Reviewerly/exHarmony huggingface dataset:
A multi-UAV system for coverage path planning applications with in-flight re-planning capabilities

This paper presents the development and implementation of a multi-UAV system focused on coverage path planning on multiple separated areas capable of re-planning the collective mission in case of unexpected events. For this purpose, we present a distributed-centralized architecture that uses heuristic and computationally efficient methods to perform the planning/re-planning and decision-making tasks during the control of the mission execution. We performed a computational evaluation of the algorithms, comparing them with other proposals, together with experiments in simulated and real flights. The results show that the system can distribute tasks equitably among the aircraft in an efficient way, even in the middle of the flight, when facing unexpected events; and show a higher computational efficiency when compared to multiple proposals in the state of the art.
Validity of Coffee Cocoa Local Wisdom-Based Digital Modules In Senior High School

This study aims to analyze the validity aspects of a digital module based on the local wisdom of cocoa coffee that has been developed. The research method used is the R and D (Research and Development) research method with the Four-D development model (Define, Design, Develop, Disseminate). In the 4D development stage, in the Develop section, module development and validation activities are carried out by three media and material experts. The data collection technique used a validation questionnaire. The data analysis technique used descriptive analysis. The validation results for each aspect are 86.06% construct validation, 91.11% content validation, and 87.78% language validation, and these three aspects are in the very good category. The overall validation results show that the digital module based on local wisdom of cocoa coffee reaches a validity score of 88.32% which is in the very good category and is feasible to use. Thus, it can be concluded that the digital module based on the local wisdom of cocoa coffee can then be used in the physics learning process in high school as an alternative solution for innovative learning resources based on local wisdom.
Recommendation System in the Form of an Ontology-Based Chatbot for Healthy Food Recommendations for Teenagers

Adolescents need adequate nutrition to support their growth and to avoid nutritional problems, such as malnutrition or obesity. Nutritional issues during adolescence can significantly influence health problems in adulthood. Although information about nutrition science is widely available on the internet, accurate interpretation requires specialized knowledge of nutrition science. Therefore, a system is needed to provide direct recommendations for healthy food to adolescents. In this study, a recommendation system in the form of a chatbot was developed to recommend healthy food that meets the nutritional needs of adolescents. The system was constructed using Ontology supplemented with Semantic Web Rule Language (SWRL), enabling the recommendation of food according to adolescents' health conditions. From the collected sample data, 150 food menus were recommended. Validation results by nutrition experts showed a precision value of 0.75, a recall of 1, and an F1-score of 0.857. These results indicate that the system is capable of providing appropriate food recommendations for adolescents.
THE USE OF TURN-TAKING STRATEGY BETWEEN INTROVERTED AND EXTROVERTED STUDENTS IN ENGLISH AS FOREIGN LANGUAGE (EFL)

Language is the main aspect of education. Improving English as a foreign language (EFL) learners’ speaking skills is a crucial communication requirement. In speaking skills, aspects of speech such as pronunciation, intonation, tone, stress, and fluency are highly emphasized. Furthermore, mental processes such as understanding, reasoning, adapting, turn-taking, and responding also play an essential role in speech. Turn-taking is a hugely important thing in conversation, especially in discussion. To take a turn in conversation is a big deal. Personality should consider factors in learning a second language. Extroverts and introverts have different learning styles, which will affect their speaking English learning. This research aimed to seek the used turn-taking pattern and strategies between student extroverts and introverts. This research was conducted using a qualitative-descriptive approach design to the comprehensive summarization of specific events experienced by individuals or small peer groups. The subjects of this research were students in the English Education Department of Universitas Muhammadiyah Surabaya for the 2021 final examination. As a result, Extroverted students are more comfortable and eager to take the lead in initiating conversations and introverts are more comfortable in the role of responders. While introverts and extroverts utilize similar strategies for turn-taking, their implementation differs; introverts may employ structured pauses and thoughtful contributions, whereas extroverts often engage in dynamic and spontaneous exchanges to ensure active conversation participation.
Synchronization of Libraries, Archives and Museums (LAM) in Malang City as an effort to transfer information

In the information age, libraries, archives, and museums (LAM are inseparable units. There are several reasons why LAM stands alone, but the rapid development has fostered new communication and information on the information side. Technology can be used to unify the work of all these institutions. Synchronized LAM can bridge common goals, although there are differences in collections and policies. This article concludes (1) LAM can be used as a concept in the city of Malang because even though the institutions are different and have different policies, some institutions have the same function and purpose, (2) LAM has various types of collections and policies applied to users of the collection, (3) LAM is a container that provides, manages, and transfers information to users. With the LAM synchronization, it is hoped that the efforts to share cultural information in Malang City can be more efficient and comprehensive so that it can be a way to foster public interest in regional arts and culture.
Social Networking or Social Disunion: An Analysis of Cyber-Speech-Terrorism between Pakistanis and Americans

