Reviewerly/exHarmony huggingface dataset:
LAND VALUE PREDICTION MODEL IN THE URBAN FRINGE REGION USING MULTIPLE REGRESSION ALGORITHM

The existence of land has become a dream. The value continues to soar over the years, making the land become something that various parties highly desire. This phenomenon causes the demand for land also to continue to increase. This study aims to predict land values based on actual land prices in the field in the form of transaction results and bid prices with a statistical approach for mass valuation in the urban fringe area, where this area is considered an alternative area to overcome the need for housing which is getting higher and higher. Land value is estimated using a data comparison approach market and added to the cost of building construction. Multiple regression is one of the methods to get the best estimation model from big data. The magnitude of the contribution of the influence of the variables making up the Land Value can be known through the coefficient of determination (R2), which is 82.5%. Many factors affect the Land Value, such as Bid Price, Physical Land Factors, Environmental Factors, and Legal Aspects.
Movie in the Specialty of Art Practice: Post Scriptum to the Conference

On July 2–5, a conference was held (Chelyabinsk region, Miass), dedicated to art practices as a format of philosophizing and technology for developing a philosophical dialogue. The main structural elements of the conference were events that included the analytics of feature films (including author's movie). The formal integrity of the event did not exclude the substantial unity provided by the permanent focus on anthropological issues and, above all, human subjectivity. The latter, in various historical epochs, faces heterogeneous challenges, including existential ones – borderline situations, critical social circumstances, life path uncertainty, progressive technical and technological innovationism and the threat of de-anthropologization. All the cinematographic works presented in a specific manner represented the variations of responses to these challenges. The philosophical and anthropological optics of analysis made it possible to keep the main task of carrying out a philosophical dialogue in focus. The issue of subjectivity and the challenges that call it into question is optimally illustrated in the situation of modernity by means of visual and audiovisual content, which actually includes all the patterns that are significant for today's person – visibility, brevity, stimulation of affects, etc. The philosophical approach allows expanding the thesaurus of art practitioners beyond through the integration of cinematography, which can exist not only in the traditional locus of an independent direction of art, but also as a determinant for the implementation of philosophizing, a step for further development of conceptual ideas and the collaboration with the world philosophical culture.
ANALISIS STRUKTUR DAN NILAI PENDIDIKAN NOVEL DIRAWU KÉLONG KARYA AHMAD BAKRI SEBAGAI BAHAN PEMBELAJARAN

This study aims to: 1) analyze the structure of the novel Dirawu Kélong by Ahmad Bakri; 2) analyze the educational value of Ahmad Bakri's Dirawu Kélong novel; 3) as well as for learning materials for reading novels in class IX SMP. This research is qualitative research with a descriptive analysis method. The technique of collecting data using the literature study technique and the data source is the novel Dirawu Kélong by Ahmad Bakri. The results of this study are: 1) this novel is themed about the daily life of Udin, the lines used are mixed lines, and the 18 characters involved. The mandate contained in it is to advise about life so that you can think long, respect all God's creatures, and be obedient to your parents; 2) Analysis of educational values ​​in the Dirawu Kélong novel includes character education values, namely religious, honest, tolerance, discipline, hard work, creative, independent, democratic, curiosity, national spirit, love peace, love to read, care for the environment, responsibility; 3) the novel Dirawu Kélong deserves to be used as a learning material for reading novels in grade IX SMP because it covers aspects of language, psychology, and cultural background..
Africa’s Ed-Tech Platforms: Protecting Children’s Right to Privacy

Ed-tech platforms are used to create a more engaging, inclusive, and individualized learning experience. A number of these platforms utilize Artificial Intelligence (AI). AI-enabled learning tools and approaches have revolutionized the global education sector (Pedro et al., 2019). They have been recognized for their contributions to enhancing the quality of learning and teaching. AI aids teachers and students in their lessons (Pedro et al., 2019). Additionally, AI has been lauded for its potential to boost students' knowledge and learning habits, while also creating a more personalized approach to learning (Pedro et al., 2019). Children are less likely to read or understand privacy policies, and they may have a limited understanding of their right to privacy and data protection. In addition, they are more susceptible to marketing techniques that adults can identify. The existence of their personal information online poses potential safety and security risks. Therefore, privacy policies on Ed-tech platforms must incorporate children's rights and an understanding of their right to privacy. This includes online protection and security measures established to protect children's data. The primary audience for this policy brief is corporations. Although, children’s rights to privacy are a collective responsibility of the parents, legal guardians, and other individuals legally responsible for the child. In the Ed-tech space, this responsibility extends to AI platform owners, who manage the platforms, and policymakers and regulators concerned with data protection and children’s rights.
Lessons for Nigeria: Determining Authorship and Inventorship of Artificial Intelligence Generated Works

