Reviewerly/exHarmony huggingface dataset:
ANALYSIS OF LAND SUITABILITY FOR EDUCATIONAL AREA IN MAJALENGKA REGENCY

Educational area has a characteristic educational function that supports the improvement of knowledge, physical, and morals so that students can achieve their highest goals and ideals. The Educational Area of Majalengka Regency is the border point of 3 villages and 1 kelurahan, namely Panyingkiran Village, Jatipamor Village, Jatisawit Village, and Majalengka Village, and the border of 3 sub-districts namely Panyingkiran District, Kasokandel District, and Majalengka District. The Majalengka Regency Education Area, which is planned to use the healthy learning landscape concept, needs to be analyzed for the suitability of the land and whether the supporting activities can support the main educational activities. The purpose of this study is to analyze the suitability of the land around the construction site of the Politeknik Manufaktur Campus so that the area supporting educational activities there is in accordance with the carrying capacity and capacity of the land. The land suitability analysis used is an overlay analysis using the weighting point method. The result is that there are 4 suitability classes, which are not in accordance with the results of score 2 covering an area of 30.4 ha (39.01% of the total area), then quite in accordance with the results of score 3 covering an area of 25.38 ha (32.57% of the total area). , then in accordance with the results of score 4 covering an area of 20.03 ha (25.70% of the total area) and very much in accordance with the results of score 5 covering an area of 2.12 ha (2.72% of the total area).
Enhancing Student Understanding via Smart and Friendly Learning Mobile Application

In the sphere of education, testing and enhancing students' comprehension is not a simple process.This is mirrored in the assessment results, where particular courses have a high failure rate.On the UiTM system, the high failure rate is defined as the proportion of students who fail a subject that exceeds the threshold of 25 percent.Therefore, topics exceeding this limit are deemed incapable of meeting the Academic Quality UiTM objective.In this study, Basic Hydraulic courses is chosen to be a pilot study as the failure rate is high for few semesters.A creative strategy and method of teaching and learning is being proposed to increase students' understanding of the course's content as to overcome the related issue.A smartphone application known as Sahabat Maya Pelajar (SMa2P) has been introduced and integrated into the teaching and learning process.According to the examination records of the Basic Hydraulics course at the Faculty of Civil Engineering at UiTM Johor, the failure rate of this course is decrease.This is shown by comparing results between semesters of 20204 and 20212 which indicate the course failure rate decreased by 22% in the latter semester.Therefore, it is crucial to improve students' performance and comprehension by using digital tools as this platform able to incorporate interactive teaching approaches into classroom activities through smartphone application.
Image denoising using fast non-local means filter and multi-thresholding with harmony search algorithm for WSN

Several image denoising algorithms are developed so far to obtain a better denoised sensor images. But they fail to preserve the edges of the images. In order to overcome this, an attempt has been made in this paper by incorporating the various filters like fast non-local means filter (FNLMF) and high boost filter with the existing wavelet thresholding-based denoising method. However, the denoised output and the computation time are affected by the wavelet properties significantly. Hence, this paper concentrates on histogram-based multi-thresholding (HMT) as a major part to denoise the image. Here, the corrupted image is first denoised by applying FNLMF filtering section. Then the edges and minimal details of the denoised output are enhanced by utilising the HMT with harmony search algorithm (HSA)-based optimisation technique. From the simulation results, the proposed denoising method can be adoptable for WSN.
Effective hybrid feature subset selection for multilevel datasets using decision tree classifiers

Feature selection is one of the most significant procedures in machine learning algorithms. It is particularly to improve the performance and prediction accuracy for complex data classification. This paper discusses a hybrid feature selection technique with the decision tree-based classification algorithm. The feature selected using information gain (IG) is combined with the features selected from ReliefF which generates the resultant feature subset. Then the resultant feature subset is in turn combined with a correlation-based feature selection (CFS) method to generate the aggregated feature subset. To perform classification accuracy on the aggregated feature subset, different decision trees-based classification algorithm such as C4.5, decision stumps, naive Bayes tree, and random forest with ten-fold cross-validation have been deployed. To check the prediction accuracy of the proposed work eight different multilevel University of California, Irvine (UCI) machine learning datasets have been used with minimum to maximum numbers of features. The main objective of the hybrid feature selection is to improve the classification accuracy, prediction and to reduce the execution time using standard datasets.
COVIDGuardian: A Machine Learning approach for detecting the Three Cs

