Aim/Purpose: Executive doctoral programs in higher education are under-researched. Scholars, administers, and students should be aware of all common delivery methods for higher education graduate programs. Background This paper provides a review and analysis of executive doctoral higher education programs in the United States. Methodology: Executive higher education doctoral programs analyzed utilizing a qualitative demographic market-based analysis approach. Contribution: This review of executive higher education doctoral programs provides one of the first investigations of this segment of the higher education degree market. Findings: There are twelve programs in the United States offering executive higher education degrees, though there are less aggressively marketed programs described as executive-style higher education doctoral programs that could serve students with similar needs. Recommendations for Practitioners: Successful executive higher education doctoral programs require faculty that have both theoretical knowledge and practical experience in higher education. As appropriate, these programs should include tenure-line, clinical-track, and adjunct faculty who have cabinet level experience in higher education. Recommendation for Researchers: Researchers should begin to investigate more closely the small but growing population of executive doctoral degree programs in higher education. Impact on Society: Institutions willing to offer executive degrees in higher education will provide training specifically for those faculty who are one step from an executive position within the higher education sector. Society will be impacted by having someone that is trained in the area who also has real world experience. Future Research: Case studies of students enrolled in executive higher education programs and research documenting university-employer goals for these programs would enhance our understanding of this branch of the higher education degree market.

Aim/Purpose: Medical images are very sensitive data that can be transferred to medical laboratories, professionals, and specialist for referral cases or consultation. Strict security measures must be utilized to keep these data secured in computer networks when transferred to another party. On a daily basis, unauthorized users derive ways to gain access to sensitive patient medical information. Background: One of the best ways to which medical image could be kept secured is through the use of quantum cryptography Methodology : Applying the principles of quantum mechanics to cryptography has led to a remarkable new dimension in secured network communication infrastructure. This enables two legitimate users to produce a shared secret random bit string, which can be used as a key in cryptographic applications, such as message encryption and authentication. Contribution: This paper can make it possible for the healthcare and medical professions to construct cryptographic communication systems to keep patients’ transferred data safe and secured. Findings: This work has been able to provide a way for two authorized users who are in different locations to securely establish a secret network key and to detect if eavesdropping (a fraudulent or disruption in the network) has occurred Recommendations for Practitioners: This security mechanism is recommended for healthcare providers and practitioners to ensure the privacy of patients’ medical information. Recommendation for Researchers: This paper opens a new chapter in secured medical records Impact on Society Quantum key distribution promises network security based on the fundamental laws of quantum mechanics by solving the problems of secret-key cryptography . Future Research: The use of post-quantum cryptography can be further researched.

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: The aim of this study was to develop a prototype of an information-generating computer tool designed to automatically map the dental restorations in a panoramic radiograph. Background: A panoramic radiograph is an external dental radiograph of the oro-maxillofacial region, obtained with minimal discomfort and significantly lower radiation dose compared to full mouth intra-oral radiographs or cone-beam computed tomography (CBCT) imaging. Currently, however, a radiologic informative report is not regularly designed for a panoramic radiograph, and the referring doctor needs to interpret the panoramic radiograph manually, according to his own judgment. Methodology: An algorithm, based on techniques of computer vision and machine learning, was developed to automatically detect and classify dental restorations in a panoramic radiograph, such as fillings, crowns, root canal treatments and implants. An experienced dentist evaluated 63 panoramic anonymized images and marked on them, manually, 316 various restorations. The images were automatically cropped to obtain a region of interest (ROI) containing only the upper and lower alveolar ridges. The algorithm automatically segmented the restorations using a local adaptive threshold. In order to improve detection of the dental restorations, morphological operations such as opening, closing and hole-filling were employed. Since each restoration is characterized by a unique shape and unique gray level distribution, 20 numerical features describing the contour and the texture were extracted in order to classify the restorations. Twenty-two different machine learning models were evaluated, using a cross-validation approach, to automatically classify the dental restorations into 9 categories. Contribution: The computer tool will provide automatic detection and classification of dental restorations, as an initial step toward automatic detection of oral pathologies in a panoramic radiograph. The use of this algorithm will aid in generating a radiologic report which includes all the information required to improve patient management and treatment outcome. Findings: The automatic cropping of the ROI in the panoramic radiographs, in order to include only the alveolar ridges, was successful in 97% of the cases. The developed algorithm for detection and classification of the dental restorations correctly detected 95% of the restorations. ‘Weighted k-NN’ was the machine-learning model that yielded the best classification rate of the dental restorations - 92%. Impact on Society: Information that will be extracted automatically from the panoramic image will provide a reliable, reproducible radiographic report, currently unavailable, which will assist the clinician as well as improve patients’ reliance on the diagnosis. Future Research: The algorithm for automatic detection and classification of dental restorations in panoramic imaging must be trained on a larger dataset to improve the results. This algorithm will then be used as a preliminary stage for automatically detecting incidental oral pathologies exhibited in the panoramic images.

