Reviewerly/exHarmony huggingface dataset:
The Use of Encryption to Preserve the Privacy and Security of Electronic Health Records

Cloud computing is the storage of data over the Internet rather than locally on a user's device, and it is one of the most extensively used applications of computers and related technologies in today's world. Since cloud computing became publicly available, its popularity has risen. End customers may be able to obtain a better application that is more convenient, less expensive, and both effective and efficient because of cloud computing. When storing and managing sensitive data, it is critical to select a storage and management solution that provides security and privacy safeguards. Patients have long been maintained on the cloud, but the data has always been protected by ciphertext encryption. One of the most challenging challenges in a cloud computing environment is the need to protect users' online activities as well as their personal information. The healthcare system was created with the intention of addressing the demands of medical practitioners by providing a solid foundation, simple means to obtain patient information, and efficient ways to use the system. This work describes, with implementation details, an innovative approach for establishing a reliable and effective e-health cloud model employing identity-based encryption. This approach is suggested in this article. The time, power, and energy requirements for encryption and decryption of the suggested strategy were estimated and compared to those of the currently used method. It has been demonstrated that the cryptographic approach presented can reduce the time required for data decoding by up to 50%. Because the decryption process is quicker, the cryptographic procedures may be conducted with less power.
How Blockchain and IoT Affect Project Risk Management

This study examines the impact of blockchain technology and IoT on project risk management. Blockchain and the Internet of Things (IoT) provide the platform that project managers use to mitigate risks. The objectives of the study are to explore the impact of blockchain and IoT on managing the risks during project planning, execution, implementation, and closure. Therefore, the study identifies the opportunities that project managers have to optimize their project risk management. The study uses a structured questionnaire and interviews with a sample of 30 respondents to understand the correlations between variables. The findings show that businesses use IoT and blockchain technology platforms to create risk mitigation plans and implement and periodically update the project management tools. The study concludes that blockchain IoT enables stakeholders to meet the changing preferences under risk management.
Factors Analysis Affecting Academic Achievement of Undergraduate Student: A study on Faculty of Information Technology Students at Applied Science Private University

The analysis of students’ educational achievements at a university is beneficial for the university, society and students. This study aims to search for the various attributes related to academic student’s achievements. The subjects of the study were 3509 graduated students at the Applied Science Private University in Jordan from all department programs of the Faculty of Information Technology. The study is intended to analyze students profile and find its relation to and association with their university GPA (Grade Point Average) by selecting four main attributes related to the students: department, secondary certificate grade, secondary certificate city, and gender. Then it is intended to find the high effecting value for each attribute, and create main association rules through using data mining classifier like (Decision tree, naïve bayse and association rules). Finally, the result of this study may help current and new faculty students to predict the possible obtained GPA to control their performance and try to enhance it.
The Growing Importance of Modern Technology in Education

Technology is the blessing of God. It includes the production and utilization of technological tools and their interaction with society, the environment, and various domains of human activity. The impact of technology on society has been profound, influencing civilization, art, and science. The role of technology in our daily lives is essential, providing solutions to complex problems and simplifying processes that would otherwise be challenging. Technology has transformed education, making it more accessible, efficient, and effective. This study seeks to explore the significance of technology in modern education, examine various technological tools, and evaluate their benefits for students.
User Feedback based Trust Analysis in Cloud Computing using Machine Learning Approach

Trust on cloud services is a serious concern regardless of the increasing deployment and utilization of mission critical applications, which continues to obstruct users from complete implementation over cloud platforms. End-users need to be confident of different service parameters on the cloud deployment. Available solutions for trust modelling are either outdated, lack several details or are specific to limited cloud structures. This work presents neural network based approach to classify trust based on customer feedback on any cloud platform to improve selection and adoption of cloud computing resources. The results of the evaluation show that the proposed model offers reliable results for classifying trust of any cloud services based on the feedback of existing customers. This work further propose a generic way that can be used to preprocess multi attributed dataset of trust management and it confirms that consumer feedback is a worthy way to review the overall reliability.
Factors Affecting the Adoption of Amazon Web Services in Government Institutions in Jordan