On January 30, 2020, WHO officially declared the outbreak of COVID-19 a Public Health Emergency of International Concern. Japan announced the state of emergency and implemented safety protocols the "Three Cs", a warning guideline addressing to voluntarily avoid potentially COVID-19 hazardous situations such as confined and closed spaces, crowded places and close-contact settings that lead to occurrence of serious clusters. The primary goal of this research is to identify the factors which help to estimate whether the user is in the Three Cs. We propose COVIDGuardian, a system that detects the Three Cs based on data such as CO2, temperature, humidity, and wireless packet log. The results show that estimation of closed space had the highest accuracy followed by close-contact settings and crowded places. The ensemble Random Forest (RF) classifier demonstrates the highest accuracy and F score in detecting closed spaces and crowded spaces. The findings indicated that integrated loudness value, average CO2, average humidity, probe request log, and average RSSI are of critical importance. In addition, when the probe request logs were filtered at three RSSI cutoff points (1m, 3m, and 5m), 1m cut-off points had the highest accuracy and F Score among the Three C models.
Theoretical and Methodological Basis for Studying the Needs and Advantages in Youth Activities

This article studies the harmony of needs and interests in the activities of young people in the information society, revealing the conceptual foundations and socio-philosophical aspects of the harmony of needs and interests, conflicts in meeting the needs and interests of young people in the space of information struggle, the commonality of needs and interests in the process modernization of society and building a civil society on the basis of means of provision.
Prevention of Professional Deformation of Employees of Internal Affairs Bodies: Psychological, Pedagogical, Organizational and Legal Aspects

The article is devoted to the issue of professional deformation of employees of internal affairs bodies and prevention of its occurrence and development. The subject of the study are regulations, scientific publications and conditions for the organization of work on the prevention of professional deformation of employees in the internal affairs bodies of the Russian Federation. The methodological basis of the research is an interdisciplinary approach that allows accumulating the achievements of scientists from different fields – pedagogy, psychology, management and law. During the research, analysis, synthesis, comparison, observation, study of experience, special legal methods of cognition were used. The reasons for the appearance of professional deformation of employees of internal affairs bodies are considered. Special attention is paid to the stages of formation of professional deformation of employees of internal affairs bodies. In order to reduce the risk of exposure to the development of occupational deformation, the authors state the need for timely prevention of occupational deformation and offer its possible options. The scientific novelty of the study lies in the complex of preventive measures proposed by the authors that contribute to the prevention of professional deformation of employees of internal affairs bodies. The authors come to the conclusion that for the successful implementation of preventive measures to prevent the development of professional deformation, it is necessary to expand the staff of the psychological service, develop the institute of mentoring, develop and adopt programs for the prevention of professional deformation of employees in specific departments of internal affairs bodies, taking into account the specifics of their activities, improve pedagogical and other conditions for the prevention of professional deformation of employees of internal affairs bodies. The results of the study will be useful to specialists of personnel and psychological services, the management staff of the internal affairs bodies, as well as specialists in educational work of higher educational institutions that train future employees of the internal affairs bodies of Russia.
CNN Hyperparameters Optimization Using Random Search For Image Classification

In the last decade, deep learning in general and Convolutional Neural Networks (CNN) have achieved a human level and outstanding performance in almost all computer-based systems such as classification(text, images, and videos). Building an efficient CNN architecture and finding the most suitable layers requires time. In addition, tuning and setting CNN parameters such as the number of filters, size of filters, Dense rate, Dropout value, etc., has an essential effect on the overall performance of the CNN model. This paper investigated the effects of CNN hyperparameter optimizations using Random Search. To achieve our goals, we selected to investigate the hyperparameter optimizations of MobileNetV2 and VGG19 models when used for image classification. Here, we have combined four mask detection datasets of approximately 6K, 12K, 4k, and 4k images into one dataset. Overall, the results of the experimental works showed that using the hyperparameter optimization technique improved the overall performance of both MobileNetV2 and VGG19 models. In addition, VGG19 outperformed MobileNetV2 across Accuracy, Precision, recall, and F1 score evaluation matrixes.
Privacy-Preserving Energy Trade Using Double Auction in Blockchain Offline Channels

Blockchain is a promising tool to implement peer-to-peer energy trade algorithms because it lowers the cost of electricity by eliminating 3rd parties such as the utility companies from energy trade and by creating a secure trade platform. However, the state of the art blockchain-based peer to peer energy trade solutions have privacy and scalability problems. In this paper, we proposed a novel method to execute double auction-based peer to peer energy trade in blockchain offline channels to enhance security, privacy and scalability of peer to peer energy trade. We prove that the proposed decentralised double auction is secure, privacy-preserving and more efficient as McAfee’s double auction.
Towards Cost-Efficient Management for Power Purchase Agreements Using Blockchain Technology

