Nnamdi Azikiwe University Journals
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Development of pacemaker using signal conditioning, sensor integration and control systems techniques
No full textThe rising incidence of mortality in hospitals today can be attributed, in part, to the inadequacy and inefficiency of existing medical instruments to swiftly and accurately diagnose ailments. This underscores the urgent need for the development of effective medical equipment, such as pacemakers. In this context, observations from a conventional bradycardia case revealed a heart rate of 0.85 Hz, which falls below the normal healthy threshold of 1.0–1.67 Hz. However, with the integration of a pacemaker, the system was able to immediately sense, process, and correct this anomaly, restoring the heart rate to a healthy range. Similarly, in the domain of biomedical instrumentation, conventional battery voltage was observed to be approximately 2.4 V, insufficient for efficient charging and sustained device operation. Upon integration of the pacemaker system, the voltage was processed and elevated to 2.88 V, effectively meeting the operational threshold (2.8 – 3.0 V) and significantly enhancing the charging and working capability of the battery-powered medical device. These findings affirm the critical role of pacemakers and related instrumentation in improving the diagnostic and therapeutic efficacy of modern healthcare systems
Phyto-chemical screening, proximate analysis mineral composition of musa paradisiaca leaf ash (MPLA) for water treatment applications
No full textThe pervasive issue of accessing potable water remains a critical challenge in numerous developing nations, conventional water treatment methodologies frequently rely on synthetic chemicals, which often necessitate importation at considerable expense, potential health risks, exemplified by the correlation between aluminum-based coagulants and the onset of Alzheimer\u27s disease, the production of substantial sludge volumes. Consequently, the imperative to mitigate the risks inherent in synthetic chemical usage necessitates the exploration of cost-effective and sustainable alternatives for water treatment, without compromising coagulation efficacy or microbiological integrity. Natural coagulants present an environmentally conscious alternative to their chemical counterparts. Musa Paradisiaca leaf ash is an agricultural waste in need of disposal. In this work the characterization of Musa paradisiaca leaf ash was undertaken to investigate suitability for water treatment applications. The results reveal the existence of Aluminium (AI) 12.3%, 7.5%, Carbon (C) 7.0%, 6.67%, Calcium (Ca) 5.20%, 22.09%, Iron, (Fe) 3.0%, 5.0%, Nitrogen (N) 4.0%, 4.0%, Oxygen (O) 20.3%, 10.43%, and Silicon (Si) 47.3%, 44.31% for Musa paradisiaca leaf ash and Musa paradisiaca stalk ash respectively. The result for nutritional content are as follows 1.95 mg/100g and 2.35 mg/100g for tannin, 0.16 mg/100g and 0.19 mg/100g for phytate, 0.48 mg/100g and 1.72 mg/100g for alkaloid, 8.7 mg/100g and 2.7 mg/100g for saponin, 36.55 mg/100g and 38.14 mg/100g for flavonoid, 18.6 mg/100g and 2.1 mg/100g for crude protein 9.5 mg/100 and 9.6 mg/100g for moisture content, 7.3 mg/100g and 9.2 mg/100g for ash content, 54.4 mg/100g and 63.5 mg/100g for carbohydrate, 1.6 mg/100g and 0.9 mg/100g for crude lipids and 8.6 mg/100g and 14.7 mg/100g for crude fibre for Musa paradisiaca leaf ash and Musa paradisiaca Stalk ash respectively
Prediction of Welding Parameters to Minimize Undercut Defects in Arc Welding Using Response Surface Methodology (RSM): A Robust Multi-Factorial Analysis
No full textUndercut defects in gas metal arc welding (GMAW) compromise weld integrity and structural performance, leading to increased rework costs and potential safety risks. Traditional trial-and-error approaches for parameter optimization are inefficient and lack scientific rigor. This study aims to systematically investigate and optimize welding parameters (current, voltage, and speed) to minimize undercut defects in low-carbon steel welds using a data-driven approach. The research employed Response Surface Methodology (RSM) with a face-centered central composite design, conducting 20 experimental runs to analyze parameter effects. Advanced statistical tools, including ANOVA and regression analysis, were used to develop a predictive model and identify optimal welding conditions. The quadratic model demonstrated exceptional accuracy (R² = 0.998) in predicting undercut formation, with welding speed emerging as the most influential parameter. The study successfully identified optimal parameters (200 A, 21.5 V, 85 mm/sec) that reduced undercut by %, providing a reliable framework for quality improvement in industrial welding applications. These findings recommend adopting RSM-based optimization to enhance weld quality while reducing production costs. Future work should explore the model\u27s applicability to other materials and joint configurations
