Aim/Purpose: This article examines how learning activities draw on resources in the work context to learn. Background The background is that if knowledge no longer is seen mainly as objects, but processes, how then to understand boundary objects? Our field study of learning activities reveals the use of pictures, documents and emotions for learning in the geographically distributed Norwegian Labor Inspection Authority Methodology: The study is a qualitative study consisting of interview data, observation data, and documents. Contribution: Contribute to practice based theorizing. Findings: Three ideal types of representing practices have been identified, i.e., ‘Visualizing’, ‘Documenting’ and ‘Testing’. All three are combined with storytelling, sensing, reflections and sensemaking, which point at the importance of processes in learning. The article also add insights about how emotions can be an important resource for boundary spanning – and sensemaking – by creating the capability of reflecting upon and integrating different knowledge areas in the in- practice context. Recommendations for Practitioners: Look for boundary objects within your field to promote online learning. Recommendation for Researchers: Study boundary objects in work context to understand learning. Impact on Society Role of objects in human learning. Future Research: Focus on how emotions can be used for online learning.

Aim/Purpose: Although cassava is one of the crops that can be grown during the dry season in Northeastern Thailand, most farmers in the region do not know whether the crop can grow in their specific areas because the available agriculture planning guideline provides only a generic list of dry-season crops that can be grown in the whole region. The purpose of this research is to develop a predictive model that can be used to predict suitable areas for growing cassava in Northeastern Thailand during the dry season. Background: This paper develops a decision support system that can be used by farmers to assist them determine if cassava can be successfully grown in their specific areas. Methodology: This study uses satellite imagery and data on land characteristics to develop a machine learning model for predicting suitable areas for growing cassava in Thailand’s Nakhon-Phanom province. Contribution: This research contributes to the body of knowledge by developing a novel model for predicting suitable areas for growing cassava. Findings: This study identified elevation and Ferric Acrisols (Af) soil as the two most important features for predicting the best-suited areas for growing cassava in Nakhon-Phanom province, Thailand. The two-class boosted decision tree algorithm performs best when compared with other algorithms. The model achieved an accuracy of .886, and .746 F1-score. Recommendations for Practitioners: Farmers and agricultural extension agents will use the decision support system developed in this study to identify specific areas that are suitable for growing cassava in Nakhon-Phanom province, Thailand Recommendation for Researchers: To improve the predictive accuracy of the model developed in this study, more land and crop characteristics data should be incorporated during model development. The ground truth data for areas growing cassava should also be collected for a longer period to provide a more accurate sample of the areas that are suitable for cassava growing. Impact on Society: The use of machine learning for the development of new farming systems will enable farmers to produce more food throughout the year to feed the world’s growing population. Future Research: Further studies should be carried out to map other suitable areas for growing dry-season crops and to develop decision support systems for those crops.

Aim/Purpose. Capture the Flag (CTF) challenges are a popular form of cybersecurity education where students solve hands-on tasks in a game-like setting. These exercises provide learning experiences with various specific technologies and subjects, as well as a broader understanding of cybersecurity topics. Competitions reinforce and teach problem-solving skills that are applicable in various technical and non-technical environments outside of the competitions. Background. The Information Search Process (ISP) is a framework developed to under-stand the process by which an individual goes about studying a topic, identifying emotional ties connected to each step an individual takes. As the individual goes through the problem-solving process, there is a clear flow from uncertainty to clarity; the individual’s feelings, thoughts, and actions are all interconnected. This study aims to investigate the learning of cybersecurity concepts within the framework of the ISP, specifically in the context of CTF competitions. Methodology. A comprehensive research methodology designed to incorporate quantitative and qualitative analyses to draw the parallels between the participants’ emotional experiences and the affective dimensions of learning will be implemented to measure the three primary goals. Contribution. This study contributes significantly to the broader landscape of cybersecurity education and cognitive-emotional experiences in problem-solving. Findings. The study has three primary goals. First, we seek to enhance our under-standing of the emotional and intellectual aspects involved in problem-solving, as demonstrated by the ISP approach. Second, we aim to gain in-sights into how the presentation of CTF challenges influences the learning experience of participants. Lastly, we strive to contribute to the improvement of cybersecurity education by identifying actionable steps for more effective teaching of technical skills and approaches. Recommendations for Practitioners. Competitions reinforce and teach problem-solving skills applicable in various technical and non-technical environments outside of the competitions. Recommendations for Researchers. The Information Search Process (ISP) framework may enhance our understanding of the emotional and intellectual aspects involved in problem-solving as we study the emotional ties connected to each step an individual takes as the individual goes through the problem-solving process. Impact on Society. Our pursuit of advancing our understanding of cybersecurity education will better equip future generations with the skills and knowledge needed to ad-dress the evolving challenges of the digital landscape. This will better pre-pare them for real-world challenges. Future Research. Future studies would include the development of a cybersecurity curriculum on vulnerability exploitation and defense. It would include practice exploiting practical web and binary vulnerabilities, reverse engineering, system hardening, security operations, and understanding how they can be chained together.

This paper explores the issues facing digital forensics in South Africa. It examines particular cyber threats and cyber threat levels for South Africa and the challenges in addressing the cybercrimes in the country through digital forensics. The paper paints a picture of the cybercrime threats facing South Africa and argues for the need to develop a skill base in digital forensics in order to counter the threats through detection of cybercrime, by analyzing cybercrime reports, consideration of current legislation, and an analysis of computer forensics course provision in South African universities. The paper argues that there is a need to develop digital forensics skills in South Africa through university programs, in addition to associated training courses. The intention in this paper is to promote debate and discussion in order to identify the cyber threats to South Africa and to encourage the development of a framework to counter the threats – through legislation, high tech law enforcement structures and protocols, digital forensics education, digital forensics skills development, and a public and business awareness of cybercrime threats.