Technological advancements have transformed the globe into a village with the advent of social media and these developments have brought so many advantages wrapped in dangers. Distance of thousand miles is just a click away i.e. web/internet; which is promoting togetherness by using networking and disunion in terms of cyber-hate, simultaneously. Pak-US shares a love-hate relationship with some unclear goals. Henry Kissinger's quote ‘America has no permanent friends or enemies, only interests’ exactly defines American mindset whereas America is not less than a fantasy for Pakistanis. This paper is concerned with the critical analysis of cyber-hate-speech between Pakistan &amp; US by considering major issues of current year. Sample data has been collected from WordPress, Twitter, Linked-in and face-book and analyzed on both quanto-qualitative measures. Observations have shown that knowingly &amp; unknowingly social networking websites have turned into war zones with the exchange of hate feelings without the discrimination of age, gender, religion and social status.
E-KYC System Using Blockchain

Abstract: Know your client or simply KYC, is a process utilized by businesses and financial institutions to identify their clients and evaluate any potential risks associated with illegal intentions and unethical behavior. The term KYC often refers to bank regulations and anti-money laundering regulations aimed at governing these activities. Due to concerns over bribery and unethical behavior, companies of all sizes are required to implement KYC to ensure their agents, consultants, and distributors comply with anti-bribery regulations. Despite the use of traditional KYC systems, there are limitations to their effectiveness. To address these limitations, a proposed system has been developed that uses the immutable nature of Distributed Ledger Technology (DLT) to create a tamper-proof system. This system enables customers and financial institutions to verify and record KYC documents on the DLT, providing greater efficiency, cost reduction, improved customer experience, and end-to-end transparency in integrating customer documents into the bank's database. Additionally, this system eliminates the need for repeated KYC checks performed by banks through the creation of a secure and common blockchain database. The blockchain's secure nature ensures that unauthorized changes to the data are immediately invalidated and the use of a proof-of-reputation concept makes the verification process more robust.
impact of online learning for the growth and development of Junior High School Students in Medan

The Covid-19 pandemic has greatly impacted all lines of people’s lives, including the teaching and learning process. In order to anticipate the spread of Covid-19, the government enforces an online teaching and learning process. Activities that take place online, of course affect the level of student acceptance and also the physical and psychological conditions of students. This study aims to determine the impact of online learning on the growth and development of junior high school students in Medan City. The research was conducted through a quantitative approach with the type of correlational research. The results of the study found that online learning, affect students’ psychology as expressed by about 54,75% respondents. In addition, the absence of parental support and motivation in accompanying students during online learning as stated by about 62,25% of respondents certainly makes students feel less cared for.
Implementation of decentralized techniques in e-commercewebsite

After the coronavirus pandemic struck in 2020, administrative agencies around the globe imposed strict lockdownsin every sector. The biggest of them was imposed in India. The only things allowed were the essential services likemedical and grocery. But due to the sudden panic of the unknown disease, there was a huge rush to buy andstockpile items. Long queues and crowds were developed, which may have led to rapid transmission of the virus.We, as a team, tried to find a solution by putting their shops online so that they could take orders remotely anddistribute them without the risk of long queues and infection. Gromore Shoppe was developed to make thesesmall local shops online. Retail owners can now catalogue their products on the web and take orders from thelocality. They can process them quickly and distribute them with minimal risk of contact. This solution will firstintroduce them to the web and its benefits and make them sufficient enough so that they can even expand easilyand effectively
Transforming African education systems throughthe application of IoT

The project sought to provide a paradigm for improving African education systems through the use of theInternet of Things (IoT). The created IoT model for Africa will enable African countries, notably Namibia, toexchange educational content and resources with other African countries. The objective behind the IoT paradigmin Africa’s education sector is to provide open access to knowledge and information. The study revealed that thereare no recognized platforms in African education systems that are utilized by African governments to interact,communicate, and share educational materials directly with African institutions. As a result, the current researchdeveloped a model for transforming African education systems using the IoT in the Namibian context, which willserve as a centralized online platform for self-study, new skill acquisition, and self-improvement using materialsprovided by African institutions of higher learning. Everyone is welcome to use the platform, including students,instructors, and members of the general public.
A Heterogeneous Graph to Abstract Syntax Tree Framework for Text-to-SQL