Integrating Statistical Diagnostics and Machine Learning for Predicting House Prices in Nigeria
No full textAccurate prediction of house prices is critical for real estate valuation, mortgage risk assessment, and urban planning. Traditional statistical models, such as multiple linear regression, provide interpretable insights but are often constrained by multicollinearity, heteroscedasticity, and limited explanatory power. In contrast, machine learning algorithms are capable of capturing complex relationships but frequently lack transparency. This study integrates statistical diagnostics with machine learning techniques to develop a more robust predictive framework for the Nigerian housing market, using a dataset of 12,592 residential properties. Regression diagnostics, including multicollinearity checks and residual analysis, were combined with multiple linear regression, Ridge regression, Lasso regression, Random Forest, and Gradient Boosting. Results show that Ridge and Lasso regression provided the most reliable performance, with Ridge achieving the best balance between predictive accuracy (R² = 0.204) and interpretability. Ensemble methods, unexpectedly, underperformed due to the categorical-heavy structure of the data. The findings highlight the value of hybrid approaches that embed diagnostics into machine learning pipelines, offering models that are both transparent and practically useful for policy and decision-making
Finite element modelling and prediction of cutting temperature in carbide insert cutting tool
No full textThe finite element modeling and prediction of cutting temperature in carbide insert cutting tool was investigated in this study under varying process parameters of 200-600rpm spindle speed, 0.05-0.15mm/rev feed rate and 0.5-1.5mm depth of cut. The aim of the study is to show how efficient Finite Element method is in predicting the cutting temperature of carbide cutting tool, by comparing its predictive strength to the experimental machining operation. To achieve the aim of the study, seventeen varying cutting tool tests were conducted using the three levels Box-Behnken’s design (BBD) of experiment. Combing both methods enhances the accuracy of the prediction efficiency compared to the single method techniques. FEM predicted cutting temperature were found to be 72.10 oC and 72.66oC respectively at 200rpm spindle speed, 0.1mm/rev feed rate and 0.5mm depth of cut. The model had a mean percentage error of 0.58% and a R2 value of 0.9987. Validation of the model using reliability plot indicated no significant difference between the experimental observations and the model prediction.
 
Infuence of Land Use / Land Cover on Soil Properties at the Forestry Research Institute of Nigeria (FRIN), Oyo State, Nigeria
No full textLand cover transformation in and around the Forestry Research Institute of Nigeria (FRIN) can significantly alter soil physical and chemical properties, with potential impacts on soil fertility and ecosystem health. This study investigates how different land use types; undisturbed and harvested Gmelina arborea plantations (UGP and HGP) influence soil characteristics at FRIN in Jericho, Ibadan, Oyo State. Soil samples were taken at two depths (0-15 cm and 15-30 cm) and analysed at the IARandT, Moor Plantation soil laboratory for particle size distribution, pH, Organic Carbon (OC), Organic Matter (OM), Total Nitrogen (TN), exchangeable bases, cation exchange capacity (CEC), and micronutrient levels. The results showed differences between UGP and HGP land use types. UGP soils were slightly acidic pH (5.6), while HGP soils were slightly alkaline pH (6.5). At the 0-15 cm depth, UGP had higher OC (10.5), OM (17.68), and TN (1.054) compared to HGP OC (7.64), OM (12.97), TN (0.056). This pattern held at 15-30 cm, with UGP consistently exhibiting richer nutrient profiles. Exchangeable base levels and trace element concentrations in the UGP showed lower levels of Ca²⁺, Mg²⁺, K⁺, Na⁺, and trace elements like Fe3⁺, Zn²⁺, and Cu²⁺ than HGP, while maintaining higher CEC. The study concludes that differences exist in soil characteristics between UGP and HGP within FRIN. The findings show the importance of sustainable land management practices to support soil fertility and ecosystem health. The study recommends re-afforestation of harvested plantations to preserve soil quality and counteract the negative effects of land use changes
Effect of Organic Soil Amendments on Growth and Yield of Amaranthus viridis L.