Aim/Purpose: Little is known of the cultural competence or leadership styles of a minority owned newspaper. This autoethnography serves to benchmark one early 1990s example. Background: I focused on a series of flashbacks to observe an African American weekly newspaper editor-in-chief for whom I reported to 25 years ago. In my reflections I sought to answer these questions: How do minorities in entrepreneurial organizations view their own identity, their cultural competence? What degree of this perception is conveyed fairly and equitably in the community they serve? Methodology: Autoethnography using both flashbacks and article artifacts applied to the leadership of an early 1990s African American weekly newspaper. Contribution: Since a literature gap of minority newspaper cultural competence examples is apparent, this observation can serve as a benchmark to springboard off older studies like that of Barbarin (1978) and that by examining the leadership styles and editorial authenticity as noted by The Chicago School of Media Theory (2018), these results can be used for comparison to other such minority owned publications. Findings: By bringing people together, mixing them up, and conducting business any other way than routine helped the Afro-American Gazette, Grand Rapids, proudly display a confidence sense of cultural competence. The result was a potentiating leadership style, and this style positively changed the perception of culture, a social theory change example. Recommendations for Practitioners: For the minority leaders of such publications, this example demonstrates effective use of potentiating leadership to positively change the perception of the quality of such minority owned newspapers. Recommendations for Researchers: Such an autoethnography could be used by others to help document other examples of cultural competence in other minority owned newspapers. Impact on Society: The overall impact shows that leadership at such minority owned publications can influence the community into a positive social change example. Future Research: Research in the areas of culture competence, leadership, within minority owned newspapers as well as other minority alternative publications and websites can be observed with a focus on what works right as well as examples that might show little social change model influence. The suggestion is to conduct the research while employed if possible, instead of relying on flashbacks.

Aim/Purpose: To capture digital training experiences, the paper introduces a novel data collection method – a graphic questionnaire. It aims to demonstrate the opportunities and limitations of this tool for collecting feedback from socially disadvantaged participants of digital literacy training about their progress. Background: In training of digital skills for disadvantaged audiences through informal educational interventions, it is important to get sufficient knowledge on factors that lead to their progress in the course of training. There are many tools to measure the achievements of formal education participants, but assessing the effectiveness of informal digital skills training is researched less. The paper introduces a small-scale case study of the training programme aimed at the developing of reading and digital skills among the participants from three socially disadvantaged groups – people with hearing impairments, children from low income families, and elderly persons. The impact of the training on participants was evaluated using different tools, including a short graphic questionnaire to capture the perceptions of the participants after each training. Methodology: We performed a thematic analysis of graphic questionnaires collected after each training session to determine how the students perceived their progress in developing literacy and digital skills. Contribution The findings of the paper can assist in designing assessment of digital literacy programmes that focus not only on final results, but also on the process of gaining digital skills and important factors that facilitate progress. Findings: The graphic questionnaire allowed the researchers to get insights into the perception of acquired skills and progressive achievements of the participants through rich self-reports of attitudes, knowledge gained, and activities during training sessions. However, the graphic questionnaire format did not allow the collection of data about social interaction and cooperation that could be important in learning. Recommendations for Practitioners: Graphic questionnaires are useful and easy-to-use tools for getting rich contextual information about the attitudes, behaviour, and acquisition of knowledge in digital literacy training. They can be used in applied assessments of digital literacy training in various settings. Their simplicity can appeal to respondents; however, in the long-run interest of respondents in continuing self-reports should be sustained by additional measures. Recommendations for Researchers: Researcher may explore the variety of simple and attractive research instruments, such as “honeycomb” questionnaires and similar, to facilitate data collection and saturate feedback with significant perception of personal experiences in gaining digital literacy skills. Impact on Society: Designing effective digital literacy programmes, including engaging self-assessment methods and tools, aimed at socially disadvantaged people will contribute to their digital inclusion and to solving the issues of digital divide. Future Research: Exploration of diverse research methods and expanding the research toolset in assessing digital literacy training could advance our understanding of important processes and factors in gaining digital skills.

