Reviewerly/exHarmony huggingface dataset:
Distributed ledger technology for supply chain and public governance as a response for sustainability issues

Purpose:The purpose of this article is to systematize the problems faced by modern supply chains and problems observed in the field of public governance, as well as to indicate solutions to these problems based on the currently developing Distributed Ledger Technology.Design/methodology/approach: The purpose of the article was achieved based on a thorough analysis of contemporary scientific articles and a number of industry reports, as well as websites of institutions involved in the development of DLT with particular emphasis on Blockchain technology.Moreover, two case studies on DLT implementation were presented.Findings: A number of problems have been identified related to the sustainable development of supply chains and societies.They can be systematized by taking into account the concept of the triple bottom line.There are DLT solutions that emphasize sustainable development.Examples of such solutions are described in the article.Research limitations/implications: (if applicable) If research is reported on in the paper, this section must be completed and should include suggestions for future research and any identified limitations in the research process.Practical implications: The use of DLT-based systems in supply chain management and in public management solves specific problems.The article shows how the architecture of DLT systems contributes to the increase in the transparency of the supply chain or public service.Moreover, the article indicates that the implementation of blockchain solutions contributes to increasing the trust in the supply chain management and public governance.Social implications: Described examples of DLT application show a number of benefits for society in terms of pro-ecological behavior, as well as in terms of security of data flowing through the public services system, which is often the subject of public concern.Originality/value: The originality of the article is to emphasize the importance of DLT for shaping sustainable development and to present the described technology as a way to reduce the negative impact of problems identified in the area of both supply chain management and public governance.
Loss functions for train document image segmentation models

The work is devoted to improving the quality of the results of image segmentation of documents of various scientific articles and legal acts by neural network models by learning using modified loss functions that take into account the features of images of the selected subject area. The analysis of existing loss functions is carried out, as well as the development of new functions that operate both with the coordinates of the bounding boxes and using information about the pixels of the input image. To assess the quality, a neural network segmentation model with modified loss functions is trained, and a theoretical assessment is carried out using a simulation experiment showing the convergence rate and segmentation error. As a result of the study, rapidly converging loss functions were created that improve the quality of document image segmentation using additional information about the input data.
Non-invasive Individual Sensing System for Collecting Biometric Indicators

The daily stress we, as population, are subjected has negative impacts on physical and mental health, making people age faster. With the increase in life expectancy, the population started to search for ways to ensure they reach the older ages with a healthier and better lifestyle, resulting in an increase of interest and demand for thermalism and wellness tourism. Although thermalism is recognized to have several benefits with regard to the combat and prevention of certain pathologies, this has not yet been fully proven. So, in this paper, we presented a sensing system, capable of not only recording thermalist’s biometric data, but also getting the data ready and prepared to be processed by any analytic tool with the aim of showing the impact that this sector has on the health of its practitioners.
Excellent Service and Utilization of Information Technology on Stakeholder Satisfaction and Organizational Performance

The purpose of this study was to analyze the influence of excellent service by utilizing information technology on the satisfaction of stakeholders, which has an impact on organizational performance.This study was descriptive with a quantitative approach.There were two types of variables in this study: the independent and dependent variables.To analyze the data in this study, the Statistical Program for Social Science (SPSS) was used.From the proposed model, excellent service by utilizing information technology positively and significantly affected stakeholder satisfaction.Furthermore, stakeholder satisfaction also had a positive and significant effect on organizational performance.Then from the study's final results, it could be concluded that there was a significant influence between the causal relationship of excellent service by utilizing information technology on organizational performance through stakeholder satisfaction.The novelty of this research is that apart from excellent service, there is also a positive influence on the use of technology on stakeholder satisfaction and organizational performance.This could be a consideration for every information technology user and organization by utilizing it as much as possible in increasing competitiveness.
Structural Control of Ore Mineralization in the Southeastern Margin of Western Nigeria Basement

Structural analyses are often ignored in mineral prospecting endeavor of any geological terrain despite the importance of geological structures in the formation of ore deposits.This paper correlates the results of mineral prospecting campaign to those of the structural analysis in the southeastern margin of the western Nigeria basement.The mineral prospecting was executed by essentially geochemical-exploration methods, while the structural analysis was achieved by lineament analysis using Landsat-8 imagery.The mineral prospecting campaign eventually led to the discovery of gold bearing marble deposit in the Dagbala area; silver and copper bearing silicified sheared rock in the Dagbala, Ojirami, Erurhu and Atte areas; lead and zinc bearing metaconglomerate around Egbigele; uranium and thorium bearing pegmatite in the Dagbala area.The Landsat-8 lineament analysis showed the presence of a shear zone in the central, folds in the SW, and fractures in the NE parts of the study area.The relation between the two is such that the gold and silver-copper mineralization is associated with the shear zone, the lead-zinc mineralization to the folds, and the uranium-thorium mineralization to the fractures.Indeed, geological structures guide mineralization and their analysis can be employed for mineral prospecting.
Quantum simulation of fermionic systems using hybrid digital-analog  quantum computing approach

