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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
- This community features research articles from FUTO staff published in journals hosted by FUTO
- 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
- A community of printed document containing information about activities in FUTO
- A community of series of lectures aimed at educating FUTO staff and the public about a specific area of study
- A community of question(s) administered to FUTO students in an examination
- Published Research Outputs
- Theses and dissertations by students and staff from all the Schools in FUTO
Recent Submissions
''Why do i have to do research? question students' often ask''
(Federal University of Technology, Owerri, 2016-11-02) Dozie, I. N. S
Analysis and simulation of pole synchronous generator with finite element method and blondel theory to enhance performance
(Federal University of Technology, Owerri, 2022-12) Okon, Paul Edet
Synchronous generators are the only means of converting mechanical energy to electrical energy for bulk electrical power generation. As a result of saturation in its electromagnetic structure, prediction of its performance often involves approximations that seek to account for the effect of saturation. Therefore, it is necessary to develop an accurate method for prediction of the field patterns in magnetic structure to ensure precise performance evaluation. In order to compute the magnetizing reactance of salient-pole synchronous generator apart from using finite element method, a modified winding function approach was developed in this reseach, which utilize the actual winding distribution and the shape of the pole arc. This research seeks to utilize the finite element variational method (finite element method magnetics) for magnetostatic computation for magnetic field distribution in the air gap for cylindrical and salient-pole type generator. The comparative analysis of the magnetic field distribution is used to illustrate the Two Reaction Theory. The obtained results indicate magneto-motive force comparison of salient 4-pole and cylindrical rotor generator, which clearly demonstrate Andrew Blondel Theory (Two-Reaction Theory). ANSYS Maxwell also is utilized in this research to simulate and analyze salient-pole synchronous generator in order to evaluate the generator performance through electromagnetic field computation. The ANSYS Maxwell results include, moving torque, winding currents, magnetic flux linkages, induced voltages, self and mutual inductances, damper bar voltage/current and others characteristic of synchronous generator under no-load, load and three phase short circuit conditions. The results obtained agreed with the conventional acceptable parameters for the salient-pole synchronous generator.
Development of an improved model for big data analytics using dynamic multi-swarm optimization and unsupervised learning algorithms
(Federal University of Technology, Owerri, 2021-07) Oleji, Chukwuemeka Philips
An improved model for big data analytics was developed in this work using dynamic multi-swarm optimization and unsupervised machine learning algorithms. The problems of premature convergence of traditional data mining models due to the influence of heterogeneous data types and the voluminous nature of big data were solved with the developed Dynamic-K-reference Clustering Algorithm. Java programming language was used for implementation and Python Jupyter Notebook, Apache Spark frameworks were utilized for the virtualization of the clustered output results. The developed model was used to analyze a big dataset of Boko Haram insurgency attacks in Nigeria. The big dataset of
Boko Haram terrorist attacks was scraped from the social media. The attributes of the dataset including the area of attacks, period of attacks, death tolls, and attack strategies were used for the analysis for the period of 2008 to May 2019. The output clustered results of the area of attack produced 64% at Borno, Abuja 1.3%, Adamawa 1.3%, Gombe 3.8%, Kano, 2.5%, Kastina 2.5%, Maiduguri 20% and Yobe 5% respectively. The output clustered results of death tolls at different years produced 4.1% on 2011, 15.6% on 2012, 3.4% on 2013, 6.0% on 2014, 42.6% on 2015, 0.0% on 2016, 2.8% on 2017, 6.0% on 2018 and 19.5% on 2019 respectively. The results show constant attacks of Boko Haram insurgency in the study area, which had led to millions of people currently displaced and killed. The Dynamic-K-reference clustering algorithm is resourceful enough to provide clustering accuracy of 0.9820 and clustering sum of square error of 0.0018 from the analysis of the Boko Haram attacks dataset. In other to validate Dynamic-K-references clustering algorithm its performance was compared with the existing algorithms on six datasets from the machine learning repository: Hepatitis, Australian Credit Approval, German Credit Data, Starlog Heart, Soybean and Yeast. The analysis of four datasets with Dynamic-K-references clustering algorithm when compared with PSO-based K-prototype algorithm produced performance improvement of 22%, 17%, 34%, and 12%, respectively. Similar analysis of Soybean and Yeast datasets with the existing MixKmeansXFon algorithm and the Dynamic-K-reference clustering algorithm produced performance improvement of 13.8% and 13.7% respectively. From the analysis the Dynamic-K-reference algorithm was found to be robust and very efficient at expelling outliers from its dissimilar clusters/classifications. Future work should develop big data analytic services with the improved Dynamic-K-reference clustering algorithm and other improved models of its kind using a serviceoriented architectural methodology for real time analysis and prediction.
Thanksgiving mass
(St. Thomas Aquinas Catholic Chaplaincy Pastoral Council, FUTO, 2016-06-12) St. Thomas Aquinas Catholic Chaplaincy Pastoral Council
Environmental conservation information needs of farmers in Owerri West Area of Imo State, Nigeria
(Global Journals Inc. (USA), 2013) Nnadi, F. N.; Chikaire, J.; Echetama, J. A.; Umunnakwe, P. C.; Ihenacho, R. A.
The enormous consequences of the wanton devastation of the environment inspired this study that evaluated the environmental conservation in Owerri West Area of Imo State, Nigeria. The objectives of the study was; to determine the socio-economic characteristics of the farmers, ascertain the farmers environment conservation information needs, investigate their environmental conservation practices and identify the problem militating against sustainable environment conservation practices. The data for the study was collected from 120 randomly selected farmers from 6 communities out of the 18 existing communicates in the area of study. The data collected were analyzed with the use of descriptive statistics such as frequency counts, percentages, mean. The result showed that farmers needed information in the area of environmental disaster management and funding sources for environmental management. The perceived effects of environmental conservation were to improve the farmers’ socio-economic life and reduce hazards. The results also showed that inadequate knowledge base of environmental conservation practices was a major problem militating against environmental conservation and that maturing was the most conservation practice carried out by the farmers. It was however recommended that extension education campaigns on environmental conservation practices should be intensified and the socio-economic determinants of the farmers’ information need to be considered in interventions and advocacies