Reviewerly/exHarmony huggingface dataset:
Android Based College App Using Flutter Dart

In today's world, communication and information sharing between teachers and students have increasingly shifted to online platforms such as Google Classroom, Gmail, Google Forms, WhatsApp, and more. To address the diverse needs of educational institutions, we developed an app that supports all devices, including mobile phones, laptops, and tablets. The Android app for mobile and tablet websites supports all devices seamlessly. This app provides comprehensive information on attendance, examination schedules, lecture notes, fee details, event notifications, and online tests, catering to all the requirements of the institution. We developed this app using the latest technology, including Flutter and Dart, with Firebase integration. Additionally, we created a web application that is easily accessible via desktops. This website, along with the app, is connected to the same Firebase server, ensuring synchronized data access. The institute has taken a step further by developing its own Android application and website to enhance efficient communication with its students. These platforms are exclusively accessible and available to authorized users associated with the institute, ensuring privacy and security.
Real-World Aircraft Recognition based on RF Fingerprinting with Few Labeled ADS-B Signals

Automatic Dependent Surveillance-Broadcast (ADS-B) is considered as a radar alternative in air transport systems, yet lack of authentication and encryption make it vulnerable to attack. In this paper, we propose a noise-robust radio frequency fingerprinting (RFF) approach for practical aircraft identification scenarios with a small sample size to address these issues. We develop a preprocessing method to improve noise-robustness by zero-padding useless signals and use a Siamese Networks-based few-shot training scheme for RFF recognition. The method is evaluated on a real-world ADS-B dataset, showing that signal preprocessing increases aircraft recognition accuracy by approximately 20% compared to using raw signals directly in small sample cases. Even with tens of labeled samples, our method achieves over 90% accuracy, outperforming other CNN identifiers by over 30%.
CONCEPT OF INFORMATION SYSTEM FOR CULTURAL HERITAGE SITES RENOVATION USING AUGMENTED REALITY

Cultural heritage is key to identity and development. Many valuable objects are affected by time, natural elements and financial lack. Innovative technologies are crucial for their preservation. The paper develops an information system based on augmented reality (AR) for the restoration of cultural heritage. This extends AURA's approach to preserving musical spaces by applying AR to cultural objects. New techniques improve AURA, allowing accurate restoration of objects affected by time. 3D modeling and machine learning allow to create virtual replicas with precision down to the smallest detail. Augmented reality and machine learning open new perspectives for the preservation of cultural values. The paper proposes an innovative approach of using AR for cultural heritage restoration. The authors offer unique solutions for accurate modeling of 3D models of objects. The purpose of the paper is to develop an information system for the restoration of cultural heritage through AR. This will increase the possibilities of preservation and research of values. Using AR and 3D modeling can improve the restoration of objects and provide access for researchers and the public. In future research, the proposed approaches and methods will be implemented to expand the functionality of the information system. This will include developing interactive interfaces for interacting with virtual models of cultural heritage, analyzing data for a deeper understanding of restoration processes and trend detection, as well as integrating cutting-edge information technologies, such as virtual reality and natural language recognition systems, using artificial intelligence. The primary goal is to improve the processes of preserving and studying cultural heritage through the use of modern information technologies.
ANALYTIC SOLUTION OF ONE-DIMENSIONAL FRACTIONAL GLYCOLYSIS MODEL

Glycolysis, which occurs in the cytoplasm of both prokaryotic and eukaryotic cells, is regarded to be the primary step employed in the breakdown of glucose to extract energy. As it is utilized by all living things on the planet, it was likely one of the first metabolic routes to emerge. It is a cytoplasmic mechanism that converts glucose into carbon molecules while also producing energy. The enzyme hexokinase aids in the phosphorylation of glucose. Hexokinase is inhibited by this mechanism, which generates glucose-6-P from adenosine triphosphate (ATP). This paper’s primary goal is to quantitatively examine the general reaction–diffusion Glycolysis system. Since the Glycolysis model shows a positive result as the unknown variables represent chemical substance concentration, therefore, to evaluate the behavior of the model for the non-integral order derivative of both independent variables, we expanded the concept of the conventional order Glycolysis model to the fractional Glycolysis model. The nonlinearity of the model is decomposed through an Adomian polynomial for evaluation. More precisely, we used the iterative Laplace Adomian decomposition method (LADM) to determine the numerical solution for the underlying model. The model’s necessary analytical/numerical solution was found by adding the first few iterations. Finally, we have presented numerical examples and graphical representations to explain the dynamics of the considered model to ensure the scheme’s validity.
FDI, Information and Communication Technology, and Economic Growth: Empirical Evidence from Morocco

