This study aims to analyze the opportunities for implementing Non-Cash Transactions (Non-Cash Applied Transactions) at Village-Owned Enterprises as the application of Enterprise Resources Planning (ERP) Theory in North Sumatra. This type of research is quantitative descriptive research. The test was carried out by using Structural Equation Modeling analysis with the Formative approach. The tool used is SmartPLS. The study population was village-owned enterprises in Simalungun, Batubara and Asahan districts, North Sumatera, Indonesia. The sampling technique was carried out by using purposive sampling method. In addition, an assessment of community perceptions of implementation was also carried out. The research variables used are supervision, provider support, banking support (support of banking facilities), human aspect, regulation, resistance, commitment and training. The training variable at Village Business Entities has a significant partial effect on the Successful Application of Non-Cash Transactions of Village Business Entities in North Sumatra. This shows that the more frequent training and assistance are held at village business entities, the easier it will be to implement non-cash transactions at village enterprises. Meanwhile, the variables of Supervision, Provider Support, Banking Support, Human Resources, Regulation, Resistance and Commitment did not have a significant effect on the success of village non-cash transactions in North Sumatra.

This paper focuses on the application of foamed bitumen technology in the production of asphalt mixtures. This technology replaces the common asphalt binder with foamed bitumen for production of asphalt mixtures. Given the foaming, it is possible to produce asphalt mixture at a lower working temperature. This “eco-friendly” technology has been increasingly used by the asphalt mixture producers in Europe because of reducing the energy demands of the asphalt mixture productions. In this paper, first the technology of the foamed bitumen production is explained and then the results of laboratory research are presented, in which selected empirical and functional parameters of two types of asphalt mixtures of the asphalt concrete type (AC) are compared. These mixtures were produced in two versions, one of them containing the common asphalt binder and the other one the foamed bitumen. While comparing the samples, attention was paid especially to the comparison of the stiffness modulus of the laboratory-produced asphalt mixtures according to EN 12697-26 and to their low-temperature characteristics according to EN 12697-46.

This study investigated the impact of triple project constraints including time, cost, and quality on construction projects. The main goal was to examine several construction-related barriers, most of which were caused by time delays, cost overruns, and poor project quality. In addition, improper cost estimation planning can occasionally result in overestimation or underestimation, which can cause construction projects to be delayed or tasks to go unfinished. To improve the construction industry's routine and produce successful projects that satisfy its stakeholders, the study aims to investigate the impact of project cost, project quality, and project time with a moderating function for organizational support. A questionnaire survey was held, and overall findings indicate that managing triple constraints significantly impacts on the success of construction projects. Organizational support also moderates the detrimental effects of project cost, project quality, and project duration on the success of construction projects.

Although the relationship between resilience and career success has been well documented, very few studies relate these variables in developing economies, and especially in entrepreneurship in Nigeria. Additionally, how commitment actually shapes this relationship is conspicuously neglected. This empirical investigation was aimed at examining the influence of entrepreneurial career resilience on the three facets of entrepreneurial career success, i.e. career satisfaction, perceived career achievement and perceived financial attainment through the mediating role of entrepreneurial career commitment. The study used cross sectional data approach to collect data from 390 active entrepre-neurs. The participants were selected using purposive sampling technique. PLS-SEM statistical software (Smart-PLS 3) was used to test the formulated hypotheses. The findings suggested that; entrepreneurial career resilience was a positive predictor of the career satisfaction and perceived ca-reer achievement but it did not predict perceived financial attainment; that, entrepreneurial career resilience predicted entrepreneurial career commitment; that, entrepreneurial career commitment predicted career satisfaction, perceived career achievement and perceived financial attainment. Moreover, entrepreneurial career commitment significantly influenced the relationships of entrepreneurial career resilience and the two facets of entrepreneurial career success.

Infectious waste disposal remains one of the most serious problems in the medical, social and environmental domains of almost every country. Selection of new suitable locations and finding the optimal set of transport routes for a fleet of vehicles to transport infectious waste material, location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Determining locations for infectious waste disposal is a difficult and complex process, because it requires combining both intangible and tangible factors. Additionally, it depends on several criteria and various regulations. This facility location problem for infectious waste disposal is complicated, and it cannot be addressed using any stand-alone technique. Based on a case study, 107 hospitals and 6 candidate municipalities in Upper-Northeastern Thailand, we considered criteria such as infrastructure, geology and social & environmental criteria, evaluating global priority weights using the fuzzy analytical hierarchy process (Fuzzy AHP). After that, a new multi-objective facility location problem model which hybridizes fuzzy AHP and goal programming (GP), namely the HGP model, was tested. Finally, the vehicle routing problem (VRP) for a case study was formulated, and it was tested using a hybrid genetic algorithm (HGA) which hybridizes the push forward insertion heuristic (PFIH), genetic algorithm (GA) and three local searches including 2-opt, insertion-move and interexchange-move. The results show that both the HGP and HGA can lead to select new suitable locations and to find the optimal set of transport routes for vehicles delivering infectious waste material. The novelty of the proposed methodologies, HGP, is the simultaneous combination of relevant factors that are difficult to interpret and cost factors in order to determine new suitable locations, and HGA can be applied to determine the transport routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation efficiently in this case.

