Scopus Research — Prof.Dr.Wael Jabbar Abed Al-nidawi

E-voting, or electronic voting, entails the incorporation of technology into the electoral process in order to address the shortcomings of conventional voting systems. E-voting systems have evolved and are expected to advance further in the future. However, e-voting systems face varying degrees of acceptance and resistance across different countries due to various influencing factors which remain controversial and context dependent. Hence, the aim of this study is to review prevailing studies on e-voting adoption, leveraging on the PRISMA statement, to determine the theoretical frameworks and models utilized and to ascertain the factors influencing the adoption in developing countries over the past five years. The study identified 17 related articles from 10 different countries and investigated them in light of the research questions. The Unified Theory of Acceptance and Use of Technology (UTAUT) and Technology Acceptance Model (TAM) are identified as the top frameworks commonly employed. In addition, other theories and models like the Diffusion of Innovation (DOI) theory, the Theory of Planned Behavior (TPB), trust models, and ethnographic approaches are also commonly used for investigating e-voting adoption systems. To deepen understanding regarding the adoption of e-voting in emerging nations, it is crucial to conduct longitudinal studies to track its progress over time. Additionally, comparative evaluations across different regions and countries, with the integration of qualitative and quantitative research methods, are essential for a comprehensive analysis of e-voting adoption patterns. © 2025 Mohammed H. Chalabi, Hazura Mohamed & Wael J. Al-Nidawi

Social media platforms provide an open forum for people to express their opinions about products, services, and brands. Sentiment analysis can help businesses and organizations monitor their brand reputation in real time. Recent research has shown that deep learning models are effective at a number of jobs related to Sentiment Analysis (SA). Typically, the fully connected layer is used for feature extraction, and a layer is used to perform classification tasks. This study used a deep learning architecture that uses Long Short-Term Memory (LSTM) for feature extraction and machine learning techniques. Support Vector Machine (SVM), Xgboost, Random Forest, Decision Tree, KNN, Logistic Regression, and Naive Bayes are employed for Arabic Sentiment Analysis in order to classify the Arabic reviews. In addition, an ensemble model was proposed that uses the seven machine learning techniques by voting, and the multilingual BERT was used for sentiment analysis. Six publicly accessible datasets were used to test the suggested technique. BERT consistently achieved the highest accuracy scores on all six datasets, ranging from 83.04% to 97.45%. LSTM also performed well on most datasets, achieving the second-highest accuracy scores after BERT. Its accuracy scores ranged from 81.871% to 96.984%. The ensemble models also performed well on the datasets, with accuracy scores ranging from 81.41% to 96.51%. The other models, including SVM, Xgboost, RF, DT, KNN, LR, and NB, showed good to moderate performance on the datasets, with accuracy scoresranging from 70% to 96.75%. © 2025 Author(s).

Providing high-quality services is an essential strategy for achieving business success in the service sector, particularly in terms of consumer satisfaction. E-banking offers a digital platform that facilitates the management of various banking requirements, from basic to advanced, through the use of digital devices. The purpose of this research study is to determine e-banking on the quality of services provided by their bank and their general level of satisfaction with the bank. Additionally, there is an effort to determine the specific dimension of service quality that has an opportunity to enhance customer satisfaction. However, when studying countries that are developing, academic investigations have shown a gap in the adoption and use of several factors that contribute to customer satisfaction within the context of technology. Literature review of existing studies on service quality and customer satisfaction has been done. In the context of e-banking in Iraq, this study is to ascertain the key components and relationships between e-service quality and customer satisfaction. In order to assess the quality of e-services within the specific context of online banking in Iraq, it is necessary to develop a conceptual model of customer satisfaction. © School of Engineering, Taylor’s University.

