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Machine Learning is an intelligent methodology used for prediction and has shown promising results in predictive classifications. One of the critical areas in which machine learning can save lives is diabetes prediction. Diabetes is a chronic disease and one of the 10 causes of death worldwide. It is expected that the total number of diabetes will be 700 million in 2045; a 51.18% increase compared to 2019. These are alarming figures, and therefore, it becomes an emergency to provide an accurate diabetes prediction.

Health professionals and stakeholders are striving for classification models to support prognosis of diabetes and formulate strategies for prevention. The authors conduct literature review of machine models and propose an intelligent framework for diabetes prediction.

The authors provide critical analysis of machine learning models, propose and evaluate an intelligent machine learning-based architecture for diabetes prediction. The authors implement and evaluate the decision tree (DT)-based random forest (RF) and support vector machine (SVM) learning models for diabetes prediction as the mostly used approaches in the literature using our framework.

This paper provides novel intelligent diabetes mellitus prediction framework (IDMPF) using machine learning. The framework is the result of a critical examination of prediction models in the literature and their application to diabetes. The authors identify the training methodologies, models evaluation strategies, the challenges in diabetes prediction and propose solutions within the framework. The research results can be used by health professionals, stakeholders, students and researchers working in the diabetes prediction area.

Nutrition labels provide a cost-effective method of conveying nutrition information to consumers. This study aimed to assess the use of nutrition facts panels, knowledge of traffic light labelling (TLL) and perceived healthiness of food items using TLL among consumers.

A web-based cross-sectional study was conducted among adults in the United Arab Emirates (UAE) (n = 1,322). TLL knowledge score was derived for each participant. Conjoint analysis was used to calculate the utilities and relative importance of the perceived healthiness scores for four attributes (fat, saturated fat, total sugar, salt) at the aggregate level.

Participants had a positive attitude towards TLL but were less familiar with TLL than the nutrition facts panel (47.4 vs 85.8%). The mean TLL knowledge score was 3.6 out of 7 (51.6%). Younger age, higher education, higher income, and health-related qualifications were associated with higher scores. Conjoint analysis showed that participants tend to choose products with greener labels, especially for sugars (80.1%) and avoid red labels for fats. Sugars had the highest percentage value of relative importance compared to the other attributes (27.1%).

The study outcomes offer valuable insights into the extent of consumer awareness, comprehension and utilization of nutrition facts panels in the UAE. These findings contribute essential knowledge for a deeper understanding of the impact of nutrition labels on consumer behaviour and decision-making in the region.

Vending machines (VMs) provide quick access for snack foods and beverages for students during their study days. These vended foods have been reported to affect the student's nutritional status and contributing to obesity by increasing the caloric intake. This study aimed to evaluate the nutritional value of snacks and beverages provided by VM at the university campuses.

A cross-sectional observational study in one large urban university with four campuses was conducted. In total, 55 VMs were found distributed over 50 buildings of the four university campuses. Of the vending slots surveyed, only 57 snacks and beverage food items were found repeated. These items were vended and analyzed using nutrient databases, and their nutritional quality was assessed using nutrient adequacy ratio and nutritional quality score.

Most vended snacks were salty (77%) and sweet (23%). Neither snacks nor beverages were nutrient-dense, and the majority (65%) of snacks and beverages were calorie-dense, with high contents of sugar, sodium and saturated fat; while they were low in vitamins C and A, calcium, iron, sodium, protein and dietary fibers. None of the vended beverages met the low calorie, low sugars and high-fiber criteria.

One limitation of the current work is represented in the fact that VM snacks and beverages are not fixed throughout the year days, and exposed to continuous changes, depending on the customers' attitudes and economic and financial considerations related to the operating contractor company and the customer students. Thus, a continuous, long-term evaluation is suggested to be conducted for a more representative and reflective evaluation of the nutritional quality of vended snacks and beverages.

Poor nutritional quality has been found for vended foods. Healthier food options should be provided to improve students' dietary intake.

Attention has to be directed toward the nutritional quality of VM foods, and how to provide adolescents and young adults with healthy options.