Aim/Purpose: This work aims to understand why a disparity between the popularity of smart phones and the limited adoption of m-banking exists. Accordingly, this study investigates factors that affect a person’s decision to adopt m-banking services. Such an investigation seeks to determine if and to what extent customers’ mobile phone experience as well as their awareness of m-banking services influence their intention to use such services? Background: This study developed a conceptual model to determine the influence that users’ mobile phone experience as well as users’ awareness of m-banking services had on users’ behavioral intention to use m-banking in Saudi Arabia. Methodology: The quantitative method used to collect data was a survey questionnaire tech-nique. A questionnaire with non-structured (close-ended) questions was formulated. A random sample, targeting banking customers in Saudi Arabia, was selected. This study collected data using a cross-sectional survey. Of those surveyed, 389 provided valid responses eligible for data analysis. SPSS v.22 was used to analyze the data. Contribution: This study produced helpful results and a new m-banking conceptual model. The developed conceptual model focused integrally on users’ awareness and experience as antecedents of m-banking adoption and highlighted the im-portance of differentiating between measuring the users’ characteristics in adopting e-banking in general and m-banking services in particular. In addition, this type of model has the ability to synthesize new control variables as well as to study technology acceptance in developing countries. This study, based on an extended UTAUT model, set out to discover what factors might affect customers’ intentions to use m-banking in Saudi Arabia. Findings: The results show that service awareness has a direct effect on performance and effort expectancy, but not on perceived risk. Moreover, mobile phone experience fails to impact the relationships in the same hypothesized direction. As anticipated, performance expectancy, effort expectancy, and perceived risk have direct and significant effects on behavioral intentions to use m-banking. However, customer awareness fails to impact the relationships of performance expectancy, effort expectancy, and perceived risk on behavioral intentions to use m-banking. Recommendations for Practitioners: Banks should target customers by distributing useful information and applying measures to increase acceptance. Banks need to introduce something imaginative to convince bank customers to abandon existing service channels and adopt m-banking services. Banks should make m-banking services the easiest service for conducting bank transactions and/or help customers conduct transactions that they cannot do any other way. Recommendation for Researchers: Other factors, such as trust, culture, and/or credibility should be investigated along with user’s awareness and experience factors in m-banking services. There is a need to focus on a specific type of m-banking. Thus, it may be fruitful to study the adoption of different systems of m-banking services. Impact on Society: This study suggests that m-banking services should be designed and built based on a deep understanding of customers’ needs using extensive testing to assure that applications and sites function well in a mobile setting. Future Research: Future researchers should apply the conceptual model developed in this study in different settings, different countries, and to different technologies.

Aim/Purpose: The paper’s objective is to examine the challenges of using the mobile phone to mine location data for effective contact tracing of symptomatic, pre-symptomatic, and asymptomatic individuals and the implications of this technology for public health governance. Background: The COVID-19 crisis has created an unprecedented need for contact tracing across South Africa, requiring thousands of people to be traced and their details captured in government health databases as part of public health efforts aimed at breaking the chains of transmission. Contact tracing for COVID-19 requires the identification of persons who may have been exposed to the virus and following them up daily for 14 days from the last point of exposure. Mining mobile phone location data can play a critical role in locating people from the time they were identified as contacts to the time they access medical assistance. In this case, it aids data flow to various databases designated for COVID-19 work. Methodology: The researchers conducted a review of the available literature on this subject drawing from academic articles published in peer-reviewed journals, research reports, and other relevant national and international government documents reporting on public health and COVID-19. Document analysis was used as the primary research method, drawing on the case studies. Contribution: Contact tracing remains a critical strategy in curbing the deadly COVID-19 pandemic in South Africa and elsewhere in the world. However, given increasing concern regarding its invasive nature and possible infringement of individual liberties, it is imperative to interrogate the challenges related to its implementation to ensure a balance with public governance. The research findings can thus be used to inform policies and practices associated with contact tracing in South Africa. Findings: The study found that contact tracing using mobile phone location data mining can be used to enforce quarantine measures such as lockdowns aimed at mitigating a public health emergency such as COVID-19. However, the use of technology can expose the public to criminal activities by exposing their locations. From a public governance point of view, any exposure of the public to social ills is highly undesirable. Recommendations for Practitioners: In using contact tracing apps to provide pertinent data location caution needs to be exercised to ensure that sensitive private information is not made public to the extent that it compromises citizens’ safety and security. The study recommends the development and implementation of data use protocols to support the use of this technology, in order to mitigate against infringement of individual privacy and other civil liberties. Recommendation for Researchers: Researchers should explore ways of improving digital applications in order to improve the acceptability of the use of contact tracing technology to manage pandemics such as COVID-19, paying attention to ethical considerations. Impact on Society: Since contact tracing has implications for privacy and confidentiality it must be conducted with caution. This research highlights the challenges that the authorities must address to ensure that the right to privacy and confidentiality is upheld. Future Research: Future research could focus on collecting primary data to provide insight on contact tracing through mining mobile phone location data. Research could also be conducted on how app-based technology can enhance the effectiveness of contact tracing in order to optimize testing and tracing coverage. This has the potential to minimize transmission whilst also minimizing tracing delays. Moreover, it is important to develop contact tracing apps that are universally inter-operable and privacy-preserving.

Aim/Purpose: The study aims to explore the attributes of self-phubbing and partner-phubbing, as well as their impact on marital relationship satisfaction and the quality of communication. Furthermore, it aims to comprehend how these characteristics could impact an individual’s total level of life satisfaction. Background: The study aims to establish a clear association between specific mobile phone usage behaviors and their subsequent impact on relationship satisfaction and the quality of communication. This study investigates the effects of two types of behaviors on interpersonal relationships: self-phubbing, which refers to an individual being deeply absorbed in their own mobile phone use, and partner-phubbing, which refers to witnessing one’s partner being deeply absorbed in a mobile device. Methodology: This study utilizes a quantitative approach. The poll involved 150 smartphone users in Malaysia who are in relationships, and they participated by completing a questionnaire. The data analysis was performed using the Partial Least Squares-based Structural Equation Modeling method. Contribution: This research addresses the gap and gives insight into the consequences of self and partner phubbing and its impact on the relationship and life satisfaction among partners by providing a research model that was validated with primary data. Findings: The results of this survey show that smartphone conflicts harm relationship satisfaction but not communication quality. It was revealed that communication quality does not directly bring a negative impact on life satisfaction, but it directly affects relationship satisfaction, which, in turn, harms life satisfaction. Recommendations for Practitioners: The findings of this study can be used by practitioners to improve relationship counseling and therapy. Through the integration of the notion of phubbing and its impact on relationship happiness, couples can receive guidance on how to reduce the tension that arises from using smartphones. Recommendation for Researchers: Previous research was conducted exclusively on only an individual’s phubbing behavior, but limited work was done on the partner’s phubbing behavior. Future researchers can enhance this model by identifying more factors. Impact on Society: This study addresses broader societal ramifications in addition to the dynamics of particular relationships. This study promotes a more mindful use of smartphones by exposing the complex relationships between technology use, relationship happiness, and general life contentment. This will ultimately lead to healthier relationships and improved societal well-being. Future Research: In the future, we are going to implement an artificial neural network approach to test this data to predict the most important factors that influence phubbing.