The subject of sentiment analysis through social media sites has witnessed significant development due to the increasing reliance of people on social media in advertising and marketing, especially after the Corona pandemic. There is no doubt that the prevalence of the Arabic language makes it considered one of the most important languages all over the world. Through human comments, it can know things if they are positive or negative. But in fact, the comments are many, and it takes work to evaluate the place or the product through a detailed reading of each comment. Therefore, this study applied deep learning approaches to this issue to provide final results that could be utilized to differentiate between the comments in the dataset. Arabic Sentiment Analysis was used and gave a percentage for each positive and negative commentary. This work used eight methods of deep learning techniques after using Fast Text as embedding, except Ara BERT. These techniques are the transformer (AraBERT), RNN (Long short-term memory (LSTM), Bidirectional long-short term memory (BILSTM), Gated recurrent units (GRUs), Bidirectional Gated recurrent units (BIGRU)), CNN (like ALEXNET, proposed CNN), and ensemble model (CNN with BI-GRU). The Hotel Arabic Reviews Dataset was utilized to test the models. This paper obtained the following results. In the Ara BERT model, the accuracy is 96.442%. In CNN, like the Alex Net model, the accuracy is 93.78%. In the suggested CNN model, the accuracy is 94.43%. In the suggested LSTM model, the accuracy is 95%. In the suggested BI-LSTM model, the accuracy is 95.11%. The accuracy of the suggested GRU model is 95.07%. The accuracy of the suggested BI-GRU model is 95.02%. The accuracy is 94.52% in the Ensemble CNN with BI-GRU model that has been proposed. Consequently, the AraBERT outperformed the other approaches in terms of accuracy. Because the AraBERT has already been trained on some Arabic Wikipedia entries. The LSTM, BI-LSTM, GRU, and BI-GRU, on the other hand, had comparable outcomes. © 2023, International Journal of Interactive Mobile Technologies. All Rights Reserved.

Information and communication technology has a significant influence on employee procedures. Businesses are investing in e-CRM technologies, yet it is difficult to assess the performance of their e-CRM platforms. The DeLone and McLean Information Systems Success framework can be modified to the current e-CRM assessment difficulties. The new framework's different aspects provide a concise framework for organizing the e-CRM key metrics identified in this study. The purpose of this study is to apply and verify that the Updated DeLone and McLean IS Model can be employed to explain e-CRM adoption among employees, along with the extended Updated DeLone and McLean Model with its five output factors, namely system quality, service quality, information quality, ease of use employee satisfaction. For this study, data was collected from 300 employees working on e-CRM and the data were analyzed using PLS-SEM. The experimental framework has a significant effect and shows that most of the hypotheses of the study are supported. Moreover, the framework contributes to the area of the success of e-CRM and individual performance. © 2022 The Authors.

As a result of the COVID-19 pandemic in numerous nations across the globe, all public schools in Iraq were forced to close. Teachers were put in a difficult position because of the necessity of accommodating online learning. The Ministry of Education in Iraq has obligated all schools to substitute face-to-face teaching processes with online learning. The Ministry also put forward several educational projects and platforms, such as Newton, Classera, and My School through Educational TV. Although these projects were urgent, they created many issues for students, teachers and schools. The results of this study reveal that online learning in Iraq experienced substantial growth during the breakout of the Corona virus crisis. Schools have the potential to take advantage of the new educational methods, and also transform their teaching practices. On the other hand, this new approach faces many challenges, including technological, educational, and social. Unreliable communications and a weak Internet are among the biggest challenges, as well as many students' lack the electronic devices required for learning. Moreover, despite the abundance of digital resources, both teachers and students have low abilities at using electronic tools. The study recommended the necessity of accelerating technological readiness by training students and teachers to use technological applications and providing educational platforms that have the ability to meet their needs, as well as strengthening the role of educational supervision. © 2023 Author(s).

Silicon carbide is a crucial structure material because of its wide applications in different fields, such as electronics. The impurities have negative impact on the homogenous sinterability of nano SiC during the sintering process, especially the silicon dioxide. So, the consolidation of SiC nanopowders was conducted by the microwave-current assisted sintering process. Field emission scanning electron microscope (FESEM), energy dispersive x-ray spectroscopy (EDS) and x-ray diffraction (XRD) were utilised to examine the nanopowders and sintered samples of SiC. The results showed that the smallest average grain sizes of sintered specimens of treated and untreated-SiC nanopowders were 331 and 428 nm, respectively. The relative densities of sintered specimens of treated and untreated-SiC nanopowders were around 97.1% and 93.8%, respectively. In conclusion, the nanostructure of sintered SiC was the benchmark of the microwave-current assisted sintering technique. © 2023 Vietnam Academy of Science & Technology

Vehicular Network (VANET)) is facing a lot of considerable issues affecting the network's performance. Factors like the massive number of nodes lacking inherent organization, also fast and frequent topological changes, makes routing one of the challenging tasks in VANET. In this paper, a new routing mechanism is developed to modify the operation's technique of AODV routing protocol to be used effectively in VANETs. The new mechanism of the modified AODV protocol (UAODV) is based on the idea of reducing the overhead of the protocol through the prevention of the broken link's predecessor node from the initiation and sending of the RERR toward the source node and after that, begins the procedure of the generation of a new message of the RREQ for repairing broken link rather than source node. Our developed mechanism illustrates that the UAODV protocol outperforms the original AODV in vehicular network environments. The results, which are verified by comparison with available experimental data, demonstrated that the average overhead of the UAODV has been reduced by 11.72% compared to original AODV. In addition to that, the number of the lost packets has been reduced by 31.90% and the transmission time for the packets has been decreased by 42.28% compared to original AODV. The proposed mechanism effectiveness evaluation is confirmed by comparing the efficiency of UAODV to the efficiency of the original AODV under different nodes mobility speed as well as different network load. The updated protocol (UAODV) improves the efficiency of the network by decreasing bandwidth consumption by protocol overhead. © School of Engineering, Taylor's University.