In an economic recession, cloud computer infrastructure will play an important role in public organizations and the private sector, as it reduces, in addition to providing many other advantages, the expense of accessing information technology (IT) software. In public sector organizations, cloud computing is currently not widely used, particularly for Jordan for several reasons and factors. The objective of this analysis is to recognize and understand these variables that could influence the adoption of cloud computing in the Jordan government industry, to understand the theoretical context of this issue through the proposal of a conceptual model, and to assist and direct Jordanian government organizations in implementing cloud computing in practice. This study employed a hybrid methodology approach consisting of two steps of data collection and analysis. The first phase of the online survey was based on the literature survey and technically performed. Descriptive and one direction frequency statistics, inferential analysis and regression analysis have been used for the quantitative analyses of the results. 19 theories have been tested. The quantitative data were analyzed to detect factors which can influence the adoption and the importance of cloud computing. To engage in this study four Jordanian organizations have been selected. Thematic interpretation of the results was used to analyses them. The considerations studied were divided into three major categories: the organizational and technical background, environmental and external constraint and the advantages perceived. In addition to this, the study found a theoretical model that does not address the influences and challenges of the adoption of cloud data and proposes a new concept model to improve understanding of these facets by conducting a comprehensive literature survey which would lead to the identification of possible factors that could influence the introduction of cloud computing.
Blockchain and Edge Computing Integration Boosts Scalability and Reduces Latency

Nowadays, the integration of blockchain and edge computing has become important in computer science due to the significant advantages it can bring to a range of real-world applications. By combining the strengths of both technologies, it is Combining the strengths of both technologies makes it possible to create a highly secure and reliable network with reduced latency and efficient transaction processing. This article explores the challenges and opportunities of combining these two technologies, including the scalability barrier of blockchain and the management and security challenges of edge computing. This paper discusses some of the theories and research challenges associated with this integration, including developing efficient consensus algorithms and enabling data sharing and provenance. this paper concludes by highlighting the potential benefits of this technology in the field of medicine and healthcare, finance, supply chain management, and Internet of Things.
The Effect of Virtual Reality and Augmented Reality on Managing Projects

This report highlights how digital disruption and transformation have affected project management. Amazon was selected as the organization, and project management was chosen as the industry. Primary research-based open-end interviews with thirty project managers and secondary research based on a review of past literature were conducted to perform this study. It was found that digital disruption has occurred in the project management industry, which has modified the behaviors, needs, and expectations of people in society, the market, and the industry. It was found that virtual reality (VR) and augmented reality (AR) has disrupted the project management industry. The AR caused a shift in the consumer (sponsor/client) wants in the project management industry. Customer derives the demand want from. Therefore the businesses and their competitors’ activities are modified to adapt the AR and VR-based technologies. AR and VR reduced the project managers’ efforts, time, and resources. Moreover, the metaverse is another technology that will cause significant digital disruption and digital transformation in the project management industry.
The Role of Technology of Mind Mapping on Internal Auditing in Risk Management: Evidence from Jordanian Commercial Banks

The study aimed to examine the tole pf technology of mind mapping on internal auditing in risk management for commercial banks listed on the Amman Stock Exchange. Internal audit was measured by (professionalism, independence, transparency and disclosure, and adherence to professional standards). In order to deal with the problem of the study and achieve its objectives; descriptive and analytical approach was adopted. The study population consisted of (13) Jordanian commercial banks, after developing a questionnaire as a tool for the study, the researcher was able to distribute it to (13) banks, where (156) questionnaires were distributed to employees, managers, and department heads works in internal audit and risk management departments in Jordanian commercial banks, (121) questionnaires were retrieved, after excluding incomplete questionnaires, the final total was (108) questionnaires.The study found a set of results, the most important of which is the existence of a statistically significant impact of internal auditing, measured by (professional competence, independence, transparency and disclosure, adherence to professional standards) on risk management in Jordanian commercial banks.The study came out with a set of recommendations, the most important of which commercial banks should pay attention to the internal audit department by determining the nature of internal audit services and its activities in a documented manner to increase its professional competence, and to provide the largest possible amount of independence for the internal audit department in order to enable it to perform its duties in the required manner, and to disclose all Important information obtained by internal auditing in a fair, honest, and truthful manner.
A Decade of Studies on Cyber Security Training in Organizations using Social Network Analysis: A Systematic Literature Review Through Keyword co-Occurrence Network

