configurations and hyperparameters for superior algorithm classification. This research signifies an integration of disparate realms, intertwining cross-language clone detection and algorithm identification within a unified framework. The exploration of data augmentation for cross-language clone detection and the employment of CNN-GMNs for algorithm identification converge to furnish significant contributions to both domains. These insights, thus, hold promise for advancing the fields of software engineering and programming education
Evolutionarymethodoffunctionsapproximationbyrealpolynomials

Thispaperproposesahybridmethodfordeterminingthecoefficientsofapolynomialwhosepowercoefficientsarerealnumbersusingageneticalgorithm(GA).Theinputisasetofdiscretevaluesofthefunctionarguments.Themainfocusofourapproachistoapproximatefunctionsusingrealpolynomials,whichprovidemoreflexibilitycomparedtocubicpolynomials.Ourapproachinvolvesatwo-stepoptimizationprocess.Inthefirststep,thepowercoefficientsofthepolynomialareequaltocubicpolynomialpowers.ThenapproximationcoefficientsofthecubicpolynomialarecalculatedusingGA.Inthesecondstep,insteadofcubicpolynomialisintroducedpolynomialwithrealpowers.InthissteptheapproximationcoefficientsofpolynomialaresetasconstantandpowercoefficientsofpolynomialarecalculatedusingGAtorefinethesolution.Thismakesitpossibletoquicklyandaccuratelyapproximateagivenfunctionwithapolynomialwhosepowersarerealnumbers.Theevolutionarynatureofthemethodensuresadaptabilityandtheabilitytoovercomefunctionalobstacles,thusachievingbetteroverallapproximationperformance.Researchhasshownthat,comparedtoconventionalpolynomials,significantlyhigherapproximationaccuracyhasbeenachieved
Analysis and improvement of methods and means for eliminating distortions in image and video signals

The main purpose of this article was to study existing image processing methods, binarization and noise reduction, and to develop an improved adaptive thresholding algorithm. The analysis of methods and tools for eliminating distortions in image and video signals is an urgent task in numerous fields, including medicine, computer vision, and document science. The article discusses in detail the existing binarization and noise reduction methods, highlighting their advantages and limitations. However, the main achievement is the development and implementation of an improved adaptive thresholding algorithm. This algorithm considers the specific features of the image and automatically adapts the binarization threshold for better processing quality. It is a significant contribution to the field of image processing and can be used in various fields, including medical diagnostics and visual object detection in images.
Implementasi Game Math Puzzle sebagai Media Pembelajaran Numerasi Siswa SDN 02 Badrain

School with relatively low literacy and numeracy skills are an indicator of where campus teaching programs are held. Therefore, students from the Faculty of Teacher Training and Education at the University of Mataram who were registered as campus teaching participants for grade 6th placement at SDN 02 Badrain created the "Math Puzzle Game" program. The aim of this program is to improve students' numeracy skills through the application of math puzzle games which are expected to be a fun learning medium as well as improving problem solving skills, sharpening logical skills, strengthening number understanding abilities, and encouraging teamwork. The target of this program is students in grades 4, 5, and 6. The method for implementing the "math puzzle game" program uses several stages, namely preparation, implementation, and evaluation or improvement. The results of applying the math puzzle game are that students have the ability to think quickly and critically when solving puzzles, students understand basic mathematical concepts, and students succeed in applying their understanding of the relationship between numbers and solving mathematical problems correctly. It is hoped that this service can be continued and carried out more optimally in the future learning process. Seeing the aim of service through this program is very important as an effort to improve students' numeracy skills.
Penetration Testing Tangerang City Web Application With Implementing OWASP Top 10 Web Security Risks Framework

The speed of technological development has made it possible for all people to be connected to one another. The creation of web-based information systems that help in all areas, including government, health, and education, is one of the forces behind the development of technology. With these technological advancements, websites are susceptible to cybercrimes that could end in the theft of crucial data. Top 10 Web Application Security Risks is the most effective prevention process for decrease company information leaks. On the website tangerangkota.go.id, the researcher will conduct a test using the Top 10 Web Application Security Risks technique. Top 10 Web Application Security Risks consist of Broken Access Control, Cryptographic Failures, Injection, Insecure Design, Security Misconfiguration, Vulnerable and Outdated Components, Identification and Authentication Failures, Software and Data Integrity Failures, Security Logging and Monitoring Failures, Server-Side Request Forgery. The penetration testing results found on the Tangerang City website which are 4 injections, 2 broken access controls, 1 security misconfiguration.
COMPARISON OF H-INFINITY AND ENSEMBLE KALMAN FILTER FOR ESTIMATING MOTION OF MIDDLE FINGER