Aim/Purpose: This study analyzes the mechanism of Internet capability (IC) driving knowledge creation performance (KCP). We consider the mediating role of strategic flexibility and the moderating role of informatization density. Background: The key to achieving KCP for firms is to transform knowledge created into new products or services and to realize the economic benefits. However, the research has not paid enough attention to firms’ KCP. Based on dynamic capability theory, this study empirically reveals how firms drive KCP through Internet capability. Methodology: The study uses survey data from 399 organizations in China. Through structural equation modeling, this study assesses the relationship between Internet capability, strategic flexibility, and KCP and uses hierarchical regression to test the moderating role of informatization density. Contribution: First, this study expands research on knowledge creation and focuses on the further achievement of knowledge creation performance. The study also enriches the exploration of KCP in the Internet context and deepens the research on the internal mechanism by which Internet capability influences KCP. Second, this study highlights the important role of informatization density in the Internet context and expands the research on the impact of external factors on the internal mechanism. Findings: First, Internet capability has a significantly positive effect on both strategic flexibility and KCP. Furthermore, Internet capability directly impacts strategic flexibility, yet it affects KCP both directly and indirectly through strategic flexibility, which confirms that strategic flexibility is a partial mediator in the relationship between Internet capability and KCP. Second, strategic flexibility positively influences KCP. Third, informatization density has a significant moderating effect on the relationship between Internet capability and KCP. Recommendations for Practitioners: The results indicate that firms should consider the importance of Internet capability and strategic flexibility for KCP in the Internet context. This study also provides a theoretical basis that could guide the Chinese government’s informatization construction of the industrial chain. Recommendation for Researchers: Researchers could further explore the role of other mediator variables (e.g., business process management, organizational agility) and consider the role of other moderator variables (e.g., resource commitment, learning orientation). Impact on Society: This study provides a reference for enterprises with similar cultural backgrounds in using Internet capability to enhance their competitive advantage. Future Research: Future research could collect data from various countries and regions to test the research model and conduct longitudinal studies to increase the robustness of the conclusions.

Aim/Purpose: The aim of this study is to examine empirically the effects of certain key Critical Success Factors (CSFs) for the implementation of Enterprise Resource Planning (ERP) Systems on the comprehensive achievement of the crucial roles of Computer-Based Information Systems (CBISs) Background: The effects of the CSFSs were examined in the higher education sector in the Kingdom of Saudi Arabia (KSA) using a case study of the ERP adoption in Prince Sattam Bin Abdulaziz University. Methodology: A theoretical model was proposed based on the literature written on the CSFs and the roles of CBISs in business. The model encompasses six key CSFs and their associations with the realization of the crucial roles of CBISs. To test the proposed model, a questionnaire was developed by considering the most frequently used measurements items in the ERP’s literature. The data were collect-ed from 219 key stakeholders. Contribution: This study acts as one of the few empirical studies in assessing the effects of the important CSFs for ERP implementation upon its successful implementation. Its outcomes provide more insights and clarifications about the effects of six key CSFs on the comprehensive achievement of the crucial CBIS’s roles. Particularly, the uniqueness of this study lies in addressing the effects of these CSFs on the achievement of the vital CBIS’s roles collectively rather than the achievement of each role individually. Moreover, the study examined these effects in the higher education environment, which is characterized by its own special business processes and services. Findings: The results reveal that the six key CSFs have a positive relationship with the comprehensive achievement of the crucial roles of CBISs. These findings are consistent with many previous studies on the effects of the CSFs on the realization of the expected benefits of the enterprise systems. Recommendations for Practitioners: The managers and other key stakeholders should carefully manage the vital aspects of the CSFs in order to realize the promised ERP’s benefits, including the CBIS’s roles. Future Research: Additional empirical examinations are needed to investigate the effects of the rest of the CSFs on realizing the roles of information systems.

Aim/Purpose: The clustering techniques are normally considered to determine the significant and meaningful subclasses purposed in datasets. It is an unsupervised type of Machine Learning (ML) where the objective is to form groups from objects based on their similarity and used to determine the implicit relationships between the different features of the data. Cluster Analysis is considered a significant problem area in data exploration when dealing with arbitrary shape problems in different datasets. Clustering on large data sets has the following challenges: (1) clusters with arbitrary shapes; (2) less knowledge discovery process to decide the possible input features; (3) scalability for large data sizes. Density-based clustering has been known as a dominant method for determining the arbitrary-shape clusters. Background: Existing density-based clustering methods commonly cited in the literature have been examined in terms of their behavior with data sets that contain nested clusters of varying density. The existing methods are not enough or ideal for such data sets, because they typically partition the data into clusters that cannot be nested. Methodology: A density-based approach on traditional center-based clustering is introduced that assigns a weight to each cluster. The weights are then utilized in calculating the distances from data vectors to centroids by multiplying the distance by the centroid weight. Contribution: In this paper, we have examined different density-based clustering methods for data sets with nested clusters of varying density. Two such data sets were used to evaluate some of the commonly cited algorithms found in the literature. Nested clusters were found to be challenging for the existing algorithms. In utmost cases, the targeted algorithms either did not detect the largest clusters or simply divided large clusters into non-overlapping regions. But, it may be possible to detect all clusters by doing multiple runs of the algorithm with different inputs and then combining the results. This work considered three challenges of clustering methods. Findings: As a result, a center with a low weight will attract objects from further away than a centroid with higher weight. This allows dense clusters inside larger clusters to be recognized. The methods are tested experimentally using the K-means, DBSCAN, TURN*, and IDCUP algorithms. The experimental results with different data sets showed that IDCUP is more robust and produces better clusters than DBSCAN, TURN*, and K-means. Finally, we compare K-means, DBSCAN, TURN*, and to deal with arbitrary shapes problems at different datasets. IDCUP shows better scalability compared to TURN*. Future Research: As future recommendations of this research, we are concerned with the exploration of further available challenges of the knowledge discovery process in clustering along with complex data sets with more time. A hybrid approach based on density-based and model-based clustering algorithms needs to compare to achieve maximum performance accuracy and avoid the arbitrary shapes related problems including optimization. It is anticipated that the comparable kind of the future suggested process will attain improved performance with analogous precision in identification of clustering shapes.

