Systems Engineering- Staff Publications

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    Open Access
    An Optimized Telecommunication System Topology for Expenditure Minimization and Improved Spectral Utilization Efficiency
    (FUNAI Journal of Science and Technology, 2015) Ogunwolu, L.; Ibidapo-Obe, O.; Adeyemi, T.
    Capital expenditures (CAPEX) and Operational Expenditure (OPEX) have always been on the high side if transmission networks are not efficiently planned to minimize these costs. The arrays of antenna often sighted on mast/tower around often post a major risk to the industry as CAPEX increases with increased hardware and signal processing cost. This paper explores the use of point to multipoint (PMP) method of backhauling traffic for cognitive radio network as veritable alternative to existing transmission Point to Point (PTP) Topology in other to minimize CAPEX and OPEX as well as improve spectra utilization efficiency. The work is focused on small cell deployment for more data penetration in a redundant setup to improve system availability. In the work, the Dijkstra Algorithm for Shortest route analysis was used to prove the advantage of Point to multi point approach in the optimal path planning in a transmission network taking cognizance of path costs as the capital expenditure, path loss, latency, throughput, frequency channel allocation. Furthermore, a spectrum utilization problem was defined, formulated and analyzed. Solution of this model was validated using a simulated setup on a section of Ikorodu ( and ) transmission axis. Results obtained from the analysis show that our model of PMP method of transmitting/backhauling is more capable of improving the spectral efficiency of a wireless telecommunication network and outperforms the PTP topology on all network measures influencing capital and operational expenditures.
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    Open Access
    A Decision Support Model and Analysis for Aircraft Maintenance Planning
    (International journal of Mathematics Analysis and Optimization: Theory and Application, 2015) Ogunwolu, L.; Popoola, O.P.; Ibeh, S. C.
    Aircraft maintenance planning and scheduling is a major decision airline operators must make. If properly done, this can result in huge cost savings and high productivity. Maintenance downtime (from daily inspections, component replacements and different types of scheduled checks) is a key operational bottleneck that must be minimized while maintaining aircraft for safety and reliability. This paper provides a planning model which determines the optimal solutions to aircraft maintenance planning and scheduling using a Non-Linear Pure Binary Mathematical Program solved using the Evolutionary Algorithm search engine of the Excel Solver. Results obtained using data from an actual airline for the proposed model and heuristic results in a higher likelihood of meeting operational flight schedule at relatively minimized overall downtime. There is an optimal balance between constraints set by irregular component failures, regulatory maintenance requirements and the anticipatory expectations of meeting projected flight schedule over a given period operation.
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    Open Access
    A Linguistic Fuzzy Expert System for Contagious Diseases Detection and Isolation
    (UNILAG Journal of Medicine, Science and Technology, 2014) Osigbemeh, M.S.; Ogunwolu, F.O.; Omoare, A.A.; Inyiama, H.C.
    This paper presents an electronic Expert system platform to detect and diagnose existing and new cases of contagious diseases as they occur with minimal contact with the index patient(s) and healthcare personnel with a confidence level that can be used to initiate or suggest appropriate follow-up action(s). The aim is to use ICT tools for patient-diagnosis, raise a red flag in real-time and thus contain contagious cases which may degenerate into an epidemic by providing a way to analyze vague and ambiguous input data from visible and reported symptoms in patients. A re-useable Expert system which makes use of fuzzy reasoning techniques and design methodology was used in this work. The Expert system is premised on rule-based fuzzy logic which captures the ambiguity, imprecision and nuances involved in disease reporting and detection using the Mamdani model. The software developed for the Fuzzy Expert system, called SOSIC, presents its diagnosis with fuzzy values between 0 to 1 corresponding to its level of confidence for the fuzzy inputs. The current approach to e-diagnosis and detection of contagious diseases using the SOSIC software is not completely contactless, thus ongoing investigations are geared towards improving SOSIC to be contactless. The developed system which runs on a computer system provides a safe procedure with minimum contact between patients and healthcare personnel to address early detection and diagnosis issues that may help forestall chain-infection and epidemics. The fuzzy based Expert system can be further extended to accommodate the detection of a wider array of symptoms as new cases arise; thus this paper fulfils an identified need in safe healthcare practice.
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    Open Access
    Modeling and Optimization of an Electric Power Distribution Network Planning System Using Mixed Binary Integer Programming
    (Nigerian Journal of Technology, 2017) Ogunwolu, L.; Ero, O.; Ibidapo-Obe, O.
    In this paper, the electric distribution network expansion planning problem (EDNEPP) was solved by a mixed binary integer programming (MBIP) formulation of the network, where the steady-state operation of the network was modelled with non-linear mathematical expressions. The non-linear terms are linearized, using piecewise linearization of the nonlinear expressions, so as to ensure the model computational compatibility with existing commercial optimization solvers. The linearized formulation is verified to ensure its solution optimality and degree of error deviation. The proposed network model formulation considers the alternatives of installation of new transformers of various capacities to reinforce already existing ones at substations of the network, choosing and construction of new substations given feasible locations, re-conductoring of existing feeders in the network, construction of new feeders given various conductor types alternatives, cost lost as a result of power interruption, and changes in the overall network topology. The cost of interruption would contain a cost term called ‘cost of goodwill’, which was brought into the model formulation, to measure the loss in confidence of consumers to distributors of power as a result of interrupted power supply, which is prevalent in developing nations. Two test systems of 23 and 54 nodes was used in showing the efficiency of the proposed network model formulation.
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    Open Access
    Modelling. Optimization and Analysis of Re-Entrant Flowshop Job Scheduling with Fuzzy Processing Times
    (Nigerian Journal of Technology, 2017) Ogunwolu, L.; Sosimi, A.; Obialo, S.
    This paper presents a makespan minimization of -jobs -machines re-entrant flow shop scheduling problem (RFSP) under fuzzy uncertainties using Genetic Algorithm. The RFSP objective is formulated as a mathematical programme constrained by number of jobs and resources availability with traditional scheduling policies of First Come First Serve (FCFS) and the First Buffer First Serve (FBFS). Jobs processing times were specified by fuzzy numbers and modelled using triangular membership function representations. The modified centroid defuzzification technique was used at different alpha-cuts to obtain fuzzy processing times (FPT) of jobs to explore the importance of uncertainty. The traditional GA schemes and operators were used together with roulette wheel algorithm without elitism in the selection process based on job fuzzy completion times. A test problem of five jobs with specified Job Processing and Transit Times between service centres, Job Start Times and Job Due times was posed. Results obtained using the deterministic and fuzzy processing times were compared for the two different scheduling policies, FCFS and FBFS. The deterministic optimal makespan for FBFS schedule was 61.2% in excess of the FCFS policy schedule. The results also show that schedules with fuzzy uncertainty processing times provides shorter makespans than those for deterministic processing times and those under FCFS performing better than those under FBFS policy for early jobs while on the long run the FBFS policy performs better. The results underscore the need to take account of comprehensive fuzzy uncertainties in job processing times as a trade-off between time and costs influenced by production makespan.