This is the first study conducted in the United Arab Emirates (UAE) and Gulf Cooperation Council countries (GCC) assessing the nutritional value of vending machine foods in university settings.

As the work context is dynamically changing, enhancing employee engagement through personal and organizational means is still capturing the attention of organizations as well as human resources researchers and practitioners. Thus, the purpose of this paper is to examine the relationships between self-leadership, employee engagement, and perceived organizational support and to test the moderating effect of perceived organizational support.

Data were collected through an online self-reporting questionnaire, with a total of 225 employees from Lebanon and 251 employees from the United Arab Emirates (UAE). Moderating analysis was conducted using Process v3.3 on both samples.

Results have shown that self-leadership and perceived organizational support were positively related to employee engagement in both countries. However, perceived organizational support served to enhance self-leadership and employee engagement in the UAE, but not in Lebanon.

The findings of this study can be used to help organizations as well as human resources and regional managers operating in the Middle East in giving insights about investing in self-leadership strategies and positively influence employee perception of organizational support to strengthen employee engagement.

This study is unique in exploring the moderating role of perceived organizational support on the relationship between self-leadership and engagement, and original in theoretically proposing and empirically examining the interaction between perceived organizational support and self-leadership. The context of the study in which the proposed relationships were tested for the first time in Lebanon and the UAE, is also novel as both countries are distinguished from other Middle Eastern countries.

Engaged employees are a critical asset in any business. This is largely because engaged employees tend to proffer innovative solutions to complex problems in the workplace. The purpose of this paper is to examine the relationship between engagement and innovation as moderated by the use of 360-degree evaluation.

A survey targeting employees in Lebanon solicited their perceptions of 360-degree evaluation, engagement and innovative behaviors along with a statement as to whether their firm used 360-degree evaluations or not. Structural equation modeling (SEM) was used to test the moderating effect of 360-degree evaluations on the latent variables of engagement and three facets of innovation.

SEM results show that 360-degree evaluations serve to enhance engaged employees’ innovative work behavior. However, ideation (creation and implementation) behaviors are more strongly influenced by the presence of 360-degree evaluation as compared to their “tangible” counterpart (technology and financial resource use).

Respondents selected for this research were randomly sampled employees in Lebanon. A stronger study strategy would be to study paired departments within organizations – one implementing 360-degree evaluation and another not implementing it.

Managers, seeking to engender and strengthen innovative behaviors in engaged employees, should utilize 360-degree evaluation processes. Furthermore, the 360-degree evaluations should be designed to probe both tangible (technology and financial resource use) and intangible (idea generation and implementation) facets of innovation.

This study yields a deeper understanding of the relationship between engagement and innovative behaviors in the workplace along with managerial insights into the design and use of 360-degree evaluation.

This study aims to evaluate 125 research libraries in North America to identify whether they incorporate reference and social networking tools in their library's website.

A content analysis of 125 library websites is conducted to determine whether libraries who are members of the Association of Research Libraries (ARL) incorporate and promote reference and social networking tools in their website. For the purpose of this study, a list of reference and social networking tools was chosen and each library's website was visited to determine first, which reference and social networking tools from this list appear on their library's homepage and, second, which tools appear elsewhere on the library's website.

The results show that even though most of these reference and social networking tools are incorporated into their library's websites, their presence is lower on their library's homepage.

Academic and research libraries should incorporate reference and social networking tools on their library's homepage to make these services more visible and more easily accessible to their users.

This study demonstrates the importance of the right placement for reference and social networking tools on ARL websites.

In this study, the central objective is to foresee stock market signals with the use of a proper structure to achieve the highest accuracy possible. For this purpose, three hybrid models have been developed for the stock markets which are a combination of support vector machine (SVM) with meta-heuristic algorithms of particle swarm optimization (PSO), imperialist competition algorithm (ICA) and genetic algorithm (GA).All the analyses are technical and are based on the Japanese candlestick model.

