A comparative evaluation of state-of-the-art cloud migration optimization approaches

Cloud computing has become more attractive for consumers to migrate their applications to the cloud environment. However, because of huge cloud environments, application customers and providers face the problem of how to assess and make decisions to choose appropriate service providers for migrating their applications to the cloud. Many approaches have investigated how to address this problem. In this paper we classify these approaches into non-evolutionary cloud migration optimization approaches and evolutionary cloud migration optimization approaches. Criteria including cost, QoS, elasticity and degree of migration optimization have been used to compare the approaches. Analysis of the results of comparative evaluations shows that a Multi-Objectives optimization approach provides a better solution to support decision making to migrate an application to the cloud environment based on the significant proposed criteria. The classification of the investigated approaches will help practitioners and researchers to deliver and build solid approaches

Critical success factors for ERP systems’ post-implementations of SMEs in Saudi Arabia: a top management and vendors’ perspective

Although numerous case studies have determined the critical success factors (CSFs) for enterprise resource planning (ERP) during the adoption and implementation stages, empirical investigations of CSFs for ERP in post-implementation stages (after going live) are in scarcity. As such, this study examined the influence of top management support and vendor support as CSFs on the post-implementation stage of ERP systems in small and medium enterprises (SMEs) established in the Kingdom of Saudi Arabia (KSA). A total of 177 end-users of ERP systems from two manufacturing organizations in KSA that had implemented on-premises ERP systems were involved in this study. Data gathered from structured questionnaires were analyzed using SmartPLS3 and SPSS software programs. The regression analysis was performed to assess the correlations among the variables. Out of seven CSFs identified from the literature, the impact of top management support was significant on user training, competency of internal Information Technology (IT) department, and effective communication between departments, but insignificant on continuous vendor support. Meanwhile, continuous vendor support had a significant influence on continuous integration of the system, but was insignificant on user interfaces and custom code. The study outcomes may serve as practical guidance for effective post-implementation in ERP systems. Referring to the proposed research model, ERP post-implementation success in KSA was significantly influenced by top management support, whereas continuous vendor support displayed a substantial impact on the continuous integration of ERP systems

Addressing Behavioral Drift in Ransomware Early Detection Through Weighted Generative Adversarial Networks

Crypto-ransomware attacks pose a significant cyber threat due to the irreversible effect of encryption employed to deny access to the data on the victim’s device. Existing state-of-the-art solutions are developed based on two assumptions: the availability of sufficient data to perform detection during the pre-encryption phase, and that ransomware behavior is static and does not change over time. However, such assumptions do not hold as data collected during the pre-encryption phase of the ransomware attack are limited and does not contain sufficient patterns needed to identify the attack. Additionally, the evasion techniques like polymorphism and metamorphism used by ransomware lead to behavioral drift that could defeat those solutions. Therefore, this paper addresses these two issues by proposing a weighted Generative Adversarial Networks (wGANs) technique. Firstly, the proposed wGAN was used to generate synthetic data that imitate the behavior of ransomware and simulate the evolution of the attacks. Then, the mutual information was used to estimate the significance of features for different timeframes, thereby helping the detection model to handle the behavioral drift in emerging ransomware variants. Experimental evaluation demonstrates that the proposed wGAN is more robust against behavioral drift compared to the state-of-the-art solutions. The wGAN achieved higher accuracy and lower false alarm rates of 97% and 0.0088 respectively

A Novel Explainable CNN Model for Screening COVID-19 on X-ray Images

Due to the rapid propagation characteristic of the Coronavirus (COVID-19) disease, manual diagnostic methods cannot handle the large number of infected individuals to prevent the spread of infection. Despite, new automated diagnostic methods have been brought on board, particularly methods based on artificial intelligence using different medical data such as X-ray imaging. Thoracic imaging, for example, produces several image types that can be processed and analyzed by machine and deep learning methods. X-ray imaging materials widely exist in most hospitals and health institutes since they are affordable compared to other imaging machines. Through this paper, we propose a novel Convolutional Neural Network (CNN) model (COV2Net) that can detect COVID-19 virus by analyzing the X-ray images of suspected patients. This model is trained on a dataset containing thousands of X-ray images collected from different sources. The model was tested and evaluated on an independent dataset. In order to approve the performance of the proposed model, three CNN models namely Mobile-Net, Residential Energy Services Network (Res-Net), and Visual Geometry Group 16 (VGG-16) have been implemented using transfer learning technique. This experiment consists of a multi-label classification task based on X-ray images for normal patients, patients infected by COVID-19 virus and other patients infected with pneumonia. This proposed model is empowered with Gradient-weighted Class Activation Mapping (Grad-CAM) and Grad-Cam++ techniques for a visual explanation and methodology debugging goal. The finding results show that the proposed model COV2Net outperforms the state-of-the-art methods

