Welcome to FUTOSpace
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:
Communities in FUTOSpace
Select a community to browse its collections.
- This community features addresses and speeches delivered by the University management and other official visitors to FUTO
- A community of media or content used to convey information about an event organized at the university
- 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
Intelligent evaluation system for software quality measurement
(Federal University of Technology, Owerri., 2022-12) Nwandu, Ikenna Caeser
The concern about the large-scale and complexity of contemporary software
cannot be over-emphasized. This is inclined to the assurance of standardized
software quality which is essential for preventing disastrous effects of releasing
fault-prone systems. This thesis designed an intelligent model that uses various
metrics corresponding to six quality attributes (namely Reliability, Usability,
Efficiency, Functionality, Maintainability and Portability) to measure the quality of
software. This agreed to the assertion that software quality evaluation process is an
instrument that observes the characteristics of a software product. In software
engineering, the primary quality evaluation and assurance technique that
establishes confidence over successful execution of software is termed software
testing. Software testing usually identifies and applies metrics to software products
in order to promote and assess their quality. This thesis designed an intelligent
evaluation model in conformance with software testing principles. The objective of
the model is to apply reinforcement learning in its software evaluation process to
measure six software attributes in terms of speed of execution and to ensure
optimal decision-making in the evaluation process, such that the model returns a
reliable outcome. The model utilized a formulated model equation, whose input are
the measured attributes, to achieve the evaluation. The model is developed using
extreme programming principles, an agile framework whose operation is based on
simplicity. It also adopted object-oriented analysis and design methodology which
allowed the utilization of various artifacts including use cases, data flow, sequence,
flowchart, entity-relationship and class diagrams to describe the architecture and
functionality of the system. The model was implemented using Python
programming language with the database design on MySQL platform. The model
is further validated by comparing its performance measures on test data gotten
from the functional information of Oil-palm Management Program and Estate
CanePro. These tests data produced quality values of 0.9 and 1.0 respectively via
the model equation. These results gave the indication that the resource software
perform efficiently owing to the fact that the model’s value benchmark is best as it
approaches unity. The result of comparing the outcomes showed that reinforcement
learning makes software evaluation dynamic and precise. The results indicated that
the model independently determines the strategies to follow during evaluations and
the same set of data consistently gives the same outcome. The result also showed
that the reliability of a software is directly proportional to its usability and
maintainability. However, the result also showed that having a high portability
value does not guarantee the reliability and/or maintainability of a given software.
Modelling of Nigeria’s Liquefied Natural Gas Shipping Trade
(Federal University of Technology, Owerri., 2022-12) Igboanisi, Chinaemerem C.
Nigeria has the largest proven natural gas reserves in Africa and its reserves ranked as ninth (9th) largest in the World- accounting for 188.8tcf (trillion cubic feet) of proven reserves as at the year 2019. However, Nigeria’s capacity to participate in the global natural gas shipping trade and earn freight revenue has been constrained by shipping tonnage market domination by other nations. Thus, as the nation strives to improve her revenue earnings through robust visible and invisible trade policy; it has become imperative to investigate empirically the determinants of Nigeria’s international shipping
trade in Natural gas.
This research developed the gravity model of Nigeria’s natural gas
(NLNG) shipping trade to determine the factors affecting NLNG international freight market. The secondary data for the study comprised of volume of natural gas production (in billion cubic meters) shipped between Nigeria and other trading partner countries, geographical distance data between trading partner countries, population mass of trading partners, price of natural gas and bilateral trade agreements. Others include: logistics performance indices and shipping freight rates. These were sourced from global databases, Nigeria LNG limited, the Nigerian Ports Authority and covered the periods
between years 2003 to 2020. To address the hypotheses governing this research, we developed an augmented gravity model of natural gas shipping trade in Nigeria’s international freight market and examined trends in demand. The following variables were found statistically significant in explaining NLNG trade namely: quality of transport infrastructure (-225.448), geographical distance (-232.721), trade agreement (42.534) and population mass (0.955). These coefficients are in their natural logs and can therefore be
interpreted as elasticities. In terms of most important trading blocs or shipping routes, the most important shipping routes (which are dummy variables) are namely: The United States of America (3,360.056), EuroAsia (3,090.082), Europe (904.810) and South America (786.413). These findings indicate that robust policy interventions are needed to promote trade with our trading partners. Robust investments are also needed in our transport infrastructure quality (especially that of bunkering facilities for LNG vessels) in order to reduce impediments to trade.
From the positive trend analysis results, demand
for natural gas is positive and the federal government should encourage more private sector investment in LNG shipping fleet to increase Nigeria’s participation in LNG international freight market. As recommendation for further studies, modelling of constraints of natural gas trade involving gasification and re-gasification stations should be explored in order to expand the scope of the present work.