Aim/Purpose: This study investigated a model of mobile esports acceptance among urban citizens based on an extended Technology Acceptance Model (TAM). Background: Currently, esports are increasingly popular and in demand by the public. Supported by the widespread development of mobile devices, it has become an interactive market trend to play games in a new model, mobile esports. Methodology: This study collected data from 400 respondents and analyzed it using partial least squares-structural equation modeling (PLS-SEM). Contribution: This study addresses two research gaps. The first gap is limited esports information systems studies, particularly in mobile esports acceptance studies. The second gap is limited exploration of external variables in online gaming acceptance studies. Thus, this study proposed a TAM extended model by integrating the TAM native variables with other external variables such as visual appeal, enjoyment, social interaction, and competition to explore mobile esports acceptance by urban citizens. Findings: Nine hypotheses were accepted, and four were rejected. The visual appeal did not affect the acceptance. Meanwhile, social interaction and enjoyment significantly affected both perceived ease of use and usefulness. However, perceived ease of use surprisingly had an insignificant effect on attitude toward using mobile esports. Moreover, competition significantly affected the acceptance, particularly on perceived usefulness. Recommendations for Practitioners: Fresh and innovative features, such as new game items or themes, should be frequently introduced to enhance players’ continued enjoyment. Moreover, mobile esports providers should offer a solid platform to excite players’ interactions to increase the likelihood that users feel content. On the other hand, the national sports ministry/agency or responsible authorities should organize many esports competitions, big or small, to search for new talents. Recommendation for Researchers: Visual appeal in this study did not influence the perceived ease of use or usefulness. However, it could affect enjoyment. Thus, it would be worth revisiting the relationship between visual appeal and enjoyment. At the same time, perceived ease of use is a strong driver for the continued use of most online games, but not in this study. It could indicate significant differences between mobile esports and typical online games, one of which is the different purposes. Users might play online games for recreational intention, but players would use mobile esports to compete, win, or even get monetary rewards. Therefore, although users might find mobile esports challenging and hard to use, they tend to keep playing it. Thus, monetary rewards could be considered a determinant of the continuation of use. Impact on Society: Nowadays, users are being paid for playing games. It also would be an excel-lent job if they become professional esports athletes. This study investigated factors that could affect the continued use of mobile esports. Like other jobs, playing games professionally in the long term could make the players tedious and tired. Therefore, responsible parties, like mobile esports providers or governments, could use the recommendations of this study to promote positive behavior among the players. They will not feel like working and still con-sider playing mobile esports a hobby if they happily do the job. In the long run, the players could also make a nation’s society proud if they can be a champion in prestigious competitions. Future Research: A larger sample size will be needed to generalize the results, such as for a nation. It is also preferable if the sample is randomized systematically. Future works should also investigate whether the same results are acquired in other mobile esports. Furthermore, to extend our knowledge and deepen our understanding of the variables that influence mobile esports adoption, the subsequent research could look at other mobile esports acceptability based on characteristics of system functionality and moderator effects. Finally, longitudinal data-collecting approaches are suggested for future studies since behavior can change over time.

Aim/Purpose: This study identifies the elements that influence intentions to purchase from the most popular Arabic online classifieds platform, OpenSooq.com. Background: Online purchasing has become popular among consumers in the past two decades, with perceived risk and trust playing key roles in consumers’ intention to purchase online. Methodology: A questionnaire survey was conducted of Internet users from three Jordanian districts to investigate how they used the OpenSooq platform in their e-commerce activities. In total, 202 usable responses were collected, and the data were analyzed with PLS-SEM for hypothesis testing and model validation. Contribution: Though online trading is increasingly popular, the factors that impact the behavior of consumers when purchasing high-value products have not been adequately investigated. Therefore, this study examined the factors affecting perceived risk, and the potential impact of privacy concerns on the perceived risk of online smartphone buyers. The study framework can help explore online behavior in various situations to ascertain similarities and differences and probe other aspects of online buying. Findings: Perceived risk negatively correlates with online purchasing behavior and trust. However, privacy concern and perceived risk, transaction security and trust, and trust and online purchasing behavior exhibited positive correlations. Recommendations for Practitioners: Customers can complete and retain online purchases in a range of settings illuminated in this study’s methods and procedures. Moreover, businesses can manage their IT arrangements to make Internet shopping more convenient and build processes for online shopping that allow for engagement, training, and ease of use, thus improving their customers’ online purchasing behavior. Recommendation for Researchers: Given the insight into the understanding and integration of variables including perceived risk, privacy issues, trust, transaction security, and online purchasing behavior, academics can build on the groundwork of this research paradigm to investigate underdeveloped countries, particularly Jordan, further. Impact on Society: Understanding the characteristics that influence online purchasing behavior can help countries realize the full potential of online shopping, particularly the benefits of safe, fast, and low-cost financial transactions without the need for an intermediary. Future Research: Future research can examine the link between online purchase intent, perceived risk, privacy concerns, trust, and transaction security to see if the findings of this study in Jordan can be applied to a broader context in other countries.

