Reviewerly/exHarmony huggingface dataset:
Inclusive Virtual Reality Learning: Review and 'Best-Fit' Framework for Universal Learning

The rise of Virtual Reality (VR) in educational contexts has highlighted the need to design Virtual Reality Learning Applications (VRLAs) that prioritize inclusivity, accommodating a spectrum of learner needs. Despite the surging interest, there is a noticeable gap in research that delves into the specifics of creating VRLAs that are rooted in inclusive educational theory. This research sought to extract insights and recommendations for the development of VRLAs tailored for diverse student populations. The intention was to scrutinize research focused on the inclusive design elements of VRLAs, leading to the establishment of preliminary Inclusion Guidelines for VR Learning (IGVRL). Adopting the "best-fit" framework synthesis technique, the research anchored its findings in the Universal Design for Learning (UDL) framework. UDL was developed to mold learning experiences to meet the requirements of heterogenous learners. Using UDL as a coding framework, a comprehensive literature review was undertaken, adhering to the SPIDER search strategy. The review of literature revealed distinct design recommendations that facilitate inclusive learning within VRLAs. Information was systematically categorized based on UDL's nine classifications and subsequently distilled into the preliminary IGVRL. It's pertinent to note that these guidelines, while offering a foundational perspective, necessitate further in-depth evaluations for validation. The analytical process brought to the fore several themes that UDL did not adequately encompass, such as the nuances of embodied learning, the focus on VR contents and their immersive properties, and the pivotal role of collaboration and cooperation in VRLAs. These insights underscore the further need for research in these areas. Although some facets of VR accessibility were discussed, a deeper exploration into this domain was identified as crucial, reiterating the importance of accessibility in underpinning inclusive education. The research underscores the potential of VRLAs in promoting inclusivity within educational settings and introduces the preliminary IGVRL for VRLA design, specifically targeting K-12 contexts. This paper emphasizes the continuum of research required to refine and validate these guidelines, ensuring their applicability and efficacy in diverse educational scenarios.
An Improved Variational-Based Model for Denoising and Segmentation of Vector-Valued Images

Preserving important features such as edges is one of the main concerns in models for denoising and segmenting vector-valued (colour) images. The Rudin-Osher-Fatemi (ROF) model is a well-known variational-based image denoising model that is capable of reducing image noise while preserving image edges. However, the ROF model is not formulated for denoising colour images and is less effective in preserving corners and weak edges. On the other hand, a variational-based selective segmentation model for colour images called the selective distance segmentation (DSS2) model has recently been proposed, which can effectively partition or extract a specific object in an image. However, the DSS2 model has problems in segmenting colour images with noise, which may result in poor segmentation. Therefore, in this research, we first modify the ROF model to denoise vector-valued images by including the edge detector and extending the formulation into a vector-valued framework. Second, we reformulate the DSS2 model by incorporating the modified ROF model as a new fitting term in the DSS2 model. Peak signal-to-noise ratio (PSNR) is used to measure the image quality, while Jaccard and Dice similarity index are used to evaluate the segmentation quality. The comparison between our proposed model and existing model shows that our model is more effective as indicated by higher PSNR, Jaccard and Dice similarity index values.
Evaluating the Impact of Financial Stability and Monetary Stability on Economic Growth: Evidence from an Emerging Economy

Financial stability and monetary stability both make an essential contribution to sustainable industrial growth and well-established industrial sectors contribute to sustainable economic development. The fundamental objective of this study is to create an FSI index to quantify financial strain in Pakistan. While utilizing monthly data starting from 2004-11 to 2017-7 the Financial Stress Index has four indicators which include TED spread, yield spread, stock price volatility, and exchange rate volatility through principal component analysis (PCA). An ARDL co-integration model is used to investigate the long-term and short-term relationships between time series data. The primary takeaways from this research are that financial stability and industrial production are positively correlated, while inflation and industrial production are negatively correlated. This study fills a knowledge gap by analyzing the impact of financial and monetary stability on economic growth in Pakistan using the Financial Stress Index. Lastly, this study sheds light on the financial and monetary concerns of Pakistan.
Simulating quantum backﬂow on a quantum computer

Abstract Quantum backﬂow is a counterintuitive eﬀect in which the probability density of a free particle moves in the direction opposite to the particle’s momentum. If the particle is electrically charged, then the eﬀect can be viewed as the contrast between the direction of electric current and that of the momentum. To date, there has been no direct experimental observation of quantum backﬂow. However, the eﬀect has been simulated numerically (using classical computers) and optically (using classical light). In this study, we present the ﬁrst simulation of quantum backﬂow using a real quantum computer.&amp;#xD;
Assessing EFL Listening and Speaking Skills During Remote Teaching