We consider a hybrid digital-analog quantum computing approach, which allows implementing any quantum algorithm without standard two-qubit gates. This approach is based on the always-on interaction between qubits, which can provide an alternative to such gates. We show how digital-analog approach can be applied to simulate the dynamics of fermionic systems, in particular the Fermi-Hubbard model, using fermionic SWAP network and refocusing technique. We concentrate on the effects of connectivity topology, spread of interaction constants as well as on errors of entangling operations. We find that an optimal connectivity topology of qubits for the digital-analog simulation of fermionic systems of arbitrary dimensionality is a chain for spinless fermions and a ladder for spin-1/2 particles. Such a simple connectivity topology makes digital-analog approach attracting for the fermionic quantum simulation.
BungeeNeRF: Progressive Neural Radiance Field for Extreme Multi-scale Scene Rendering

Neural radiance fields (NeRF) has achieved outstanding performance in modeling 3D objects and controlled scenes, usually under a single scale. In this work, we focus on multi-scale cases where large changes in imagery are observed at drastically different scales. This scenario vastly exists in real-world 3D environments, such as city scenes, with views ranging from satellite level that captures the overview of a city, to ground level imagery showing complex details of an architecture; and can also be commonly identified in landscape and delicate minecraft 3D models. The wide span of viewing positions within these scenes yields multi-scale renderings with very different levels of detail, which poses great challenges to neural radiance field and biases it towards compromised results. To address these issues, we introduce BungeeNeRF, a progressive neural radiance field that achieves level-of-detail rendering across drastically varied scales. Starting from fitting distant views with a shallow base block, as training progresses, new blocks are appended to accommodate the emerging details in the increasingly closer views. The strategy progressively activates high-frequency channels in NeRF's positional encoding inputs and successively unfolds more complex details as the training proceeds. We demonstrate the superiority of BungeeNeRF in modeling diverse multi-scale scenes with drastically varying views on multiple data sources (city models, synthetic, and drone captured data) and its support for high-quality rendering in different levels of detail.
Secret Sharing-Based Energy-Aware and Multi-Hop Routing Protocol for IoT Based WSNs

Abstract: Modern advancements in insolent sensors, RFID, Web - based machineries, and technical requirements are made possible by the Internet of Things (IoT). Sensor nodes are often employed to collect and transmit sensed data and are thought of as intelligent devices. In addition to these inherent limitations, sensor nodes are also open to a number of security risks. In order to improve the quality of renewable energy with multi-hop information security versus malicious acts, this work provides (ESMR) protocol. There are three primary components to the suggested procedure. The network field is first divided into inlet and outlet zones depending on the placement of the nodes. Additionally, a large number of clusters are created in each zone based on the proximity of the node neighbourhood. Second, the suggested effective secret sharing mechanism is used to protect the data transfer from cluster members in each zone to the bowl node. In order to reduce routing disruption, the suggested approach examines the mathematical analysis of data connections. The work described offers a multi-hop, compact, secure data analyst solution for limited wireless communications based on the Internet of Things (WSNs). In terms of bandwidth by 38 percent, network available bandwidth by 34 percent, electricity intake by 34 percent, median end-to-end postponement by 28 percent, and high latency by 36 percent when compared to the conventional work, the experimental results of the part of the application and secure number of co routing protocol
An optimization method for characterizing two groups of data

Abstract Feature selection aims to choose a subset of features, out of the set of candidate features, such that the selected set best represents the whole in a particular aspect. We propose an optimization model for the problem of selecting features in the presence of two groups of data. The objectives include minimizing the number of selected features and maximizing similarities within the same group and differences between different groups. We use the lexicographic method and prove several properties of the problem. We show that obtaining even feasible solutions for the problem can be challenging. Therefore, we propose matheuristic algorithms. We test our algorithms on both randomly generated and real‐world datasets. The computational results indicate that the proposed matheuristics deliver quality solutions in a reasonable amount of time.
कार्यमूलकताका दृष्टिले कक्षा छ को नेपाली पाठ्यपुस्तकमा समाविष्ट व्याकरण {Grammar included in the Nepali textbook of grade six from the point of view of practicality}