Upper extremity paresis is a condition in which a person experiences muscle weakness in one or both hands. This condition can cause impairment in motor function, hinder daily activities, and affect the life quality of the sufferer. In some cases, paresis can result from nerve injury, neurological disease, or an accident. To help improve the life quality of the sufferer experiencing upper extremity paresis, the development of the Finger Prosthetic Arm Robot, an assistive robotic hand designed to provide assistance in the movement of the finger experiencing paresis, is required. This technology aims to restore its functional ability and the independence of the patient in performing daily activities, such as picking up objects, grasping, and performing other precise movements. The main purpose of this paper, the researcher compared two methods to estimate the motion of the middle finger robot, that is, the H-infinity method and the Ensemble Kalman Filter (EnKF) method. The simulation results show that both methods had almost the same accuracy, and the simulation by generating 800 ensembles was more accurate than that by generating 400 ensembles with an accuracy difference of about 10% above the accuracy rate of 98%.
DevOps, Continuous Integration and Continuous Deployment Methods for Software Deployment Automation

In the fast-paced landscape of software development, the need for efficient, reliable, and rapid deployment processes has become paramount. Manual deployment processes often lead to inefficiencies, errors, and delays, impacting the overall agility and reliability of software delivery. DevOps, as a cultural and collaborative approach, plays a central role in orchestrating the synergy between development and operations teams, fostering a shared responsibility for the entire software delivery lifecycle. Continuous Integration is a fundamental DevOps practice that involves regularly integrating code changes into a shared repository, triggering automated builds and tests. Continuous Deployment complements Continuous Integration by automating the release and deployment of validated code changes into production environments. The purpose of this research is to create a software deployment automation system to make it easier and reliable for organizations to deploy software. In conclusion, the results of this research show that by adopting DevOps, Continuous Integration, and Continuous Deployment, organizations can achieve enhanced collaboration, shortened release cycles, increased deployment frequency, consistent deployment, and improved overall software quality.
Industrial Operation Performance: Unveiling the Influence of Information Quality, Sharing, and Customer Relationships

The foundation of optimal and proficient operational performance is contingent upon the caliber of information. Organizations that prioritize the acquisition, examination, and application of high-quality information are more likely to optimize their operational processes, save costs, enhance customer satisfaction, and achieve a competitive edge in their respective industries. The main objective of the study was to identify the effect of business supply chain practices (information Sharing, information quality, and Customer Relationships) and operation performance in the Jordanian food industries sector in the al Hassan industrial estate. To answer the problem of the study a questionnaire was developed and distributed to 67 employees. The descriptive and analytical approaches were used to attain the study's goal. The study found a statistically significant effect of supply chain practices (information Sharing, information quality, &amp; Customer Relationships) on operation performance. The implementation of efficient customer relationship (CR) strategies has been observed to yield numerous favorable consequences for enterprises. For example, it is improved operational efficiency, decreased costs, increased revenue, and the construction of a more sustainable company framework.
OPTIMIZATION OF K-MEANS CLUSTERING USING PARTICLE SWARM OPTIMIZATION ALGORITHM FOR GROUPING TRAVELER REVIEWS DATA ON TRIPADVISOR SITES

K-Means Algorithm can be used to group tourists based on reviews on tourist destination objects. This algorithm has a weakness that is sensitive to the determination of the initial centroid. The initial centroid that is determined at random will decreasing the level accuracy, often gets stuck at the local optimum, and gets a random solution. Optimization algorithms such as PSO can overcome this by determining the optimal initial centroid. The optimal number of clusters (K) will be determined using the Elbow method by calculating the SSE value of the resulting cluster. The average Silhouette Coefficient (SC) is used to measure the quality of the clusters produced by the K-Means Algorithm with and without the PSO Algorithm. This study uses secondary data obtained from the UCI Machine Learning Repository with the name Travel Reviews Data Set which consists of 980 records and 10 attributes. The test results show that K=2 is the optimal number of clusters. The K-Means and PSO Algorithm gives an average SC value of 0.300358 which is better than without the PSO Algorithm of 0.300076. The optimal PSO hyperparameter generated is the number of particles=30, \varphi_1=2.2, and {\ \varphi}_2=3 at maximum iteration of 100.
OBSTACLE AVOIDANCE IN QUADCOPTER NAVIGATION USING MODIFIED LOCAL MEAN K-NEAREST CENTROID NEIGHBOR METHOD