Aim/Purpose: ************************************************************************ After its investigation, the Research Ethics, Integrity, and Governance team at RMIT University found that the primary author of this paper breached the Australian Code and/or RMIT Policy and requested that the article be retracted. ************************************************************************** This paper aimed to examine the influence of ethical and transformational leadership on employee creativity in Malaysia’s private higher education institutions (PHEIs) and the mediating role of organizational citizenship behavior. Background: To ensure their survival and success in today’s market, organizations need people who are creative and driven. Previous studies have demonstrated the importance of ethical leadership in fostering employee innovation and good corporate responsibility. Research on ethical leadership and transformational leadership, in particular, has played a significant role in elucidating the role of leadership in relation to organizational citizenship behavior (OCB). In this study, we have focused on ethical and transformational leadership as an antecedent for enhancing employee creativity. Despite an increase in leadership research, little is known about the underlying mechanisms that link ethical leadership and transformational leadership to OCB. Because it sheds light on factors other than ethical leadership and transformational leadership that influence employees’ extra-role activity, this research is relevant theoretically. OCB may have a mediating function between ethical leadership and transformational leadership style and employee creativity because it is associated with the greatest outcomes, but empirical research has yet to prove this. So, one of the study’s goals is to add to the hypotheses about how ethical leadership style and transformational leadership affect employee creativity by using an important mediating variable – OCB. Methodology: This study adopted a quantitative approach based on a cross-sectional survey and descriptive design to gather the data in a specific period. A convenient sampling approach was used to gauge 275 employees from Malaysia’s PHEIs. To test the hypotheses and obtain a conclusion, the acquired data was analyzed using the partial least square technique (PLS-SEM). Contribution: The study contributes to leadership literature by advancing OCB as a mediating factor that accounts for the link between ethical and transformational leadership and employee creativity in the higher education sector. Findings: According to the research, OCB has a substantial influence on the creativity of employees. Furthermore, ethical leadership boosted OCB and boosted employee creativity, according to the research. OCB and employee creativity have both been demonstrated to benefit greatly from transformational leadership. Further research revealed that OCB is a mediating factor in the link between leadership styles and creative thinking among employees. Recommendations for Practitioners: Higher education institutions should focus on developing leaders who value transparency and self-awareness in their interactions with followers and who demonstrate an inner moral perspective in addition to balanced information processing to ensure positive outcomes at the individual and organizational levels. Higher education institutions should place a priority on hiring leaders that exhibit ethical and transformational traits to raise awareness of these leadership styles among employees. Recommendation for Researchers: The new study also adds significantly to the body of knowledge by examining the relationship between ethical and transformational leadership and the creativity of the workforce. It aimed to identify the relationship between transformational leadership style and individual creativity in higher education by examining the mediating influence of OCB. Impact on Society: Higher education institutions should devise strategies for developing ethical and transformative leaders who will assist boost OCB and creativity within their workforce. Students and faculty in higher education can benefit from these leadership methods by learning to think in more diverse ways and by developing thought processes that lead to a larger pool of innovative ideas and solutions. As a consequence, employees who show creative behavior may be effectively managed by leaders who utilize ethical and transformational leadership styles and motivate them to show OCB that allow them to solve creative problems creatively. Future Research: A mixed-methods approach should be used in future research, and this should be done in public institutions in developing and developed nations to put the findings to use and generalize them even further. Future research will be able to examine other mediators to learn more about how and why ethical and transformational leadership styles affect PHEI employees’ creativity.

Aim/Purpose: This study aimed to increase our understanding of how the stages of the customer purchase journey, privacy trade-offs, and information sensitivity of different business service sectors affect consumers’ privacy concerns. Background: The study investigated young consumers’ willingness to provide consent to use their personal data at different phases of the customer journey. This study also examined their readiness to provide consent if they receive personal benefits, and how information sensitivity varied between different individuals and business sectors. Methodology: Data was collected by a quantitative survey (n=309) and analyzed with R using the Bayesian linear mixed effect modeling approach. The sample consisted of university students in Finland, who represented a group of young and digitally native consumers. The questionnaire was designed for this study and included constructs with primarily Likert-scale items. Contribution: The study contributed to data privacy and consent management research in information sensitivity, privacy trade-off, and the customer journey. The study underlined the need for a stronger user experience focus and contextuality. Findings: The results showed that readiness to disclose personal data varied at different phases of the customer journey as privacy concerns did not decrease in a linear fashion throughout the purchase process. Perceived benefits affected the willingness to provide consent for data usage, but concerned consumers would be less trade-off oriented. Self-benefit was the most relevant reason for sharing, while customization was the least. There is a connection between the information sensitivity of different business sector information and privacy concerns. No support for gender differences was found, but age affected benefits and business sector variables. Recommendations for Practitioners: The study recommends approaching consumers’ data privacy concerns from a customer journey perspective while trying to motivate consumers to share their personal data with relevant perceived benefits. The self-benefit was the most relevant benefit for willingness to provide consent, while customization was the least. Recommendation for Researchers: The study shows that individual preference for privacy was a major factor directly and via interaction for all three models. This study also showed that consumers’ subjective decision-making in privacy issues is both a situational and a contextual factor. Impact on Society: This study could encourage policymakers and societies to develop guidelines on how to develop privacy practices and consent management to be more user centric as individuals are increasingly concerned about their online privacy. Future Research: This study encourages examining consumers’ motivational factors to provide digital consent for companies with experimental research settings. This study also calls to explore perceived benefits in all age groups from the perspective of different information in various business sectors. This study shows that privacy concern is a contextual and situational factor.

