Reviewerly/exHarmony huggingface dataset:
Leveraging Blockchain Technology for Data Integrity Verification in Cloud Storage

Cultivating and preserving the integrity and security of data within the ever-expansive landscape of cloud storage remains a paramount concern for both individuals seeking seamless access to their digital assets and organizations entrusted with safeguarding sensitive information. In this dynamic digital realm, conventional integrity checking methods have at times fallen short, leaving potential vulnerabilities in their wake and raising the pressing need for more robust solutions that can guarantee data's authenticity and immutability. This article is a comprehensive exploration of the cutting-edge synergy between blockchain technology and the intricate world of cloud storage systems. The convergence of these two domains represents a quantum leap in the quest for unparalleled data integrity verification. Blockchain, renowned for its decentralized architecture and its immutable, tamper-proof ledger, emerges as a game-changer. When seamlessly integrated with cloud storage platforms, this innovative pairing ushers in a new era in data security and trustworthiness. Within this paradigm, data integrity transcends the conventional confines. It adopts the characteristics of a decentralized ledger that is accessible to and verifiable by all authorized participants, thereby diminishing the risk of fraudulent manipulation or unauthorized access. By virtue of its tamper-resistant design, any alteration to stored data leaves an indelible trace in the blockchain, ensuring an immutable historical record of all transactions, actions, and modifications. This fusion of blockchain technology and cloud storage systems heralds a transformational breakthrough. It empowers users and organizations to maintain the sanctity of their data, confidently access their digital assets, and collaborate with the assurance that their information remains intact and inviolable. The overarching outcome of this innovation is not merely a fortified bulwark against data breaches and cyber threats, but also the establishment of unwavering trust, redefining the relationship between data and the digital sphere.As we venture further into this article, we will delve into the mechanics and intricacies of this groundbreaking integration, uncover its multifaceted benefits, and acknowledge the potential challenges that accompany this transformative approach. We will navigate real-world case studies that spotlight organizations that have embraced blockchain-infused cloud storage solutions. Furthermore, we will gaze into the crystal ball to predict the future trends and profound implications that this revolution brings to the forefront of data security and trust in the cloud storage landscape.This article is poised to serve as an authoritative guidepost, shedding light on how the fusion of blockchain and cloud storage redefines data integrity and security for the digital age. Through a comprehensive understanding of these innovations, readers will gain not only a glimpse into the present, but also a glimpse of the dynamic future where data is not just secure, but utterly invulnerable and replete with trust.
Publishing Via Social Media Sites and The Civil Liability of the Publisher in The Jordanian Legislation

This study showed the adequacy of the legal regulation of civil liability resulting from publishing via social media sites, and it also showed the lack of legal texts that dealt with this subject, which raises many problems. Then the study dealt with the issue of civil liability for publishing via social media sites in the Jordanian law: the concept of civil liability, whether contractual or tort, the provisions of this responsibility, and then the pillars of civil liability (error, damage, and causal relationship). This study discussed the legal protection for electronic publishing and the compensation due, with the obligation to pay compensation and the consequences of it. The study concluded that it is necessary to conclude an international agreement that regulates the relationship to solve the problems that occur when the actual location of the data that led to electronic violations is in one country and the victim is in another. The Jordanian legislator is responsible for clearly and explicitly regulating the procedures affecting the sanctity of private life, by enacting a law regulating electronic publishing through social media sites. The law must regulate the amount of fair compensation commensurate with the electronic damage
Using spatial elimination and ranking methods in the renewable energy investment parcel search process

The study presents a framework for an elimination algorithm aimed at determining potential investment locations for photovoltaic farms in three separate counties located in northeastern Poland. The research focuses on identifying environmental and economic criteria for solar farm locations, establishing boundary values, and discussing the outcomes of multi-criteria decision support using the Boolean method and Borda ranking methods. Through the amalgamation of the elimination algorithm and a multi-criteria decision-making model, ten different location variants were derived, ranging from the best (Variant 1) to the worst (Variant 10), out of a total of 1024 variants. The results highlight five critical criteria that persisted after the elimination algorithm: distance from medium voltage lines, distance from roads, parcel shape, average parcel width, and average slope. The analysis revealed that the analysed counties have between 150 and 1336 optimal locations (depending on the analysed area) that satisfy all the specified conditions. This method, which enables the swift and reproducible identification of suitable areas for photovoltaic farm construction, can be applied in various European regions.
Masked Face Recognition using YOLOv5 and Generative Adversarial Networks Algorithm for Attendance Machine

