APPLICATION

This paper examine the level of application of information and communication technology for academic activities by the undergraduate of the university of Benin. Survey method was adopted to carefully collect data from 402 respondents in the University of Benin through three stages using the simple random, stratified and simple sampling procedure. The study anchored on the technological determinism and diffusion of innovation theories. The rationale behind the study is to find out whether students have access to ICT tools and the impact it have on students, ascertaining the most commonly use ICT gadgets and the challenges encountered in utilising such tools and to determine the usage expertises. Findings show that undergraduate students of UNIBEN have access to ICTs gadgets especially smart phones which remains the most commonly accessible ICTs, however data subscription, and poor Internet connection remain the highest hindrances to the operation of ICT as it was discovered that many could not access or possess the necessary ICT of their choices such as laptops due to financial hindrances and this have a negative effect on the academic performance of undergraduate students of UNIBEN academically and socially. Findings also reveal that Internet remains the most visited students zoom when preparing for exams whereas ARTIFICIAL INTELLIGENCE (AI) also gained momentum through the Internet as few or average percentage still leverage on textbooks and handouts materials. However, it was discovered that the university lacks proper infrastructure specifically loaded with ICTs gadget. Those that answers the availability of ICTs in their department express clear responses of it ineffectiveness. Findings also show that students, though have good operational intelligence, expertise of ICTs tools, yet, lacks good and balanced managerial intelligence as students spent much time on social media, gratifying self for pleasure. This affects the academic performance in no little measures. To this end, the study recommend that institutions should pay more attention to the development of ICT and flow with ICT trends. Also, free WiFi should be made available to aid Internet connectivity and more ICTs infrastructure should be considered with urgent response and attention. In conclusion, ICT user must take precautions measure to guide against addition to social media and the internet as this will have negative influence in their academics.

Welding is a vital manufacturing process used in several industries, including aerospace, automotive, and construction. However, residual and induced stresses that develop during welding due to rapid heating and cooling cycles often affect the structural integrity of the weldment thereby reducing the integrity of the structure. The study investigates the application of Artificial Neural Networks (ANN) in predicting the actual maximum stress in Tungsten Inert Gas (TIG) weldments and develop a predictive model capable of accurately estimating the actual maximum stress in TIG welded joints based on key process parameters such as welding current, voltage, and gas flow rate. Twenty (20) experimental runs as generated by the Central Composite Design (CCD) was used to carry out TIG welding on mild steel plates. A Universal Stress Testing Machine was used to measure the actual maximum stress in the weldment and the result was recorded for each experimental run. This experimental result was then analyzed using ANN. ANN trained trained the neural network with fourteen (14) of the observations and use three for network validation and another three for network testing. The best validation performance value of 80.6689 was observed at epoch 5 with an overall performance value of 0.96864. ANN predicted response values was compared with the experimental result and it showed a meritorious correlation with the experimental result trend. The results revealed that the developed ANN model achieved high prediction accuracy with minimal error, confirming its capability to learn and represent the complex nonlinear relationship between the welding input parameters and the resulting actual maximum stress