Abstract The document analyzes the relationship between FDI (Foreign Direct Investment), ICT (Information and Communication Technology), and economic growth in Morocco for the period from 1990 to 2021 using the ARDL model. Three models have been evaluated, with economic growth, FDI, and ICT as dependent variables in each respective model. In model (1), the results indicate that in the short term, economic growth is not positively related to FDI and ICT. However, in the long term, FDI positively contributes to economic growth, while ICT negatively affects it. A controlled inflation rate has a positive short-term effect, and the level of education shows a positive relationship in both the short and long term. In Model (2), economic growth and government spending have a significant short-term effect on FDI, while ICT has no effect. In the long term, economic performance and inflation remain important for FDI. Model (3) confirms a significant short-term relationship between FDI and ICT, with a negative impact. However, ICT is positively influenced by the inflation rate and the level of education. In the long term, FDI, demographic changes, and education have favorable and significant effects, while economic growth has a negative impact. Regarding the Granger causality test by Toda-Yamamoto, the cause-and-effect relationship between ICT and economic growth is strong and unidirectional, while economic growth influences the level of ICT development. On the other hand, the causality between FDI and ICT concerning economic growth is indirect and depends on factors such as population growth, education level, and inflation rate. JEL classification numbers: C190, F21, F30, L96, O55. Keywords: Economic growth, FDI, Information and Communication technology, ARDL model, Toda-Yamamoto causality.
Vulnerability Detection With K-Nearest Neighbor and Naïve Bayes Method using Machine Learning

In this day and age, the use of the Internet has increased. SQL injection is a serious security threat on the Internet for various dynamic websites. As the use of the Internet for various online services increases, so make the security threats that exist on the Web. SQL injection attacks are one of the most serious security vulnerabilities on the Web. Most of these vulnerabilities are caused by a lack of input validation and the use of SQL parameters. SQLMap is an application from the Kali Linux operating system that is useful for injecting data on a website by using the features available in this application. In this paper, author conducts a security assessment to detect attacks on a website, more precisely to detect SQL Injection attacks, using the K-Nearest Neighbor method and naïve bayes. The results obtained are that the website being tested has SQL Injection vulnerabilities, and the K-Nearest Neighbor method is the best method for this case because it has an accuracy of 94.2%. In comparison, the Naïve Bayes method has an accuracy of 80%.
Natural Language Processing

Natural language processing (NLP) stands halfway between computer science computational linguistics, and it is dedicated to the conversion of written and spoken natural human languages into structured mineable data. Through the combination of linguistic, statistical and AI methods NLP can be used either to determine the meaning of a text or even to produce a human-like response. NLP is already part of our everyday life as it is widely implemented in our computer software or in our mobile phones. As hospitals produce a large amount of written free-text data, NLP may play an important role to develop tool for clinical decision support, evidence-based medicine, or even research. Indeed, NLP application in the field of medical informatics has received an increasing attention in the recent years. Undoubtedly, radiology is particularly suited to benefit from applications of NLP, given that the primary mode of inter-physician and physician-to-patient communication is by way of the written radiology report.
IMPACT OF EDUCATION ON ECONOMIC GROWTH. THE CASE OF RWANDA

This paper focused on the impact of education on economic growth in Rwanda. It was an attempt to explore the extent to which investment in education level by the Government of Rwanda affects its economic growth hence the output level is achieved. The government of Rwanda has year by year increased budget for education. In 2019/20, the Government of Rwanda allocated FRW 310.2 billion to the education sector, up from FRW 278.2 billion in 2018/19, reflecting an increase of 11.5 per cent in nominal terms or 10.4 per cent in real terms. The study adopted Cobb-Douglas production function with rate of returns being constant to scale where human capital is treated as an independent factor of production in the human capital augmented growth model. Data that exists from the National Institute of Statistics Rwanda for a period 1999 to 2019 reports. The results revealed that human capital plays an important role in economic growth mainly as an engine for improvement of the output level. There is compelling evidence that human capital increases productivity, suggesting that education really is productivity-enhancing rather than just a device that individuals use to signal their level of ability to the employer. The variables were significantly fit the model as it was shown by the R 2 Adjusted –higher than 55% which shows strong goodness of fit in the short run estimated model. As conclusion since there was no problem of multicollinearity the goodness of fit is achieved. The study concludes that education has positive effect on economic growth. The study recommends that the government of Rwanda should encourage the citizen to engage in education. The government of Rwanda might do this directly by supporting infrastructure, small farmers, building schools in order to resolve those problem and external aids have significant on economic growth. Keywords: Education, Human Capital, Economic Growth, Cobb-Douglas Function , Rwanda CITATION: Rwigema, P. C. (2020). Impact of education on economic growth. The case of Rwanda. The Strategic Journal of Business &amp; Change Management , 7(2), 490 – 512.
A Brief Study on the Fake Review Detection methods on Ecommerce Websites using Machine Learning, Artificial Intelligence, and Data Science

