International Journal of Innovations in Engineering Research and Technology
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EFFECT OF SAFETY PREPAREDNESS ON SAFETY PERFORMANCE OF PETROL STATIONS IN SELECTED STATES IN THE NIGER DELTA
Full text linkThis study was carried out to examine the effect of safety preparedness on safety performance of petrol stations operating in selected states in the Niger Delta. Two variables were used to operationalize safety preparedness, namely tangible and intangible safety preparedness. Two variables were also used to capture safety performance, namely near-miss occurrence and accident occurrence. The study adopted cross-sectional and correlational research designs. Multi-stage sampling technique was used to sample petrol stations operating in three states in the Niger Delta (Akwa-Ibom, Bayelsa and Rivers States) while Taro Yamane formula was used to calculate sample size of 440 petrol station attendants from the study population. Structured questionnaire designed based on 5-point Likert scale and checklist designed based on Department of Petroleum resources (DPR) regulations, were used for data collection while reliability of the instruments was determined using Cronbach alpha index. Descriptive statistics and regression were used for the data analysis
ASSESSMENT OF SURFACE AND GROUND WATER QUALITY AROUND ARTISANAL REFINING OPERATION SITES IN OHAJI / EGBEMA LGA, IMO STATE
Full text linkThis study assessed the distribution of water quality for surface and groundwater samples collected within artisanal refining sites in Ohaji/Egbema local government area in Imo state. The sampling technique involved collecting ten groundwater and ten surface water samples around artisanal refining sites within the distances of 0-100m, 100-200m, 200-300m, 300-400m, 400-500m, Four control samples (two each for surface water and groundwater) were also collected at distances of over 10km from the refining sites. Some physicochemical parameters were analyzed, and water quality index were also calculated for difference distances based on measured physicochemical parameters and WHO standards using weighted arithmetic mean methods
“YIN-YANG” BINARIES OF DUALITY IN ANITA DESAI’S CRY THE PEACOCK
Full text linkAnita Desai’s Cry the Peacock is among the early novels that herald the development of psychological fiction in India. The work reveals the inner-world of Maya and revolves around events and experiences that ultimately lead her to murder her husband, Gautama. Maya has been severely scrutinised as a neurotic in a psychoanalytic light. This research paper attempts to associate “Maya and Gautama” as an inseparable union of “Yin-Yang”
BLEACHING OF CRUDE PALM OIL BY ACTIVATED NISE CLAY: PROCESS KINETICS, ISOTHERM AND THERMODYNAMIC STUDIES
Full text linkON THE INEQUALITIES CONCERNING POLYNOMIAL-EXPONENTIAL BOUNDS FOR INVERSE TRIGONOMETRIC FUNCTION
Full text linkRecent research works on mathematical inequalities shows the importance bounds of polynomial-exponential type for various functions
ORGANIZATIONAL RESILIENCE AND EMPLOYEE PERFORMANCE IN CRISIS ECONOMY
Full text linkThe aim of the study was to critically analyze the significance of organizational resilience on employee performance, especially during crisis situation, such as the recent Covid-19 pandemic that keep all the nations and business organizations in a state of chaos It could be seen that firms all over the world are crying wolf due to the loss of manpower, low profitability, low productivity, poor service delivery and so on, as a result of the Covid-19. The cause of the low performance could be attributed to not being pro-active by the employees, or non-anticipation of perturbations, inability to learn from experience, inability to adapt and dynamic capability to work in any given environment and changes in policies and programmes as the situation demand to achieve organizational sustainability. Therefore, organizational resilience is the ability of organizations to prepare, absorb shock or develop resistance in the face of perturbations within its environment, and surmount all insurmountable to move to a better next level. The study concluded that organizational learning, adaptive capacity and dynamic capability have significant relationship with employee performance. Hence, the study recommended that management should foster conducive organizational learning, adaptive capacity and dynamic capability, as these will equip the employees to remain with the organization, and put up their best work effort for increased productivity and profitability
ENHANCING THE PROPERTIES OF CONCRETE BY USING ALKALINE SOLUTION AND ITS COMPARATIVE STUDY WITH CONVENTIONAL CONCRETE