Text-to-SQL is the task of converting a natural language utterance plus the corresponding database schema into a SQL program. The inputs naturally form a heterogeneous graph while the output SQL can be transduced into an abstract syntax tree (AST). Traditional encoder-decoder models ignore higher-order semantics in heterogeneous graph encoding and introduce permutation biases during AST construction, thus incapable of exploiting the refined structure knowledge precisely. In this work, we propose a generic heterogeneous graph to abstract syntax tree (HG2AST) framework to integrate dedicated structure knowledge into statistics-based models. On the encoder side, we leverage a line graph enhanced encoder (LGESQL) to iteratively update both node and edge features through dual graph message passing and aggregation. On the decoder side, a grammar-based decoder firstly constructs the equivalent SQL AST and then transforms it into the desired SQL via post-processing. To avoid over-fitting permutation biases, we propose a golden tree-oriented learning (GTL) algorithm to adaptively control the expanding order of AST nodes. The graph encoder and tree decoder are combined into a unified framework through two auxiliary modules. Extensive experiments on various text-to-SQL datasets, including single/multi-table, single/cross-domain, and multilingual settings, demonstrate the superiority and broad applicability.
Hubungan Antara Konformitas Teman Sebaya dengan Pengambilan Keputusan Studi Lanjut Siswa SMP

THE CORRELATION BETWEEN PEER CONFORMITY WITH FURTHER STUDY DECISION MAKING OF JUNIOR HIGH SCHOOL. This research was holded based on the phenomenon of Junior High School students who were less independent in further study decision making, so that they adapted based on peer conformity. The research aims to find out the relatonship between peer conformity with further study decision making in Junior High School students. This type of research is ex post facto quantitative with a correlational design. The samples of this research totaled 233 students from five schools with cluster sampling and proportional random sampling techniques. The instruments is used consisted of further study decision making scale, and peer conformity scale. Based on the result analysis, it showed that level further study decision making is high, level peer conformity is medium, and there is finded a negative and significant relationship between peer conformity and further study decision making (r=-0,364, p=0,000 &lt; 0,05).
Implementation of web application for disease predictionusing AI

The Internet is the largest source of information created by humanity. It contains a variety of materials availablein various formats, such as text, audio, video, and much more. In all, web scraping is one way. There is a setof strategies here in which we get information from the website instead of copying the data manually. Many web-based data extraction methods are designed to solve specific problems and work onad hocdomains. Various toolsand technologies have been developed to facilitate web scraping. Unfortunately, the appropriateness and ethicsof using these web scraping tools are often overlooked. There are hundreds of web scraping software availabletoday, most of them designed for Java, Python, and Ruby. There is also open-source software and commercialsoftware. Web-based software such as Yahoo! Pipes, Google Web Scrapers, and Firefox extensions for Outwitare the best tools for beginners in web cutting. Web extraction is basically used to cut this manual extractionand editing process and provide an easy and better way to collect data from a web page and convert it into thedesired format and save it to a local or archive directory. In this study, among other kinds of scrub, we focus onthose techniques that extract the content of a web page. In particular, we use scrubbing techniques for a varietyof diseases with their own symptoms and precautions.
Performance Assessment of some Phishing predictive models based on Minimal Feature corpus

Phishing is currently one of the severest cybersecurity challenges facing the emerging online community. With damages running into millions of dollars in financial and brand losses, the sad tale of phishing activities continues unabated. This led to an arms race between the con artists and online security community which demand a constant investigation to win the cyberwar. In this paper, a new approach to phishing is investigated based on the concept of minimal feature set on some selected remarkable machine learning algorithms. The goal of this is to select and determine the most efficient machine learning methodology without undue high computational requirement usually occasioned by non-minimal feature corpus. Using the frequency analysis approach, a 13-dimensional feature set consisting of 85% URL-based feature category and 15% non-URL-based feature category was generated. This is because the URL-based features are observed to be more regularly exploited by phishers in most zero-day attacks. The proposed minimal feature set is then trained on a number of classifiers consisting of Random Tree, Decision Tree, Artificial Neural Network, Support Vector Machine and Naïve Bayes. Using 10 fold-cross validation, the approach was experimented and evaluated with a dataset consisting of 10000 phishing instances. The results indicate that Random Tree outperforms other classifiers with significant accuracy of 96.1% and a Receiver’s Operating Curve (ROC) value of 98.7%. Thus, the approach provides the performance metrics of various state of art machine learning approaches popular with phishing detection which can stimulate further deeper research work in the evaluation of other ML techniques with the minimal feature set approach.
Retracted: Differentially Private Singular Value Decomposition for Training Support Vector Machines

[This retracts the article DOI: 10.1155/2022/2935975.].
Retracted: Big Data Value Calculation Method Based on Particle Swarm Optimization Algorithm

[This retracts the article DOI: 10.1155/2022/5356164.].
Retracted: Sustainable Trend of Big Data in Enterprise Supply Chain Under the Artificial Intelligence Green Financial System