प्रस्तुत लेख सन्दर्भपूर्ण प्रयोग अभ्यासबाट शिक्षण गर्नुपर्ने कार्यमूलक व्याकरण सम्बन्धी सैद्धान्तिक मान्यताका आधारमा कक्षा छ को वर्तमान नेपाली भाषा पाठ्यपुस्तकका व्याकरण अभ्यासको विश्लेषण गर्ने उद्देश्यमा केन्द्रित छ । यस लेखमा वर्णनात्मक विधिको अवलम्बन गरी उक्त पुस्तकमा दिइएका व्याकरण अभ्यास सम्बन्धी तथ्यहरूको व्याख्या विश्लेषण गरिएको छ । लेखबाट उक्त पाठ्यपुस्तकका व्याकरणका पाठ्यवस्तुहरूलाई कार्यमूलक व्याकरणका मान्यतासँग मेल खाने गरी सङ्गठन गरिएको, प्रश्नहरू कार्यमूलक प्रकृतिका बनाइएको, अभ्यासहरूमा भाषिक प्रकार्यलाई जोड दिइएको, सम्प्रेषण तथा कार्यकलाप आश्रित सिकाइ सम्भावनालाई प्रश्रय दिइएको जस्ता निष्कर्षमा पुगिएको छ । समग्रमा वर्तमान कक्षा छ को नेपाली भाषा पाठ्यपुस्तक कार्यमूलक व्याकरणात्मक मान्यताका दृष्टिले अग्रगामी रहेको देखिन्छ । तथापि वास्तविक जीवन सम्बद्धताका आधारमा अभ्यासहरू शिथिल रहेकाले यसतर्फ भने सचेतता अपनाउनुपर्ने देखिन्छ । &#x0D; {The present article is focused on the purpose of analyzing the grammar exercises of the current Nepali language textbooks of class six based on the theoretical assumptions related to functional grammar that should be taught through contextual practice. In this article, the explanation of facts related to grammar practice given in the book has been analyzed by adopting the descriptive method. From the article, it has been concluded that the grammar content of the textbook is organized in accordance with the principles of functional grammar, the questions are functional in nature, the linguistic function is emphasized in the exercises, and communication and activity-based learning possibilities are encouraged. On the whole, the Nepali language textbook of the sixth grade seems to be a pioneer in terms of functional grammatical recognition. However, as the practices are relaxed based on real life relevance, it seems that awareness should be adopted in this regard.}&#x0D;
LECTURERS’ PERCEPTION ON THE USE OF WEEKLY QUIZZES IN EFL CLASSROOM

This research aims to describe and determine the lecturer's reasons for using weekly quizzes in the EFL classroom. This research used a qualitative research design. The instrument of the research was an interview. To get the sample, the researcher used random cluster sampling. There was one lecturer in English Education Study Program at Universitas Negeri Makassar. The result of the research showed that there are several reasons for the lecturer to use weekly quizzes, including to (a) increase students learning motivation, (b) make students feel challenged, (c) encourage students to be creative in answering questions and interact with each other, (d) avoid cheating in class, (e) know the extent of students understanding of the material that has been taught, (f) help the lecturer assess teaching in class and students activity, and (g) start the discussion in class. According to the research results, it can be concluded that the use of weekly quizzes in the EFL classroom can be a tool to determine and measure students' understanding of the material that had been taught previously.
Internet of Things (IoT) &amp; Underwater Network Forensics

The proliferation of IoT devices and technology in recent years cannot be overstated. With the diverse area of application, IoT devices will be prone to unscrupulous attacks. Applying digital forensics in this field makes it a multi-faceted area that necessarily implies a lot of challenges out to be addressed in order to ensure compatibility. This research extensively considers existing literature with the view of highlighting the application areas of IoT, underwater networks and digital areas as well the research challenges that needs attention in order to realize a robust IoT and underwater forensics regime. These recommendations as well policy directions were also added Keywords: Internet of Things (IoT), Underwater Network Forensics, Cybersecurity, Compatibility BOOK Chapter ǀ Research Nexus in IT, Law, Cyber Security &amp; Forensics. Open Access. Distributed Free Citation: Timothy Kwaku (2022): Internet of Things (IoT) &amp; Underwater Network Forensics Book Chapter Series on Research Nexus in IT, Law, Cyber Security &amp; Forensics. Pp 291-300 www.isteams.net/ITlawbookchapter2022. dx.doi.org/10.22624/AIMS/CRP-BK3-P47
A Distributed Ledger Technology Roadmap for Albania: Some Preliminary Reflections

Albania is a small country of the West Balkans situated in Southeast Europe still in the early stages of distributed ledger technology (DLT) adoption.In this research note, we begin to investigate the cryptocurrency regulatory framework and propose a national blockchain roadmap for the country.Albania was one of the first European nations to elaborate a cryptocurrency regulatory framework aimed at safeguarding users from the dangers of fraud and imposing sanctions in situations of misuse.Our proposed national blockchain roadmap includes emerging priorities such as licensed entities, digital divide reduction, remittances digitisation, Ethereum 2.0, blockchain FDI, e-voting, and the quadruple helix system.
How Many Public Corporations Recognise “Token Economy” Technologies as Materially Significant? Evidence from 10-K Reports