E-readiness assessment is one of the crucial aspects for attaining successful implementation of e-learning systems in higher education. The readiness assessment should consider various factors such as technical readiness, content readiness, financial readiness and human resources readiness. Many studies related to e-learning in developing countries including middle east have emerged to investigate organizations readiness and the veritable factors that can hinder the e-learning successful adoption and implementation. Different analysis approaches and models have been developed for such purpose. However, they commonly utilized to examine the e-learning from single perspective such as instructors, students and administrators. Based on the reality of e-learning in higher education in the Middle East countries and Iraq in particular, this research proposed a conceptual model for investigating the effect of macro-environment on e-learning readiness using PESTLE (social, economic, technological, political, legal, environmental) factors. This model can help to assess and provide a clear vision on the external barriers that hinder e-learning adoption and implementation, consequently put an effective plan to avoid the effect of such barriers. This can assist to reduce time and effort and ensure successful implementation of e-learning. © School of Engineering, Taylor's University.

In spite of the benefits of cloud computing, it is associated with high risks that need an effective security program. Framework of information security governance ensures successful management of information security risk and oversight, and helps to protect an organization's information. However, no standard or common criteria have been specified to help organizations in evaluating and selecting the proper cloud computing information security governance framework. Hence, this paper aims to identified the main and sub criteria to help organizations for evaluating the target frameworks. To achieve this aim, a critical review has been conducted to identify the current frameworks. The related frameworks are analyzed to indicate and identify the main and sub criteria that can be used to evaluate the current frameworks and facilitate the frameworks selection process. All criteria will be subjected to an evaluation process via interviews with specialists to define the criteria significance and capability in evaluating and differentiating the existing frameworks. The interview data is analyzed using content analysis method. The analysis of interviews data has found that all the experts agreed that main and sub criteria are very important, 20% of them indicated that these criteria are essential but lack to other sub-criteria such as awareness, valuation of assets and documents control. Furthermore, 70% of the experts indicated that it is difficult to rank the criteria because they have the same importance. Following that, it is recommended that a considerable work is still needed to specify a proper selection method of a suitable cloud computing information security governance framework based on standard or common criteria. Copyright © 2019 American Scientific Publishers All rights reserved.

Intrusion detection systems are being received a growing interest by researchers to develop different methods and techniques to overcome their problems and improve the efficiency in detecting various attacks against computer systems and networks. The overall performance of IDSs is a result of the efficiency and effectiveness of the main functions of IDS and any performance deterioration is significantly due to defects in these functions. Therefore, a theoretical foundation of IDSs is required to realize the boundaries, functions and capabilities of IDs and enhance the related research. This paper introduces an overview of the IDS principles, taxonomy, and functions. It also gives a brief on the intrusion detection systems common challenges. Furthermore, a generic intrusion detection system model is developed. Copyright © 2019 American Scientific Publishers All rights reserved.

Governments are responsible for providing services to the public easily, efficiently, therefore they introduced electronic government as a way to minimize costs, enhance services, save time and augment performance and efficacy in the public sector. E-service Quality is one of the critical issues in the failure or success of e-government projects. It promotes the efficiency and effectiveness of governments and the relationships with users and enhances their satisfactions. Measurement of e-service quality is a complex process because it depends on citizens‟ perception that is difficult to be realized and measured. This paper aims to review scales measurement of e-government services quality that providing an evaluating scale based on defining the significant e- service quality dimensions. These dimensions cover important e-services requirements to enhance e-service quality. © 2018 Institute of Advanced Engineering and Science. All rights reserved.

National Electronic ID (NeID) has been adopted in e-government by many countries due to its ability to enhance and raise the authentication quality. The authentication process aims to identify the correct recipient of the e-government services which is a major challenge. This paper provides a review on national electronic identification system in some selected countries and review some practices to enable and facilitate accessing e-government services. Finally, the benefits of a NeID have been discussed. © 2015 IEEE.