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A key element of many Natural Language Processing (NLP) applications is Named Entity Recognition (NER). It involves categorizing and identifying text into separate categories, such as identifying a location or an individual's name. Arabic NER (ANER) is also utilized in numerous other Arabic NLP (ANLP) tasks, such as Machine Translation (MT), Question Answering (QA), and Information Extraction (IE). ANER systems can often be classified into three major groups: rule-based, Machine Learning (ML), and hybrid. This study focuses on examining ML-based ANER developments, particularly in the context of Classical Arabic, which presents unique challenges due to its complex morphological structure and limited linguistic resources. We propose a supervised approach that integrates word-level, morphological, and knowledge-based features to improve NER performance for Classical Arabic. Our method was evaluated on the CANERCorpus, a specialized dataset containing annotated texts from Classical Arabic literature. The Naive Bayes (NB) approach achieved an F-measure of 80%, with precision and recall levels at 86% and 75%, respectively. These results indicate a significant improvement over traditional methods, particularly in dealing with the intricate structure of Classical Arabic. The study highlights the potential of ML in overcoming the challenges of ANER and provides directions for further research in this domain. [ABSTRACT FROM AUTHOR]

Predicting court rulings has gained attention over the past years. The court rulings are among the most important documents in all legal systems, profoundly impacting the lives of the children in case of divorce or separation. It is evident from literature that Natural language processing (NLP) and machine learning (ML) are widely used in the prediction of court rulings. In general, the court decisions comprise several pages and require a lot of space. In addition, extracting valuable information and predicting legal decisions task is difficult. Moreover, the legal system's complexity and massive litigation make this problem more serious. Thus to solve this issue, we propose a new neural network-based model for predicting court decisions on child custody. Our proposed model efficiently performs an efficient search from a massive court decisions database and accurately identifies specific ones that especially deal with copyright claims. More specially, our proposed model performs a careful analysis of court decisions, especially on child custody, and pinpoints the plaintiff's custody request, the court's ruling, and the pivotal arguments. The working mechanism of our proposed model is performed in two phases. In the first phase, the isolation of pertinent sentences within the court ruling encapsulates the essence of the proceedings performed. In the second phase, these documents were annotated independently by using two legal professionals. In this phase, NLP and transformer-based models were employed and thus processed 3,000 annotated court rulings. We have used a massive dataset for the training and refining of our proposed model. The novelty of the proposed model is the integration of bidirectional encoder representations from transformers (BERT) and bidirectional long short-term memory (Bi_LSTM). The traditional methods are primarily based on support vector machines (SVM), and logistic regression. We have performed a comparison with the state-of-the-art model. The efficient results indicate that our proposed model efficiently navigates the complex terrain of legal language and court decision structures. The efficiency of the proposed model is measured in terms of the F1 score. The achieved results show that scores range from 0.66 to 0.93 and Kappa indices from 0.57 to 0.80 across the board. The performance is achieved at times surpassing the inter-annotator agreement, underscoring the model's adeptness at extracting and understanding nuanced legal concepts. The efficient results proved the potential of the proposed neural network model, particularly those based on transformers, to effectively discern and categorize key elements within legal texts, even amidst the intricacies of judicial language and the layered complexity of appellate rulings. [ABSTRACT FROM AUTHOR]

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Underwater Wireless Sensor Networks (UWSNs) obtains more attention due to their wide range of applications such as underwater oil field discovery, Tsunami monitoring systems, surveillance systems, and many more. In such a resource-constrained environment, sensors are more vulnerable to malicious attacks. Node authentication and secure communication is one of the vital issues in UWSNs. In this study, a secure and lightweight key management framework for UWSNs is proposed. The proposed framework includes key generation, key distribution, revocation, and authentication mechanisms along with lightweight implementation, and scalability. We use an elliptic curve-based algorithm for key distribution, and certificate revocation list (CRL) for key revocation. We also examine the performance of the proposed framework taking into account the amount of communication overhead as well as the level of security. The simulation results show that the proposed framework provides better security with less communication overhead compared to existing frameworks. This framework can be used for secure data communication in UWSNs, which has various applications in oceanography, environmental monitoring, and military operations. [ABSTRACT FROM AUTHOR]

Enterprise resource planning (ERP) has been found to have a key role in the management of higher learning institutions (HLIs) and schools. However, the literature shows no universal model to support and shed light on the adoption of ERP, which lessens the chances for an effective ERP adoption and usage. Therefore, a new model is needed for successful adoption and the eventual enhanced decision-making, and as such, there is a need to investigate the factors that can bring about ERP system adoption. Models for ERP adoption in literature are few and far between, and what few exist are not applicable as they do not cover all the major factors that can contribute to adoption success. Hence, in this article, an ERP adoption model was brought forward for HLIs for the promotion of their decision-making process. The model was developed through the integration of DeLone and McLean's information success model and the technology, organisation and environment (TOE) theory. The study distributed 500 survey questionnaire copies online and collected 364 from HLIs respondents, after which they were retrieved, and data were analysed through partial least squares structural equation modeling (PLS-SEM) 3 statistical software. On the basis of the obtained analysis findings, technological, organisational and environmental factors had significant and positive effects on ERP adoption, and ERP adoption had a positive and significant effect on the decision-making of HLIs. The entire factors were found to be significant in their effects, and ERP adoption sufficiently explained variance extracted from decision-making. The study contributes to the literature through the pioneering measurement of factors categorised under technological, organisational and environmental dimensions, with ERP adoption and decision-making encapsulated in a single model. [ABSTRACT FROM AUTHOR]