Aim/Purpose: Most people use their phones for work and communication. Businesses today require sustainable mobile phones to limit the environmental impact of mobile phones. According to the Environmental Protection Agency (EPA), a green product uses less energy. Green smartphones need low radiation emission, are made from recyclable materials, and are designed to last longer than typical smartphones. Further, the manufacturing process needs to have a low environmental impact. The present study aims to identify the influence of variables (such as Green Awareness, Environmental Concern, Altruism, and Willingness to Pay) on green smartphone purchase intention among academics in the Sri Lankan higher education sector. Background: With the swift technological advances, almost everyone has begun to use smartphones. Simultaneously, smartphone manufacturers have begun to release cutting-edge smartphone models to the general public. As a result, it has generated a significant amount of e-waste for the environment. As a result, therefore, the sustainability of green smartphones has become a major societal concern in the developed world, but this is not yet true in the developing world Methodology: The study used a qualitative research method in which the authors attempted to acquire primary data by conducting in-depth interviews with academics from the Sri Lankan higher education sector using a semi-structured interview guide. Eight interviews were conducted, audio recorded, and word-to-word transcribed for content analysis. Researchers used content analysis to determine the presence, meanings, and linkages of specific words, themes, or concepts. Contribution: The findings provide important environmental insights for smartphone makers and society, such as introducing waste reduction programs and energy-saving practices and creating awareness among people to change their consumption patterns. The study will provide valuable insights into the green smartphone phone purchasing intentions of academics in a developing country, especially helping green smartphone producers and marketers construct effective tactics with the insight of the current study based on university faculty members’ viewpoints. Findings: The current study’s findings revealed that academics acknowledge the need for environmental protection with an awareness of the green concept and environmental concerns. According to the interviews, most participants intended to move from their present smartphone to an ecologically friendly phone, as they explained on altruism. This implies that even academics in underdeveloped countries are worried about environmental issues and have shown a more robust understanding of these issues and how environmentally aware individuals’ activities may assist the earth’s sustainability. Further, academics have a willingness to pay for a green smartphone. Recommendations for Practitioners: Academics prioritize environmental conservation when making purchases. This implies that manufacturers and enterprises should focus on developing and in- novating more environmentally friendly products. Recommendation for Researchers: Using only academics as a sample approach is severely limited if the study’s population comprises people with various qualities. Nevertheless, this study presented only four independent variables, and more factors impacting green smartphone purchasing intention may exist. As a result, it is proposed that future research consider other factors. Impact on Society: It was discovered that most participants displayed altruism in their product purchases, implying that policymakers must strengthen the moral practice of concern for the welfare and happiness of other humans, even in developing countries. Future Research: A further in-depth study focusing on many perspectives such as limits and motivations for purchasing green products in various socioeconomic groups with varying moderating factors such as gender, education, rural-urban, and so on would be advantageous. Individual (emotions, habits, perceived behavioral control, trust, values, personal norm, knowledge) and situational (availability, product attributes, subjective norm, brand, eco-labeling) variables should be included in future research.