The COVID-19 pandemic has driven the development of touchless and automatic face recognition technologies. Detection and recognition of masked faces is a relevant solution in the effort to control the spread of the virus. To prevent the transmission of the COVID-19 virus from becoming more widespread, there is a need for a human contactless system that can analyze and identify individuals wearing masks. This research focuses on face verification that determines whether the faces belong to the same person and classifies the faces into specific identities for the attendance process. This research is built and designed on the case of imperfectly exposed faces by testing the capabilities of You Only Look Once version 5 (YOLOv5) and Generative Adversarial Networks (GAN) algorithms by looking at the results of their standard metrics including loss, accuracy, precision, recall and f1-score. The accuracy achieved in the masked face recognition system using GAN is 99.8%. On the other hand, the accuracy using the validation set by GAN is 99.7%. While the training loss that has been achieved in this study is 0.64 and the validation loss achieved is 6.45. With these results the system successfully detects according to the time of detection on the web attendance system. The YOLOv5 algorithm is implemented in the detection process to get the bounding box on the registered face. Meanwhile, the GAN algorithm is used for masked face recognition that has been integrated into the designed web attendance system. The various trainings that have been conducted resulted in an accuracy rate of 99.8% for real-time implementation. The proposed system successfully detects the name and its accuracy rate despite the use of masks.
AUTHENTICITY AND READABILITY OF GOOGLE TRANSLATE TRANSLATING RELIGIOUS TEXTS RELATED TO CHARACTER EDUCATION WRITTEN IN ENGLISH INTO INDONESIAN

Character education and information and communications technology (ICT) cannot be separated in discussing the Indonesian students in the post-millennial era. In this research, what is meant by character education is the religious teaching in the Holy Quran, whereas what is meant by ICT is the translation machine named Google Translate. The Holy Quran in this research is one which is translated from Arabic into English by Abdullah Yusuf Ali. The character education of the Holy Quran usually refers to the verses of Al Luqman, and the studies investigating the work of Google Translate usually concern the scientific texts and information or news. Different from the previous studies, this research do not investigate the verses of Al Luqman nor the scientific and informative ones. The aims of this research are to observe the religious texts belonging to the Holy Quran translated into English which contain universal character education and to investigate the authenticity and readability of the work of Google Translate translating such texts. The method employed in conducting this research is Mixed Method proposed by Hesse-Biber. Besides, the triangulation approach proposed by Turner is used. Thus, the researcher not only making use of the official Holy Quran of Ministry of Religious Affairs, but also involving both the lecturers of Islam Religion and of Bahasa Indonesia. This research found that the character education which is universal in nature could be read in the Holy Quran not only in Sura Al Luqman but also in Sura Al Furqon verses 63-77. Qualitatively the Google Translate work translating Sura Al Furqon verses 63-77 underwent the meaning distortion due to the Indonesian sentences whose both cohesion and coherence were violated. Meanwhile, quantitatively, it was found that 40% of the verses examined could be categorized unreadable or incomprehensible and that 60% of the verses examined could be categorized as undergoing the meaning distortion.
The Analysis of the Students’ English Achievement (A Case Study on the Students of Islamic Early Childhood Education of Islamic College of Auliaurrasyidin)

Today, mastery of more than one language becomes a phenomenon that attracts the attention of people, especially young people as the nation’s successor. However, the results of learning English for most students, including university students, are still very poor. This article aims to analyze students’ learning achievement, and provide an overview of the problems they faced in learning English. This study is qualitative research. This is focused on the English learning achievement of 1st semester students of the Islamic Early Childhood Education (PIAUD) Study Program of STAI Auliaurrasyidin. Data were collected using in-depth interview and documentation. They were analyzed using the Miles and Huberman model which consists of data reduction, data display, and conclusions. The results showed that the students’ low English learning achievement were caused by the English sentence and grammatical structure that often confusing, poor of vocabulary knowledge that impacts on the difficulty in translating English sentences. In addition, lack of self-confidence also triggered students’ low learning achievements.
THE STRATEGIES USED BY STUDENTS TO LEARN A LANGUAGE WHEN THEY NO LONGER LEARN ONLINE: A SURVEY STUDY ON GRADE 12 STUDENTS IN ONE SCHOOL IN JAKARTA