The primary function of an electronic records management system (ERMS) is to support organisations in providing effective records management services by enabling efficient remote access to the organisations' records. This helps the organisation to continue running during emergency events, such as the COVID-19 pandemic. The need to study ERMS for accessing records remotely has increased dramatically, due to the increase in daily use. The situation arising from the COVID-19 pandemic has increased the need for implementing proper digital systems, such as ERMS, to enable efficient work processes and enhance business continuity. An ERMS has the potential to allow organisations to create records and workflows off-site. During a pandemic, the ability to structure processes digitally helps in maintaining operations remotely. This study aims to provide a narrative review of the ERMS literature with an emphasis on explaining the primary components of ERMS that act as enablers for the implementation of the system in the oil and gas sector of developing countries. The current study proposes ERMS roles and responsibilities that could enhance business continuity. The authors use a qualitative narrative review and analyse the literature related to this study and its findings. The results show that, in cases of risk or crises, staff members need to have easy access to their records and documents to remain productive. An ERMS allows professionals to remain active and work off-site. Thus, ERMS play a significant role in protecting an organisation's content through the monitoring and control over who has authorisation to access its records. [ABSTRACT FROM AUTHOR]

In the modern world, the amount of information stored in modern technology has been exponentially increasing. Access to vast amounts of information has changed how governments, institutions, organizations, and individuals conduct their business and record keeping. The increased use of cloud computing in conjunction with information and communication technologies (ICT), office automation, and digitalization has altered how electronic records are generated. Organizations should embrace this emerging environment to ensure competent operations and regulatory compliance well into the future. The absence of framework makes it difficult to implement the Electronic Records Management System (ERMS). Thus, this study proposed a framework for ERMS implementation and identified the most critical factors that are related to the ERMS characteristics and cloud characteristics. The ERMS implementation will improve Yemeni public sector educational institution competency and such implementation will be facilitated by the proposed framework. The study uses the Technology Acceptance Model 3 (TAM3) to implement a cloud Electronic Records Management System (ERMS). In addition to that, the study used a quantitative approach method and distributed questionnaires to 350 academicians and managers in the Yemeni public education sector. Variable relationships were identified using Partial Least Square-Structural Equation Modelling (PLS-SEM) through a second-order analysis method. All the identified factors were found to be essential and have a significant relationship with the behavioral intention to implement ERMS. The findings also revealed that ERMS plays a substantial and vital role in the competency of educational organizations. In other words, the study results demonstrated the importance of ERMS and Cloud dimension to ERMS implementation as well as the significant effect of ERMS implementation on public sector educational competency. These findings of the study have the potential to assist in shaping the direction of theory and empirical studies concerning the ERMS, particularly in its implementation to support the competency of educational institutions. [ABSTRACT FROM AUTHOR]

Electronic Records Management System (ERMS) is a computer program or set of applications that is utilized for keeping up to date records along with their storage. ERMS has been extensively utilized for enhancing the performance of academic institutions. The system assists in the planning and decision-making processes, which in turn enhances the competencies. However, although ERMS is significant in supporting the process of decision-making, the majority of organizations have failed to take an initiative to implement it, taking into account that are some implementing it without an appropriate framework, and thus resulted in the practice which does not meet the accepted standard. Therefore, this study identifies the factors influencing the adoption of ERMS among employees of HLI in Yemen and the role of such adoption in the decision-making process, using the Unified Theory of Acceptance and Use of Technology (UTAUT) along with Technology, Organization and Environment (TOE) as the underpinning theories. The study conducts a cross-sectional survey with a questionnaire as the technique for data collection, distributed to 364 participants in various Yemeni public Higher Learning Institutions (HLI). Using AMOS as a statistical method, the findings revealed there are significant and positive relationships between technology factors (effort expectancy, performance expectancy, IT infrastructure and security), organizational factors (top management support, financial support, training, and policy),environmental factors (competitiveness pressure, facilitating conditions and trust) and behavioral intention to adopt ERMS, which in return has a significant relationship with the process of decision-making in HLI. The study also presents a variety of theoretical and empirical contributions that enrich the body of knowledge in the field of technology adoption and the electronic record's domain. [ABSTRACT FROM AUTHOR]

An electronic records management system (ERMS) is tightly linked with most of the daily activities of educational organisations and leads to enhance their performance and decision-making. The aim of this article is to identify the significant factors that could influence the ERMS adoption in higher professional education (HPE). The methodology of this article started with identifying the factors through theory analysis and literature and also recommended by experts. Technology–organisation–environment (TOE) theory was used for factor classification. Qualitative approach was used through the interview with experts to validate and verify the proposed framework. This article presents the results of a study which identifies the issues involved in the utilisation and adoption of ERMS. More than 100 previous works and six well-known theories were critically reviewed to identify the main factors for successful ERMS adoption in different areas with the aim of proposing a taxonomic framework that can depict and identify the main factors that have an impact on the success of ERMS adoption. The proposed framework includes 11 factors categorised into three dimensions. The framework is validated and verified by experts. The adoption factors identified here provide a sound theoretical basis for research to understand, support and facilitate the adoption of ERMS to HPE benefit. The proposed framework could help to improve educational outcomes and the successful implementation of ERMS. [ABSTRACT FROM AUTHOR]