Reviewerly/exHarmony huggingface dataset:
Psychometric Properties of an Instrument to Evaluate Students’ Perception of Learning Objects in Statistics

Digital Learning Resources (DLRs) have the function of facilitating learning; however, the evaluation regarding their functionality is limited since there are few tools for this purpose. Of these, the instrument that stands out is “Perception of the use of Digital Learning Resources in Statistics” (IPDLR-S), which allows for evaluating the perception of undergraduate university students about the functionality of the LDRs. With the objective of providing a tool with scientific quality, the IPDLR-S instrument underwent to an analysis of construct validity and reliability. The instrument was applied to 1,148 university students, the construct validity analysis was performed using an exploratory (EFA) and confirmatory (CFA) factor analysis, and the reliability was determined by ordinal Cronbach’s alpha. According to the EFA, it was found that all the items are represented in the factorial model; however, differences were found for the theoretical model since a fourth dimension emerges (Cooperative Learning). On the other hand, using the CFA, the resulting factorial model showed a good fit (GFI = 0.999, RMSEA = 0.064, CFI = 0.999, and TLI = 0.999). Overall reliability, as well as by factor showed an optimal value (ordinal Cronbach’s alpha &gt; .98). The IPDLR-S instrument has adequate psychometric properties.
A new age of cyber: transitioning from security to safety

As we shift further and further into the digital realm, the threats that face us are outpacing even the most aggressive digital transformation efforts. For businesses, tackling security is no longer a matter of making IT systems more robust – it is about the safety of the entire organisation.
Decentralized Finance: Safety and Security

Over the past couple of years, DeFi has been growing at a rapid pace. As of January 2022, it is estimated that there are more than USD 237 billion worth of digital assets combined into DeFi projects. There has been a continuous growth of the DeFi movement since the beginning of 2020, and it is most likely that this growth will be sustained in the future. It is becoming more evident that regulators are increasingly aware of DeFi and its rapid growth. Because of this, there are sporadic efforts aimed at creating regulations that will govern the use of DeFi by existing and future participants. In this section, we provide an overview of the potential risks and security concerns that come with DeFi as well as elaborate on the regulatory context in the European Union. In the context of blockchain technology, it is important to remember that since it gives more power to individuals as opposed to companies or other regulated intermediaries such as banks, there is a greater need for responsibility within the network. DeFi risks can be classified into four different types, namely financial risks, technology risks, procedural risks, and regulatory risks.
Decentralized Finance: Technical Basis

In this chapter, we take a close look at the technology that makes the concept of decentralized finance (DeFi) a reality. We provide insights into the technical mechanics of DeFi and its environment in order to gain a better understanding of the development process of the DeFi ecosystem. We discuss the uses and value of blockchain technology, under which we elaborate on distributed ledger technology and its pioneering role in facilitating DeFi instruments. We discuss the implications of blockchain technology as well as that of Ethereum’s ecosystem in the financial market and explain how these together can create a significant transition—in other words, a disruption—of the overall economic and financial system as we know it today.
An Investigation on the Legal Protection of Cryptocurrency Investors, Comparative Legal Analysis

Millions of people, individuals, companies and other entities invested tremendous money in different cryptocurrencies worldwide. Many reports issued by regulators in many countries worldwide indicate a lack of reliable information clarifying the legal status of cryptocurrency products and the regulatory protection given when offered in the local market. However, the legal protection in some jurisdictions requires regulators to approve crypto assets-related products when introducing them to the market. In contrast, in others, it is proposed that a regulated financial institution like banks can endorse the approval of the cryptocurrency before its introduction to the market. It is worth noting that prudential regulation and conduct do not exist in many jurisdictions, which means that investors’ funds do not enjoy the protection provided to financial products and services such as e-money or online brokerages. Plenty of Crypto-asset are offered for selling in many jurisdictions; hence, it becomes almost impossible to bring them under specific regulations or even to place an effective monitoring system. One of the main reasons behind this is that cryptocurrency companies’ headquarters carefully select their firms’ locations in flexible jurisdictions for the regulations, taxation and legal systems. Therefore, most cryptocurrency trading transactions are carried out through firms and institutions primarily functioning in offshore registered financial entities. Furthermore, although cryptocurrencies are traded and exchanged in different countries, many lack the legal or regulatory framework to deal with related activities. Even though some jurisdictions require cryptocurrency activities to be registered or obtain a low authorization level, the purpose of such regulations is limited. Therefore, inadequate or non-existent regulatory instructions can negatively impact legal protection and enforcement. This paper investigates the legal risk imposed on cryptocurrency traders and explores the level of attention provided to regulatory, monitoring and supervision of legal and financial conduct worldwide. Furthermore, it will critically assess the capabilities and willingness of the current jurisdictions to address the issues concerning the legal complex facing the investors. It further examines the level, extent and context of legal protection frameworks given to cryptocurrency investors in different jurisdictions.
Impact of Applying Kaizen Approach on Financial Performance in Light of Digital Transformation