Aim/Purpose: This paper aims to investigate and understand the intentions of management undergraduate students in Hangzhou, China, regarding the adoption of Artificial Intelligence (AI) technologies in their education. It addresses the need to explore the factors influencing AI adoption in the educational context and contribute to the ongoing discourse on technology integration in higher education. Background: The paper addresses the problem by conducting a comprehensive investigation into the perceptions of management undergraduate students in Hangzhou, China, regarding the adoption of AI in education. The study explores various factors, including Perceived Relative Advantage and Trialability, to shed light on the nuanced dynamics influencing AI technology adoption in the context of higher education. Methodology: The study employs a quantitative research approach, utilizing the Confirmatory Tetrad Analysis (CTA) and Partial Least Squares Structural Equation Modeling (PLS-SEM) methodologies. The research sample consists of management undergraduate students in Hangzhou, China, and the methods include data screening, principal component analysis, confirmatory tetrad analysis, and evaluation of the measurement and structural models. We used a random sampling method to distribute 420 online, self-administered questionnaires among management students aged 18 to 21 at universities in Hangzhou. Contribution: This paper explores how management students in Hangzhou, China, perceive the adoption of AI in education. It identifies factors that influence AI adoption intention. Furthermore, the study emphasizes the complex nature of technology adoption in the changing educational technology landscape. It offers a thorough comprehension of this process while challenging and expanding the existing literature by revealing the insignificant impacts of certain factors. This highlights the need for an approach to AI integration in education that is context-specific and culturally sensitive. Findings: The study highlights students’ positive attitudes toward integrating AI in educational settings. Perceived relative advantage and trialability were found to impact AI adoption intention significantly. AI adoption is influenced by social and cultural contexts rather than factors like compatibility, complexity, and observability. Peer influence, instructor guidance, and the university environment were identified as pivotal in shaping students’ attitudes toward AI technologies. Recommendations for Practitioners: To promote the use of AI among management students in Hangzhou, practitioners should highlight the benefits and the ease of testing these technologies. It is essential to create communication strategies tailored to the student’s needs, consider cultural differences, and utilize the influence of peers and instructors. Establishing a supportive environment within the university that encourages innovation through policies and regulations is vital. Additionally, it is recommended that students’ attitudes towards AI be monitored constantly, and strategies adjusted accordingly to keep up with the changing technological landscape. Recommendation for Researchers: Researchers should conduct cross-disciplinary and cross-cultural studies with qualitative and longitudinal research designs to understand factors affecting AI adoption in education. It is essential to investigate compatibility, complexity, observability, individual attitudes, prior experience, and the evolving role of peers and instructors. Impact on Society: The study’s insights into the positive attitudes of management students in Hangzhou, China, toward AI adoption in education have broader societal implications. It reflects a readiness for transformative educational experiences in a region known for technological advancements. However, the study also underscores the importance of cautious integration, considering associated risks like data privacy and biases to ensure equitable benefits and uphold educational values. Future Research: Future research should delve into AI adoption in various academic disciplines and regions, employing longitudinal designs and qualitative methods to understand cultural influences and the roles of peers and instructors. Investigating moderating factors influencing specific factors’ relationship with AI adoption intention is essential for a comprehensive understanding.

As a result of the rapid development of Information and Communication Technology (ICT) and the growing interest in Internet-based tools for language classroom, it has become a pressing need for educators to locate, evaluate and select the most appropriate language-learning digital resources that foster more communicative and meaningful learning processes. Hence, this paper describes a mixed research project that, on the first hand, aimed at proposing a Checklist for evaluating language websites built on the principles of the Communicative Approach, and on the second hand, sought to strengthen the teachers’ Knowing-how-to-do skill as part of their digital competence. To achieve these goals, a four-phase research procedure was followed that included reviewing relevant literature and administering qualitative and quantitative research methods to participants (i.e., language teachers, an expert in the Computer-Assisted Language Learning (CALL) field and a college professor) in order to gain insights into problematic issues and, thereafter, to contribute to the creation and validation of the Checklist model and the Study Guide. The findings revealed that: (a) evaluating language websites leads to the enhancement of the teachers’ practical skills and their knowledge of the technological language; and (b) having an assessment instrument allows educators to choose the materials that best meet their communicative teaching purposes.

Aim/Purpose: The research work investigated the information seeking process of undergraduates in a specialised university in Nigeria, in the course of a group assignment. Background: Kuhlthau’s Information Search Process (ISP) model is used as lens to reveal how students interact with information in the affective, cognitive and physical realms. Methodology: Qualitative research methods were employed. The entire seventy-seven third year students in the Department of Petroleum and Natural Gas and their course lecturer were the participants. Group assignment question was analysed using Bloom’s Taxonomy while the information seeking process of the students was garnered through dialogue journaling on WhatsApp Messenger. Contribution: The research explicates how students’ information seeking behaviour can be captured beyond the four walls of a classroom by using a Web 2.0 tool such as WhatsApp Messenger. Findings: The apparent level of uncertainty, optimism, and confusion/doubt common in the initiation, selection, and exploration phases of the ISP model and low confidence levels were not markedly evident in the students. Consequently, Kuhlthau’s ISP model could not be applied in its entirety to the study’s particular context of teaching and learning due to the nature of the assignment. Recommendations for Practitioners: The study recommends that the Academic Planning Unit (APU) should set a benchmark for all faculties and, by extension, the departments in terms of the type/scope and number of assignments per semester, including learning outcomes. Recommendation for Researchers: Where elements of a guided approach to learning are missing, Kuhlthau’s ISP may not be employed. Therefore, alternative theory, such as Theory of Change could explain the poor quality of education and the type of intervention that could enhance students’ learning. Impact on Society: The ability to use emerging technologies is a form of literacy that is required by the 21st century work place. Hence, the study demonstrates students’ adaptation to emerging technology. Future Research: The study is limited to only one case site. It would be more helpful to the Nigerian society to have this study extended to other universities for the purpose of generalisation and appropriate intervention.

Tensions are a ubiquitous feature of social life and are manifested in a number of particular forms: contradictory logics, competing demands, clashes of ideas, contradictions, dialectics, irony, paradoxes, and/or dilemmas. This essay aims to explore in detail tensions surrounding seven common findings of the information seeking literature relating to: interpersonal communication, accessibility, level of skill, individual preferences, psychological limits, inertia, and costs. Our incomplete understanding of these tensions can lead us to suggest resolutions that do not recognize their underlying dualities. Human information behavior stands at the intersection of many important theoretical and policy issues (e.g., personalized medicine). Policy makers need to be more attuned to these basic tensions of information seeking recognizing the real human limits they represent to informing the public. So, even if you build a great information system, people will not necessarily use it because of the force of these underlying tensions. While rationality rules systems, irrationality rules people. The proliferation of navigator roles over the last several years is actually a hopeful sign: recognition that people need a human interface to inform them about our ever more complex health care systems.