After the Covid-19 pandemic, lessons have been back to normal and students and teachers conduct the learning and teaching face to face at schools. The change of the three factors, i.e., the fact that the students learn at school, the time they use to commute, and the direct and easy communication with friends and teachers, might reduce their time to use gadgets or devices to access information. This might also result in the change of strategies used to learn English language, especially pronunciation. Therefore, the writer is interested in finding out what language learning strategies the students use in the normal situation and how it has changed from the ones they deployed during the pandemic. In this recent study, just like the previous one, the data was analyzed quantitatively by using a SILL questionnaire developed by Oxford (1990). The respondents of this study were grade 12 students in a senior high school in Jakarta. The respondents were not all the same students as the previous study but they all belonged to the same grade and some of them were actually the same students. The findings in this recent study show the difference in the strategies used by the students in learning English. The most strategies used in this face-to-face learning are compensation strategies, metacognitive strategies, cognitive strategies, social strategies, memory strategies, and affective strategies. The study also found the students used more strategies during the online learning period (2022) than during the onsite learning period (2023). The results of this study might be useful for teachers to give them insight about their students’ learning strategies and can help them improve their teaching in class.
A Survey on Age and Gender Detection Using Deep Learning

Abstract: The age and gender information are very important for various real world applications such as social understanding, biometrics, identity verification, crowd behavior analysis etc. There are numerous works proposed for age and gender prediction in the past several years. The age and gender detector project aims to develop an advanced AI system capable of accurately determining the age and genders of individuals from images. As we can see, the model outputs are mostly special parts as well as wrinkles, which are important for age and gender prediction. This project utilizes deep learning techniques to analyze special features and patterns, enabling real time identification and classification of age and gender attributes.
SECURITY ISSUES IN LIBYAN GOVERNMENT COMPANIES

The growth of technology, communications, and the cyber-Internet has led to a revolution in how data and information are sent and used online. As a result, internet security has become a crucial concern, particularly in safeguarding sensitive data in the government company. Government company a vital infrastructure for modern society, is also a lucrative target for cyber attacks, which could potentially expose sensitive customer information. This study highlights the importance of internet security in safeguarding sensitive data in government companies such as telecommunications companies. The study conducted in Libya employed an interview technique to evaluate the information security policy of government companies and identified several vulnerabilities that require mitigation to protect networks from cyber attacks. The study emphasizes the significance of information security in government companies and provides insights that can assist companies in developing and implementing effective policies to safeguard their networks.
Analysis of Interest in Reading Narratives in Indonesian Language Subjects in Class V MI Masyhudiyah

This study is motivated by a lack of interest in reading narratives in Indonesian language lessons for especially elementary school students at MI Masyhudiyah Giri. This study aims to determine the interest in reading in grade V MadraI Masyhudiyah Giri, to find out what factors cause the lack of interest in reading grade V students, to find out the role of the teacher in raising interest in reading of grade V students MI Masyhudiyah, and The Role of Schools in Encouraging Interest in Reading stories in grade V MI Masyhudiyah Giri Kebomas Gresik. The form of this research is descriptive research that uses observation, interviews, and questionnaires. This interview technique involved 10 students from class V representatives at MI Masyhudiyah. This interview was conducted in a structured manner. As a result, we found an internal factor that caused this problem lack of interest in reading narratives in grade V students of MI Masyhudiyah Giri were gender, internal desire, interest in visual media and electronic media. The findings of the classification of the text method of reading indicate an interest in reading narratives in Indonesian language lessons. The importance of improving narrative reading for students is to increase knowledge and broad insight.
Application of the K-Means Method for Clustering Capture Fisheries Products in North Aceh with A Data Mining Approach

North Aceh is one of the districts that has great potential in the maritime and fisheries sector, because part of the North Aceh region is a supplier of captured fisheries products. The problem with this research is that there is no model of a clustering system for captured fisheries products in North Aceh District, so it will be difficult to determine which areas produce superior and non-superior types of fish. This research aims to classify captured fishery results for the 2021-2022 period using the K-Means algorithm with a Data Mining approach to determine superior and non-superior fish types. Therefore, this research can help a little in providing information about the types of fish that are superior and not superior or the types of fish that are most numerous and the types of fish that appear the least at fishing ports in North Aceh District. The stages carried out in this research started from compiling research instruments and literature review, data collection and analysis, designing a clustering system model and implementing the system. This research produces 2 clusters, namely cluster 1 is superior fish and cluster 2 is non-superior fish. The K-Means algorithm with a Data Mining approach can be used to group types of capture fishery products at fishing ports in North Aceh District.
Dually Computable Cryptographic Accumulators and Their Application to Attribute Based Encryption