Aim/Purpose: This research aims to evaluate models from meta-learning techniques, such as Riemannian Model Agnostic Meta-Learning (RMAML), Model-Agnostic Meta-Learning (MAML), and Reptile meta-learning, to obtain high-quality metadata. The goal is to utilize this metadata to increase accuracy and efficiency in identifying chili varieties in smart agriculture. Background: The identification of chili varieties in smart agriculture is a complex process that requires a multi-faceted approach. One challenge in chili variety identification is the lack of a large and diverse dataset. This can be addressed using meta-learning techniques, which allow the model to leverage knowledge learned from other related tasks or artificially expand the dataset by applying transformations to existing data. Another challenge is the variation in growing conditions, which can affect the appearance of chili varieties. Meta-learning techniques can help address this challenge by allowing the model to adapt to variations in growing conditions with task-specific embeddings and optimizations. With the help of meta-learning techniques, such as data augmentation, data characterization, selection of datasets, and performance estimation, quality metadata for accurate identification of chili varieties can be achieved even in the presence of limited data and variations in growing conditions. Furthermore, the use of meta-learning techniques in chili variety identification can also assist in addressing challenges related to the computational complexity of the task. Methodology: The research approach employed is quantitative, specifically comparing three models from meta-learning techniques to determine which model is most suitable for our dataset. Data was collected from the variety assembly garden in the form of images of chili leaves using a mobile device. The research successfully gathered 1,974 images of chili leaves, with 697 images of large red chilies, 649 images of curly red chilies, and 628 images of cayenne peppers. These chili leaf images were then processed using augmentation techniques. The results of image data augmentation were categorized based on leaf characteristics (such as oval, lancet, elliptical, serrated leaf edges, and flat leaf edges). Subsequently, training and validation utilized three models from meta-learning techniques. The final stage involved model evaluation using 2-way and 3-way classification, as well as 5-shot and 10-shot learning scenarios to select the dataset with the best performance. Contribution: Improving classification accuracy, with a focus on ensuring high-quality data, allows for more precise identification and classification of chili varieties. Enhancing model training through an emphasis on data quality ensures that the models receive reliable and representative input, leading to improved generalization and performance in identifying chili varieties. Findings: With small collections of datasets, the authors have used data augmentation and meta-learning techniques to overcome the challenges of limited data and variations in growing conditions. Recommendations for Practitioners: By leveraging the knowledge and adaptability gained from meta-learning, accurate identification of chili varieties can be achieved even with limited data and variations in growing conditions. The use of meta-learning techniques in chili variety identification can greatly improve the accuracy and reliability of the identification process. Recommendation for Researchers: Using meta-learning techniques, such as transfer learning and parameter optimization, researchers can overcome challenges related to limited data and variations in growing conditions in chili variety identification. Impact on Society: The findings from this research can help identify superior chili seeds, thereby motivating farmers to cultivate high-quality chilies and achieve bountiful harvests. Future Research: We intend to verify our approach on a more extensive array of datasets and explore the implementation of more resilient regularization techniques, going beyond image augmentation, within the meta-learning techniques. Furthermore, our goal is to expand our research to encompass the automatic learning of parameters during training and tackle issues associated with noisy labels. Building on the insights gained from our observed outcomes, a future objective is to enhance the refinement of model-agnostic meta-learning techniques that can effectively adapt to intricate task distributions with substantial domain gaps between tasks. To realize this aim, our proposal involves devising model-agnostic meta-learning techniques specifically designed for multi-modal scenarios.

Aim/Purpose: The research aims to investigate the factors that influence the continuous use of mobile banking applications to complete banking monetary transactions. Background: Despite a significant increase in the use of mobile banking applications, particularly during the COVID-19 pandemic, new evidence indicates that the use rate of mobile banking applications for operating banking monetary transactions has declined. Methodology: The study proposed an integrated model based mainly on the process virtualization theory (PVT) with other novel factors such as mobile banking application anthropomorphism and virtual process failure risk. The study model was empirically validated using structural equation modeling analysis on quantitative data from 484 mobile banking application users from Jordan. Contribution: The study focuses on continuing use or post-adoption behavior rather than pre-adoption behavior. This is important since the maximum and long-term viability, as well as the financial investment in mobile banking applications, depend on regular usage rather than first-time use or initial experience. Findings: The results indicate that process virtualizable and anthropomorphism have a strong positive impact on bank customers’ decisions to continue using mobile banking applications to complete banking monetary transactions. Meanwhile, the negative impact of virtualization process failure risk on continuous use has been discovered. The found factors explain 67.5% of the variance in continuous use. Recommendations for Practitioners: The study identified novel, significant factors that affect bank customers’ decisions to use mobile banking applications frequently, and these factors should be examined, matched, satisfied, or addressed when redesigning or upgrading mobile applications. Banks should provide users with clear directions, processes, or tutorials on how to complete monetary transactions effectively. They should also embrace Artificial Intelligence (AI) technology to improve their applications and products with anthropomorphic features like speech synthesizers, Chatbots, and AI-powered virtual bank assistants. This is expected to help bank customers conduct various banking services conveniently and securely, just as if interacting with real people. The study further recommends that banks create and publish clear norms and procedures, as well as promote tolerance and protect consumers’ rights when the process fails or mistakes occur. Recommendation for Researchers: The study provides measurement items that were specifically built for the context of mobile banking applications based on PVT notions. Researchers are invited to reuse, test, and modify existing measurement items, as well as submit new ones if necessary. The study model does not consider psychological aspects like trust and satisfaction, which would provide additional insight into factors affecting continuing use. Researchers could potentially take a different approach by focusing on user resistance and non-adoption. Impact on Society: Financial inclusion is problematic, particularly in underdeveloped nations. According to financial inclusion research, Jordanians rarely utilize mobile banking apps. Continuous usage of mobile banking applications will be extremely beneficial in closing the financial inclusion gap, particularly among women. Furthermore, it could help the country’s efforts to transition to a digital society. Future Research: The majority of study participants are from urban areas. Future studies should focus on consumers who live in rural areas. It was also suggested that the elderly be targeted because they may have different views/perspectives on the continued use of mobile banking applications.