The purpose of the present study was to analyse how English as a Foreign Language (EFL) listening and speaking skills were assessed during remote teaching as a result of the COVID-19 pandemic. The participants were 174 senior high school students in public and private institutions, 102 EFL teachers, 32 high school authorities, and 80 students’ parents. The methodology comprised a quantitative approach in which students’, teachers’, and authorities’ surveys were analysed. The instruments employed consisted of a five-point Likert scale that included strongly agree, agree, neutral, disagree, and strongly disagree regarding items related to assessment. The findings suggest that for assessing listening and speaking skills the teachers in the research mostly used online technological tools such as quizzes, chatrooms, and blogs. Furthermore, the assessment instruments included oral presentations, questioning, as well as listening and speaking tests. Finally, formative and summative assessments were mainly employed to evaluate students’ listening and speaking skills during the pandemic.
FACIAL EXPRESSION EMOTION RECOGNITION USING LOCAL BINARY PATTERNS HISTOGRAMS

Local Binary Patterns (LBP) histograms are used as texture descriptors by the proposed facial expression emotion detection system to identify various face expressions in photos. Localized facial patterns are represented by histograms formed by the extraction of LBP features based on pixel intensity comparisons after pre-processing operations such as picture normalization and scaling. Using a labeled emotion dataset, these histograms are used as feature vectors to train a machine learning model. The model's performance is evaluated using evaluation measures, such as accuracy, precision, recall, and F1 score. The system, which was developed with OpenCV and scikit-learn, shows a reliable and useful method for recognizing facial expressions that can be used in practical settings. Key Words: Facial Recognition, Deep Learning, Image Recognition
Untangling the Processes of Bitcoin: An Organizational Learning Perspective

Bitcoin is a complex phenomenon, whether in terms of the macro factors affecting its price or its role in the global energy infrastructure. However, extant literature pays too little attention to exploring the internal mechanisms of the protocol to be able to link them to how they affect the visible characteristics of Bitcoin. This paper uses secondary data from highly reputable Bitcoin-focused sources to systematically map the processes that enable Bitcoin to function as a peer-to-peer cash system. Novelty is achieved by applying the established and versatile “4I” organisational learning framework to provide a new lens through which to understand how the processes within Bitcoin enable and facilitate different types of changes to the protocol. Further insights are provided to organisational learning from Bitcoin, in relation to managing mission-critical changes to organisational systems. In addition, it presents an option for dealing with irreconcilable internal differences to “hard-fork” part of the organisation. While the scope of this paper is limited to secondary data, opportunities for further research, including primary data collection, are outlined to explore how Bitcoin knowledge disseminates within communities or companies.
Aksesibilitas Pemustaka Penyandang Disabilitas Di Dinas Kearsipan Dan Perpustakaan Provinsi Sumatera Barat Berdasarkan Standar IFLA Checklist

This research aims to analyze the accessibility of library and archives services for people with disabilities in the West Sumatra Provincial Archives and Library Service, the accessibility of users with disabilities in the West Sumatra Province Archives and Library Service based on IFLA Checklist standards, and the obstacles faced in fulfilling accessibility for people with disabilities at the Provincial Archives and Library Service West Sumatra. This research uses qualitative research with descriptive methods. Data collection techniques use observation, interviews and documentation studies. The data validation technique uses triangulation, namely triangulation of data sources. The data validation technique uses the Miles and Hubermen model which consists of data reduction, data presentation, drawing conclusions and verification. The results of this research are as follows. Firstly, accessibility at the West Sumatra Provincial Archives and Library Service has not yet been fully realized because there are still many shortcomings found in the implementation of accessibility services for people with disabilities, such as the ease of library users in meeting their needs has not been fully realized and the only library material collections available are books with braille printing. Second, accessibility at the West Sumatra Archives and Library Service based on the IFLA Checklist Standard reached 40.54%. Thus, it can be said that accessibility for users with disabilities in the Archives and Library Service is still not in accordance with the IFLA Checklist standards. The research results from the IFLA Checklist standard amounted to 111 items which were 45 items which were appropriate while which were 66 items which were not appropriate. Third, the obstacles faced by the West Sumatra Province Archives and Library Service in fulfilling accessibility for disabled users from various aspects such as the lack of available funding, lack of technical knowledge of implementation, and limited human resources who are competent in providing services for users with special needs or disabilities.
The Linked Factor of Customer Satisfaction and Loyalty in F&amp;B Industry: A Study of Operational Performance Factor