Quadcopter is a type of Unmanned Aerial Vehicle (UAV) technology, characterized by simple mechanical structure, ease of flying and good maneuvering. In its usage, the quadcopter is required to evade obstacles in its path. Thus, an obstacle avoidance system in a 3D space with both static and dynamic obstacles is. Avoidance direction is determined by considering nearest distance based on the dimensions of the obstacle. Due to limited battery capacity, the quadcopter also needs to consider energy efficiency in obstacle avoidance. The obstacleâ€™s properties and movement direction are also needed in considering the correct avoidance direction. Using a modified Local Mean K-Nearest Centroid Neighbor (LMKNCN) algorithm results in a 97.5% accuracy for avoidance direction decision. The learning process between training data and testing data yielded a computation duration of 0.142341 seconds. The simulations showed that the quadcopter is able to avoid static and dynamic obstacles to reach its destination without collisions.
ASPECT EXTRACTION IN E-COMMERCE USING LATENT DIRICHLET ALLOCATION (LDA) WITH TERM FREQUENCY-INVERSE DOCUMENT FREQUENCY (TF-IDF)

Social media is a common thing that people use. Posts or comments found on social media describe someoneâ€™s feelings and opinions so there have to be important topics that can be extracted from social media. In the e-commerce field, topic is an interesting thing to know because it can describes peopleâ€™s opinion towards a product. However, the large number of social media users is currently making the process of finding topics from social media difficult, so computer assistance is needed. One method that can be used is Latent Dirichlet Allocation (LDA). LDA is a good method for extracting topics, but the drawback is that sometimes the topics are incomprehensible. To cover up the drawback, TF-IDF feature selection method is used so that less important words can be skipped so LDA can generate a better topic. The best hyperparameter values â€‹â€‹obtained were 10 iterations, 10 topics, Î± and Î² values consecutively 0,1 and 0,01. The best feature selection percentile value is 90. This value is used to find the threshold that can be used as the lower limit of the TF-IDF value of each word so that the word with greater TF-IDF value can be used as feature.
Résumés en Français

Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn Email Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Résumés en Français. Am J Intellect Dev Disabil 1 January 2024; 129 (1): 86–87. doi: https://doi.org/10.1352/1944-7558-129.1.86 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest Search
Development of emoticon design education content for online learning of art subjects by 5th and 6th graders in elementary schools

As remote communication becomes more active due to the advancement of information and communications technology and the spread of diseases such as COVID-19, the importance of emoticons that convey non-verbal expressions is recognized in social and economic terms. Thus, although emoticon-related education is being provided in school art education, only brief definitions and examples are provided for emoticon-related content, and in-depth design education activities are lacking in terms of content. Above all, after COVID-19, as most classes at schools are conducted in parallel with online classes, art subjects focusing on practical and experiential learning are in need of a change in their implementation methods. Therefore, in this study, emoticon design, a topic that is easy to apply and has the value of timeliness in online classes, was selected as the topic and developed based on the 2015 revised curriculum achievement standards. The main development content elements make up for the shortcomings found in previous research, such as ‘necessity of emoticons, origin of emoticons and concept, materials, design production method, reference materials, and examples of use.’ The developed content was reviewed by three elementary and middle school teachers in the areas of ‘difficulty, suitability for application, and validity of content structure’, and the results were found to be appropriate in all three areas.
The conflict between China’s restrictions on cross-border data transfer and US discovery of evidence

Journal Article The conflict between China’s restrictions on cross-border data transfer and US discovery of evidence Get access Qianwen Zhang Qianwen Zhang Department of Law, Southwest Jiaotong University, Chengdu, People’s Republic of China cdzqw@hotmail.com Search for other works by this author on: Oxford Academic Google Scholar International Data Privacy Law, ipad025, https://doi.org/10.1093/idpl/ipad025 Published: 27 December 2023
Quantum conditional mutual information of W state in non-inertial frames