Large graphs or automata have their data that cannot fit in a single machine, or may take unreasonable time to be processed. We implement with MapReduce and Giraph two algorithms for intersecting and minimising large and distributed automata. We provide some comparative analysis, and the experiment results are depicted in figures. Our work experimentally validates our propositions as long as it shows that our choice, in comparison with MapReduce one, is not only more suitable for graph-oriented algorithms, but also speeds the executions up. This work is one of the first steps of a long-term goal that consists in a high level distributed graph processing language.

Aim/Purpose: The increasingly growing number of virtual high schools around the world has engendered new modes for teaching and learning and a promising area of re-search. While research in this emerging field has mostly taken a comparative lens that highlights differences between traditional modes of teaching and online teaching, research on high school students’ and teachers’ perspectives has remained dearth. Background: This study identifies students’ and teachers’ perceptions of their learning and teaching advanced level mathematics and/or physics in the first Israeli virtual high school (VHS), which was launched five years ago. Methodology: A survey of 41 questions was disseminated to the first graduating cohort of 86 Grade-12 students as well as to 22 VHS teachers. Additional data sources include students’ essays on what it means to be a student in a VHS and field notes from a pedagogical development day. Contribution: The purpose of this study is to highlight the workings of the Israeli VHS and in particular its important building blocks that include a teacher-tutor model, an ongoing gauging of students’ work through a Learning Management System (LMS), and a continual teacher-developer interaction for the purpose of developing cutting-edge, technology-based course content. Findings: Given the unique features of the Israeli VHS, both teachers and students report on feelings of unit pride, motivation, and investment in teaching and learning in the VHS. Recommendations for Practitioners: The Israeli VHS uses a combination of a teacher-tutor format, together with tools for gauging students’ work and ongoing interaction between the teachers and the course content designers. Such a context creates new, fertile ground for technology-based, fully online teaching and learning of school mathematics and physics that may contribute to alleviating the problem of decreasing numbers of learners who are interested in taking advanced-level courses. Recommendation for Researchers: Further exploration of aspects for improvement in the teaching model of the VHS, its design, and its support system and for finding out factors that impact attrition lay down important research trajectories that have not yet been trodden. Impact on Society: Issues of equity and the democratization of learning of advanced STEM subjects are now possible to be seriously considered in a principled manner within the context of the VHS. Future Research: Future research may focus on the affordances, possibilities, and limitations of learning within a VHS to ensure a more robust process that will allow more students to learn advanced mathematics and physics.

Aim/Purpose: This study examines the influence of Performance Expectancy (PE), Effort Expectancy (EE), and Facilitating Conditions (FC) on the use of smart phones for mobile learning by postgraduate students in University of Ibadan, Nigeria. Background: Due to the low level of mobile learning adoption by students in Nigeria, three base constructs of the Unified Theory of Acceptance and Use of Technology (UTAUT) model were used as factors to determine smart phone use for mobile learning by the postgraduate students in the University of Ibadan. Methodology: The study adopted a descriptive survey research design of the correlational type, the two-stage random sampling technique was used to select a sample size of 217 respondents, and a questionnaire was used to collect data. Descriptive statistics (frequency counts, percentages, mean, and standard deviation), test of norm, and inferential statistics (correlation and regression analysis) were used to analyze the data collected. Contribution: The study empirically validated the UTAUT model as a model useful in predicting smart phone use for mobile learning by postgraduate students in developing countries. Findings: The study revealed that a significant number of postgraduate students used their smart phones for mobile learning on a weekly basis. Findings also revealed a moderate level of Performance Expectancy (???? =16.97), Effort Expectancy (???? =12.57) and Facilitating Conditions (???? =15.39) towards the use of smart phones for mobile learning. Results showed a significant positive relationship between all the independent variables and use of smart phones for mobile learning (PE, r=.527*; EE, r=.724*; and FCs, r=.514*). Out of the independent variables, PE was the strongest predictor of smart phone use for mobile learning (β =.189). Recommendations for Practitioners: Librarians in the university library should organize periodic workshops for postgraduate students in order to expose them to the various ways of using their smart phones to access electronic databases. Recommendation for Researchers: There is a need for extensive studies on the factors influencing mobile technologies adoption and use in learning in developing countries. Impact on Society: Nowadays, mobile learning is increasingly being adopted over conventional learning systems due to its numerous benefits. Thus, this study provides an insight into the issues influencing the use of smart phones for mobile learning by postgraduate students from developing countries. Future Research: This study utilized the base constructs of the UTAUT model to determine smart phone use for mobile learning by postgraduate students in a Nigerian university. Subsequent research should focus on other theories to ascertain factors influencing Information Technology adoption and usage by students in developing countries.