The difficulty for two parties to efficiently manage the contract conditions and clauses defined in a Power Purchase Agreement introduces several challenges. This manuscript addresses the current management limitations that arise during its lifecycle and offers a new vision adequate to the business implications, the need of transparency and the requirements of edge computing continuous monitoring. Considering the relevant actors, the main scenarios driven by the Power Purchase Agreements and their state-of-the-art contract designs, this manuscript proposes a novel method and procedure to enhance the cost-efficiency of the installations, granting the consumer self-management and the confidence and the guarantee of origin through a trustworthy distributed solution. The method proposed enables total traceability and integrity on the PPA performance in the long-term by applying blockchain technology. A new operational design is proposed, explaining the energy balance and energy cost formulas required by businesses. The results show that blockchain enhances the way of managing data, the data ownership, and the market opportunity.
Profitable Fee Controller for Payment Channel Networks

Payment channel networks (PCN) are one of the promising second layer solutions for the scalability issue of cryptocurrencies. They offer high throughput and low-cost transactions for the users. However, practical and design issues of PCN hinder users from embracing the technology. This paper focuses on how to increase user adoption by boosting revenue as transaction mediators. Our approach is twofold; reduce the cost of refilling channels due to channel exhaustion and collectively acquire a maximum gain from all channels belonging to the respective nodes. For that, we devise a novel fee controller based on Model Predictive Control (MPC), where we formulate the problem as an Optimal Control Problem (OCP). It is optimized to obtain maximum profit while proactively alarming the payers about the exhaustion through a dynamic fee mechanism. We evaluate the proposed fee controller’s effectiveness compared with the conventional static fee controller and OptimizedFee controller. Our experimental simulations demonstrate that the proposed fee controller successfully improves the revenue and controls channel exhaustion simultaneously.
Decentralised Argumentation for Data Vetting in Blockchains

Although it is difficult to overwrite the data kept in blockchains, there are numerous incidents of false data insertion in blockchains. Current blockchain technologies can not prevent such false insertion into blockchains. In this paper, we present a blockchain model that can prevent such immutable lies. We have several contributions in this paper: we developed a decentralised argumentation protocol that allows auditors to decide the validity of a claim, we developed an incentive system for the auditors not to withheld any evidence for or against a claim, we developed methods to execute the decentralised argumentation protocol in blockchain offline channels for high scale execution of the proposed data vetting method. We prove that the proposed data vetting method executed in the blockchain offline channel network is correct.
Proofs and Limitations of the Pathway Protocol

Blockchain technology offers efficient solutions for a multitude of use-cases, but one of the most successful areas in which this technology has been applied is the field of decentralized finance (DeFi). Decentralized exchanges allow a large number of users to exchange one cryptocurrency for another, without the need for any central authority with any degree of control over the process. Although many different models of decentralized exchanges have been proposed, the Automated Market Maker model currently seems to be the most widely applicable and, therefore, successful. As in the classical financial world, companies and projects may seek to solicit or provide market making services for various trading pairs on exchanges. While for orderbook-based exchanges, the execution of such services is studied deeply and rather straightforward, for AMMs the process becomes more complicated. To solve this, different approaches to market making are offered by the Pathway protocol, focused on two major goals: first, to bring the token price for a particular trading pair to a certain target price, and second, to keep the liquidity of that trading pair intact. The original publication on the Pathway protocol describes its design and goals in detail, but lacks mathematical evidence that the protocol is formally capable of achieving these goals. Therefore, this paper delves a little deeper into the mathematical background of the protocol and formally proves its most important characteristics claimed by the original paper. Last but not least, this paper provides a more in depth discussion of the benefits and limitations of the Pathway protocol, based on the presented mathematical foundations.
A Model of Decentralised Distribution Line Using Layer 2 Blockchains

At least one-third of the food produced for human consumption is lost and wasted due to inefficient perishable product distribution plans. Currently used distribution plans are static and centralised as a single entity decides on a distribution plan where products may move along a predefined path. In this paper, we developed a dynamic distribution plan generation algorithm where distribution paths are dynamic. We used blockchain offline channels to develop decentralised, secure, and privacy-preserving dynamic distribution plans in a multi-party supply chain. Our algorithm generates distribution plans using real-time quality information about perishable goods so that products may be sold before their shelf life expires. Our algorithm ensures the privacy of all actors in a supply chain as inventory and order information of all actors remains privacy-preserved.
ELI Principles on the Use of Digital Assets as Security