This study aims to identify impact of applying Kaizen approach on Financial Performance in light of digital transformation in Jordanian industrial companies (JIC) listed at Amman Stock Exchange (ASE). In order to achieve study objectives, an analytical descriptive approach was followed, a questionnaire developed by researcher to measure Kaizen approach and digital transformation, meanwhile, financial performance was measured by (ROA and ROE). Where 150 questionnaires were distributed to sample members, and number of valid ones for analysis was (109), representing (72.7%) of study sample. Study population consisted of (34) companies, and study sample was limited to (30) companies within financial period (2010–2020). Findings showed that there is an effect at significance level (α ≥ 0.05) for applying of Kaizen approach on ROA and ROE in light of digital transformation in JIC listed at ASE. Study recommended necessity of encouraging employees of industrial companies listed at ASE.
Analyzing the Relationship Between Using Modern Digital Technologies (MDTs) and Financial Performance (FP) of Jordanian Telecommunication Companies (JTCs)

Due to the impact of global digital transformation on various aspects of business, this study aimed to analyze the effect of using modern digital technologies (MDTs) on the financial performance (FP) of Jordanian telecommunication companies (JTCs), and to explore the demographic characteristics (DCs) that enhancing this relationship. To conduct this study, the descriptive analytical approach was used to collect and analyze data. Accordingly, a questionnaire was designed and distributed to HR and IT managers in the five telecommunications companies (TCs) operating in the Jordanian business environment (JBE). In addition, financial reports of companies were used to extract the FP. All questionnaires retrieved and were analyzable. To test hypotheses, the multivariate regression analysis was used. The results showed that there is a statistically significant effect of using MDTs on the FP of JTCs. In addition, the results indicated that DCs of companies, especially capital size and digital maturity (DM) of employees, have a significant mediating effect on the aforementioned relationship. Accordingly, the study recommended JTCs to keep a close eye on the latest digital technology developments in the telecommunication services field, to invest these technologies in improving their FP. In addition, JTCs are recommended to focus on developing employees’ digital skills by involving them continuously in training courses, seminars and related conferences.
Analysis of Credit Cards Fraud Detection: Process and Techniques Perspective

Credit card fraud detection is the process of identifying and preventing fraudulent transactions before they can cause financial damage. This involves using advanced algorithms and machine learning techniques to analyze transaction data in real-time and detect patterns that may indicate fraudulent activity. Effective fraud detection systems are essential for ensuring the security and integrity of the credit card payment system, protecting both financial institutions and cardholders from financial losses. The main objectives of this study are to explain the process and techniques. This study analyzes a global dataset of credit card transactions using regression analysis and artificial neural networks. A regression research found that new balance origin, new balance destination, old balance origin, transaction type, and amount all statistically effect fraud transactions, while old balance destination and transaction length do not. This study used artificial neural networks to identify credit card fraud detection properties. According to the statistics, Old Balance locations are most importantly considered for credit card fraud. This study shows that the models can detect fraudulent activity using real credit card transaction data, providing significant insights into credit card fraud detection approaches.
Impact of Cash Flow Statement Elements on Financial Performance: The Mediating Role of Capital in Private Hospitals in Jordan

The study aims to test the impact of the elements of the cash flow statement on the financial performance of private hospitals in Jordan. The study sample includes (5) private hospitals for the period between (2016–2020), with a capital of more than fifteen million JD. The path analysis method is also used, through the Structural Modeling Program (Smart PLS) in order to achieve the study’s objectives and answer the study’s hypotheses. This study finds, there is an impact of elements of cash flows of operating, investing, and financing activities on the financial performance measures through (liquidity ratios, financial leverage, and profitability). Also, there is an impact of cash flows of operating activities, on the volume of capital in private hospitals. The study recommends decision-makers to pay attention to private hospitals of the elements of the cash flow list and manages it efficiently. The capital is taken into account when evaluating the financial performance of private hospitals. Finally, the study recommends to conduct the study variables on other sectors, such as the financial sector, industrial sectors, and other service sectors to understand how the elements of their cash flow affect performance.
The Role of Social Media on Marketing Entrepreneurial Projects in Jordan: A Field Study