Abstract: Customer reviews play an important role in influencing purchasing decisions on ecommerce websites, which are becoming increasingly popular for online shopping. The appearance of phoney reviews, on the other hand, might have a substantial impact on the credibility and dependability of these platforms. As a result, fake review identification has developed as a significant study field, with machine learning, artificial intelligence, and data science techniques emerging as promising approaches to solving this issue. In this review paper, we present a complete overview of the most recent strategies for detecting fraudulent reviews on ecommerce websites, with a focus on the use of machine learning, artificial intelligence, and data science. We evaluate the usefulness of several approaches, such as feature-based, behaviour-based, and deep learning-based techniques, in detecting false reviews. We also discuss the obstacles and future directions in fake review detection research, including imbalanced datasets, adversarial attacks, multimodal fake reviews, real-time detection, explainability, ethical implications, and domain knowledge incorporation. The goal of this review article is to provide a thorough overview of the present research environment in false review identification on ecommerce websites utilising machine learning, artificial intelligence, and data science, as well as to guide future research in this area
Application of Metaverse and Its Underlying Challenges in the 21st Century

With the advancement of technology, the concept of the Metaverse has risen in the twenty-first century. Emerging technologies like artificial intelligence, blockchain technology, and others have made a significant impact, particularly after the onset of the COVID-19 pandemic. This study focuses on the various applications of the Metaverse in different fields. It is observed that the Metaverse is now being widely used in areas such as environmental sustainability, urban resource management, smart city planning, and legal frameworks. Many businesses are rapidly increasing their investment in the Metaverse. Notably, cities such as Singapore and South Korea have provided examples of leveraging digital technology after the pandemic in the provision of public services. The study acknowledges that, despite the benefits and advantages, the Metaverse presents some issues such as privacy concerns, an increase in greenhouse gas emissions, data storage concerns, and potential imitation of behavior at the virtual level. Therefore, it is crucial to address these issues and establish proper guidelines for the ethical and responsible use of the Metaverse technology.
Security, Ethics and Privacy Issues in the Remote Extended Reality for Education

The adoption of Extended Reality (XR), an umbrella term for augmented, virtual, and mixed reality, has grown over the last few years. But this adoption has been accelerated with the impact of the pandemic, which has demonstrated the value of this technology as future of learning technology. As a result, XR is becoming a popular solution to facilitate remote learning, remote conferences, and remote working. To mitigate the problems of remote learning, a trend is emerging among authorities to emphasize the potential for new technologies such as artificial intelligence and virtual, augmented, or mixed reality to create engagement, providing a kinesthetic aspect of learning and addressing students’ attention problems. XR with wearable devices can make the learning process more productive and even more interesting. Despite the fact that remote learning with XR offers several interesting educational advantages as compared to in-person classroom environments, it has its own downsides that have not been addressed in previous research and considerable research gaps remain in this area. When these devices are used in public places, they can infringe on other people’s rights as well. As for security concerns, the more we live our lives online and virtually, the more vulnerable we can become to hackers. These privacy and security risks include input and output data, user interaction data, and identification of both the user and devices. This chapter addresses these ethics, security, and privacy-related issues in line with XR in education. In the broader view, this chapter will focus on a better understanding of the human value of XR for learning purposes in the remote setting with responsible design.
Blockchain in banking: a study on central bank digital currency

The banking sector has been greatly impacted by the technological outburst of the twenty-first century. Bitcoin, the first crypto asset created on block chain technology, has firmly established itself in the financial sector since its introduction in 2009. The market capitalization of uncontrolled crypto assets has grown at an unprecedented rate, posing a threat to the banking industry and the economy. Illegal activities such as terrorist funding and money laundering find refuge in the unregulated world of crypto assets. To keep up with the demands of the computer-savvy Generation Next, banks worldwide have adopted various technologies and improved their service standards. However, central banks continue to follow the traditional system of issuing hard currency bank notes, which do not match the aspirations of most end users. As a result, Central Banks worldwide are currently brainstorming the introduction of a Central Bank Digital Currency (CBDC). This study aims to explore the theoretical aspect, feasibility, and status of CBDC. Four Central Banks have already issued CBDC, while others are in the process of doing so. Block chain under Distributed Ledger Technology is the most suitable and widely accepted platform for issuing CBDC. Robust computer security measures must be established to prevent hacking and ensure monetary stability for CBDC. During the initial stages of CBDC implementation, hard currency banknotes and CBDC will run parallelly until any possible initial hiccups are resolved. CBDC has the potential to boost banking and finance, trade finance, and cross-border international settlements.
Using Digital Resources in Geometry Lessons

