ABSTRACT
This research work, aims at mitigating the manual and low yield approach of the local system groundnut oil extraction which generally affects both the quantity and quality of the extracted oil. During the course of this research, studies were carried out on groundnut oil extraction which revealed that the optimum temperature for groundnut oil extraction is 90°C. This temperature at the preparatory heating chamber was properly controlled in this task by adopting an automation technique in which PID based microcontroller was deployed. A model of preparatory heating chamber and a PID controller were developed and deplored. The models were validated through a simulation process by varying the temperature parameters of the PID controller in order to achieve a desirable transient response of the system. After several simulations, a set of optimal parameters were obtained that exhibited a commendable improvement was achieved, thus improving the robustness and stability of the system.

ABSTRACT
Abstract: The application of AI (Artificial Intelligence) and IoT (Internet of Things) technologies in teaching and learning has become a powerful trend, positively impacting and transforming both teaching methods and students' learning approaches. In the field of education, the use of AI and IoT technologies is still relatively new and is being gradually implemented. Therefore, this paper focuses on the design of STEM themes, specifically regarding AI & IoT technologies. Particularly, designing STEM topics around smart homes controlled by AI & IoT technology will help students understand real-world applications, as well as the operational principles of control circuits. It will also enable them to grasp automation techniques that enhance device monitoring, ultimately guiding career paths and fostering creative thinking skills while developing students' competencies in high school.

ABSTRACT
This article examines several foundational theories related to practical workshops. Building upon these theories, the research presents findings on the current operational model of the practical workshop and the human resources involved in its development at FPT Polytechnic Hanoi College. The study was conducted through surveys, interviews, and data analysis from both faculty members and students. By analyzing the successes and limitations of the existing workshop model and its human resources at FPT Polytechnic, the article proposes a range of strategies aimed at enhancing the operational framework and improving the quality of human resources, ultimately fostering a more conducive learning and practical environment for students.

ABSTRACT
Tanzania heavily depends on United States Dollar (USD) foreign currency to import various goods and services into the country. Failure to correctly forecast exchange rates between USD and Tanzanian Shillings (TZS) may pose risks such as inability to import intended goods and services, possibility of losing money in stock exchange markets and other investment businesses in case of unexpected currency appreciation or depreciation as well as poor investment decisions in foreign exchange markets. To address this, this study has developed and comparatively evaluated performances of LSTM (Long Short-Term Memory) and BiLSTM (Bidirectional LSTM) deep learning models for forecasting daily USD to TZS exchange rates. The findings reveal that, BiLSTM model outperforms LSTM in forecasting daily USD to TZS exchange rates, achieving a MAPE (Mean Absolute Percentage Error) score of 0.363 on test set (unseen data) compared to a MAPE score of 1.471 achieved by LSTM model. This study recommends to the prospective Artificial Intelligence (AI) researchers and software developers to use BiLSTM instead of LSTM model to forecast (predict) USD to TZS exchange rates. Also, this study has developed USD to TZS exchange rates dataset which can be used by AI researchers, saving them time and costs involved with creating datasets from scratch. This study has also developed ready to use BiLSTM and LSTM models which can be used by Tanzanian business men and women involved in stock exchange markets, foreign exchange markets and other businesses, to predict daily USD to TZS exchange rates and make appropriate business and investment decisions.

ABSTRACT
There is a litany of fundamental problems with Einstein’s theory of relativity. The Lorentz transformation (LT), which the centerpiece of his theory, is not internally consistent, thereby proving that it is not valid. It claims that lengths can contract while times increase without changing the value of its ratio, the speed of light. It argues in favor of the symmetric character of time dilation, even though the experiments with circumnavigating clocks carried out in 1970 by Hafele and Keating contradict this claim. It also claims that events which are simultaneous for one observer may not be so for another, even though the Global Positioning system relies on the assumption that the emission of light pulses occurs at exactly the same time for both the atomic clock on an orbiting satellite and its counterpart of the Earth’s surface. Wikipedia supports Einstein’s theory at every turn. The Law of Causality, which Newton relied upon in formulating his First Law of Kinetics, is never mentioned by Wikipedia in the context of Einstein’s theory. The fact that an alternative (Newton-Voigt) space-time transformation has been introduced which is consistent with the Law of Causality and Galileo’s Relativity Principle (RP) is totally ignored by Wikipedia. The Uniform Scaling Method of physical properties is ignored as well, despite its usefulness in comparisons of the results of experiments from the vantage points of different rest frames. All of these inadequacies of Wikipedia are discussed in detail below.

ABSTRACT
Irrigation is the regular application of water to the crops so that the water supply to the crop will assist it to grow well. Irrigation is mainly useful in areas where there is a shortage of rainfall. The aim of this study is to optimize an IoT-based model for smart irrigation using the drop method. However, the objectives of the study are to; design an IoT-based model for smart irrigation and implement the optimized IoT-based model for smart irrigation. This study achieved its target; an optimized IoT model for smart irrigation using the drip method. The program has made the following functionality: login page wireframe, dashboard wireframe, system user case diagram, actuators page wireframe, sensor page wireframe and application interface design. The model was tested and approved to fulfill its mission and objectives such as designing an IoT-based model for smart irrigation, implementing the optimized IoT-based model for smart irrigation using the drip method with Python programming language, testing and evaluating the performance of the optimized IoT-based model for smart irrigation water using drip method was then deployed to the farm. Also, helps to solve the problem of scarcity of empirical evidences in the area of the study.

ABSTRACT
In 1960 Schiff published a paper which questioned to what extent the full formalism of Einstein’s General Theory of Relativity (GRT) is required in the calculation of three key experimental effects (the gravitational red shift, the deflection of light rays that pass close to the Sun, and the precession of the perihelion of Mercury’s orbit around the Sun), but rather “may be correctly inferred from weaker assumptions that are well established by other experimental evidence.” He noted that the method he employed was not capable of describing the third of the above effects, however. In the present work it will be shown that the latter deficiency has been removed by expanding his scaling procedure to cover the acceleration due to gravity g in Newton’s theory of gravitation, thus further strengthening his argument against the essentiality of GRT. In addition, the scaling procedure has been extended to include other key physical quantities such as energy, momentum and force and even the Universal Gravitation Constant G. The significance of these theoretical developments for the terrestrial experiments of Pound et al., is also discussed.