A Shoveling-related Pain Intensity Prediction Expert System for Workers’ Manual Movement of Material

In this study, a fuzzy-based expert system called the Pain Intensity Prediction Expert System (PIPES) was developed to predict pain severity risk (PSR) in shoveling-related tasks. The primary objective was to develop a non-changing rating risk assessment ergonomics tool that both efficient and comparable with those obtained from human ergonomics experts in the field of application. PIPES used fuzzy set theory (FST) to make decisions about the level of pain associated with a selected worker base on the measured task variables, namely scooping rate, scooping time, shovel load, and throw distance as input and PSR as the result. Values obtained from variable measurements from a sand shoveling task were run with PIPES, and the results were compared with the workers’ self-reported pain (WSRP) intensity using a numeric rating scale (NRS) tool. The result of validation showed that there was a strong positive relationship between WSRP NRS and PIPES NRS, with a correlation coefficient of 0.70. The independent sample t-test for mean difference showed that WSRP had a statistically significantly lower level of NRS (4.35 ± 2.1) compared to PIPES (4.75 ± 2.2), t (38) = - 0.591, p = 0.558. With a significance level of 0.001 at 95% confidence, the groups’ means were not significantly different. The study developed an expert system, PIPES, which can be used as a computerized representation of ergonomics experts, who are scarce. PIPES can be applied to construction industries, sand mine locations, and any workplace where materials are manually moved using a shovel

FUZZY LOGIC APPROACH TO ENERGY PLANNING IN NIGERIA

Energy planning is an important tool for power system utility company and consumer’s profitability and satisfaction respectively. This paper is a study of energy planning (forecasting) in Ogun state of Nigeria using Fuzzy Logic model. Population and gross domestic product (GDP) are used as the independent variables to forecast load demand based on the previous load demand. After arranging the variables into 5 membership functions and the 19 rules were created, the fuzzy logic model forecast the annual load demand for the next 10 years with a percentage error margin 0.95 % to 21.79 % which results to a mean absolute percentage error (MAPE) of 8.34 %. The result of the forecast shows that within the next 10 years, 2019 to 2028, an average power load of 1985.66 MWH will be required

FUZZY LOGIC APPROACH TO ENERGY PLANNING IN NIGERIA

Energy planning is an important tool for power system utility company and consumer’s profitability and satisfaction respectively. This paper is a study of energy planning (forecasting) in Ogun state of Nigeria using Fuzzy Logic model. Population and gross domestic product (GDP) are used as the independent variables to forecast load demand based on the previous load demand. After arranging the variables into 5 membership functions and the 19 rules were created, the fuzzy logic model forecast the annual load demand for the next 10 years with a percentage error margin 0.95 % to 21.79 % which results to a mean absolute percentage error (MAPE) of 8.34 %. The result of the forecast shows that within the next 10 years, 2019 to 2028, an average power load of 1985.66 MWH will be required

Development of a Permeable Meter for Mould Industries Using Locally Sourced Materials

One of the major factors for production of quality casting is the control of properties of moulds and cores to make them uniform and consistent quality. Permeable meter is used for the determination of the venting ability of sand moulds and cores. This testing equipment is being imported to the country as at today. The cost is high, and they are not readily available to foundry operators.Hence there is need to design and develop a permeable meter using locally sourced materials and make it available at an affordable price, thereby improving foundry technology in Nigeria. Two different method could be used to measure permeability of sand; determination of air flow rate and measurement of pressure difference between the orifice and the top of sand specimen. The first method was adopted in the development of the Permeable meter. On testing, the values of permeability measured using the equipment was comparable to the results obtained from thestandardized imported one. The cost of production was 30% of the cost of imported one, not even now that exchange rate to international currency has skyrocketed. The work has incorporated design and fabrication principles that resulted in a relatively cheap product that can be constructed locally by an average Fabricator and Technicia

FUZZY LOGIC APPROACH TO ENERGY PLANNING IN NIGERIA

Energy planning is an important tool for power system utility company and consumer’s profitability and satisfaction respectively. This paper is a study of energy planning (forecasting) in Ogun state of Nigeria using Fuzzy Logic model. Population and gross domestic product (GDP) are used as the independent variables to forecast load demand based on the previous load demand. After arranging the variables into 5 membership functions and the 19 rules were created, the fuzzy logic model forecast the annual load demand for the next 10 years with a percentage error margin 0.95 % to 21.79 % which results to a mean absolute percentage error (MAPE) of 8.34 %. The result of the forecast shows that within the next 10 years, 2019 to 2028, an average power load of 1985.66 MWH will be required

Women's behavioral patterns in domestic tasks in Western Nigeria : hazards forecasting with neural network classifier

Behavioral pattern is the characteristic ways a person acts and has been recognized as a cause of many home accidents (h-accd). This study reviewed the types and prevalence of injuries among women in domestic works and proposes a model using Artificial Neural Network (ANN) function to forecast the safety level of women in domestic duty. The study was conducted in some parts of Western Nigeria among 340 subjects (171 married and 169 unmarried) using questionnaire. SPSS was used for data analysis. The ANN function was developed in MATLAB 2015a using the subjects’ behavioral patterns and the model was used to predict safety in domestic duties (d-duties) among some women. ‘Cuts/laceration’ (40%) and ‘skin contact with hot substance’ (35.6%) were commonly reported. Carelessness (26.5%) and distraction (22.1%) were the main leading factors across the groups. Marital status and h-accd (Chi-square =4.323 and p= .038); ‘hours spent on domestic works’ and ‘the h-accd’ were both significant among other tested groups variables. With the developed ANN function, the results of the MSE was 0.33626 indicating that the function predicted the exact value. The result of the predicted h-accd (safety= -0.5445, hazards= 1.0228) in d-duties of the tested variables with the ANN function, showed a very low level of safety. The article concludes that the developed model is reliable and a recommended ergonomic tool useful in all homes, most especially where women perform most domestic works.http://vc.bridgew.edu/jiwshj2021Electrical, Electronic and Computer Engineerin