The focus of this research is to investigate how operational performance affects customer satisfaction and loyalty in the food and beverage industry. Starbucks has been selected as this research object. Conducting a survey and referring to other studies of journals and articles to support the assisting data are the research methods employed. According to the research results, 71 % of respondents are pleased with current Starbucks services and products. The studies also revealed that the majority of customers had heard of Starbucks on social media. The study’s findings reveal that operation success is significantly linked to customer satisfaction. Customer satisfaction has been described as a significant mediator between service quality and customer loyalty. Having a clear understanding of the hypothesized relationship in the study encourages Starbucks to figure out the best action to gain or increase customer loyalty by providing good service quality to build a loyal customer base and customer satisfaction.
Bitcoin on Economic Growth (Case of 8 Asia Countries)

In recent years, the price of Bitcoin has risen sharply on balance, despite some fluctuations. The latest price surge of the largest cryptocurrency prompted talk about Bitcoin's future. This research was conducted to confirm the impact of cryptocurrency which is Bitcoin on economic growth in Asian countries. Many studies have talked about cryptocurrencies on the technological side, but there are still few references to research that analyzes cryptocurrencies with economic growth. Using panel data regression, this study correlates cryptocurrencies, in this case, Bitcoin, as a type of cryptocurrency that is best known with GDP as a variable that represents economic growth. This study also has 4 other variables as control variables which will ensure the results are not biased. Namely the Internet (I), Capital (K), Labor (L), and Technology (T), as in Solow's growth theory which reviews growth through its supply side, the function of production inputs. This study took samples from 8 Asian countries with the most Bitcoin transactions (Japan, China, India, Singapore, Indonesia, Malaysia, Thailand, and Hongkong) from 2014 to 2020.
Analysis of Web Vulnerability Using Open-Source Scanners on Different Types of Small Entrepreneur Web Applications in Malaysia

Most of Malaysia’s small entrepreneurs have switched to online platforms as an alternative to their physical businesses. Social media sites such as TikTok, Instagram, Twitter, and Facebook provide free advertising tools and convenient access to a broader global target. However, security issues on these websites remain questionable as users are exposed to web attacks due to the vulnerabilities on the websites. Considering the cost and lack of awareness of the importance of cybersecurity, some organizations find it not profitable to invest in securing their websites. Therefore, this paper aims to test Malaysian small entrepreneurs’ web applications using open-source scanners and analyse the results of web vulnerabilities detected. To do so, two types of open-source scanners, OWASP ZAP and IRONWASP, were installed to scan five websites found through advertisements on social media sites. The web vulnerability identification was based on the top 5 OWASP web vulnerability reports, and the results showed that five types of web vulnerabilities were detected. The analysis of the results showed that the top 5 web vulnerabilities in Malaysian small entrepreneurs’ websites are the ‘Missing Session Timeout’ vulnerability with 81.84 percent, the ‘Sensitive Information Passed as Clear Text in GET URL’ vulnerability with 14.74 percent, and the ‘Session ID Cookies not Marked Secure’ vulnerability with 2.47 percent. This paper provides security analysis on Small Medium Enterprise (SME) websites for future enhancement and consideration during development and implementation to avoid possible attacks. Therefore, developers are advised to handle these vulnerabilities by carefully managing the session timeout, and users are recommended to log out from the websites immediately after they are done.
Modern Implementation of the Natural-Philosophical Concept of Cognition on the Basis of the Empirical-Metaphysical General Systems Theory

The article examines the relationship between philosophy and science, as well as the possible role of general systems theory in the formation of the field of consolidated philosophical and scientific knowledge. It is argued that the existing arguments concerning the incompatibility of philosophy with the criteria of scientificity only point to the existence of differences between philosophical knowledge and knowledge within the framework of private sciences. At the same time, philosophy is the methodological and paradigmatic basis of all sciences. It is suggested that it is expedient to return to the natural-philosophical concept of cognition, according to which the core of science is philosophy, and private sciences act as tools of cognition of separate subject areas. The methodological basis for the realization of the natural-philosophical concept today can be the general theory of systems, supplemented by the ontological component. In the article the idea of a common field of knowledge formed by philosophy and all private sciences is put forward. This field of cognition is formed by areas of three types: metaphysical knowledge, private sciences, and areas of generalized or universal knowledge, the cogni-tion of which can be carried out only by means of the general theory of systems. An extended version of the general theory of systems is proposed – the empirical-metaphysical general theory of systems, which, in the author’s opinion, possesses the necessary capabilities for the realization of philosophical cognition. The pro-posed general theory of systems includes an epistemological component (metaphysics of material being) as well as an ontological component. А cognition of complex non-deterministic objects within the framework of empirical-metaphysical general theory of systems is realized by a wide set of tools: collections of patterns and primitives of systems, secondary laws and properties of objects, evolutionary way of cognition and laws of evo-lutionary growth of complexity of systems, as well as methodology of formation of reliable knowledge.
Stress Detection and Mitigation through Discovery of Optimal Lecture Delivery Method for STEM-Enrolled University Students