In this paper, examples of the use of digital resources in geometry lessons are considered. The aim of the study is to solve the problem of using digital educational resources to activate students’ thinking, increase their interest in learning geometry, improve their ability to memorize new concepts, and activate their own self-learning skills. The study used such scientific methods as observation, questionnaire and analysis. Based on the analysis of the questionnaire results, conclusions were drawn about the need to study geometric concepts using digital resources, competently combining them with traditional teaching methods.
SISTEM REKOMENDASI PERJALANAN WISATA BERBASIS EXPERT SYSTEM DAN ALGORITMA GENETIKA

The development of tourism cannot be separated from the use of E-Tourism technology as a medium for disseminating and promoting tourism information through the media of certain sites. The existence of these sites is still considered static and simple. Site providers are considered not prioritizing responsiveness and interactivity to users. Users need a system that is able to respond and iteratively is able to provide recommendations for the needs of tourists personally. The problem of responsive and interactive concepts on tourist sites has been tried to solve previously through several previous studies. These studies have given good results. However, the implementation of the previous methods is seen as still having weaknesses. For example, it has not been able to meet the personal aspects of the specific tourist needs. considering that each tourist has different characteristics. Seeing these problems, the researchers developed a system that is able to provide a travel recommendation by combining the Genetic algorithm and the Rule Base Expert System (RBES). Users are given a recommended travel route based on the location and time that is suitable by the Genetic algorithm. Furthermore, RBES is tasked with perfecting the results of these recommendations by adjusting them to tourist characteristics. The results of the combination of the two methods show that the improvement of the route and travel time can be improved personally by RBES in accordance with the characteristics of tourists.&#x0D; Keywords: E-Tourism, Genetika, Rule Base Expert System, Recommendation System&#x0D;
Exploring Employees’ Computer Fraud Behaviors using the Fraud Triangle Theory

Background: Employee computer fraud is a costly and significant problem for firms. Using the fraud triangle theory, this study explores the extent to which an employee’s perception of opportunity, rationalization, and work pressure will contribute to their likelihood of committing computer fraud (i.e., intentional, malicious, or while motivated through a self-interest gain of information systems (IS) security policy non-compliance behaviors). Method: A model is proposed and empirically validated through survey data collected from various industries from 213 computer-using employees with financial responsibilities within their organizations in the U.S. Results: This study’s findings suggest when individual employees experience high levels of work pressure, they may be more likely to commit computer fraud. Organizations can guard against this behavior by monitoring their employees’ assigned workload and performance expectations to prevent these unwanted behaviors. This study demonstrates a need for future research to investigate further the motivations employees may have besides financial greed when committing different types of computer abuse behaviors. Conclusion: This study, based upon the fraud triangle theory, empirically reveals the importance of monitoring general work pressure to guard against employees committing computer fraud behaviors. Computer fraud behaviors should be considered a distinct type of information security violation behavior.
A Survey on UAV Applications in Smart City Management: Challenges, Advances, and Opportunities

Smart management of urban space is an important way to achieve the goal of sustainable urban development. Unmanned aerial vehicles (UAVs) have been widely used in urban space management work and have greatly improved the level of it. UAV technology assisting urban space management involves many technical details and has generated a number of problems. Therefore, a systematic review of the applications of UAVs in urban spatial management work is very necessary and can provide a comprehensive reference for relevant researchers. This is conducive to the generation of more new insights, methods, and applications. However, according to our research, there is a lack of relevant systematic investigation. We screened and researched a large number of relevant literatures (about 230) with the help of search tools such as Web of Science and IEEE Explore, and combined with our own working experience to review and summarize the field in an all-round way. Taking the definition, needs, and challenges of urban spatial management as an entry point, this paper systematically summarizes the task flow, working paradigm, technical system, and application direction of UAV-assisted urban spatial management. It also takes our recently developed UAV urban management system as an example to provide an introduction on how to integrate advanced technologies such as UAV and artificial intelligence. Finally, this paper summarizes several concluding findings and proposes several future research directions. The research in this paper shows that UAV technology has already played a great role in urban spatial management work, but it is still far from realizing automation and intelligence, and it needs to continue to make efforts in terms of methods, systems, applications, and policies. In order to achieve these goals, UAV technology can be further integrated with advanced technologies such as deep learning, more types of UAV industry applications can be carried out, more functional UAS can be developed, and better management policies can be formulated.