Artificial Intelligence (AI) has gained widespread momentum in today’s tech-savvy world. AI is now capable of creating copyright works and inventions without human intervention. Such AI-created works challenge the frontiers of intellectual property rights (IPR), particularly those on patents and copyright. The extant copyright and patent laws in Nigeria (Copyright Act, 1988, and Patent Act, 1970) were drafted when AI authorship and inventorship were not a primary consideration. The international legal framework on IPR has also not addressed this issue conclusively. Using a doctrinal method of legal research, this paper examines the challenge AI poses to authorship and inventorship under copyright and patent laws. It also takes a peek into advanced jurisdictions which have had the opportunity to address these issues, to draw lessons for Nigeria where a National Centre of AI and Robotics has recently been established and these issues are envisaged to arise as the Centre carries out its objectives. This paper finds that under the extant legal framework in Nigeria, an AI system cannot be designated as an author or inventor. Considering the advancement in AI technology, this will exclude AI-created works and inventions from intellectual property protection in Nigeria. While drawing lessons from other jurisdictions, this paper recommends a responsive regulation of AI technology through a legislative amendment that accommodates AI systems as authors or inventors with a presumption of law that allows ownership, rights, and liabilities to be borne by the owners of such systems.
The Regulation of Deepfakes in Kenya

‘Truth has become elusive.’ ‘We are entering into an age of information apocalypse.’ ‘Seeing is no longer believing unless you saw it live.’ These and similar statements characterise most discussions in the present highly digital age. With the borderless nature of the Internet, it is possible to share videos, photos, and information with countless people provided one has a reliable internet source and a smart gadget, for instance, a mobile phone. Technological advancements have also made it possible for tech-savvy individuals to compile computer programs that make it possible to swap faces and replace them with those of celebrities, politicians, et cetera. Yet even more sophisticated technology uses Artificial Intelligence (AI) methods to create videos and photos that are not easily distinguishable from the real ones. ‘Deepfakes’ has become a buzzword. Along this line, this paper posits that there is widescale misinformation due to deepfakes and assesses the regulation of deepfakes in Kenya to curb the misinformation. It recommends pragmatic ways to train forensic experts and to create awareness among members of the public for detecting deepfakes, hence curbing their negative effects.
Eliminating Safe Havens for Transnational Cybercrimes in the African Continental Free Trade Area

The continuous advancement in technology makes cybercrimes effortlessly transnational. Existing literature reveals that the inadequacies of cybercrime-specific legislations, procedural powers, and enforceable mutual legal assistance provisions constitute jurisdictional challenges to the prosecution of transnational cybercrimes (TNCCs). This paper appraises the adequacy of legal responses to jurisdictional challenges of TNCCs in the African region, especially the African Union Convention on Cyber Security and Personal Data Protection (the Malabo Convention). It argues that the presence of states without substantive or procedural laws on cybercrimes, or both, constitutes safe havens that challenge the effectiveness of such laws in states where they are present. It finds that the Malabo Convention has the potential to be a tool for eliminating safe havens in the African region and given the inter-connection between trade and TNCCs, it suggests that it could be made operational through its annexation as one of the protocols to the African Continental Free Trade Area (AfCFTA) Agreement. The author concludes that purely domestic legal responses to cybercrimes are inadequate and suggests a holistic approach through the operationalization of an effective regional instrument as a way to diminish safe havens for TNCCs in the African region.
Teaching and Learning Speaking For The First Grade of Nursing Academy In Academic Year of 2019/2020

The problems of the study are : (1) how is the teaching and learning process of speaking English of the first grade of Nursing Academy of Purworejo regency in Academic Year of 2019/2020. (2) Whyare the problems found during the teaching and learning process of speaking English of the first grade of Nursing Academy of Purworejo Regency. Tehe theories which are used as a basis of this. Study are the nature of language, teaching and learning, the model of curiculum in Nursing Academy. Teaching and learning of speaking English, the lesson plan of speaking English, media and the source of learning, act. Based on the data analysis, it can be concluded that: (1) Some Casees occur during the teaching and learning of speaking English . (2) the students find the difficulties in pairing and perfoming speaking because the situdents limited of vocabularies, pronounciation, and grammar mastery. This research is a casestudy done at the first grade of Nursing Academy Purworejo regency in Academic Year of 2019/2020. The technique of sampling is purposive sampling. The data to get from: 910 the teaching and learning process of Speaking English language; (2) the informants: they are the teacher of English lesson of the first grade and the students; and (3) the document. The technique of the data gathering are: (1) obseravtion; (2) indepth interview; and (3) document analysis. The observation was done to capture the teaching and learning process of speaking, indepth interview was done to test. The bvalidaty process of speaking, to get the data from document, a document analysis done are syllabus, the lesson plan the criteria of minimal achiesment and students assessment. The gathered data were analysed by using reduction, data presentation and conclusion drawing.&#x0D; Key word: process, during, limited, conclusion, Assessment.
Role of chat bots in online training of personnel of modern enterprise

