Latest Articles
ABSTRACT
There are two frequently used systems of units for physical properties. The mks System employs the meter (m) and kilogram (kg) as the units of distance and inertial mass, whereas the British System employs foot (ft) and pound (lb) in their place. In many cases, a conversion between the numerical values of a given object can be obtained by simply making use of the respective ratios of these quantities. It is helpful to realize that any physical property can be expressed as a product of the variables of distance, inertial mass and time. One can expand the applicability of the two Systems to the description of electromagnetic properties by adding the Coulomb (Coul) to this list. The situation is made more complicated by the fact that the British System employs a unit of force (lbf) which depends on the location of the object lying within a gravitational field with a particular value of g. As a consequence, 1 lbf = 4.44822 N = 32.173722 ft lb / s2 within the British System itself. Relationships between the units of energy and power are also disussed.
Original Research Article
ABSTRACT
This study aims to investigate the effect of corrosion on the failure load and bond strength of concrete cube members and evaluate the efficacy of Zanthoxylum exudate/resin as a corrosion inhibitor. The results showed that corrosion significantly reduced the failure load and bond strength of concrete cube specimens, whereas coating with different thicknesses of Zanthoxylum exudate/resin extract improved the failure load and bond strength of the coated specimens compared to the corroded specimens. The percentile values also confirmed that the coated specimens had higher strength values than the corroded specimens. Furthermore, the study examined the effect of corrosion on the measured diameter of steel bars, revealing that corrosion caused a reduction in the measured diameter of the steel bars. The use of Zanthoxylum exudate/resin as a corrosion inhibitor showed potential in reducing the corrosion of mild steel reinforcement in concrete. The findings of this study suggest that the use of corrosion inhibitors can be an effective solution to mitigate the negative effects of corrosion on concrete structures and improve their strength and service life. Further research is needed to determine the long-term effectiveness of natural extracts as corrosion inhibitors for mild steel reinforcement in concrete.
Original Research Article
ABSTRACT
This study investigates the corrosion protection of buried steel pipes coated with Cordia Boraginaceae exudates. Utilizing galvanized steel pipes with an initial diameter of 168.3 mm and a wall thickness of 7.11 mm, the effectiveness of the coatings was evaluated through mechanical and corrosion assessments. Coated samples demonstrated a significant reduction in corrosion rates, averaging approximately 0.5 mm/year, compared to 2.5 mm/year for uncoated samples. Weight loss measurements indicated an average of 3 grams for coated samples versus 15 grams for uncoated samples, highlighting substantial protection. Mechanical tests showed a tensile strength reduction from approximately 400 MPa to 280 MPa for coated samples post-exposure, while yield strength and elongation were also impacted. Adhesion strength measured around 8 MPa, indicating robust bonding between the coating and substrate. Coating porosity was assessed at approximately 5%, demonstrating effective barrier properties against corrosive agents. Environmental factors, such as chloride content (up to 19,500 mg/L) and pH levels (ranging from 7.1 to 8.2), were shown to significantly influence corrosion dynamics. The findings confirm the potential of Cordia Boraginaceae exudates as a sustainable alternative to synthetic corrosion inhibitors, providing effective protection in aggressive environments. This research contributes valuable insights into the application of natural coatings for enhancing the longevity and reliability of buried steel infrastructure.
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.
Original Research Article
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.
Original Research Article
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.