No full textA pot experiment was carried out to evaluate the effect of some soil organic amendments on the growth and yield of Amaranthus viridis L. in Ifite-Ogwari, Ayamelum L.G.A. of Anambra State. The study was laid out in a completely randomized design (CRD) with seven treatments and replicated three times. The treatments were Topsoil (T1) , Rice husk +Topsoil (T2), Rice Straw + Rice Husk + Topsoil (T3), Rice Straw + Topsoil (T4), Rice Straw + Topsoil + Poultry Manure (T5), Rice Straw + Rice Husk + Topsoil + Poultry Manure (T6), Rice Husk + Topsoil+ Poultry Manure(T7). Each soil amendment combination were mixed in the ratio of 3:2:1; where Topsoil represented the 3 parts, Rice straw and/or Rice husk represented the 2 parts, and Poultry manure represented the 1 part. In situations where rice husk and rice straw were mixed, the two parts was in the ratio of 1:1 for each of the rice residues. The treatments were separated using the least significant difference (LSD) at 5% probability level. The addition of organic soil amendments, particularly those involving poultry manure (PM), had positive effects on the growth parameters and yield of A. viridis. The RS+TS+PM treatment consistently showed promising results in terms of plant height, leaf number, leaf area, stem girth, and leaf yield. Since the RS+TS+PM treatment gave the highest yield, it is recommended that farmers use this mixture for growing A. viridis due to its nutrient content
Advancing Global Smart Agriculture with AI and IoT: A Systematic Review of Technologies, Applications, and Challenges
No full textThe integration of Artificial Intelligence (AI) and the Internet of Things (IoT) is transforming agriculture by enhancing precision farming, improving resource efficiency, and promoting sustainability. This study systematically reviews emerging AI and IoT applications in smart agriculture, examining their role in agricultural productivity, identifying barriers to adoption, and assessing their impact on climate-smart practices. A structured data extraction process was employed, sourcing peer-reviewed studies from databases such as PubMed, Scopus, IEEE Xplore, and Google Scholar. Eligibility criteria ensured a focus on AI and IoT applications in crop management, pest control, food safety, and supply chain optimization, with studies published between 2019 and 2024 included. Thematic and statistical synthesis categorized findings based on technological innovations and agricultural applications. The results highlight the transformative potential of AI and IoT in optimizing agricultural processes, though challenges such as high implementation costs, technical limitations, and socio-cultural barriers persist. To maximize the benefits of these technologies, policymakers and stakeholders must invest in infrastructure, enhance digital literacy among farmers, and promote inclusive policies that facilitate the adoption of AI and IoT, particularly in resource-limited settings. This review provides valuable insights for advancing smart and sustainable agricultural practices globally
Innovative Feed Technology in Aquaculture Production in Nigeria
No full textAuaculture is the fastest growing food sector in Nigeria which has the potential to meet the increasing demand for fish and ensure food security. The success of aquaculture heavily relies on the quality and efficiency of the feed provided to fish. High quality fish feed is important for the success of aquaculture because it significantly affects fish health, growth, and the sustainability of aquaculture operations. One of the significant challenges in aquaculture production is the high cost and limited availability of sustainable fish feed. In recent years, there has been a growing interest in the development of innovative feed technology that can help to improve the efficiency and sustainability of aquaculture production in Nigeria. These technologies include the use of sustainable alternative feed ingredients, advanced feed processing methods, implementation of automated feeding systems and the use of functional feed additives. Traditional fish feed are typically based on fishmeal and fish oil, which are expensive and in limited supply. Sustainable alternatives to fish meal such as plant-based proteins, insect meals, single-cell proteins, and microalgae improve feed sustainability, reduce costs of feed production and reliance on wild fish stocks. Advancements in feed processing, including extrusion, pelleting, and encapsulation improve feed digestibility, reduce nutrient losses, and enhance feed conversion efficiency. Technological innovations in automated feeding systems such as AI-driven sensors, drones, and automated feeders minimize waste, improve feed conversion ratios, and reduce operational costs. The inclusion of functional feed additives, such as prebiotics, probiotics, enzymes, and immunostimulants enhance feed digestibility, boost immune function, and promote growth performance in fish. Continued research and investment in feed innovation will be important for the long-term success of the aquaculture sector in Nigeria
LOGISTICS SERVICE RECOVERY AND CUSTOMER RETENTION IN THE CONSTRUCTION AGGREGATES INDUSTRY IN CROSS RIVER STATE
No full textThis research was on logistics service recovery and customer retention in the construction aggregates industry in Cross River State. We sought to determine the effects of post-failure analysis, communication management and technical innovation management on customer retention in the construction aggregates haulage business. Cross-sectional survey research design was adopted. Using a structured questionnaire, primary data were elicited from 182 personnel from the operations, logistics and marketing department of haulage companies in Akamkpa. The data obtained were descriptively analyzed, while hypotheses testing was done using multiple linear regression. The findings of the study revealed that post-failure analysis, communication management and technical management had significant positive effects on customer retention in the construction aggregates haulage business in Akamkpa. Hence, the study recommended, among others, that: logistics companies should initiate a well-coordinated post-failure analytical exercise in the aftermath of every failure incident in order to identify the type of failure that has occurred, its root causes, impact on its operations and the recovery measures required to address the incidents; and logistics companies should prioritize effective communication during service failures by providing factual, timely, and transparent information to customers in an empathetic way to lessen the adverse impacts of the incidents on customers and to provide confidence in their recovery capabilities.