The high availability of technology-related jobs is currently not fulfilled by enough supply of technology graduates, specifically the ones coming from science, technology, engineering, and mathematics (STEM) courses. This is related to the low enrolment rate of STEM-based courses at Universities. The notion that STEM subjects are intense and difficult to pass could be the reason of such phenomena. This research experimented different lecture delivery methods comprising of different seating arrangements, inclusion or exclusion of break, group size, and room size to investigate the generated levels of stress among STEM students, so that the method that would induce minimum stress could be discovered. The analysis of the generated heart rates as stress indication concludes that the level of difficulty of STEM subject’s topic is the one that most affected students’ level of stress, while inclusion of break during class is imperious to destress students. Class arrangement with far seating was discovered to be potentially more stressful for certain students indicated by the high level of resting heart rate in one of the experiments. Importantly, it was also found that regardless of lecture delivery method, STEM subjects in general remained challenging that was suggested by the consistently high recorded heart rates, which was also a sign of active learning engagement - besides implying the level of stress. Finally, gender-wise, there is no visible data pattern that could hint that certain gender is more vulnerable to stress when handling STEM subjects.
Transfer Learning with EfficientNetV2S for Automatic Face Shape Classification

The classification of human face shapes, a pivotal aspect of one&amp;rsquo;s appearance, plays a crucial role in diverse fields like beauty, cosmetics, healthcare, and security. In this paper, we present a multi-step methodology for face shape classification, harnessing the potential of transfer learning and a pretrained EfficientNetV2S neural network. Our approach comprises key phases, including preprocessing, augmentation, training, and testing, ensuring a comprehensive and reliable solution. The preprocessing step involves precise face detection, cropping, and image scaling, laying a solid foundation for accurate feature extraction. Our methodology utilizes a publicly available dataset of female celebrities, comprising five face shape classes: heart, oblong, oval, round, and square. By augmenting this dataset during training, we magnify its diversity, enabling better generalization and enhancing the model&amp;rsquo;s robustness. With the EfficientNetV2S neural network, we employ transfer learning, leveraging pretrained weights to optimize accuracy, training speed, and parameter size. The result is a highly efficient and effective model, which outperforms state-of-the-art approaches on the same dataset, boasting an outstanding overall accuracy of 96.32%. Our findings demonstrate the efficiency of our approach, proving its potential in the field of face shape classification. The success of our methodology holds promise for various applications, offering valuable insights into beauty analysis, cosmetic recommendations, and personalized healthcare.
The Mediating Effect of School Adjustment on the Relationship between a Creative School Environment and Children's Happiness

This study examined the mediating effect of children's school adjustment on the relationship between a creative school environment and children’s happiness. For this purpose, an analysis was performed of data from the 12th Panel Study on Korean Children conducted in 2019. The participants were 1,393 fifth-grade elementary school students. Data were analyzed using descriptive statistics, one-way ANOVA, Pearson correlation analysis, confirmatory factor analysis, and structural equation modeling using SPSS 25.0 and AMOS 23.0 programs. The principal results were as follows. Firstly, there were significant positive correlations among creative school environment, children's school adjustment, and happiness. Secondly, the creative school environment significantly affected children's school adjustment and happiness. Thirdly, children's school adjustment had a positive effect on their happiness. Fourthly, the creative school environment had an indirect effect on children's happiness through school adjustment. The results thus demonstrate that school is a social environment that strongly influences children's happiness. Therefore, to improve children's school happiness, it is essential to consider the relationship between a creative school environment and school adjustment.
Extrinsic Calibration for Large FOV Based on Inverse Depth Parameterized Bundle Adjustment

Abstract To overcome the reliance on high-precision calibration plates in camera calibration, this paper proposes an extrinsic calibration method suitable for 3D-DIC in large field of view. The method combines image feature algorithms with DIC techniques to extract matching point pairs from the left and right images of binocular cameras. These matching point pairs are then homogenized within the field of view. Next, initial values of the extrinsic parameters are solved based on epipolar constraint theory. Finally, the calibration parameters are nonlinearly optimized using the bundle adjustment method. To achieve stable and reliable numerical optimization in large field of view applications, the calibration control points' spatial coordinates are represented using inverse depth parameterization. In scenarios where there might be a lack of sufficient calibration control points, speckle patterns are artificially introduced to supplement the scene features. However, there is a lack of reliable experimental basis on how to add calibration control points within the field of view. Therefore, through simulations, the factors affecting calibration accuracy are analyzed to guide the actual calibration process. The proposed method's reliability and accuracy in large field of view 3D measurement are verified through experiments.&amp;#xD;