Reviewerly/exHarmony huggingface dataset:
Toward Smart and Immersive Classroom based on AI, VR, and 6G

The technological revolutions greatly impact current and future Classrooms. These advances in technology include the revolution of artificial intelligence, virtual reality, and super highspeed internet. In the coming next generation (6G), the data rate will be very sufficient for live scenes in virtual reality applications such as telepresence and teleoperation. This paper review and discuss next-generation technologies in AI, VR, and communication. Moreover, we examine the motivation for establishing an Advanced Technology based Smart and Immersive Classroom (SIC) and the advantages of its availability to the virtual society. Recent advances in computer and communications technology have delivered capabilities to tomorrow’s SIC. Advances in virtual reality and real-time streaming on the internet have created a revolution in curricula and classrooms. Index Terms—Virtual Reality in education; 6G for education, Artificial Intelligence in education, Immersive Classroom
Block Ciphers Analysis Based on a Fully Connected Neural Network

With the development of high-speed network technologies, there has been a recent rise in the transfer of significant amounts of sensitive data across the Internet and other open channels. The data will be encrypted using the same key for both Triple Data Encryption Standard (TDES) and Advanced Encryption Standard (AES), with block cipher modes called cipher Block Chaining (CBC) and Electronic CodeBook (ECB). Block ciphers are often used for secure data storage in fixed hard drives, portable devices, and safe network data transport. Therefore, to assess the security of the encryption method, it is necessary to become familiar with and evaluate the algorithms of cryptographic systems. Block cipher users need to be sure that the ciphers they employ are secure against various attacks. A Fully Connected Neural Network (FCNN) model was initially used to assess how well the models were classified. Then, all models, including encoder models, were assessed using True Positive (TP) measures for successful classification of the discovered encoder and False Positive (FP) measures for imprecise categorization. The accuracy value, retrieval, loss, precision value, and F1 score were then calculated using a confusion matrix to assess the model's efficacy (abbreviated as F1). ECB results with an accuracy of 85% and CBC results with an accuracy of 88% were produced, and the parameters of the FCNN model were tweaked to provide better results. These results helped to identify the encryption algorithm more precisely and evaluate it.
INFORMATION SYSTEM SECURITY EVALUATION USING COBIT 5 FRAMEWORK

Most companies use information technology to develop their business. But there are things to note, some threats can occur and cause losses. Undesirable events hinder the achievement of company goals and strategies. PT XYZ believes that information security is important in all business activities. Threats that can compromise information security. Information is an important asset for PT XYZ. Therefore, it is necessary to evaluate or measure the controls and activities that have been implemented to protect company data/information. Evaluation in this paper uses the COBIT 5 Framework which focuses on Manage Security Services (DSS05). Keywords: Evaluation, COBIT 5, Manage Security Services, Capability Level
Making Drone Data FAIR Through a Community-Developed Information Framework

Small Uncrewed Aircraft Systems (sUAS) are an increasingly common tool for data collection in many scientific fields. However, there are few standards or best practices guiding the collection, sharing, or publication of data collected with these tools. This makes collaboration, data quality control, and reproducibility challenging. To that end, we have used iterative rounds of data modeling and user engagement to develop a Minimum Information Framework (MIF) to guide sUAS users in collecting the metadata necessary to ensure that their data is trust-worthy, shareable and reusable. This paper briefly outlines our methods and the MIF itself, which includes 74 metadata terms in four classes that sUAS users should consider collecting for any given study. The MIF provides a foundation which can be used for developing standards and best practices.
Correlated product of experts for sparse Gaussian process regression

Abstract Gaussian processes (GPs) are an important tool in machine learning and statistics. However, off-the-shelf GP inference procedures are limited to datasets with several thousand data points because of their cubic computational complexity. For this reason, many sparse GPs techniques have been developed over the past years. In this paper, we focus on GP regression tasks and propose a new approach based on aggregating predictions from several local and correlated experts. Thereby, the degree of correlation between the experts can vary between independent up to fully correlated experts. The individual predictions of the experts are aggregated taking into account their correlation resulting in consistent uncertainty estimates. Our method recovers independent Product of Experts, sparse GP and full GP in the limiting cases. The presented framework can deal with a general kernel function and multiple variables, and has a time and space complexity which is linear in the number of experts and data samples, which makes our approach highly scalable. We demonstrate superior performance, in a time vs. accuracy sense, of our proposed method against state-of-the-art GP approximations for synthetic as well as several real-world datasets with deterministic and stochastic optimization.
Why Are We Teaching Factorisation at a Time When the Planet Is Getting Hotter Every Year?