In the dynamic field of cybersecurity within intelligent vehicle systems, the sophistication of threats necessitates continual advancements in security technologies. Traditional Network Intrusion Detection Systems (NIDS) often fall short in detecting emerging and sophisticated intrusion methods, primarily due to their reliance on static datasets that fail to capture the nuanced dynamics and complexity of modern network intrusions. This study presents a sophisticated simulation for NIDS tailored to intelligent vehicle environments, utilizing the extensive capabilities of Scapy—a robust network manipulation tool—to generate a highly accurate dataset of network traffic reflective of real-world scenarios. We created a diverse dataset involving 100,000 network flows, covering a wide array of benign, malicious, and anomalous traffic patterns, to thoroughly evaluate the detection capabilities of our proposed system. This dataset was analyzed using a deep learning framework employing a Convolutional Neural Network (CNN), which demonstrated outstanding performance metrics: an accuracy of 99.08%, precision of 98.96%, recall of 99.11%, and an F1 score of 99.03%. These metrics showcase the system's enhanced capability to precisely classify various network flows, emphasizing the importance of realistic synthetic data in boosting the training and accuracy of NIDS in intelligent vehicles. The results of this research are significant, marking a step forward towards more flexible and preemptive security measures for intelligent vehicles, and effectively narrowing the gap between simulation-based testing and real-world network environments.

The numerical simulation of fatigue behavior of the Aluminum 7075-T6 cantilever beam with an angular crack has been investigated. Cracks are located separately in three different positions of the investigated beam. To predict the fatigue behavior of the cantilever beam the crack propagation was manually simulated. Compression load is applied in different stress ratios between zero and one; then, the obtained numerical results of this research are compared with the experimental results. It is observed that increasing the stress ratio increases the percentage of the fatigue life of the sample significantly. Ascending growth of fatigue life is slow and more severe by increasing of the stress ratio for the first and the third position, respectively. By increasing the stress ratio, the rate of deviation of the crack decreases and it converges to 0° in parallel to the width of the beam. This result is also observed with an increase in the distance from the support of beam. Furthermore, it is also revealed that by the increase in the initial length of the crack, the fatigue life initially reduces with smaller ratios. However, along the larger cracks, the decreasing ratio of fatigue life increases significantly.

Distribution of goods is one of the main issues that directly affect the performance of the companies since efficient distribution of goods saves energy costs and also leads to reduced environmental impact. The multi-compartment vehicle routing problem (MCVRP) with a heterogeneous fleet of vehicles is encountered when dealing with this situation in many practical cases. This paper is motivated by the fuel delivery problem where the main objective of this research is to minimize the total driving distance using a minimum number of vehicles. Based on a case study of twenty petrol stations in northeastern Thailand, a novel two-phase heuristic, which is a variant of the Fisher and Jaikumar Algorithm (FJA), is proposed. The study first formulates an MCVRP model and then a mixed-integer linear programming (MILP) model is formulated for selecting the numbers and types of vehicles. A new clustering-based model is also developed in order to select the seed nodes and all customer nodes are considered as candidate seed nodes. The new Generalized Assignment Problem model (GAP model) is formulated to allocate the customers into each cluster. Finally, based on the traveling salesman problem (TSP), each cluster is solved in order to minimize the total driving distance. Numerical results show that the proposed heuristic is effective for solving the proposed model. The proposed algorithm can be used to minimize the total driving distance and the number of vehicles of the distribution network for fuel delivery.

The objective of this study was to examine the role of green Human Resources Management (HRM) in the green supply chain (SC) and firm performance. The relationships between green HRM, green SC, lockdown, and firm performance were examined. In addition to this, the mediating role of green SC and the moderating role of lockdown was examined. The population of the study was based on the food industry of Bahrain and various companies were selected for data collection. Therefore, data were collected from the food supply companies in Bahrain. A questionnaire was used for data collection in which cluster sampling was applied. The findings of the study highlighted that green HRM has major importance for food supply companies. It has a positive role in promoting the performance of food supply companies in Bahrain. Furthermore, green SC also plays a vital contribution to the performance of food supply companies. However, COVID-19 has a negative role in firm performance. The situation of lockdown due to COVID-19 has a negative effect on the performance of these companies.

The growth in Information and Communication Technology has brought dynamic changes to financial payment systems through smart devices, and mobile payment systems are significant among different smart payment systems. Further, the Technology Acceptance Model's components affect the smart payment user's behavior. Moreover, students are a substantial part of society and are more inclined to use mobile payments. Therefore, the present research examines the influence of technology adoption factors on the perception of students using mobile payments. The study adopted TAM components as influencing factors, such as Perceived usefulness, perceived ease of use, Perceived cost, and Perceived trust. The data was collected from 100 respondents consisting of male and female students. The study employed simple regression analysis to report the results. The results show that the perception of students towards the use of m-payment is strong, with a mean of 1.52. The result is similar to the explanatory variables, ranging from 1.77 to 1.97. The study found that the technology adoption factors, such as Perceived usefulness, perceived ease of use, and Perceived cost, positively influenced the students' perception of using mobile payments with p-values ranging from 0.001 to 0.049. The results of Perceived trust were positive but insignificant. Therefore, the present research observed a significant influence of technology adoption factors on the perception of students using mobile payment.