The direction of training employees online is relatively young and is gaining more and more popularity in such areas as e-commerce services, call centers, and the gaming industry. Therefore, the topic is relevant, international, and unified approaches in the classification and methods of creation have not yet been developed. The chatbot can be deployed on websites, mobile apps, social media messaging apps, SMS/text messaging, and other communication channels to serve as frontline virtual agents for staff, as well as work behind the scenes with agents through it. learning. Chat-bot communication with the worker in a dialog mode allows the company to answer questions and provide information using natural language to conduct training, increasing the comprehensibility and interest of the staff. This research paper presents an analysis of the use of a chatbot as a tool for online training of an organization’s personnel, reveals its advantages, disadvantages, and ways of development in a company. The article is filled with examples of practical cases of introducing a chatbot into the learning process, including a description of a successful long-term training project in a global international company.
Bounds on the covering radius of repetition code in Z2 Z6

In this paper, the covering radius of codes over R = Z 2 Z 6 with different weight are discussed. The block repetition codes over R is defined and the covering radius for block repetition codes R are obtained.
Students and education during the COVID-19 pandemic

The COVID-19 pandemic has grown a worldwide health concern and has imposed a significant impact on education. As a result, halfway through the second semester of 2019/2020, learning methods were delivered through distance learning (DL). The purpose of the paper is to study the specifics of online education during the Covid-19 pandemic. A comprehensive diagnostic study of the psychological characteristics of students included the following methods: the test of life-meaning orientations (LMO), adapted by D.A. Leontiev (2006), diagnostics of the motivational structure of personality. Based on the results of the conducted empirical research, duration of study influenced student preference. Plus, Higher number of first-year students preferred DL compared to their seniors. Notwithstanding some challenges, students could adjust to the new education methods of full DL, and the majority recognized combined learning that combined classroom and distance learning can be performed subsequently. The COVID-19 pandemic transforms the application of technology in education and teaching approaches in the near future.
AUDIT SISTEM INFORMASI MENGGUNAKAN STANDAR KERANGKA KERJA COBIT 5.0 DI RUMAH SAKIT

Hospital is a place where health facilities are located to support the services of the sick. Each hospital usually has services in the form of registration, pharmacy to cashier. In this study, the audit was carried out using the COBIT 5.0 (Control Objective For Information and Related Technology) framework standard which is a framework created by ISACA (Information System Audit and Control Association) and ITGI (Governance Institute) in 1992 which is a standard information technology controls that have been applied internationally. COBIT 5.0 has 5 Domains, namely EDM (Evaluate, Direct And Monitor), APO (Align, Plan and Support), BAI (Build, Acquire and Implement) DSS (Deliver, Service and Support) and MEA (Monitor, Evaluate And Assess). But in this study only focuses on the use of the APO domain only. This study resulted in the maturity value of the maturity level system with a maturity level value of 2.6 which is included in level 2, namely managed process. That is, the process at this level is implemented into a process setting (planned, monitored, evaluated) and the work products of the process are implemented, controlled and maintained appropriately. Measures the extent to which work products are produced by a well-regulated process.
Solving the Challenge of Volumetric Video Production and Streaming: An End-to-end Perspective of Technologies and Device Ecosystem Capabilities and Performance

Volumetric models and assets are great elements for content creators to use in the development of appealing immersive experiences. We can think about live sport events with the entire scene captured as volumetric elements and streamed to the mobile devices of thousands of consumers. However, distribution to consumers of high-quality immersive experiences using volumetric assets has been challenged by a number of factors including visual fidelity, bandwidth, latency, and device processing power. Content creators have been constrained from expressing the full potential intended for their original experience. In this paper you will learn about methods to stream volumetric video assets from an end-to-end perspective including an overview of production systems and suitable volumetric compression profiles (using point cloud compression) that can be used to render on any display for a wider reach: VR headsets, AR glasses, and flat screens. An ecosystem overview with device capabilities and performance is presented, and further included an analysis of content and end-user security functionality. Finally, this paper explores the evolution and opportunities of volumetric video streaming using 5G Cloud/Edge infrastructure to process and distribute volumetric content to any device, minimizing device processor power consumption, minimizing overall delay, and providing the best possible user experience.
Students’ Evaluating of Online Learning Quality at Al Baha University and Their Satisfaction with Online Courses