The author draws on his Eastern wisdom tradition of Hinduism-Buddhism to narrate his decades-long scholarly journey to expand the mathematics teacher education program of his university, culminating in the establishment of postgraduate programs (MEd, MPhil, PhD) in STEAM Education. The goal of these programs is to empower teachers in schools across Nepal to develop transformative curricula and pedagogies that foster cultural and environmental sustainability.
An Integrated View of Knowledge Management Enablers, Components, and Benefits: Comprehensive Literature Review

The key to success in the 21 st century, knowledge-based economy, will be the effective and efficient management of knowledge.Knowledge Management (KM) has a direct impact on organizational success.KM in a knowledge-based economy entails growth, value, and improving living standards through knowledge creation, storage, and dissemination.This study aims to integrate KM enablers, components, and benefits into a single view through a comprehensive literature search.The integrative view of these three factors would facilitate the understanding of KM initiatives within organizations.This paper performs a comprehensive literature review to explain the KM enablers, components, and benefits.From the literature review, KM enablers have been explained in different ways.However, this paper categorized them into eight (8) classes: organizational culture, organizational structure, management support, champion support, design of KM strategy, performance and evaluation, training, and technologies.Additionally, this study identified six (6) major components of KM: people, processes, technology, information/content, governance, and strategy.In this study, the KM benefits were seen to support business organizations to achieve both process outcomes and organizational outcomes.
Use of ICT to Promote Literacy in Sub-Saharan Africa

Literacy, accessibility, technology and digital education are central concerns of this article. The iconic theme is the use of ICT to promote literacy in the region of Sub-Saharan Africa. In fact, today more than ever, literacy remains a major challenge for such region. In view of the social environment and economic crisis, the future of the strategies of literacy dependent, among other things, on Sub-Saharan of significant investments in innovation and ICT, in order to consolidate the integration of programs literacy in the recent approaches based on ICT. Indeed, the development of mobile technology, the convergence of all media to digital media and the rapid development of the Internet have changed the portrait of the sector of literacy on Africa. An important point to remember is that this region faces an illiteracy to double facet, digital illiteracy at the same time classic illiteracy. However, the efficiency of the integration of ICT in literacy does not depend so much on technological advances but rather on the effective implementation of these programs to improve the Sub-Saharan populations’ daily lives. In fact, this study highlights good practices and also a set of constraints and challenges that continue to hamper the creation, implementation of literacy programs and activities, notably through the use of ICT in the Sub-Saharan African countries. At the same time, this study allows to locate a number of challenges and opportunities for the ICT and literacy in the region.
Additive Bayesian Network Modeling with the <i>R</i> Package <b>abn</b>

The R package abn is designed to fit additive Bayesian network models to observational datasets and contains routines to score Bayesian networks based on Bayesian or information theoretic formulations of generalized linear models. It is equipped with exact search and greedy search algorithms to select the best network, and supports continuous, discrete and count data in the same model and input of prior knowledge at a structural level. The Bayesian implementation supports random effects to control for one-layer clustering. In this paper, we give an overview of the methodology and illustrate the package's functionality using a veterinary dataset concerned with respiratory diseases in commercial swine production.
Modeling and Analyzing the Dynamic Impact of Financial Development on Economic Growth in Syria

There is a link between economic progress and Financial Development. In order to analyze the potential for influencing Economic Growth, this study will look at the underlying elements that drive the development of Syria’s Financial Sector. The research team is also speculating on how much Economic Growth these effects will bring. A Dynamic Linear Model that takes into account Financial Reforms and changes on the Legal System was used to analyze the Impact of Financial Development on Economic Growth between 1980 and 2018. We were able to measure many dimensions of Financial Development with the use of a new IMF Financial Development Indicator, overcoming the limits of single traditional variables that have been widely used. The ARDL Bounds Test approach, which is based on unit root tests, was used. The Error Correction Model was also applied. The country’s Financial Development had a favorable and statistically significant effect on Economic Growth in Syria in the short and long terms. A lot of factors influence Economic Growth, including the Legal System, overall Government Expenditure, and the Exchange Rate. The Supply Leading Hypothesis of Patrick (1966) was realized in Syria,hence Financial Development leads to Economic Growth, consistent with the proposal of “more Finance, more Growth” (Levine, 2003). Financial Development is a necessary condition and prerequisite for Economic Growth in Syria, which is consistent with the (Finance Lead Growth Theory). The model could be very useful in decision-making, especially those related to reform policies to promote the SDGs or to modify current policies in response to a possible global financial crisis or shock.
Solar Radiation Forecasts and a Tiny House PV Off-Grid System