Aim/Purpose: The aim of this paper is to propose an ensemble learners based classification model for classification clickbaits from genuine article headlines. Background: Clickbaits are online articles with deliberately designed misleading titles for luring more and more readers to open the intended web page. Clickbaits are used to tempted visitors to click on a particular link either to monetize the landing page or to spread the false news for sensationalization. The presence of clickbaits on any news aggregator portal may lead to an unpleasant experience for readers. Therefore, it is essential to distinguish clickbaits from authentic headlines to mitigate their impact on readers’ perception. Methodology: A total of one hundred thousand article headlines are collected from news aggregator sites consists of clickbaits and authentic news headlines. The collected data samples are divided into five training sets of balanced and unbalanced data. The natural language processing techniques are used to extract 19 manually selected features from article headlines. Contribution: Three ensemble learning techniques including bagging, boosting, and random forests are used to design a classifier model for classifying a given headline into the clickbait or non-clickbait. The performances of learners are evaluated using accuracy, precision, recall, and F-measures. Findings: It is observed that the random forest classifier detects clickbaits better than the other classifiers with an accuracy of 91.16 %, a total precision, recall, and f-measure of 91 %.

Aim/Purpose: The present study aims to frame the relationship between job and personal resources (namely, organizational identification and emotional intelligence), burnout, and musculoskeletal disorders (i.e., back pain, upper limb pain, lower limb discomfort), into the theoretical framework provided by the JD-R health model. Background: Empirical research indicates a connection between burnout and the onset of musculoskeletal problems, one of the most important occupational health issues affecting all jobs and organizations. In light of the JD-R health model, we investigated the association between personal and job resources with burnout and musculoskeletal disorders. Methodology: An anonymous online questionnaire was answered by 320 workers (82.4% female, Mage = 42.18; SDage = 12.24) investigating their perceived level of burnout, the presence of musculoskeletal pain (back, neck, and shoulder), and their level of organizational identification and emotional intelligence. Descriptive analysis, correlation, and moderated mediation model were performed using SPSS. Contribution: We confirmed the role of personal and organizational resources in the salutogenic process considered by the JD-R health model. Emotional intelligence, decreasing the perceived level of burnout, limited the development of musculoskeletal disorders. Moreover, when organizational identification presented low and medium levels, the association between emotional intelligence and burnout strengthened. Findings: Our results showed a negative, indirect effect of emotional intelligence on musculoskeletal disorders via burnout. Moreover, we found a moderation of organizational organization, indicating that at low and medium levels of identification, the association between emotional intelligence and burnout is stronger. Recommendation for Researchers: In addition to work factors involved in the link between burnout and musculoskeletal disorders, it is also important to consider personal and emotional factors, which can decrease the occurrence of adverse consequences. Future Research: Future research developments could contribute to a deeper understanding of the mechanisms linking emotional intelligence, burnout, and musculoskeletal problems, as well as consider objective indicators of burnout levels or consider using ecological data collection methodologies (e.g., ecological momentary assessment), to identify patterns and associations between burnout and musculoskeletal disorders.

Aim/Purpose: The purpose of this study is to determine the impact of pre-listening activities on Arabic-speaking EFL learners’ comprehension of spoken texts. Background: This study aims to contribute to the current research and to increase our understanding about the effectiveness of pre-listening activities. Specifically, this study seeks to clarify some of the research in this area that seems to be incongruent. Methodology: The study investigates two widely implemented activities in second language (L2) classrooms: vocabulary preteaching and content previewing. Ninety-three native-Arabic speaking EFL learners, whose proficiently levels were beginner, intermediate, or advanced, were randomly assigned to a control group or one of three experimental groups: the vocabulary-only (VO) group, content-only (CO) group, or vocabulary + content (VC) group. Each of the experimental groups received one of the treatments to determine which pre-listening activity was more effective and whether additional pre-listening activities yield additional comprehension. Listening comprehension of the aural text was measured by a test comprising 13 multiple-choice and true-false questions. Contribution: The present study provided additional explanations regarding the long-standing contradicting results about vocabulary preteaching and content previewing. Findings: The results showed that pre-listening activities had a positive impact on Arabic-speaking EFL learners’ listening comprehension, with the VO group significantly increasing their scores on the posttest compared to those of the control or other groups. Vocabulary preteaching was particularly beneficial for more advanced learners. With regard to which pre-listening activity contributed the most to better listening comprehension, vocabulary preteaching was the most effective. Content previewing did not increase comprehension for the CO group and had no additional benefit for the VC group. Recommendation for Researchers: This paper recommends that researchers explore new pre-listening activities that have never studied. Future research should be extended to include other nations and contextual situations to extend our knowledge about the effect of pre-listening activities. As far as listening comprehension can only be achieved when listeners are attentive and engaged, the listening text should be interesting and the lexical coverage of the listening text should be appropriate for all participants. Future Research: The results are to be interpreted carefully because they are limited by the students’ L2 proficiency, demographic, and cultural backgrounds (i.e., first language (L1) proficiency, age, gender, Middle Eastern culture). Results might be quite different if the study was conducted with different populations who have different life and language learning experiences (Vandergrift & Baker, 2015). Therefore, the results of this study indicate there is much room for improvement and a need for further research.