The study aimed to identify the role of social media sites in marketing entrepreneurial projects in Jordan. The study was applied to the owners of entrepreneurial projects in Jordan, and it was represented in the dimensions of the independent variable (social media) as follows (Facebook, Twitter, Snap chat, and Instagram), and the dependent variable is the marketing of entrepreneurial projects. The study relied on the analytical descriptive approach in the procedures. It concluded that social media have a statistically significant role in marketing entrepreneurial projects, and that role is considered positive and influential as it contributes to the dissemination and development of entrepreneurial projects. Facebook has the most influential role in marketing entrepreneurial projects. The study recommended the need to diversify the content to suit the nature of commercial advertisements.
Legal Protection of Digital Works from Attacks in Cyberspace

The purpose of this research paper is to examine the role of legislation in regulating intellectual property rights in the digital age, and ensuring that all internet users have access to information in the digital environment. The widespread use of digital works in cyberspace has led to various forms of infringement, and the study aims to determine the extent to which Jordanian legislation is aligned with international conventions to provide legal protection for digital works. The research analysed the Jordanian legislation and found that it is up-to-date with modern developments in protecting against cybercrimes and copyright infringement. Based on these findings, the study suggests several recommendations, including the need for the Jordanian legislator to establish a specific legal framework for digital works and their protection, leveraging modern technological advancements.
The Impact of Applying Electronic Internal Auditing in Raising the Efficiency of Financial Performance in Jordanian Commercial Banks

This study aims to identify the impact of applying electronic internal auditing in raising the efficiency of financial performance in Jordanian Commercial Banks. In order to achieve the study objectives, the analytical descriptive approach was followed. A questionnaire consisting of (19) items was developed to measure the electronic internal auditing. A number of (168) questionnaires were distributed among the internal auditors and accountants in these banks, and the number of questionnaires valid for analysis was (137), representing (81.5%) of the study sample. The financial performance was measured by (RoA, RoE and EPS) for (13) banks within the financial period (2015–2021) Findings showed that applying electronic internal auditing reached a high level. Results also showed that there is a statistically significant effect at the significance level (α ≥ 0.05) for applying electronic internal auditing in raising the efficiency of financial performance with its indicators (ROA, ROE and EPS) in Jordanian Commercial Banks. The study recommended the necessity of holding workshops and specialized training programs periodically for auditors and accountants on electronic internal audit systems, to keep them acquainted with the latest in the field, and to help enhance the financial performance of these banks.
The Influence of Digital Strategic Orientation on Organizational Performance in the Manufacturing Jordanian

Increasingly, digitization is seen as a strategic approach for organizations to achieve organizational performance. However, to date, previous research has not provided sufficient evidence of how a company’s strategic attitude toward digitization relates to organizational performance. Thus, this research investigates relationship between digital strategic orientation and organizational performance. The building of the research framework was based on previous research and resource-based view theory, to test this framework using survey data of 107 manufacturing Jordanian sector, in Jordan context. Analysis output indicated a company’s digital strategic orientation has a positive and significant influence on organizational performance. Our findings recommend that executives can progress their company’s organizational performance and competitive advantage through increasing the Digital Transformation processes inside their organizations. Finally, we conclude practical implications for managers and policymakers with the necessitate of combining digitization with strategies.
Impact of Online Consumer Sales Promotion Tools on Customer Satisfaction: Evidence from Jordan

This study This study examines the impact of online consumer sales promotion tools on customer satisfaction among Zain Telecommunications Company customers in Jordan. Using a quantitative research design, data was collected through a self-administered survey from 500 Zain customers who had made an online purchase in the past three months. Multiple regression analysis was used to determine the relationship between online sales promotion tools (discounts, coupons, free samples, and loyalty programs) and customer satisfaction. The results indicate that online sales promotion tools have a positive impact on customer satisfaction among Zain customers, with discounts and loyalty programs having the most significant impact. The study provides valuable insights for Zain Telecommunications Company in Jordan, suggesting that effective use of online sales promotion tools can lead to increased customer satisfaction and loyalty. The findings of this study can also be beneficial to other telecommunication companies in Jordan seeking to enhance their online sales promotion strategies.
Effect of Advertising Elements on Facebook on the Mental Image of the Services of Jordanian Telecommunications Companies. (Case Study on the Customers of Umniah Company in Zarqa City)

