In this paper, experimental and numerical studies are performed to determine the maximum deflection and strength of cylindrical shells. The considered models are subjected to concentrated loads applied progressively until plastic failure of the structures. In order to determine the effect of the geometrical parameters, several models with different thicknesses, lengths, and radius are considered and analysed with various boundary conditions. The numerical analysis is carried out by the finite element method using ABAQUS code. The main objective of the present investigation is to determine the maximum strength that caused damage of the models. The results of the experimental and numerical analysis are recorded, discussed and commented on. It is observed that the thickness, length,and radius dimensions with boundary conditions have great effect on the strength load values that create damage.

In production/inventory control systems, the goal of the controller is to generate sophisticated decisions by controlling the order rate and inventory level. This paper aims at modeling a dynamic-stochastic production/inventory control system under two sources of variability (uncertainty) including uncertainties on demand rate and frustrating rate. The study deals with obtaining a robust optimal design of a Proportional-Integral-Derivative (PID) controller in in the stochastic control system. For this purpose, a new robust simulation-optimization method in the class of computational intelligence is proposed. To cope with the unknown distribution of uncertainty, the crossing weighted uncertainty scenarios are combined with the proposed method. Within this study, a new sequential robust efficient global optimization is proposed to make a trade-off between optimal and robustness terms in final optimization results. Finally, a numerical case with simulation experiments is conducted to demonstrate the advantages of the proposed policy in terms of optimal result, robustness, and computational cost.

Advancements in technology have had a profound impact on the way we learn, teach, and access knowledge. From online learning platforms to interactive educational games and virtual reality simulations, technology has transformed the traditional classroom into a dynamic, engaging, and inclusive space for education. One of the promising advancements in the field of artificial intelligence technology is ChatGPT which offers personalized and effective learning experiences by providing students with customized feedback and explanation. The effect of ChatGPT must be compared with the effect of Google at the educational level since both present a source of information and explanation. Thus, this study aims at investigating the differences between these two learning sources to measure their effectiveness from different perspectives. The model proposed in this study was evaluated using the PLS-SEM approach, utilizing data collected from 153 university students in the UAE. The results of this evaluation indicate that the GPT (Generative Pre-trained Transformer) has a significant impact on user acceptance, mediated by information quality, system quality, perceived learning value, and perceived satisfaction. These factors play a crucial role in determining users' acceptance of the GPT. However, it is important to note that some aspects of the model were not supported, suggesting that they do not have a significant predictive effect on the use of ChatGPT. Nonetheless, the findings of this study contribute to the existing literature on AI and environmental sustainability, providing valuable insights for practitioners, policymakers, and AI product developers. These insights can help guide the development and implementation of AI technologies in a way that aligns with users' needs and preferences while considering the larger environmental context.

This paper reports on a new experimental study for the behaviour of reciprocally connected and supported Fibre Reinforced Polymer (FRP) hollow square profiles axially loaded under several boundary conditions. The study aims to determine the ultimate load of the assembly and failure mechanism of mutually connected units. For the tests, FRP reciprocal frames units (RF) of 100 × 100 × 6.4 mm thick square hollow sections were designed, fabricated and assembled using mechanical fasteners. A bespoke steel test rig allowed for varied support boundary conditions. The observed failure modes were dominated by web buckling, bearing failure around the bolted areas and localised failure. The 100 × 100 mm RF unit achieved the highest load capacity of 16.4 kN and frame stiffness of 1.7 kN/mm, under the pin-pin-roller support boundary conditions. This paper presents the experimental procedure, results and observations.

Finite Element Analysis was carried out to describe the effect of frictional boundary conditions and percentage reduction on deformation modelling (forward extrusion) of Aluminum AA6063 alloy. Curved die profiles of regular polygons (square, hexagonal, heptagonal, and octagonal) were designed using MATLAB R2009b and Autodesk Inventor 2013 to generate the coordinate and the solid CAD model of the die profile respectively form a circular billet. The numerical analysis was performed using DeformTM-3D commercial package with frictional boundary conditions of 0.38 and 0.75 representing the wet and dry condition and varying the percentage reduction of 50%, 70%, and 90%. The results of the temperature distribution, effective stress, effective strain, and strain rate were reported. As the percentage area reduction increases, the extrusion pressure also increases with an increasing frictional condition, and die length. Also, extrusion pressure decreases when the side of the polygon increases from square-shaped section follow by hexagonal shaped-section and least in octagonal shaped-section for both friction factors and percentage area reductions. For a given percentage reduction and cross-sectional area, there is no distinct difference between the predictive loads for the shaped-polygons. When the result of this analysis is compared with the experimental results from the literature, it is evident that DeformTM-3D is an effective tool for finite element analysis of non-isothermal deformation processes.