The study aims to explore students&amp;rsquo; perceptions of the quality of online courses offered for them at Al-Baha University. The current study mainly explores the quality of online learning courses, students&amp;rsquo; satisfaction with online learning courses, and the effect of students&amp;rsquo; perceived quality of online learning on their satisfaction with these courses. The quality of online courses was measured based on the following factors: learning outcomes, assessment and measurement, learning resources material, learner interaction, and online course technology. An online survey was used to collect data. Seventy-nine graduate students participated in the study. Findings showed that the overall quality of online education was high, and students were predominantly satisfied with their online courses. Additionally, the study found that gender, learning outcome, learning resources, learner interaction, and online technology were significant predictors of students&amp;rsquo; satisfaction. The study includes recommendations for implementing online courses as well as suggestions for future studies.
BlockScope: Detecting and Investigating Propagated Vulnerabilities in Forked Blockchain Projects

Due to the open-source nature of the blockchain ecosystem, it is common for new blockchains to fork or partially reuse the code of classic blockchains. For example, the popular Dogecoin, Litecoin, Binance BSC, and Polygon are all variants of Bitcoin/Ethereum. These "forked" blockchains thus could encounter similar vulnerabilities that are propagated from Bitcoin/Ethereum during forking or subsequently commit fetching. In this paper, we conduct a systematic study of detecting and investigating the propagated vulnerabilities in forked blockchain projects. To facilitate this study, we propose BlockScope, a novel tool that can effectively and efficiently detect multiple types of cloned vulnerabilities given an input of existing Bitcoin/Ethereum security patches. Specifically, BlockScope adopts similarity-based code match and designs a new way of calculating code similarity to cover all the syntax-wide variant (i.e., Type-1, Type-2, and Type-3) clones. Moreover, BlockScope automatically extracts and leverages the contexts of patch code to narrow down the search scope and locate only potentially relevant code for comparison. Our evaluation shows that BlockScope achieves good precision and high recall both at 91.8% (1.8 times higher recall than that in ReDeBug). BlockScope allows us to discover 101 previously unknown vulnerabilities in 13 out of the 16 forked projects of Bitcoin and Ethereum, including 16 from Dogecoin, 6 from Litecoin, 1 from Binance, and 4 from Optimism. We have reported all the vulnerabilities to their developers; 40 of them have been patched or accepted, 66 were acknowledged or under pending, and only 4 were rejected. We further investigate the propagation and patching processes of discovered vulnerabilities, and reveal three types of vulnerability propagation from source to forked projects, as well as the long delay (over 200 days) for releasing patches in Bitcoin forks.
Device Tuning for Multi-Task Large Model

Unsupervised pre-training approaches have achieved great success in many fields such as Computer Vision (CV), Natural Language Processing (NLP) and so on. However, compared to typical deep learning models, pre-training or even fine-tuning the state-of-the-art self-attention models is extremely expensive, as they require much more computational and memory resources. It severely limits their applications and success in a variety of domains, especially for multi-task learning. To improve the efficiency, we propose Device Tuning for the efficient multi-task model, which is a massively multitask framework across the cloud and device and is designed to encourage learning of representations that generalize better to many different tasks. Specifically, we design Device Tuning architecture of a multi-task model that benefits both cloud modelling and device modelling, which reduces the communication between device and cloud by representation compression. Experimental results demonstrate the effectiveness of our proposed method.
Evaluating the Effectiveness of Pre-trained Language Models in Predicting the Helpfulness of Online Product Reviews

Businesses and customers can gain valuable information from product reviews. The sheer number of reviews often necessitates ranking them based on their potential helpfulness. However, only a few reviews ever receive any helpfulness votes on online marketplaces. Sorting all reviews based on the few existing votes can cause helpful reviews to go unnoticed because of the limited attention span of readers. The problem of review helpfulness prediction is even more important for higher review volumes, and newly written reviews or launched products. In this work we compare the use of RoBERTa and XLM-R language models to predict the helpfulness of online product reviews. The contributions of our work in relation to literature include extensively investigating the efficacy of state-of-the-art language models -- both monolingual and multilingual -- against a robust baseline, taking ranking metrics into account when assessing these approaches, and assessing multilingual models for the first time. We employ the Amazon review dataset for our experiments. According to our study on several product categories, multilingual and monolingual pre-trained language models outperform the baseline that utilizes random forest with handcrafted features as much as 23% in RMSE. Pre-trained language models reduce the need for complex text feature engineering. However, our results suggest that pre-trained multilingual models may not be used for fine-tuning only one language. We assess the performance of language models with and without additional features. Our results show that including additional features like product rating by the reviewer can further help the predictive methods.