In 1993, Benaloh and De Mare introduced cryptographic accumulator, a primitive that allows the representation of a set of values by a short object (the accumulator) and offers the possibility to prove that some input values are in the accumulator. For this purpose, so-called asymmetric accumulators require the creation of an additional cryptographic object, called a witness. Through the years, several instantiations of accumulators were proposed either based on number theoretic assumptions, hash functions, bilinear pairings or more recently lattices. In this work, we present the first instantiation of an asymmetric cryptographic accumulator that allows private computation of the accumulator but public witness creation. This is obtained thanks to our unique combination of the pairing based accumulator of Nguyen with dual pairing vector spaces. We moreover introduce the new concept of dually computable cryptographic accumulators, in which we offer two ways to compute the representation of a set: either privately (using a dedicated secret key) or publicly (using only the scheme’s public key), while there is a unique witness creation for both cases. All our constructions of accumulators have constant size accumulated value and witness, and satisfy the accumulator security property of collision resistance, meaning that it is not possible to forge a witness for an element that is not in the accumulated set. As a second contribution, we show how our new concept of dually computable cryptographic accumulator can be used to build a Ciphertext Policy Attribute Based Encryption (CP-ABE). Our resulting scheme permits policies expressed as disjunctions of conjunctions (without “NO” gates), and is adaptively secure in the standard model. This is the first CP-ABE scheme having both constant-size user secret keys and ciphertexts (i.e. independent of the number of attributes in the scheme, or the policy size). For the first time, we provide a way to use cryptographic accumulators for both key management and encryption process.
EXTRACTING THE NEEDS OF THE LABOR MARKET IN RIYADH THROUGH TWITTER USING TEXT CLASSIFICATION TECHNIQUES

Recently, Twitter has attracted a great deal of spread and attention. It is one of the most common social networking sites for sharing ideas, chats, and transfer of information and news through text. The labor market is where the supply and demand for jobs meet, with employees satisfying employer needs for certain services. On the one hand, certain jobs are being eliminated, while others are being replaced by new jobs that were not even possible a few years ago. In this paper, we focused on labor market classification of twitter data belonging to Riyadh city and written in Modern Standard Arabic. We want to classify Arabic jobs’ tweets to determine the trending of required job in Riyadh city. Twitter’s API was used to collect tweets related to labor market. Five different classifiers were used on the dataset namely; Support Vector Machine (SVM), Multinomial Naive Bayes (M-NB), Decision Tree (DT), Gradient Boosting Classifier (GBC), and Random Forest (RF).to classify the tweets based on their related job classes. We evaluated our work by four different measures which are Precision, Recall, Accuracy and F-measure. We made a comparison between the five classifiers based on those measures. The results show that RF achieved the best Accuracy and F-measure, and it equals 93.62%, 93% respectively. In addition, we found that the trend of labor market needed was administrative jobs “وظائف ادارية. “. The percentages of that job class that related to 384 jobs about 19.2%.
A practical blockchain-based framework for anti-counterfeiting and traceability

Blockchain has features that help systems overcome the inherent limitations of traditional centralized approaches. Integrating blockchain technologies into systems to improve security, privacy, and transparency is a prominent trend. Currently, consumers are very concerned about the origin and the legitimacy of the products, so it is necessary to strengthen anti-counterfeiting and traceability in product management. Many theoretical approaches have been proposed recently. In this study, we propose a practical framework based on blockchain that supports anti-counterfeiting and traceability. Based on the proposed practical framework, we implemented a pattern as a proof-of-concept of the approach. We conduct experiments at Thu Dau Mot University, a pioneer in the production and transfer of biotechnology. The results show feasibility and good results regarding the proposed practical framework. Moreover, we also published our code base to GitHub with an open license.
PENGARUH PENERAPAN ARTIFICIAL INTELLEGENCE PADA KEHIDUPAN MASYARAKAT DI INDONESIA

Technology is very important in the 4.0 revolution era in this industrial sector. The impact of technology on human life cannot be overstated. The emergence of technology brings several changes. Technological developments can be seen to go hand in hand with the development of time. The field of science and technology is always advancing and innovating rapidly, as seen from the technical breakthroughs that have been made. Rapid technological advances impact human existence and enable rapid social transformations that often occur without our even realizing it. Artificial intelligence is one of the technical advances that has the greatest potential impact. For the purpose of finding a solution to a challenge, a technology known as artificial intelligence (often referred to as AI) is used to replicate the intelligence of living and inanimate organisms. The use of artificial intelligence has an impact on human existence in various contexts. The purpose of this essay is to investigate how the use of artificial intelligence in Indonesia contributes to the ongoing transformation of society in this country. Library research is the approach used in this study. Literature research is a methodology for collecting data that involves completing a review study of books, literature, notes, and reports that are related to the problem being addressed. Researchers will read as much relevant literature as possible to collect as much data as possible in their search for hypotheses. Books, journals, periodicals, research results (theses and dissertations), and other acceptable sources such as newspapers, the internet, and other sources can all be considered library resources.&#x0D; Keywords: Technology, Artificial Intelligence, Social Change