The Principles address the use, by private parties, whether natural or legal persons, of digital assets as security for credit. In particular, the Principles are intended to focus on situations where the parties contractually agree to create a security interest in a digital asset, within the meaning of the Principles, so as to secure the performance by the security provider or another debtor of its secured obligation(s) vis-à-vis the secured creditor. The Principles treat the creation of a security interest in a digital asset as the creation, by contract, of a limited right in that asset, entitling the secured creditor to satisfaction of its claims vis-à-vis the security provider or another debtor. The right so created is to be construed as a right in rem or a functionally equivalent right, insofar as it entitles the secured creditor to enjoy priority over the security provider’s other creditors. The Principles present definitions of key concepts in the use of digital assets as security, including one for ‘digital asset’, building on the core attributes of assets within the intended scope of the Principles. The creation of a security interest through a security agreement will typically be covered by a conflict rule built on some objective connecting factor. The Principles propose that the law applicable to the creation of security interests in digital assets be identified by reference to the place of business or central administration or habitual residence of the security provider. In those cases where a clear, readily identifiable connection exists between the digital asset under consideration and one particular jurisdiction, on account of the characteristics of that asset and the environment of its creation and holding, the Principles propose that the law governing the creation of a valid security interest in that digital asset should be the law of that jurisdiction, ie, the law of the digital asset itself. Additionally, the Principles address the issue of determining the applicable law in cases where the digital asset to be used as security represents a real-world asset, tangible or intangible. Regarding the third-party effectiveness of security interests, including their priority against competing claims, the Principles propose determining the applicable law similarly to that for the creation of a security interest in digital assets. For the purposes of both creation and third-party effectiveness, the Principles presuppose compliance with the requirements of the applicable law. However, where those requirements reflect the characteristics of more conventional assets and cannot be meaningfully applied to digital assets, the Principles cater for the necessary adaptations. Finally, under the Principles, a security interest is to be extinguished once there is full payment or other satisfaction of all secured obligations.
Legal Remedies for Online Attacks: Young People’s Perspectives

Online attacks can deeply affect young people and their reputations, sometimes with serious long-term consequences. There is growing awareness of the harms of both true and false attacks on others, especially where the attacks violate trust, confidence and/or expectations of privacy. There are, however, few reported Canadian examples of young people seeking legal remedies in response to online attacks, which raises the question of whether young people understand the law as a meaningful response. This paper draws on the results of qualitative interviews with young people aged 15 to 22 about their experiences with and understandings of reputation, privacy and online attacks, with particular focus on their opinions and experiences regarding response to online attacks. In response to online abuse, young people focus on a range of goals, including minimizing damage, repairing and redressing harm, punishing perpetrators, and prevention. To achieve these goals, they look to a variety of sources of support or assistance, including themselves, members of their social groups, parents, the school (including teachers), social media platforms, police, and the justice system. Criminal and civil justice system responses are viewed as having limited effectiveness in responding to experiences of online abuse, and respondents view these alternatives as limited to the most serious cases of online aggression. We discuss the perspectives of interview participants in relation to current legal responses, and suggest that there may be a need to refocus policy attention away from traditional reactive civil and criminal law processes toward more proactive and informal response mechanisms.
Cryptocurrencies and trustees: what are the risks?

Abstract This article is interested in the risk exposure to trustees from cryptocurrency investment. Recent case law has established that cryptoassets are to be deemed as legal property, and, in consequence, can form the subject matter of a trust. This is interesting because it creates a real risk for trustees, who may purchase cryptocurrency as an investment opportunity pursuant to their statutory investment duty. The article suggests that there are three main risks for trustees: (i) regulatory risk; (ii) market risk; and (iii) reputational risk. In truth, a trustee that invests in cryptocurrency runs the risk of direct, personal liability.
The Impact of Globalization and Digitalization on Cultural Exchange between Students in the Educational Process

Globalization, the process of global integration and unification in all spheres of our life is still significant among the tendencies of the modern world. Thus, the process of globalization leads to an increase in international communication, including the field of higher education. A lot of international organizations such as the European University Association (EUA), UNESCO, the International Association for the Evaluation of Educational Achievement (IEA) and others are actively involved in the development and formation of national policies in the field of education in order to increase the level of «dialogue of cultures» between students from different countries.