In recent years cyber security training has become crucial to all organizations in order to be compliant with regulations and remain competitive in the market. To understand how vulnerabilities due to lack of employee awareness can be avoided and how organizations can provide useful training, a scientific systematic review is conducted. While traditional systematic review studies focus on analyzing publication trends, country of publication, or author affiliations, this research performs a systematic review of the field by mapping the existing state of research based on topic clustering and social network analysis. Network analysis using keyword co-occurrence is deemed to be advantageous as it enables identification of research themes and how they have evolved. The systematic review follows a four step process: data collection on cyber security training from the Web of Science database; data filtering to avoid duplicates and identify the core papers; network analysis creating the co-occurrence networks using these papers; and analyzing the patterns among key words that emerge in the literature. This research reveals the trends of core topics on cyber security training in organizations. By using the quantitative and rigorous research approach for conducting a systematic review of cyber security training in organizations in the cybersecurity field, this research contributes to filling the gap on cyber security training review. The findings highlight the trend towards adopting immersive technologies that provide insight into the employees’ cyber behavior before developing effective training.
Data Analytics Monetary Crisis Impact on Legal Instruments: A remedy role of the Unjust Enrichment Theory: Case of Lebanon

The study analyzes the impact of the monetary crisis on legal instruments that has affected Lebanon since August 2019, using concrete examples from daily transactions. It explores the relationship between the crisis and both creditors and debtors new applied methods. The study investigates how new practices designed by creditors and debtors because of the crisis, have affected some of the Lebanese legal instruments whether regarding their role, or with respect to their legal elements specified in law. The paper tested two hypotheses: first, that the crisis has had an impact on legal instruments; and second the role of the legal theory of unjust enrichment as a remedy to the said impact. The methodology of the study is based on secondary date as the study is theoretical basis. The results reveal that the crisis has created critical imbalance between the creditors’ and the debtors’ rights and obligations, due to the absence of new laws to enable Lebanese judges to interfere in the contract and restore the said balance between the contractual parties' rights and obligations as recently applied in other countries. As a result, the study attempts to assess if the theory of unjust enrichment can be used to serve as a legal remedy to compensate creditors subject to injury resulting from the current legal position, which prohibits them from refusing debtors’ payments made in Lebanese pounds (LBP) as per the low official exchange rate. The results show that this theory can be applied in the case of some legal instruments which have been affected by the crisis.
Incorporating Data Analytics into Accounting Curricula: The Case of Jordanian Universities

There is a growing recognition of the importance of analytics and big data in the accounting profession and a need for undergraduate accounting programs to better integrate these technologies into their curriculum. To find out degree to which undergraduate accounting programs in Jordanian universities have embraced analytics and big data into their curricula, this research looks at how and where data analytics and big data have affected undergraduate accounting education in accordance with the data analysis abilities that accountants need. The results show that accounting programs have not fully embraced analytics and big data. Additionally, only five accounting programs have developed a set of curricular components that offer the proper level of learning of data analytics and big data. Such a result emphasizes the need of more research to determine the best way to effectively implement these changes in the accounting education system of Jordanian Universities.
SaaSyML: Software as a Service for Machine Learning On-board the OPS-SAT Spacecraft

The SaaSyML app developed for the OPS-SAT spacecraft provides open access to on-board Machine Learning (ML) capabilities that an experimenter can interact with via RESTful Application Programming Interface (API) endpoints. The app's architecture follows the successes of Software as a Service (SaaS) in modern Web-based software engineering and implements the “as-a-Service” model, thus introducing the concept of Satellite Platform as a Service (SPaaS). An experimenter app on-board OPS-SAT can subscribe to SaaSyML's training data feed and pull measurement, telemetry, and housekeeping data from any of the spacecraft's instruments or its on-board software datapool. The ML features provided by the SaaSyML app cover both training and prediction operations. The Java Statistical Analysis Tool (JSAT) open-source java library for ML is used thus unlocking access to over 100 training algorithms on-board a flying mission. Past experiments have successfully implemented ML on-board OPS-SAT but have yet to offer any comprehensive re-usability. SaaSyML's service-oriented approach spares the experimenters the complexities of having to implement their own data provisioning and ML solutions so that they can focus instead on expanding the field of experimentation and use-cases for applied ML in space. A further novelty is also introduced with a plugin design for an software extension mechanism that allows experimenters to inject custom code to address ML needs specific to their experiments (e.g. calculating target labels/classes during supervised learning training operations). SaaSyML is developed using the Eclipse Vert.x event-driven application toolkit that runs on the Java Virtual Machine (JVM). This design choice introduces event-driven software engineering and practical use of the spacecraft dual-core payload computer and Linux environment. SaaSyML is a reference in embracing and leveraging multi-threaded and multi-core software design for space applications. This translates to non-blocking ML training and prediction operations running in parallel while multiple experimenter apps interact with the service. SaaSyML demonstrates how a more capable space-grade processor enables a paradigm shift towards developing more sophisticated client facing space software with reduced development complexity, effort, and cost.
A-ATMChain: Blockchain-based Access Control Method for Air Traffic Management