Aim/Purpose: This review paper aims to unveil some underlying machine-learning classification algorithms used for political election predictions and how stack ensembles have been explored. Additionally, it examines the types of datasets available to researchers and presents the results they have achieved. Background: Predicting the outcomes of presidential elections has always been a significant aspect of political systems in numerous countries. Analysts and researchers examining political elections rely on existing datasets from various sources, including tweets, Facebook posts, and so forth to forecast future elections. However, these data sources often struggle to establish a direct correlation between voters and their voting patterns, primarily due to the manual nature of the voting process. Numerous factors influence election outcomes, including ethnicity, voter incentives, and campaign messages. The voting patterns of successors in regions of countries remain uncertain, and the reasons behind such patterns remain ambiguous. Methodology: The study examined a collection of articles obtained from Google Scholar, through search, focusing on the use of ensemble classifiers and machine learning classifiers and their application in predicting political elections through machine learning algorithms. Some specific keywords for the search include “ensemble classifier,” “political election prediction,” and “machine learning”, “stack ensemble”. Contribution: The study provides a broad and deep review of political election predictions through the use of machine learning algorithms and summarizes the major source of the dataset in the said analysis. Findings: Single classifiers have featured greatly in political election predictions, though ensemble classifiers have been used and have proven potent use in the said field is rather low. Recommendation for Researchers: The efficacy of stack classification algorithms can play a significant role in machine learning classification when modelled tactfully and is efficient in handling labelled datasets. however, runtime becomes a hindrance when the dataset grows larger with the increased number of base classifiers forming the stack. Future Research: There is the need to ensure a more comprehensive analysis, alternative data sources rather than depending largely on tweets, and explore ensemble machine learning classifiers in predicting political elections. Also, ensemble classification algorithms have indeed demonstrated superior performance when carefully chosen and combined.

This paper presents a novel deep learning technique called quantum dilated convolutional neural network-DenseNet (Q-DenseNet) for prediction of heart disease in spark framework. At first, the input data taken from the database is allowed for data partitioning using fast fuzzy C-means clustering (FFCM). The partitioned data is fed into spark framework, where pre-processed by missing data imputation and quantile normalisation. The pre-processed data is further allowed for selection of suitable features. Then, the selected features from the slave nodes are merged and fed into master node. The Q-DenseNet is used in master node for the prediction of heart disease. The performance improvement of the designed Q-DenseNet model is validated by comparing with traditional prediction models. Here, the Q-DenseNet method achieved superior performance with maximum of 92.65% specificity, 91.74% sensitivity, and 90.15% accuracy.

Nat PAVASANT,Takashi MORITA,Masayuki NUMAO,Ken-ichi FUKUI, Vol.E107-D, No.11, pp.1453-1457
We proposed a procedure to pre-process data used in a vector autoregressive (VAR) modeling of a temporal point process by using kernel density estimation. Vector autoregressive modeling of point-process data, for example, is being used for causality inference. The VAR model discretizes the timeline into small windows, and creates a time series by the presence of events in each window, and then models the presence of an event at the next time step by its history. The problem is that to get a longer history with high temporal resolution required a large number of windows, and thus, model parameters. We proposed the local density estimation procedure, which, instead of using the binary presence as the input to the model, performed kernel density estimation of the event history, and discretized the estimation to be used as the input. This allowed us to reduce the number of model parameters, especially in sparse data. Our experiment on a sparse Poisson process showed that this procedure vastly increases model prediction performance.
Publication Date: 2024/11/01

Research growth in organisational behaviour research, has increased the importance of paying attention to anti-citizenship behaviours. The current research with the aim of quantitative combination, has examined the results of research in effect of underlying factors of organisational anti-citizenship behaviours using meta-analysis method and CMA2 software and 55 articles during the time period of 2000-2020. The results showed a positive significant link between underlying factors of organisational anti-citizenship behaviours and occurrence of these behaviours and this influence was 0.389, 0.338, 0514 and 0.498 (structural, organisational, managerial, employment and professional and socio-economic and cultural factors). The level of connection found relating to each four occurrences is '68 links, 49 links, 93 links and 71 links'. Findings indicate that minute attention has been paid to organisational anti-citizenship behaviours, especially to job and professional factors in research works. Research should be conducted to control and manage these behaviours more purposefully in organisations.

Ph.D. Dissertation Defense Modeling and Extracting Information about Cybersecurity Events from Text Taneeya Satyapanich 9:30-11:30 Monday, 18 November, 2019, ITE346? People now rely on the Internet to carry out much of their daily activities such as banking, ordering food, and socializing with their family and friends. The technology facilitates our lives, but also comes with […]

The post Defense: Taneeya Satyapanich, Modeling and Extracting Information about Cybersecurity Events from Text appeared first on UMBC ebiquity.

The PALS system captures physical context from sensed data, reasons about the context and associated context-driven policies to make access-control decisions and detect intrusions into smart home systems based on both network and behavioral data

The post paper: Context Sensitive Access Control in Smart Home Environments appeared first on UMBC ebiquity.

A man threatened to push a nine-year-old girl in the Union Canal as she cycled home from football training.

LaToya claimed self-defense, but Manassas, Virginia Prosecutor D. Burke Walker had other ideas and charged the woman with second-degree murder.

Discover the Personal Defense Weapon (PDW) - the perfect balance of firepower and portability for those in need of a defensive weapon.

President Donald Trump laid out a bold vision for America’s future—one where freedom of speech is non-negotiable, and censorship from both government and big tech is crushed.

In our civilization, any application of lethal force upon another human being is a fantastically high-stakes affair! Even if it saves your life!

WASHINGTON: U.S. President-elect Donald Trump said on Tuesday he has picked Fox News Channel host Pete Hegseth to be secretary of defense, tapping an outsider who has railed against diversity in the military.

“Pete is tough, smart and a true believer in America First,“ Trump said in a statement. “With Pete at the helm, America’s enemies are on notice - Our Military will be Great Again, and America will Never Back Down.”

Hegseth is an Army National Guard veteran and according to his website served in Afghanistan, Iraq, and Guantanamo Bay, Cuba.

Hegseth has said he left the Army in 2021 after being deemed an extremist by an Army that didn't want him anymore.

“The feeling was mutual -- I didn’t want this Army anymore either,“ Hegseth said in his book “The War on Warriors: Behind the Betrayal of the Men Who Keep Us Free.”

There is already anxiety in the Pentagon that Trump aims to root out military officers and career civil servants he perceives to be disloyal.

Culture war issues could be one trigger for firings. Trump was asked by Fox News in June whether he would fire generals described as “woke,“ a term for those focused on racial and social justice but which is used by conservatives to disparage progressive policies.