The token economy promises to enable entirely new business models that will likely disrupt many market leaders.The seeds for disruption are already upon us, powered by technical innovations such as blockchains, fungible tokens, non-fungible tokens, metaverses, and decentralised autonomous organisations.How seriously are corporations taking these emerging token economy technologies?How many corporations envision these technologies to be materially significant to their business today?We answered these questions for United States (US) corporations by analysing the five most recent annual 10-K reports, a report required by the US Securities and Exchange Commission (SEC).Of the 39,522 10-K reports examined, only five percent of corporations recognise token economy technologies as materially significant.We focus upon the top 21 corporations with the most mentions of these technologies and discuss the results through the lens of the Theory of Disruptive Innovation.
GAMBARAN KECERDASAN EMOSIONAL SISWA KELAS VII SMP NEGERI 9 CIMAHI SELAMA PEMBELAJARAN DARING

The current situation in Indonesia is the covid 19 pandemic makes the government (ministry of education) apply online learning or distance learning (PJJ) regulations. Which we don't realize this affects the emotional intelligence of students. The purpose of this study is to find out the picture of emotional intelligence of students of class VII SMPN 9 Cimahi during online learning. This research uses qualitative descriptive methods.Â Data collection techniques use interviews, interviews and documentation. Based on the results of research in SMPN 9 Cimahi there are two categories of emotional intelligence students, measurements of low emotional intelligence category and high emotional intelligence are measured by the results of emotional intelligence questionnaire scores that have previously been given by BK teachers, students with high emotional intelligence students are able to learn emotions and express in positive things and students with low emotional intelligence focused on two indicators that have not been able to facilitate attention to the task being done and do not have the ability to communicate with others.Keywords:Â Emotional Intelligence, Class VII Students, Online Learning.Â
Digital competence in scientific research in higher education

Background: Due to the current contingency due to covid 19, students and teachers have had to face new digital challenges in such a way that they seek to become aware of how important digital skills are for the learning process. However, it is evident that, in Peru, there is a digital divide due to inequality; therefore, there is no good university service due to the lack of Internet access in rural areas. The digital skills of university students allow the production of new knowledge and technological innovation from the development of digital skills. Objective: The general objective of the research was to identify the country with the most scientific production through a bibliometric and bibliographic review, to search for the production of research works on the construct of digital competence in scientific research in higher education during the period 2016- 2021. Methodology: The research was developed under a qualitative approach based on a documentary review of the studies carried out in the period 2016-2021 in Latin American countries of the digital competence variable, 44 articles registered in the Scopus database were identified.
Artificial Intelligence Based Social Distance Monitoring in Public Areas

COVID-19 is an infectious disease caused by a newly discovered coronavirus called SARS-CoV-2. There are two ways of contamination risk, namely spreading through droplets or aerosol-type spreading into the air with people's speech in crowded environments. The best way to prevent the spread of COVID-19 in a crowd public area is to follow social distance rules. Violation of the social distance is a common situation in areas where people frequently visit such as hospitals, schools and shopping centers. In this study, an artificial intelligence-based social distance determination study was developed in order to detect social distance violations in crowded areas. Within the scope of the study, a new dataset was proposed to determine social distance between pedestrians. The YOLOv3 algorithm, which is very successful in object detection, was compared with the SSD-MobileNET, which is considered to be a light weighted model, and the traditionally handcrafted methods Haar-like cascade and HOG methods. Inability to obtain depth information, which is one of the biggest problems encountered in monocular cameras, has been tried to be eliminated by perspective transformation. In this way, the social distance violation detected in specific area is notified by the system to the relevant people with a warning.
Exploring Students’ Perspective of a Platform for Digital Competence Acquisition in Schools

This study aims to evaluate the ways that the actual usage of a platform for digital competence acquisition, evaluation and certification contributes to satisfaction and perceived success of students in primary and secondary schools. A cross-sectional survey was implemented online to collect 1725 students’ answers in six European countries. The analysis of collected data was carried out by employing Pearson correlation, Partial least squares structural equation modelling (PLS-SEM) and Importance-performance map analysis (IPMA). Findings indicated that the usage of such a platform has greater effects on the impacts than on students’ satisfaction. Detailed analysis of correlations revealed that students’ decision on whether they will use the platform in the future greatly depends on how it contributes to the success of their learning processes. Results also suggest that teachers are seen as an inevitable part of such a process and are mandatory to achieve the full potential of the platform.