This study aims to shed light on the way customers determine their utilization of international payment services with blockchain applications. The primary data is collected from the 373 individuals who frequently use the international payment services in Vietnam. We apply the combination of TAM, UTAUT, and ISS models to test the determinants of the Intention to use International payment services at Commercial banks applying Blockchain. These determinants are Quality of System, Quality of Service, Quality of Information, Perceivable usefulness, Convenient usefulness, and Social influence. The research results show that (i) All of the above factors are positively associated with customers’ intention to use international payment services in Vietnamese banks which implement blockchain; (ii) The quality of information has the strongest positive impact on the customer's intended use. It refers that the international payment services in banks should be safe, accurate and timely; (iii) Differently from the hypothesis, the social influence indicator is positively related to the customer's intention to use the service, affirming the potential interests of customers on blockchain if applying successfully in banks; (iv) Although current customers have not paid much attention whether banks apply blockchain in international payment or not, they have taken concentration on fundamental risks, costs, and convenience of the services. This signal is consistent with the fact that only 2/46 commercial banks and 49 foreign bank branches in Vietnam provide international payment service with blockchain application nowadays.

The world of the Internet of Things (IoT), even though it is continuously morphing as a fresh paradigm at the intersection of technology and education, is still struggling with several difficulties that prevent its absorption into the e-learning platforms of higher education institutions (HEIs). The breadth of Internet of Things implementation in developing countries, particularly Jordan, Malaysia, Iran, Saudi Arabia, Iraq, and Bangladesh, remains behind, even though industrialized nations have made significant advancements in their utilization of IoT, with the United Kingdom, the United States of America, China, and Japan acting as prominent examples. In the realm of research that focuses on the progression of the IOT integration into the e-learning systems of economically challenged countries, there is a substantial disparity. In particular, the focus of this research is on Jordan to shed light on the primary variables that are either facilitating or hindering the adoption of the IoT within the e-learning sector of Jordan's HEIs. A comprehensive analysis of previous research has been undertaken as a first stage in this investigation. The goal of this analysis is to identify important factors that are involved in the process of IOT adoption. Following that, we used an inferential technique, collecting data from 306 respondents who were enrolled in Jordanian higher education institutions. During our investigation, we discovered that the rate of the IOT integration was significantly influenced by factors such as accessibility, usability, technical assistance, and individual capabilities. In addition, our findings suggest that factors such as attitude, behavior, financial preparedness, dependability, and training have a substantial impact on the adoption of the IOT. On the other hand, the study seemed to indicate that characteristics such as class capacity, awareness, system resources, and course design had a minor influence on the adoption rates inside HEIs. In conclusion, this study provides tangible suggestions to strengthen the integration of the IoT inside Jordanian HEIs. These recommendations provide significant insights that can be used by policy architects, government entities, and higher education institutions to overcome the challenges that relate to the deployment of IoT in the higher learning sector.

This paper presents an experimental programme designed to investigate the failure mode and ultimate capacity of pultruded glass fibre reinforced polymer (GFRP) cellular profiles subject to transverse loading. Presented in this study are the results of the characterisation of twenty six GFRP 152 × 76 × 6.4 mm I stub beams, 300 mm long. The beam specimens were categorised as plain for the control tests and those with circular or rectangular openings, centrally positioned. The specimens were subject to different loading configurations, noted as End Bearing with solid ground (EB), Interior Two Flange (ITF), Interior Bearing with solid base (IB) and End Two Flange (ETF) Results indicate a reduction in load-carrying capacity of the specimens with the opening when compared to the control specimens. The reduction was up to 20% for the specimens with circular openings and up to 25% for specimens with rectangular openings. The study revealed that loading configuration IB and ITF exhibit larger nonlinear behaviour and deformability than loading configurations EB and ETF. Various research has been conducted on its mechanical properties, connections, pultrusion techniques and web crippling behaviour of thin-walled GFRP section. Limited research can be found in the literature on the behaviour of pultruded GFRP beams with large perforation, subject to transverse static loadings.

In the present research work using a backward cup extrusion (BCE) die profile, different lubricating conditions on aluminum alloy AA6063 have been experimentally and numerically investigated to predict the extrusion load. It was obvious that due to an increase in applications of the extrusion process, many researchers have worked on the extrusion process using different methods to achieve their aims. This experiment was conducted with three different lubricants namely: Castor oil, Palm Oil and tropical coconut oil; as well as without lubricants. Different lubricating conditions were employed of varying strain rates ranges from 1.5×10-3s-1, 2.0×10-3s-1, 2.5×10-3s-1, and 3.0×10-3s-1; Numerical analysis and simulation for dry and lubricated conditions during extrusion load were also performed using DEFORM 3D software. The results show that prediction extrusion load increases with increasing strain rates. The maximum extrusion load was found to be higher for extrusion without lubricants. In all cases of strain rate, palm oil showed a lower extrusion load compared to the other lubricants. Castor oil indicated the highest extrusion load when the experiment is carried out using lubrication. There was a consistent agreement between the result gotten from the experiment and simulation result of the extrusion load-strike curve.

From the past decades, increasing attention has been paid to the quality level of technological and mechanical properties achieved by the Additive Manufacturing (AM); these two elements have achieved a good performance, and it is possible to compare this with the results achieved by traditional technology. Therefore, the AM maturity is high enough to let industries adopt this technology in a more general production framework as the mechanical manufacturing industrial one is. Since the technological and mechanical properties are also beneficial for the materials produced with AM, the primary objective of this paper is to focus more on managerial facets, such as the cost control of a production environment, where these new technologies are present. This paper aims to analyse the existing literature about the cost models developed specifically for AM from an operations management point of view and discusses the strengths and weaknesses of all models.