Abstract Quantum conditional mutual information (QCMI) is a versatile information theoretic measure. It is used to ﬁnd the amount of correlations between two qubits from the perspective of a third qubit. In this work we characterise the QCMI of tripartite W-states when some of the qubits are under accelerated motion. Here for our investigations we consider a massless fermionic ﬁeld in the single mode approximation. We consider all possible situations with respect to acceleration of the qubits. From the results we observe that QCMI can either increase or decrease depending on the role of the qubit being accelerated. Finally we discuss the connection between QCMI and correlations by studying the biseparable and separable states.&amp;#xD;
DISTANCE EDUCATION OF JUNIOR HIGH SCHOOL STUDENTS

A model of a two-level system of formation of information and communication competence of students in the educational process has been developed. At the first level of the model, teachers use information tools during lessons to form students' basic knowledge and skills. At the second level, information technologies are used by teachers in extracurricular activities as a tool for creating creative products of students (in particular, scientific research works, educational projects, posters, presentations, video demonstrations), as well as their own developments (pedagogical technologies, teaching aids, etc.), which contributes to the formation of students' comprehensive ability to apply acquired knowledge and skills in practice, and, therefore, information and communication competence.
Social Engineering Cyber Threats

The article explores the pervasive threat of social engineering in cybersecurity, emphasizing its success in infiltrating information systems by manipulating individuals rather than employing traditional hacking methods. The author underscores the vulnerability arising from human trust, as individuals, especially those lacking technology education, tend to be targets. While cryptography offers partial security, social engineering complicates overall system security. Mitigation strategies include educating employees on threats, risks, and security policies, coupled with enforcing penalties for noncompliance. Additionally, employing two-factor authentication and physical token-based access adds layers of protection. The article delves into semantic attacks, classifying various exploitation methods and emphasizing the critical role of user awareness. It addresses prevalent scams such as phishing, vishing, impersonation, and smishing, noting their impact on individuals and organizations. The study extends its focus globally, highlighting a unique advance fee fraud targeting vulnerable populations. Social engineering remains a significant challenge despite technological advancements, necessitating a multifaceted approach combining technical defenses, education, and public awareness.
The Method Of Logical Networks For Modeling Adaptive Knowledge Testing Systems

The subject of the research is the development of mathematical and algorithmic support of the intellectual toolkit for the analysis of sets of test tasks and the modeling of the process of interpreting the quality of sets of test tasks, which allows for objective and comprehensive continuous control of the knowledge of subjects of training, subject to the implementation of the concept of virtual distributed training (retraining).&#x0D; The purpose of the research is to improve the effectiveness of monitoring the knowledge of subjects of education in the distance form of education through the use of adaptive computer testing methods based on models of logical networks and the algebra of finite predicates.&#x0D; The following tasks are solved in the article: the formation of a testing model in a distributed virtual learning environment and a model of validity assessment based on the content of sets of test tasks.&#x0D; The following methods are used: methods of logical networks and algebraic programming based on the algebra of finite predicates and predicate operations, intellectual analysis of information.&#x0D; The following results were obtained: the principles of intellectual analysis were formulated in the development of a model of a universal logical network and its application to actual tasks of artificial intelligence in the field of informal information processing, namely, in the construction of knowledge testing systems for distributed virtual learning&#x0D; Conclusions. Algorithms for optimal multi-stage adaptive testing of knowledge as part of distributed virtual learning models and methods for analyzing the success of training subjects have been improved. The use of conjunctive decomposition with binary predicates achieves the goal of the research, because in this way any multi-place predicate can be represented by a logical network simulating the process of knowledge testing, the model of the subject of learning is described.
FEATURES OF ADMINISTRATION OF HIGHER PROFESSIONAL EDUCATION

Management of higher vocational education is multi-layered and multi-content, as it has a wide range of beneficiaries. It is not limited within one university and manifests itself in the extra-university environment as well. The article interprets the features of higher education management and the key outcomes emerging in the management hierarchy, proposing a harmonization of regulatory influence in different areas and a comparable measurement of managerial implications using relative indicators.&#x0D; &#x0D;