Aim/Purpose: To examine how positive/negative message framing – based on peripheral cues (regarding popularity, source, visuals, and hyperlink) – affects perceptions of credibility of scientific information posted on social networking sites (in this case, Facebook), while exploring the mechanisms of viewing the different components. Background: Credibility assessment of information is a key skill in today's information society. However, it is a demanding cognitive task, which is impossible to perform for every piece of online information. Additionally, message framing — that is, the context and approach used to construct information— may impact perceptions of credibility. In practice, people rely on various cues and cognitive heuristics to determine whether they think a piece of content is true or not. In social networking sites, content is usually enriched by additional information (e.g., popularity), which may impact the users' perceived credibility of the content. Methodology: A quantitative controlled experiment was designed (N=19 undergraduate students), collecting fine grained data with an eye tracking camera, while analyzing it using transition graphs. Contribution: The findings on the mechanisms of that process, enabled by the use of eye tracking data, point to the different roles of specific peripheral cues, when the message is overall peripherally positive or negative. It also contributes to the theoretical literature on framing effects in science communication, as it highlights the peripheral cues that make a strong frame. Findings: The positively framed status was perceived, as expected from the Elaboration Likelihood Model, more credible than the negatively framed status, demonstrating the effects of the visual framing. Differences in participants' mechanisms of assessing credibility between the two scenarios were evident in the specific ways the participants examined the various status components. Recommendations for Practitioners: As part of digital literacy education, major focus should be given to the role of peripheral cues on credibility assessment in social networking sites. Educators should emphasize the mechanisms by which these cues interact with message framing, so Internet users would be encouraged to reflect upon their own credibility assessment skills, and eventually improve them. Recommendation for Researchers: The use of eye tracking data may help in collecting and analyzing fine grained data on credibility assessment processes, and on Internet behavior at large. The data shown here may shed new light on previously studied phenomena, enabling a more nuanced understanding of them. Impact on Society: In an era when Internet users are flooded with information that can be created by virtually anyone, credibility assessment skills have become ever more important, hence the prominence of this skill. Improving citizens' assessment of information credibility — to which we believe this study contributes — results on a greater impact on society. Future Research: The role of peripheral cues and of message framing should be studied in other contexts (not just scientific news) and in other platforms. Additional peripheral cues not tested here should be also taken into consideration (e.g., connections between the information consumer and the information sharer, or the type of the leading image).

Aim/Purpose: This paper aims to investigate how Kuwaiti Academic Libraries (KALs) have responded to the rapidly evolving Smartphone-Apps (SP-Apps) environment, as well as exploring the level of electronic services provided in these libraries. Background: This study can illustrate whether the governmental, academic libraries in the State of Kuwait have already benefited from the mobile services provided by smart phones or not. Methodology: In this study, the researchers use both qualitative and quantitative methods. Therefore, questionnaires and interviews are used in order to collect in-depth data in this field. The questionnaire sample was 400 respondents. They divided in two KALs: Kuwait University Library (KUL) and Public Authority of Applied Education Training Library (PAAETL), while eight individual interviews were conducted one-to-one in this research. Contribution: This paper may be important for academic libraries to identify shortcomings in the smartphones’ content and services they provide and in highlighting efforts by libraries to address their users’ needs in this area. Findings: The findings show that most participants expressed the need to introduce an SP-App to their library. They also confirmed that there are many difficulties in creating an SP-App including lack of budget, lack of awareness of library management, lack of clarity about library management strategic objectives, and vision for an SP-App. Recommendations for Practitioners: Designing SP-Apps that have reliable content and user interface that is easy to use is a considerable challenge. For this reason, the study highly recommends introducing SP-Apps for KALs as soon as possible. Future Research: The recommendations proposed are relevant to Kuwait. Further research may be useful in this field in other developing countries, in order to test or develop the suggested strategy.

Aim/Purpose: The aim is to explore the informing flows framework as interactions within a PhD education practicing a work-integrated learning approach in order to reveal both the perspectives of industrial PhD students and of industry. Background: An under-researched field of university-industry collaboration is explored revealing both the perspectives of industrial PhD students and of industry. Methodology: Qualitative methods were applied including interviews and document studies. In total ten semi-structured interviews in two steps were conducted. The empirical context is a Swedish PhD program in informatics with a specialization in work-integrated learning. Contribution: By broadening the concept of work-integrated learning, this paper contributes empirical results on benefits and challenges in university-industry collaboration focusing on industrial PhD students and industry by applying the informing flows framework. Findings: Findings expose novel insights for industry as well as academia. The industrial PhD students are key stakeholders and embody the informing flows between practice and university and between practice and research. They are spanning boundaries between university and industry generating continuous opportunities for validation and testing of empirical results and models in industry. This may enable increased research quality and short-lag dissemination of research results as well as strengthened organizational legitimacy. Recommendation for Researchers: Academia is recommended to recognize the value of the industrial PhD students’ pre-understanding of the industry context in the spirit of work-integrated learning approach. The conditions for informing flows between research and practice need to continuously be maintained to enable short-term societal impact of research for both academia and industry. For practitioners: This explorative study show that it is vital for practice to recognize that challenges do exist and need to be considered to strengthen industrial PhD pro-grams as well as university-industry collaborations. Additionally, it is of importance to formalize a continuously dissemination of research in the industries. Future Research: Future international and/or transdisciplinary research within this field is encouraged to include larger samples covering other universities and a mix of industrial contexts or comparing industrial PhD students in different phases of their PhD education.

