Fog computing (FC) has been presented as a modern distributed technology that will overcome the different issues that Cloud computing faces and provide many services. It brings computation and data storage closer to data resources such as sensors, cameras, and mobile devices. The fog computing paradigm is instrumental in scenarios where low latency, real-time processing, and high bandwidth are critical, such as in smart cities, industrial IoT, and autonomous vehicles. However, the distributed nature of fog computing introduces complexities in managing and predicting the execution time of tasks across heterogeneous devices with varying computational capabilities. Neural network models have demonstrated exceptional capability in prediction tasks because of their capacity to extract insightful patterns from data. Neural networks can capture non-linear interactions and provide precise predictions in various fields by using numerous layers of linked nodes. In addition, choosing the right inputs is essential to forecasting the correct value since neural network models rely on the data fed into the network to make predictions. The scheduler may choose the appropriate resource and schedule for practical resource usage and decreased make-span based on the expected value. In this paper, we suggest a model Neural Network model for fog computing task time execution prediction and an input assessment of the Interpretive Structural Modeling (ISM) technique. The proposed model showed a 23.9% reduction in MRE compared to other methods in the state-of-arts.

The widespread adoption of digital technologies in tourism has transformed the data privacy landscape, necessitating stronger safeguards. This study examines the evolving research environment of digital privacy in tourism management, focusing on publication trends, collaborative networks, and social contract theory. A mixed-methods approach was employed, combining bibliometric analysis, social contract theory, and qualitative content analysis. Data from 2004 to 2023 were analyzed using network visualization tools to identify key researchers and trends. The study highlights a significant increase in academic attention after 2015, reflecting the industry's growing recognition of digital privacy as crucial. Social contract theory provided a framework emphasizing transparency, consent, and accountability. The study also examined high-impact articles and the role of publishers like Elsevier and Wiley. The findings offer practical insights for policymakers, industry leaders, and researchers, advocating for ongoing collaboration to address privacy challenges in tourism.

The sense of belonging in any organization is vital to generate a work motivation with the objective of a good organizational performance, because of this, companies usually take this point into account, ensuring that this leads to greater performance. For this reason, the objective of this article is to determine the relationship between the sense of belonging and the work motivation in the workers of a small Peruvian research company. For this purpose, a quantitative methodology was used, with a cross-sectional descriptive design. The instrument used was a survey consisting of 10 items, which were interpreted using the Likert scale. The survey was conducted and delivered to 24 workers, who were selected by non-probabilistic convenience sampling. After verifying the validity of the instrument and the study variables by means of Cronbach's Alpha statistic, we proceeded to determine the existence of correlation between the variables, which, using Spearman's Rho coefficient, obtained a 70.2% which demonstrates a moderate positive correlation, therefore it indicates that employees feel highly motivated as they feel an indispensable part of the company, therefore they feel job satisfaction by being part of the organization.

The debate on the effect of work environment on job satisfaction is very inconclusive. Most of the existing literature has focused on either the developed economy or job satisfaction and other variables other than the dimensions of the work environment. To fill the contextual and conceptual gap this study examined the effect of dimensions of work environment on job satisfaction among public sector workers in a developing economy. The study used the quantitative method and positivist philosophical viewpoint but specifically, the explanatory design was used to guide the study. A structured questionnaire was used for data collection and data analysis was done by partial least square modelling. The study found that the three dimensions of work environment such as physical, psychological and administrative work environment had a significant relationship with job satisfaction among public workers in a developing economy. It was recommended that the management of public sector organisations should improve upon the psychological, physical and administrative work environment to ensure job satisfaction among their workers. 

This study examines the influence of internal and external locus of control as mediators of financial literacy, financial attitudes, financial beliefs, and financial behavior of students in Timor-Leste. This study uses a quantitative approach with a survey method to collect sample data from students throughout Timor-Leste. Structural equation modeling (SEM) analyzes the relationship between financial literacy, financial attitudes, financial beliefs, internal and external locus of control, and financial behavior. The study’s results highlight the mediating role of internal and external locus of control in the relationship between financial literacy, financial attitudes, financial beliefs, and financial behavior of students in Timor-Leste. These findings can provide insight into the complex relationship between these factors in financial decision-making. Practical implications for educational institutions and policymakers in Timor-Leste, namely emphasizing the importance of considering internal and external locus control in financial literacy programs to improve students’ financial behavior. This study aims to fill the knowledge gap about student financial literacy by expanding the understanding of the relationship between these factors.

The aim of this study was to assess the challenges of rural landholding rights of women in Boloso sore Woreda. The population that used as source of data were sample womenfrom four kebeles,Kebele land administration committee members,Woreda women,youth and children office head,Woreda women’s association president,Woreda agriculture office head and Woreda agriculture office rural land administration desk experts.four kebeles from 28 rural kebeles selected by using systematic random sampling. Data gathered using questionnaire were analyzed using SPSS where descriptive and inferential were used for the purpose. Secondary data were collected from different relevant literatures such as reports, research results documents and publications. As to the findings,women landholding trend in the study area was highly contrasts legally ensured equal holding and using rights of women with men.The community including women themselves perceive women independent landholding as taboo and prohibits it.Even if they hold by different means,the plot of land they got or held was small in size and not conducive for agriculture and house construction. The awareness of women on rural land registration and certification benefit was also poor. Thus,rural women should be initiated to organize and struggle for their equal landholding and administering rights.

Farm households in developing countries are often involved in a variety of livelihood income-generating activities to achieve basic needs and enhance food security. However, little attention has been given to investigating the effect of livelihood diversification strategies on the adoption of agricultural land management practices. This study explored the nexus between livelihood diversification and Agricultural Land Management (ALM) practices in the Southern Ethiopian Highlands. Data for this study were gathered through a structured questionnaire, interviews, and focus group discussions. A total of 423 sample respondents were selected by using multistage random sampling techniques. The data were analyzed using the Inverse Herfindahl Hirschman Diversity Index (IHHDI), the multinomial logit model (MNL), and the probit regression model. The findings of the study revealed that on-farm income activities are the most dominant livelihood income strategies (69.1%), followed by non-farm (21%) and off-farm (9.64%). The multinomial logit model analysis demonstrated that variables such as sex, education, family size, distance to market, land size, extension contact, membership in cooperatives, and household income were the major drivers of farmers income diversification activities (p<0.05). The results of the probit analysis indicated that income from crop production, daily labor work, rents from farmland, and farm assets have a positive and significant effect on households' decisions to implement ALM practices. In contrast, incomes from remittance and migrant sources have a negative but statistically significant impact on the adoption of ALM measures. The farm household sources of income-generating strategies substantially affected the adoption intensity of ALM measures. Income generated from the on-farm sector alone cannot be considered a core income-generating activity for households or a means of achieving food security. Therefore, land management policies and program implementations should consider farmers’ livelihood diversification and income-generating strategies. In addition, such interventions need to promote sustainable farming practices, enhance innovation, and related measures for the adoption of ALM measures to ensure land sustainability.