In this article, which is discussed at a time when initiatives towards renewable energy sources are increasing and reducing fossil fuel consumption; the factors that need to be examined for the installation of an off-grid solar panel system were examined and in line with the data obtained, a system was designed for a tiny-house. An off-grid system with 10KWh power consumption with optimum irradiance data has been found on how many square meters of PV system will be needed to operate it. How to meet the stable 10KWh need for the worst month, the amount of battery capacity required has been examined. A system inventory has been allocated. The province of Pamukkale in Turkey, with a latitude of 37.89°, was chosen for the solar panel installation; It is aimed to meet all the electricity needs of the house, which was built in a forest area 8 km away from the mains, with the solar panel system to be installed. From theory to practice with an academic approach as well as solar energy sector jargon; in this article, includes a two-way study. A solar panel system was installed in line with the data obtained and the 7600Wh value that the house to be built would need, and 29 batteries integrated into the system were sized for cases where the system could not provide sufficient energy through the sun with a 1% probability. Thus, the design of the optimum "Solar Energy System" desired for a certain location and compatible estimation calculations will be able to provide examples of this study.
Classification of Mint Leaf Types Based on the Image Using Euclidean Distance and K-Means Clustering with Shape and Texture Feature Extraction

Mint is a plant that has many benefits and uses. However, some people are not familiar with the types of mint leaves because they cannot tell the difference. Actually, if you look closely, mint leaves have their own characteristic shape and texture. However, most people judge mint leaves to have a shape similar to other leaves so it is difficult to tell them apart. This paper aims to classify the types of mint leaves using the Euclidean distance algorithm and K-Means clustering with shape and texture feature extraction. The K-Means Clustering Algorithm functions as a segmentation so that the image to be classified can be separated from other objects. In the feature extraction process, metric and eccentricity parameters are used. Meanwhile, for texture feature extraction, use the parameters in the Gray Level Co-occurence Matrix (GLCM). Furthermore, the classification process uses the Euclidean Distance algorithm which has a function to represent the level of similarity between two images by taking into account the distance value from the identified image. Based on the results of the evaluation using a confusion matrix by calculating precision, recall and accuracy, the precision value is 82%, recal is 84% â€‹â€‹and accuracy is 83%.
CHeart: A Conditional Spatio-Temporal Generative Model for Cardiac Anatomy

Two key questions in cardiac image analysis are to assess the anatomy and motion of the heart from images; and to understand how they are associated with non-imaging clinical factors such as gender, age and diseases. While the first question can often be addressed by image segmentation and motion tracking algorithms, our capability to model and to answer the second question is still limited. In this work, we propose a novel conditional generative model to describe the 4D spatio-temporal anatomy of the heart and its interaction with non-imaging clinical factors. The clinical factors are integrated as the conditions of the generative modelling, which allows us to investigate how these factors influence the cardiac anatomy. We evaluate the model performance in mainly two tasks, anatomical sequence completion and sequence generation. The model achieves a high performance in anatomical sequence completion, comparable to or outperforming other state-of-the-art generative models. In terms of sequence generation, given clinical conditions, the model can generate realistic synthetic 4D sequential anatomies that share similar distributions with the real data.
Pemetaan bibliometrik terhadap perkembangan penelitian arsitektur informasi pada Google Scholar menggunakan VOSviewer

Information architecture is a process of organizing information that can make it easy for users to meet their information needs, provide current location instructions in an information link, and make it easier for users to maintain information in a large collection of information. Information architecture has an important role in designing a website, because in it there are processes of research, strategy, design, implementation, and administration that can play a role in structuring, organizing, and labeling. This study aims to determ (istilah)ine the development of research publications within 11 (eleven) years, tofind out the direction of information architecture research trends, to identify the relationship between scientific concepts, and to know the information architecture science network based on keywords (co- occurrence) and collaboration of authors (coauthorship). The method used in this research is descriptive bibliometric analysis, the data used is taken in the range of 2011 – 2021. Data collection is based on the Google scholar database with information architecture keywords and additional supporting keywords including website, design, wireframe, and labelling system with the number of publications is limited to 500 journals. Data was collected using Publish or Perish (PoP) software asmetadata. Data analysis was performed using Vosviewer software as a medium for bibliometric analysis. The results show that in the last 11 years the number of publications on information architecture research indexed by Google scholar has fluctuated, but in term (istilah)s of quantity, it has increased significantly. The highest publication growth development occurred in 2020, reaching 60 journals (14.1%), while the lowest publication occurred in 2011 with a total of 12 journals (2.8%).Mapping the development of information architecture research publications based on co-authorship shows a correlation or relationship between researchers centred on Wing Wahyu Winarno. While the mapping of the development of information architecture research publications based on keywords (co- occurrence) indicates a relationship between one term (istilah) and another accompanied by 3 dominant clusters, although this research has not been widely studied, research in the field of information architecture can create opportunities for researchers.
Agro-Food Supply Chain Traceability using Blockchain and IPFS