As an important infrastructure to ensure the security and development of civil aviation, the main goal of air traffic management (ATM) system is to guarantee the sharing and security of ATM data. However, the contradiction between ATM data sharing and privacy protection has hindered the development of ATM, resulting in data silos that are difficult to solve. Access control technology, as one of the crucial information security assurance technologies, can strongly balance the dilemma faced by ATM and promote its secure operation. In this paper, we propose an ATM-oriented access control method (A-ATMChain) that addresses the issues of fine-grained control of ATM data, data traceability and confidentiality protection. The method takes advantage of the unique traceability, tamper-evident, and smart contract of blockchain, in order to achieve secure, convenient, autonomous and fine-grained access control in ATM environment by reforming attribute-based access control (ABAC). The whole design framework and operation flow of the access control solution are presented, as well as the five algorithms implemented by smart contract in the scheme. In addition, the security of the scheme is analyzed. The scheme is proposed for smart ATM in the background of smart transportation, which will contribute to improve the security, reliability and scalability of ATM business operations and provide reference for future design and research of ATM information security assurance systems.
Geodesic Based Image Matching Network for the Multi-scale Ground to Aerial Geo-localization

Airport surveillance activities using remote sensing images are challenging due to object variations largely affecting the geo-localization and object detection/segmentation tasks. Furthermore, the problem of localization is even larger due to scale variations. Traditionally image-based geo-referencing is accomplished by superimposing ground positioning system (GPS) location to the queried image. It is also observed both the query and the geo-tagged reference images are taken from the same ground view or aerial height in the case of remote sensing images. In our research, we intend to revisit the scale effect on object variability, by introducing the concept of geodesic representations along with image-matching networks. The architecture pipeline introduces a data processing layer wherein objects are geo-referenced to generate the metadata information. This metadata consists of three-dimensional data including the orientation information of the object. A regression task is added to the training set which leverages the metadata information. We use the gradient weighted class activation maps (Grad-CAM) to generate the activation maps and selection based on high threshold values for the pixel. The orientations and the locations are further calculated using the geodesic representations. The baseline architecture for local feature extraction uses a simple Siamese network with a ResNet backbone network. A NetVLAD layer is used to generate the global features. We also introduce a Geospatial attention network (GsAN) to aid in enhanced localization of objects. The dataset used for experiments consisted of CVUSA and our custom dataset providing airport runway views for different scales and arbitrary orientations. The performance evaluations focused on recall as a retrieval metric and comparing various loss functions. The performance metrics indicate a higher accuracy rate.
Sliding Window Neural Generated Tracking Based on Measurement Model

This paper presents the outcome of several machine learning techniques used for the task of bird/drone classification based on their tracks. Instead of using static images, the dynamics and features extracted from the trajectories captured in videos are used to provide a more accurate and reliable recognition task. Standard Machine Learning methods such as SVM and Random Forest are used for learning this classification. Features based on the kinematics, Gabor filter, and Gray Level Co-occurrence Matrix are utilized. Several comparisons and experiments based on benchmark data sets are shown.
The Emergence of Quantum Computing: Intellectual Property, Partnerships, and the Aerospace Sector

Quantum computing - the use of quantum phenomena to create a new form of computing - has been gaining intense interest and investment in recent years from the academic, government, and industry sectors for numerous applications, including astrophysics and aerospace. Several federally funded quantum computing research centers and programs targeted for space applications are active in universities and NASA space centers, as the space environment of low gravity, low temperature, and vacuum pressure are uniquely useful in space. In order to move toward commercial applications, important legal and business issues must be addressed, including the patentability of quantum computing, data ownership and protection, partnering, and private financial incentives. This paper provides a general overview of quantum computing and its potential applications in aerospace and astrophysics, with a focus on partnering, patentability, protection of data, and sponsored research implications between government, academia and industry.