Prioritising Organisational Factors Impacting Cloud ERP Adoption and the Critical Issues Related to Security, Usability, and Vendors: A Systematic Literature Review

Abstract: Cloud ERP is a type of enterprise resource planning (ERP) system that runs on the vendor’s cloud platform instead of an on-premises network, enabling companies to connect through the Internet. The goal of this study was to rank and prioritise the factors driving cloud ERP adoption by organisations and to identify the critical issues in terms of security, usability, and vendors that impact adoption of cloud ERP systems. The assessment of critical success factors (CSFs) in on-premises ERP adoption and implementation has been well documented; however, no previous research has been carried out on CSFs in cloud ERP adoption. Therefore, the contribution of this research is to provide research and practice with the identification and analysis of 16 CSFs through a systematic literature review, where 73 publications on cloud ERP adoption were assessed from a range of different conferences and journals, using inclusion and exclusion criteria. Drawing from the literature, we found security, usability, and vendors were the top three most widely cited critical issues for the adoption of cloud-based ERP; hence, the second contribution of this study was an integrative model constructed with 12 drivers based on the security, usability, and vendor characteristics that may have greater influence as the top critical issues in the adoption of cloud ERP systems. We also identified critical gaps in current research, such as the inconclusiveness of findings related to security critical issues, usability critical issues, and vendor critical issues, by highlighting the most important drivers influencing those issues in cloud ERP adoption and the lack of discussion on the nature of the criticality of those CSFs. This research will aid in the development of new strategies or the revision of existing strategies and polices aimed at effectively integrating cloud ERP into cloud computing infrastructure. It will also allow cloud ERP suppliers to determine organisations’ and business owners’ expectations and implement appropriate tactics. A better understanding of the CSFs will narrow the field of failure and assist practitioners and managers in increasing their chances of success

The Internet of Drones: Requirements, Taxonomy, Recent Advances, and Challenges of Research Trends

The use of unmanned aerial vehicles or drones are a valuable technique in coping with issues related to life in the general public’s daily routines. Given the growing number of drones in low-altitude airspace, linking drones to form the Internet of drones (IoD) is a highly desirable trend to improve the safety as well as the quality of flight. However, there remain security, privacy, and communication issues related to IoD. In this paper, we discuss the key requirements of security, privacy, and communication and we present a taxonomy of IoD based on the most relevant considerations. Furthermore, we present the most commonly used commercial case studies and address the latest advancements and solutions proposed for the IoD environments. Lastly, we discuss the challenges and future research directions of IoD

Factors Influencing Academic Performance of Students in Blended and Traditional Domains

This paper aims to identify the most important and significant factors in two different areas of learning: combined and traditional learning. Several critical issues have not yet been resolved to achieve the full potential of the learning outcomes in the two domains. The objective of this paper is to review the critical factors that have a great influence on academic performance. The document focuses specifically on a set of factors such as the use of technology, the interaction processes, the characteristics of the students and the class. These identified factors were classified and discussed. The document also determines the technical and pedagogical limitations of the two declared domains. The technical and pedagogical challenges were proposed and future works were recommended

Factors Influencing Academic Performance of Students in Blended and Traditional Domains

This paper aims to identify the most important and significant factors in two different areas of learning: combined and traditional learning. Several critical issues have not yet been resolved to achieve the full potential of the learning outcomes in the two domains. The objective of this paper is to review the critical factors that have a great influence on academic performance. The document focuses specifically on a set of factors such as the use of technology, the interaction processes, the characteristics of the students and the class. These identified factors were classified and discussed. The document also determines the technical and pedagogical limitations of the two declared domains. The technical and pedagogical challenges were proposed and future works were recommended

A comparative evaluation of state-of-the-art integration testing techniques of component-based software

In the last few years, component-based software has gained widespread notice and acceptance as a method that facilitates the development of existing large, complex, and very critical systems by integrating prefabricated small pieces of software called components. Component integration becomes an essential stage in the component-based software development Lifecycle. Therefore, testing components after integration is an important activity. Due to the unavailability of source code of integrated components and due to the lack of component information or documentations, integration testing becomes more difficult and very complex task. In the literature, different techniques have been proposed with the purpose of facilitating the integration testing of component-based software. In this paper, we study, classify, and evaluate some of the existing integration testing techniques and make a comparison in order to help in develop new, better and more efficient and effective techniques for integration testing of component-based software systems