Aim/Purpose: In this article, the subjective perspectives of young people in Ghana on the use of digital media are elaborated. The aim is to make the positions of young people visible in the often adult-dominated discourse on digital media and to overcome adult-centered considerations in academic and public debates. In addition, the focus on young people from the Global South is intended to help make their underrepresented voices present in this discourse. Background: Digital media devices and Internet access are conditional on people’s social, economic, and educational participation. Many people in the Global South in particular are not yet granted such access. For children and young people worldwide, the educational opportunities offered by digital media are associated with potential threats to mental health and well-being. However, young people’s views on digital media are rarely addressed, especially in the Global South. Methodology: Based on a qualitative thematic analysis of responses to open-ended questionnaire questions, young Ghanaians’ views on smartphone use and how it affects academic success are examined. Contribution: By focusing on the subjective perspectives of young people, especially from the Global South, voices that have hardly been heard in the discourse on digital media are made audible. This should help overcome the dominant adult-centered perspectives in this discourse. Findings: For young people in Ghana, digital media are part of their everyday lives and often necessary to succeed at school. At the same time, they are concerned about the dangers, e.g., from overuse or cybercrime, for which they have few strategies to deal with. In their answers, they refer to socio-culturally specific discourses and values as well as to generational hierarchies that they perceive and deal with, which go far beyond the topic of digital media use. This makes clear the social tensions in which the debate about digitalization is embedded. Recommendation for Researchers: Young people’s knowledge of and perspectives on digital media is an important resource for learning to use them in an emancipated way. Future Research: Future research should recognize young people as experts in their own right on the issue, explore ways to include their perspectives in the discourse on digital media use and work with them to harness the future potential of the technology and avoid risks.

Labor pain and its relieving methods is one of the anxieties of mothers having a great impact on the quality of care during delivery as well as the patients' satisfaction. The propensity of using non-medicinal pain relief methods is increasing. The present study aimed to compare the effect of Acupressure at two GB-21 and SP06 points on the severity of labor pain. In this quasi-experimental single blind study started on December 2010 and ended on June 2011 in which 150 primiparous women were divided into three groups of Acupressure at GB-21 point, Acupressure at SP-6 point and control group. The intervention was carried out for 20 min at 3-4 and 20 min at 7-8 cm dilatation of Cervix. The pain severity was measured by Visual Analog Scale before and immediately, 30 and 60 min after the intervention. Then, the data were statistically analyzed. No significant difference was found among the 3 groups regarding the pain severity before the intervention. However, the pain severity it was reduced at 3-4 and 7-8 cm dilatation immediately, 30 and 60 min after the intervention in the two intervention groups compared to the control group (p<0.001). Nonetheless, no statistically significant difference was observed between the two intervention groups (p = 0.93). The results of the study showed that application of Acupressure at two GB-21 and SP-6 points was effective in the reduction of the severity of labor pain. Therefore, further studies are recommended to be performed on the application of Acupressure together with non-medicinal methods.

Myung-Hyun KIM,Seungkwang LEE, Vol.E107-D, No.11, pp.1449-1452
White-box cryptographic implementations often use masking and shuffling as countermeasures against key extraction attacks. To counter these defenses, higher-order Differential Computation Analysis (HO-DCA) and its variants have been developed. These methods aim to breach these countermeasures without needing reverse engineering. However, these non-invasive attacks are expensive and can be thwarted by updating the masking and shuffling techniques. This paper introduces a simple binary injection attack, aptly named clear & return, designed to bypass advanced masking and shuffling defenses employed in white-box cryptography. The attack involves injecting a small amount of assembly code, which effectively disables run-time random sources. This loss of randomness exposes the unprotected lookup value within white-box implementations, making them vulnerable to simple statistical analysis. In experiments targeting open-source white-box cryptographic implementations, the attack strategy of hijacking entries in the Global Offset Table (GOT) or function calls shows effectiveness in circumventing run-time countermeasures.
Publication Date: 2024/11/01

Do firms learn from their failed innovation attempts? Answering this question is important because failure is an integral part of exploratory learning. In this study, we explore whether and under what circumstances firms learn from their small failures in experimentation. Building on organizational learning literature, we examine the conditions under which prior failures influence firms' R&D output amount and quality. An empirical analysis of voluntary patent expirations (i.e., patents that firms give up by not paying renewal fees) in 97 pharmaceutical firms between 1980 and 2002 shows that the number, importance, and timing of small failures are associated with a decrease in R&D output (patent count) but an increase in the quality of the R&D output (forward citations to patents). Exploratory interviews suggest that the results are driven by a multi-level learning process from failures in pharmaceutical R&D. The findings contribute to the organizational learning literature by providing a nuanced view of learning from failures in experimentation.

Identification is integral to mentoring relationships, yet we know relatively little about the process through which mentors and protégés identify with each other, how this mutual identification shifts through the phases of the mentoring relationship, and how identification impacts the quality of the relationship over time. In this paper, we integrate theories of the self, relationships, and relational mentoring to consider the role of identification in informal mentoring. Specifically, we theorize how the process of personal identification occurs in mentoring from the perspective of both the mentor and protégé and offer a model that demonstrates how shifts in identification relate to the quality of the relationship that develops over time. We conclude with a discussion of implications for research and theory in mentoring.

The gun prohibition lobby is promising to double-down its efforts to push through more restrictive gun laws in the wake of Donald Trump's momentous election victory.