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FUTOSpace is the Federal University of Technology, Owerri open-access repository that collects, preserves and make available in digital format the intellectual output of the university's community:
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- This community features addresses and speeches delivered by the University management and other official visitors to FUTO
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- This community features books, book chapters and books published by faculty members in the university
- This Community features the proceedings of conferences, seminars and workshops hosted by the FUTO or other bodies but had staff from FUTO attending and making presentations
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- A community of series of scholarly public lectures designed to commemorate a faculty member's appointment to a professorship
- Scholarly resources with relevant discussion points for use by faculty as teaching lectures, student reading content, and study guides
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- Published Research Outputs
- Theses and dissertations by students and staff from all the Schools in FUTO
Recent Submissions
Advanced Soil and Water Management
(Federal University of Technology, Owerri, 2017) School of Agriculture and Agricultural Technology, Department of Soil Science and Technology.
Optimization of water injectivity and oil recovery through lateral radial drilling into the reservoir
(Federal University of Technology, Owerri, 2023-08) Onyejiaka, Uchenna Nonyerem
The efficiency of water injectivity into the reservoir is greatly reduced by poor reservoir permeability and near well bore damage. However, the aim of this study is to evaluate the possibility of improving oil recovery during water flooding by using radial drilling technique which has the capacity of achieving longer perforation length than the conventional perforation operation. Perforation length up to 100 m (330ft) into the fresh formation beyond damaged zone can be obtained with radial technology. Eclipse simulator, version 100 was used to model the lateral radial drill and conventional perforation into there servoir. The key project indicators that were studied are injectivity index, displacement efficiency,recovery factor and water cut using different radial drill configurations. It was observed that water injectivity was improved with radial drill case with the increasing length and number of radials as compared to the conventional wellbore perforation case. There was aprogressive increase in recovery factor with increase in number radials irrespectiveoftheradial length. Also, the water cut from the producer well was increasing as the number and length of the radials were increasing. Therefore, radial drilling is seemingly apromising technology that can be used to improve water inj ectivity and hence maximize oil recovery in a water flooding scheme.
Study of the impact of acidulated rainwater on leaf tissues of tomato(Solanum lycopersicum Linn.) and pepper(Capsicum annum Linn.)
(Federal University of Technology, Owerri, 2024-08) Adamu, Santuraki Ibrahim
The acidulation of rainwater is connected intimately with industrial development. The leaves of Tomato and Pepper were examined for the impact of acidulated rainfall on their morphology, anatomy, and physiology. Rainwater samples collected from industrial and automobile traffic congested Cities of Lagos, Port Harcourt, Kano, and Gombe (control) were used in a screen-house experiment. The effect of atmospheric gases NO2, SO2, and CO2 was determined on morphology, anatomy of phylloplane, photosynthetic chlorophylls, and agro-morphology of the plants. Statistical package R version 4.2.1 was used to analyze data. Duncan’s multiple-range test was used to determine the significance of the mean difference. The findings showed that from April through July, the concentrations of atmospheric acid derivatives were significantly (p<0.05) decreased. Morphological changes such as physical damage to the leaf, formation of white Scars, and necrosis were observed. Anatomical changes such as alterations on the cuticle and collapsed epidermal cells and the formation of lobules of scarred tissue were observed. Plants heights were significantly reducedat(p<0.05) (FTomato=7.8894; FPepper=63.835), leaf area was also significantly decreased (FTomato=16.341; FPepper=60.965;p<0.05), stem girth were also significantly (p<0.05) reduced (FTomato=8.8174;FPepper=39.3), number of leaf (FTomato=22.482; FPepper=34.265), Relative growth rate (FTomato=38.522;FPepper=40.646) and chlorophyll content (FTomato=8.4128, 2.5368, 11.411; FPepper=4.6029, 7.8154, 36.746) were also significantly(p<0.05) decreased. The findings showed that both car emissions and heavy industrial activities contributed significantly to the acidity in rainwater. It also demonstrated that acidified rainwater significantly affects the morphology, anatomy, and physiology of plants studied. It is, therefore, important to plant acidophilic trees in the study areas to reduce the effect of acid rain on other vegetable crops.
Nuclear Techniques in Soil and Plant Research
(Federal University of Technology, Owerri, 2017) School of Agriculture and Agricultural Technology, Department of Soil Science and Technology.
Development of a web-based machine learning money laundering detection and prevention model
(Federal University of Technology, Owerri, 2024-07) Chukwunonso, Hampo Johnpaul Anenechukwu
Explicitly programmed systems, rule-based systems and machine learning systems exist as antmoney laundering systems, however, these systems are for the detection and not prevention of money laundering. This thesis is concerned with the detection and prevention of money laundering by developing a web-based model that uses machine learning (ML) to detect and prevent money laundering transactions. Money laundering which is synonymous with clothes laundering is the process of transforming the real nature of the source of income or money which is usually an illegitimate source to a legitimate source. The model was developed using open datasets on financial transactions from Kaggle.com, which is an open-source website that holds a lot of data. Questionnaires were administered for data acquisition and requirement collection. The questionnaire was given out to people in the banking sector, and the data were analysed to reveal that most respondents see a need for this system and believe it will lead to better financial monitoring and decision-making. The RAD software methodology was applied and Python programming language and Python frameworks were used for this model. recall of 100%, an f1 score (f-measure) of 99.2% and a precision of 98.3% were achieved by this research against the existing system’s metrics of 97%, 97% and 98% for f1-score, precision and recall respectively.Also, an accuracy of 98.4% and 81.9% was achieved for the detection model and the prevention model respectively.