“At a basic level, do we really want only the woke ‘diverse’ recruits that the Biden administration is curating to be the ones with the guns and the guidons?” Hegseth wrote in “The War on Warriors,“ which was published in June.

“We want those diverse recruits -- pumped full of vaccines and even more poisonous ideologies -- to be sharing a basic training bunk with sane Americans,“ he said.

Trump's former U.S. generals and defense secretaries are among his fiercest critics, with some declaring him unfit for office. Angered, Trump has suggested that his former chairman of the Joint Chiefs of Staff, Mark Milley, could be executed for treason.

BATU KAWAN: US-based medical devices company Dexcom Inc has officially opened its manufacturing facility, also its first offshore manufacturing site outside the United States, in Batu Kawan, Penang.

Penang Chief Minister Chow Kon Yeow said the RM2.83 billion strategic investment will bring more than 3,000 jobs to the state, contributing to a workforce set to positively impact the lives of over three million people worldwide.

Dexcom, founded in 1999, is a global leader in continuous glucose Monitoring (CGM) technology for individuals living with diabetes.

“The establishment of this new facility highlights Dexcom’s continued commitment to take control of health through innovative CGM systems. It also reaffirms Penang’s reputation as a global hub for advanced technological industries, reinforcing its position as a preferred destination for high-quality manufacturing and innovation,” the chief minister said in his speech at the opening ceremony here today.

Chow said Penang is on the right path towards becoming the medical technology (medtech) hub of Southeast Asia by leveraging on the state’s over 50 years of industry excellence.

“Housing the largest number of medtech companies nationally and regionally, Penang remains a highly attractive location for its infrastructure availability and ecosystem that meet the needs of the medtech industry.

“For the past five years (2019-2023), Penang garnered a total of RM5.8 billion worth of investments in the scientific and measuring equipment sector, representing 45% of the nation’s total investments in this sector, involving 33 projects and generating an estimated 4,630 employment opportunities,” he said.

Dubbed the Silicon Valley of the East, Penang has the highest concentration of medical technology companies in Malaysia and Southeast Asia to date. – Bernama

KUALA LUMPUR: As the takaful industry contends with escalating medical inflation and the rising costs of healthcare, the Malaysian Takaful Association (MTA) has called for increased government and private sector collaboration to ensure affordable, accessible protection options for all Malaysians.

MTA CEO Mohd Radzuan Mohamed envisions takaful becoming a leading option for Malaysians seeking protection.

With only 60% of the population currently insured or covered by takaful, he sees untapped potential among the remaining 40%, primarily in underserved and unserved communities.

“Our goal is to make takaful an accessible option, particularly for groups like the BM40 (top 20% of B40 and bottom 40% M40), who often do not receive enough attention from traditional agents,” he told SunBiz at the recent launch of Hijrah27.

Radzuan said the takaful sector has struggled to expand its market share, currently at about 20% after four decades.

In response, he said, they are considering how digital transformation, distribution enhancements and technology can address these challenges.

“Malaysia’s transformation plan and recent initiatives, like the financial sector blueprint, outline steps to close this gap by focusing on underserved communities, leveraging financial literacy campaigns, and engaging technology to make takaful accessible,” he added.

Additionally, he said co-payments, a shared cost model between the insurer and the insured, is seen as a potential solution to rising premiums fuelled by medical inflation.

“Collaborating with the Ministry of Health and Bank Negara Malaysia, takaful providers aim to develop cost-sharing models that help balance affordability and coverage. With co-payments, premiums could become more manageable, helping to mitigate the effects of medical inflation and making Takaful accessible for more people.”
While the adoption of co-payments is currently optional, Radzuan said, making it mandatory could have far-reaching implications on the takaful industry. “A balanced co-payment structure can be beneficial, but affordability must remain a priority to avoid defeating the purpose of protection,” he emphasised.

Looking forward, Radzuan said the association is exploring new technology-driven initiatives, such as the Hijrah27 framework, to improve customer service and operational efficiency. “Collaborations with fintech firms and the rise of AI-based solutions also show promise in elevating the industry’s standards and expanding reach,” he added.

KUALA LUMPUR: The ringgit opened marginally higher against the US dollar today despite the US Dollar Index’s (DXY) strengthening, which should accelerate demand for the greenback.

At 8 am, the local note traded slightly better at 4.4330/4465 against the greenback compared with Tuesday’s close of 4.4365/4400.

Bank Muamalat Malaysia Bhd chief economist Dr Mohd Afzanizam Abdul Rashid said higher demand for the US dollar is expected as comments from US Federal Reserve (Fed) officials indicated that the prospect of an interest rate cut highly depends on upcoming economic data.

“Minneapolis Fed president Neel Kashkari suggested that he will look at the upcoming inflation data before making any decision on the interest rate.

“As such, ringgit and other emerging market currencies will likely stay weak in the near term,” Mohd Afzanizam told Bernama.

He added investors will monitor the US Consumer Price Index (CPI) print tonight, with consensus pencilling in a 2.6 per cent rise in October from 2.4 per cent previously, while Core CPI may be sustained at 3.3 per cent.

At the opening, the ringgit traded higher against a basket of major currencies.

It was higher against the British pound at 5.6463/6635 from 5.6889/6934 at Tuesday’s close, better against the euro to 4.7061/7204 from 4.7111/7148 and firmer against the Japanese yen to 2.8661/8752 from 2.8788/8812.

The ringgit also traded higher against ASEAN currencies.

Against the Thai baht, it rose to 12.7162/7637 from 12.7456/7608 at Tuesday’s close and strengthened against the Singapore dollar at 3.3107/3210 from 3.3143/3174.

The local unit marginally increased vis-a-vis the Philippine peso to 7.53/7.56 from 7.54/7.55 and was slightly higher against the Indonesian rupiah to 280.8/281.9 from 281.0/281.5 previously.

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