[This retracts the article DOI: 10.1155/2022/3065435.].
ANALISIS USER EXPERIENCE APLIKASI REGSOSEK PADA BADAN PUSAT STATISTIK INDRAMAYU MENGGUNAKAN METODE USER EXPERIENCE QUESTIONNAIRE

The advances of information technology have also brought significant changes to the government in carrying out administrative tasks and communication. In this context, sophisticated information systems enable governments to maximize their efficiency and effectiveness, to reduce costs, and to improve strategic decision-making. The Central Statistics Agency (BPS) carries out Research and Research activities in all provinces in Indonesia. The regsosek application itself is an application that is used to facilitate the collection and processing data related to the socio-economic needs of the community such as employment, health, education, and so on. The focus of this research is to find out the deficiencies or problems that exist in the application by measuring the users’ experience of the research and study application using the User Experience Questionnaire. Data analysis and evaluation are divided into two, namely quantitative data analysis for validity and reliability tests and descriptive statistical analysis using UEQ analysis tools version 11 to determine the average value (mean) of each variable. The results of the quantitative data analysis show that the validity value of the Pearson Product Moment correlation exceeds the value of 0.304 and the Croncbach alpha value of 0.613, thus the tests carried out can be relied upon to accurately and consistently measure user experience. Furthermore, the results of the descriptive statistical analysis show that the value on the clarity aspect has the lowest average value of the six aspects of UEQ, so that the conclusion is that the Regsosek application users do not understand the function and purpose of the application
Pengaruh Mata Kuliah Baca Tulis Al-Qur’an Terhadap Peningkatan Kemampuan Baca Tulis Al- Qur’an Pada Mahasiswa PAI

Al-Qur'an literacy education is one of the learning materials to direct students to the ability to read, write, understand, appreciate and make the Qur'an as a life guide. The ability to read and write the Qur'an is a skill possessed as a result of experience, education and training. This shows that the ability to read and write the Qur'an contains a learning dimension. Therefore, the importance of education in reading and writing the Qur'an in the ability of every human being to be able to read and write the Qur'an properly and correctly. This study aims to determine the effect of BTQ courses on the ability to read and write the Koran in PAI students batch 2018 at IAIN Kediri. This study uses quantitative methods with the type of correlation and regression research. The data collection technique uses a questionnaire with a population of 441 students, then a sample of 111 students is taken and the data analysis uses a simple linear regression test. And the results of this study indicate that there is a strong relationship between BTQ courses and the ability to read and write the Qur'an with a Pearson correlation value of 0.639 and there is an effect of reading and writing al- Qur'an courses on the ability to read and write the Qur'an. with the magnitude of the effect of 0.390 or 39%.
Preamble to Part Two

Abstract French orthography is a fairly regular, yet complex system. While French spellings are mostly predictable, they can be complicated, and there are many exceptions. For example, several letters often comprise a single spelling. When it comes to pronouncing the written language, challenges emerge, especially when multiple realizations of letter combinations are possible. It is also important to know which letters are typically silent in French. The key to French pronunciation lies in learning those letter combinations, and how the position of spellings within the word affects the way they are pronounced. This section of the text is a comprehensive pronunciation guide to French orthography. It provides an alphabetic list of the spellings of the French language with detailed instruction on pronunciation norms. Transcriptions for French spellings are provided in IPA. Included are options where more than one accepted pronunciation exists, and specific advice on the usual practices for francisé loanword pronunciations.
Face Detection from CCTV Footage using OpenCV and Haar Cascade

Abstract: With the rapid growth of surveillance systems, the need for efficient and accurate face detection in closed-circuit television (CCTV) footage has become increasingly crucial. Face detection plays a pivotal role in various applications, including security, law enforcement, forensic investigations, and social monitoring. This research aims to provide a comprehensive review and analysis of the existing techniques and approaches for face detection in CCTV footage. The study begins by examining the challenges and complexities associated with face detection in CCTV footage, such as variations in lighting conditions, camera angles, occlusions, and image quality. A thorough analysis of the existing literature is conducted, encompassing traditional methods such as Viola-Jones. The findings of this study contribute to enhancing the understanding of face detection in CCTV footage and provide valuable insights for researchers, practitioners, and system developers. The analysis of different approaches and their performance under varying conditions will assist in the design and implementation of robust face detection systems for real-world applications, ultimately improving the effectiveness and reliability of surveillance and security systems
Supporting Diversity Through Best Practices in Technical Standards

Noller, Diana T. DHSc, MMS, MSPT, PA-C; Lopez, Barbara J. MMH, PA-C; Todd, Athena P. MPAS, PA-C Author Information