Further as per the results achieved, the most suitable algorithm is chosen to anticipate sell and buy signals. Moreover, the authors have compared the results of the designed model validations in this study with basic models in three articles conducted in the past years. Therefore, SVM is examined by PSO. It is used as a classification agent to search the problem-solving space precisely and at a faster pace. With regards to the second model, SVM and ICA are tested to stock market timing, in a way that ICA is used as an optimization agent for the SVM parameters. At last, in the third model, SVM and GA are studied, where GA acts as an optimizer and feature selection agent.

As per the results, it is observed that all new models can predict accurately for only 6 days; however, in comparison with the confusion matrix results, it is observed that the SVM-GA and SVM-ICA models have correctly predicted more sell signals, and the SCM-PSO model has correctly predicted more buy signals. However, SVM-ICA has shown better performance than other models considering executing the implemented models.

In this study, the data for stock market of the years 2013–2021 were analyzed; the long length of timeframe makes the input data analysis challenging as they must be moderated with respect to the conditions where they have been changed.

In this study, two methods have been developed in a candlestick model; they are raw-based and signal-based approaches in which the hit rate is determined by the percentage of correct evaluations of the stock market for a 16-day period.

In this research, the main purpose is to use a suitable structure to predict the trading signals of the stock market with high accuracy. For this purpose, two models for the analysis of technical adaptation were used in this study.

It can be seen that support vector machine (SVM) is used with particle swarm optimization (PSO) where PSO is used as a fast and accurate classification to search the problem-solving space and finally the results are compared with the neural network performance.

Based on the result, the authors can say that both new models are trustworthy in 6 days, however, SVM-PSO is better than basic research. The hit rate of SVM-PSO is 77.5%, but the hit rate of neural networks (basic research) is 74.2.

In this research, two approaches (raw-based and signal-based) have been developed to generate input data for the model: raw-based and signal-based. For comparison, the hit rate is considered the percentage of correct predictions for 16 days.

The purpose of this study was to identify the challenges and solutions in the empowerment of families of children with autism in Tabriz located in the North West of Iran.

In this exploratory and qualitative study, which was conducted from January to March 2019, 14 in-depth face-to-face interviews and 1 focus group (n = 5) were conducted with family empowerment experts. Data analysis was performed based on a content analysis approach via MAXQDA v 10.

Results revealed that empowerment challenges can be classified into six main themes including shortage of facilities and specialists, family-related problems, administrative and organizational, cultural and societal, financial and other problems. The most important empowerment solutions were divided into three main themes including informing and training skills by holding empowerment programs, governmental and insurance companies support, and organizational and administrative solutions.

Limitation of this study is that families are not included; as families may also provide or challenge other solutions for empowerment based on their needs, ignoring their views may be losing part of vital information in this field. It is recommended that this research be conducted in the future from the perspective of families of people with autism and other stakeholders.

Based on the results of this study, stakeholders in the field of autism and the family empowerment can address the identified challenges and utilize solutions to improve the process of family empowerment and make more effective decisions in this regard.

Literature searches revealed a lack of any completed research in Iran specific to identifying empowerment challenges and related solutions. Efforts must be taken on root challenges which have been identified scientifically.

The goal of this research is to empirically assess whether knowledge management (KM) and learning organizations (LO) are distinct concepts and if so, to test whether KM enhances LO more or vice versa.

The authors propose an approach by which they first empirically assess the independence of those two concepts, then KM's fundamental processes, being knowledge acquisition, sharing, and utilization, are hypothesized to have a positive relationship with the different LO dimensions. Retail business employees working in organizations in Lebanon were surveyed. KM processes were first designated as dependent variables and then as independent variables. Bartlett's test, Pearson correlation, factor analysis, and regression analysis were used to test the hypothesis.

The results indicated that the two dimensions LO and KM are distinct and that KM enhances LO more than LO enhances KM.

This research extends the impact of knowledge management to include informal processes. It provides empirical evidence that managers should seek to implement formal and informal knowledge management processes into their organizational culture to enable a dynamic learning environment.

This research is significant in that up to this point the relationship between KM and LO has been posited and supported through anecdotal evidence and observation. This research provides empirical evidence of the relationship and forms the basis for further study in this area.