Full text linkThe main aim of this project was to reduce the use of cement so as to produce a CO2 emission free cementitious material and Geopolymer Concrete (GPC) was the best alternative solution present out there. GPC utilizes industrial waste material such as fly ash from thermal power station to provide practical solution to waste management as well as environmental protection method. In this study we have used low calcium fly ash (ASTM class F), along with fly ash, water was enable to bind effectively. Therefore we also have replaced water completely with alkaline solution to hold fly ash, aggregate and sand together. The alkaline solutions we have used are – sodium hydroxide (NaOH) and sodium silicate (Na2SiO3). The main purpose to introduce alkaline solution was polymerization. That is the reason scientist Davidovits named this mix as geopolymer concrete.GPC required high temperature for curing to happen the polymerization, Thus, the curing of GPC was done at ambient temperature without keeping it in water unlike the conventional concrete. Amongst both the alkali solutions i.e. NaOH and Na2SiO3, sodium hydroxide was used in different molar concentration of 10M, 12M and 14M with keeping silicate to hydroxide ratio constant as 1.5, three different sets of 9 cubes, 3 beams and 3 cylinders were casted
NOVEL ADAPTIVE AI-POWER INSULIN NAVIGATOR FOR DIABETES USING MACHINE LEARNING
Full text linkAdaptive AI-powered insulin delivery systems represent a significant advancement in diabetes management, offering enhanced precision and safety for patients with diabetes. This paper examines the development and implementation of AI-driven insulin delivery systems that dynamically adjust insulin dosages based on real-time glucose monitoring and predictive analytics. The system integrates continuous glucose sensors with adaptive AI algorithms to analyze blood glucose trends, activity levels, and dietary inputs, enabling the automatic adjustment of insulin delivery to meet individual patient needs. The study evaluates the performance of these systems in optimizing glycemic control, reducing the incidence of hypoglycemia and hyperglycemia, and improving overall patient outcomes. Key features include the ability to learn from historical data to refine dosing algorithms and the incorporation of safety mechanisms to prevent adverse events. Additionally, the paper explores user experiences and feedback, highlighting the system’s potential to improve quality of life and provide more personalized diabetes management. The integration of adaptive AI in insulin delivery systems promises to revolutionize diabetes care by offering a more responsive, accurate, and user-centric approach to insulin therapy
AUTOMATIC CONTROL OF A WHEELED ROBOT
Full text linkThis work aims to automatically control a wheeled robot from a specific location A to another B. We assume the robot’s trajectory is straight (the line (AB)). To solve this problem, we need the coordinates of point A and point B, i.e., the position sensor\u27s state. A microcontroller must then process this information. Next, the variation in coordinates mean displacement, and this variation depends on speed, so we also interest in speed here. Finally, for the robot to arrive at point B, its direction of movement must be the same as the direction of (AB). The direction depends on the orientation angle of the moving robot
MEDICAL INSURANCE PREMIUM PREDICTION WITH MACHINE LEARNING
Full text linkA machine learning method for predicting health insurance rates is presented in this article. With healthcare expenditures becoming more complex, it is critical for insurance companies and policyholders to accurately estimate insurance prices. Utilizing a dataset that included medical history, demographic data, and other pertinent variables, a variety of machine learning techniques, such as ensemble methods and regression, were used to create prediction models. R-Squared and mean absolute error were two measures used to assess these models\u27 performance. According to the developed models\u27 results, insurance premiums can be predicted with accuracy, offering useful information for insurance counteragents. This approach has the potential to optimize pricing strategies, enhance risk assessment, and improve decision-making in the healthcare insurance sector. Machine Learning-Based Prediction of Medical Insurance Premiums Make predictions about health insurance companies based on personal traits. A dataset of policyholder attributes (such as age, gender, BMI, number of children, smoking behaviors, and geography) was gathered and preprocessed .Divide the data into sets for testing and training. Create and train a model for an artificial neural network with TensorFlow and Karas. R-squared metrics and mean R-squared error were used to assess the performance of the model. created a high R-Squared predictive model that was accurate. determined the main determinants of insurance rates. Machine learning has shown promise in estimating healthcare costs. This experiment demonstrates how well machine learning predicts medical insurance rates. Insurance companies may offer more individualized insurance plans, expedite the underwriting process, and help customers make well-informed decisions about their healthcare coverage by creating these predictive models. The created model can help policyholders make educated judgments and insurance companies establish proper prices. In the long run, our research helps the insurance industry enhance data-driven techniques, which benefits insurers as well as insured individuals in general