This study aimed at identifying the effect of the advertising (commercial) elements through the Facebook on the mental image of the Jordanian telecom companies; case study on the customers of Umniah Company in the City of Zarqa. To achieve the study objectives, the researchers adopted the descriptive, analytic method. They developed an instrument to collect the data through a questionnaire, which was distributed through the simple, random sampling method over (700) customers of Umniah Company, who use the Facebook in the City of Zarqa, out of which (400) analyzable questionnaires were retrieved. The researchers further employed the convenient statistical methods applying SPSS 22 Program for data analysis. The study concluded many results such as: there is a statistically significant effect at (a ≤ 0.05) level for the commercial elements, collectively or severally, through the Facebook platform, in shaping the mental image of the services of Unmiah Company. Furthermore, the commercial elements through the Facebook platform interpret (75.2%) of the changes that take place in coining the mental image of the services of Umniah Telecom Company. In this concern, the intensives component is the most influential in the mental image with the customers of Umniah Company. Therefore, the study recommended the need to place further care by Umniah Telecom Company to the mental image formed by the customers through the company advertisements on the Facebook; particularly, the intensives and convenience variables due to their high influence in forming the mental image.
Evaluating and Detecting Fake Users in Social Media by Random Forest

Currently, users have been engaging in conversations, sharing information and producing web content via social media platforms. But in recent times, many users have been using these platforms to conduct identity faults, payment frauds, and many more without the knowledge of the actual user. For example: - On Instagram, according to the latest analysis, there are around 95 million fake accounts compared to the total number of users, which amount to 1 billion. Therefore, there are nearly 10% of fake accounts active at present. The obtained dataset lies approximately in thousands. Hence, we used GANs and deep learning to broaden the data to around 1 lakh. The conventional methods used for distinguishing between real and fake accounts were ineffective. Adopting machine learning-based approaches allowed us to identify fake accounts that can mislead users. The dataset is pre-processed using several Python tools, and a comparison model is created to identify a practical solution appropriate for the dataset that has been provided.
Cutting-Edge Technology and Blockchain: A Bibliometric Analysis (2017–2022)

This paper aims to analyze the Scopus-indexed English-language literature and apply the bibliometric methodology to show the reality of blockchain and cutting-edge technology intellectual structure and emerging trends from a large quantity of data between (2017) and (2022). The bibliometric analysis, therefore, is applied to describe this domain’s evolution and structure, including co-authorship, bibliographical coupling, and co-citation. The findings demonstrate that China is the most relevant country, the Hua Zhong University of Science and Technology is the most pertinent institution, and the ACM international conference proceeding series is the most applicable source. This paper mainly contributes to the existing literature by identifying the benchmark authors, locations of blockchain and cutting-edge technology, and journals, summarizing the most cited papers, and classifying the research classes of research streams in cutting-edge technology and blockchain, namely: blockchain, cutting-edge technology, and artificial intelligence, demonstrating the future upcoming trends.
An Effective Pipeline for Depth Image-Based Hand Gesture Recognition

In this paper, a pipeline for hand gesture recognition from depth images is presented. This depth-based image recognition system is capable of recognizing gestures with challenges like varying depths, complex backgrounds, and variation in view point, hand pose, and appearance. Firstly, we obtain a grayscale image from the depth map, segment the hand region, and perform orientation normalization and feature extraction, which is followed by classification. Two different sets of feature descriptors are extracted: Multi-Radii Circular Signatures (MRCS) and Multi-Scale Density (MSD). Different classifiers have been used to demonstrate the efficacy of the suggested pipeline. Overall accuracy of 98.90% (MRCS) and 99.78% (MSD) is obtained using the MLP classifier.
Using postural data and recurrent learning to monitor shoplifting activities in megastores

Summary Recently, researchers have placed a great deal of emphasis on modeling activity patterns to better understand human behavior. Several approaches have been researched so far to develop automatic human activity recognition systems that infer detailed semantics from visual images, aiming to understand real human behavior patterns. However, there is still a need for a cost effective solution to distinguish human actions in the real‐world environment. With this encouragement, a novel approach is proposed to recognize shoplifting acts by examining the posture evidence of the human being. This approach begins by obtaining the two‐dimensional pose reflecting human's body joints as a skeleton from the recorded frames. Subsequently, a preprocessing step is used to preprocess skeleton data, which can handle the occlusion too. Postural feature generation is then used to extract pertinent features from such preprocessed skeletons. Finally, feature deduction is performed to downsize the derived features to a smaller dimension, and activity classification is performed on such reduced features to identify shoplifting behaviors in real time. A synthetic shoplifting dataset and real store recorded videos are used to conduct the experiments, the findings of which appear more promising than those obtained using other cutting‐edge methods, with an accuracy of 97.36% and 91.66% for synthesized and real store recorded inputs.