Many blockchain initiatives significantly use the InterPlanetary File System (IPFS) to store user data off-chain.The centralized administration, ambiguous data, unreliable data, and ease of creating information islands are all issues with traditional traceability systems.This study develops a monitoring system using blockchain technology to record and inquire about product information in the supply network of Non-Perishable (NP) agro goods to address the above issues.The transparency and trustworthiness of traceability data were considerably improved by employing blockchain technology's distributed, tamper-proof, and traceable properties.To alleviate the strain on the blockchain and enable efficient information inquiry, a storage structure is built in which both public and private data are stored in the blockchain and the Inter Planetary File System (IPFS) using cryptography.Because of its ability to trace the origin of food, blockchain technology contributes to the development of reliable food supply chains and the establishment of rapport between farmers and their customers.Since it provides a secure location for data to be kept, it can pave the way for implementing data-driven farming techniques.In addition to improving data security, recording farm data in IPFS and storing encrypted file IPFS hashes in smart contracts solves the issue of blockchain storage explosion.And when used in tandem with smart contracts, it enables instantaneous outflows between parties in response to changes in data stored in the blockchain.The paper also offers simulations of the implementation and analysis of the performance.The findings validate that our system improves security for sensitive information, safeguards supply chain data, and meets the needs of real-world applications.Furthermore, it boosts throughput efficiency while reducing latency.
Towards flexible runtime monitoring support for ROS-based applications

Robotic systems are becoming common in different domains and for various purposes, such as unmanned aerial vehicles performing search and rescue operations, or robots operating in manufacturing plants. Such systems are characterized by close interactions, or even collaborations, between hardware and machinery on the one hand, and humans on the other. Furthermore, as Cyber-Physical Systems (CPS) in general and robotic applications in particular typically operate in an emergent environment, unanticipated events may occur during their operation, making the need for runtime monitoring support a crucial yet often time-consuming task. Runtime monitoring typically requires establishing support for collecting data, aggregating and transporting the data to a monitoring framework for persistence and further processing, and finally, performing checks of functional and non-functional properties. In this paper, we present our initial efforts towards a flexible monitoring framework for ROS-based systems. We report on challenges for establishing runtime monitoring support and present our preliminary architecture that aims to significantly reduce the setup and maintenance effort when creating monitors and establishing constraint checks.
The Role of Employee Engagement, Job Satisfaction and Organizational Commitment on Happiness at Work at a Saudi Organization

This research examines the meaning, causes, and effects of happiness in the workplace in a government organisation, specifically within one of the Saudi Arabian Government&amp;rsquo;s Royal Commissions. It examines the impact of employee engagement, job satisfaction, and organizational commitment on happiness at work by adopting Fisher&amp;rsquo;s framework (2010). The data was collected using a simple random sampling approach, and a questionnaire survey was designed and distributed to employees working in this government organization. Three thousand people were targeted using the convenience approach, and the response rate was 23.5%. The demographic data analysis was conducted using a descriptive statistical approach, and the hypothesis was tested using correlation and regression analysis. The results reveal that workplace happiness depends mainly on organizational commitment; however, employee engagement and job satisfaction also contribute to the individual&amp;rsquo;s happiness at work.
Major Cloud Computing Security Challenges with Innovative Approaches

Cloud computing is the most favored contemporary era as it has the cap potential to decrease its costs related to computing which improves its pliability and extensibility for further computer processes. Among the past some years, cloud computing has been well superior as a hopeful idea for business organization to one of the additives of the IT organization it really is fastest growing. There are important troubles like protection which the IT agencies take into difficulty that misplaced with the heavy insertion of cloud computing Technology. Though records may be saved in any vicinity. The important reality is Storage of records is saved best with inside the vicinity of the clients that's been the numerous varieties of worries created. In cloud computing region the maximum argued hassle is especially Security. This study mainly intends to analyze and address the major cloud computing security challenges with innovative approaches. To meet that aim, a range of scientific methods, including descriptive, analytical, observation and comparison are taken into account. Given the results, the major key to a success cloud computing projects is reaching stability among the commercial enterprise blessings and the hidden capacity dangers that can affect efficacy.