Browsing by Author "Opadiji, Jayeola"
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Item Agent-based adaptive production scheduling - a study of cooperative-competition in federated agent architecture(Springer-Verlag, Tokyo, 2009) Opadiji, Jayeola; Kaihara, ToshiyaAn increasingly popular method of improving the performance of complex systems operating in dynamic environments involves modeling such systems as social networks made up of a community of agents working together based on some basic principles of social interaction. However, this paradigm is not without its challenges brought about by the need for autonomy of agents in the system. While some problems can be solved by making the interaction protocol either strictly competitive or strictly cooperative, some other models require the system to incorporate both interaction schemes for improved performance. In this paper, we study how the seemingly contradictory effects of these two behaviours can be exploited for distributed problem solving by considering a flexible job shop scheduling problem in a dynamic order environment. The system is modeled using federated agent architecture. We implement a simple auction mechanism at each processing center and a global reinforcement learning mechanism to minimize cost contents in the system. Results of simulations using the cooperative-competition approach and the strictly competitive model are presented. Simulation results show that there were improvements in cost objectives of the system when the various processing centers cooperated through the learning mechanism, which also provides for adaptation of the system to a stream of random orders.Item Application of Off-Grid Energy Sources to Reduce Rate of Increase in Demand on National Grids(University of Ilorin and Cape Peninsula University of Technology, 2011) Olorunmaiye, John; Opadiji, Jayeola; Ajiboye, TajudeenThe demand for electrical energy from the national grids is increasing in African countries as result of population growth and construction of more residential buildings. Residential electricity usage constitutes a high percentage of electrical energy demand from national grids in most African countries because of the low level of industrialization In the last few years, some companies have started operating in Nigeria installing solar panels to charge deep-cycle batteries to supply electricity to residential buildings. A case study of a home where it was installed showed that their average monthly electricity consumption has reduced from 352.14kWh before the installation to 154.73kWh after the installation as indicated by the 3- phase meter provided by Power Holding Company of Nigeria. In that home a solar plate collector for heating water was to also installed to produce warm water for bathing. This resulted in a saving of about 2kg of Liquefied petroleum gas per month. If most residential buildings in a country adopt these technologies to provide electricity and hot water instead of using electric water heater, the energy demand from the national grid per building will reduce.Item Development of adaptive sensing algorithm for minimizing energy and bandwidth consumption in cooperative spectrum sensing technology(2019) Opadiji, JayeolaOptimized consumption of energy and bandwidth is crucial for efficient utilization of the limited electromagnetic spectrum for telecommunication purposes. Cognitive radio is one of the dynamic spectrum management applications with numerous benefits related to the management of available spectrum. But it has the challenge ofhigh energy and bandwidth usage when the cooperative scheme of spectrum sensing is applied for accurate sensing. In this paper, an adaptive spectrum sensing algorithm is developed to minimize energy and bandwidth consumption in cognitive radio spectrum sensing while ensuring accurate spectrum sensing. The adaptive algorithm was developed based on the signal-to-noise ratio conditions of the channel. Results reveal that the energy and bandwidth usage by the cooperative spectrum sensing can be significantly reduced without negatively affecting the performance and detection of the cognitive radio in varying noisy conditionsItem Development of computer-aided learning software for graphical analysis of continuous-time control systems(Faculty of Engineering, University of Ilorin, 2010-06) Opadiji, JayeolaWe present the development and deployment of a computer-aided learning tool which serves as a training aid for undergraduate control engineering courses. We show the process of algorithm construction and implementation of the software which is also aimed at teaching software development at undergraduate level. The scope of this project is limited to graphical analysis of continuous-time control systems.Item Distributed production scheduling using federated agent architecture(Springer-Verlag, Berlin,, 2007) Opadiji, Jayeola; Kaihara, ToshiyaMaking a production system readily reconfigurable in a bid to adapt to very fluid demand profile is pertinent to cost reduction and facility utilization objectives of the system. We consider a production scheduling methodology based on federated agent architecture designed for a flexible job shop with dynamic demand. The interaction protocol within the social network is based on a facilitated auction mechanism. Facilitator agents are responsible for coordinating information flow between a controller agent and processors in different job centers. These facilitators interact in such a way as to reduce tardiness of tasks once an order is accepted by the controller agent. This model employs competition at job centers to maximize financial returns and uses cooperation among facilitator agents to minimize weighted tardiness.Item Dynamic optimization of soft handoff thresholds of a base transceiver station in CDMA networks(Department of Electrical Engineering, Ahmadu Bello University, Zaria., 2011) Opadiji, Jayeola; Ayeni, Adeseko; Oyeniyi, Yetundework presents a dynamic optimization protocol which is aimed at improving the performance of a cell in a CDMA network during call handoff process by reducing the number of dropped calls. The protocol responds to a changing number of call requests in a cell by adjusting soft handoff thresholds in such a way as to minimize call drops. The optimization model and a Genetic Algorithm (GA) based solution to the dynamic optimization problem are presented. Original simulation programmes were written in Java and results from simulations performed using the proposed method and the existing handoff protocol based on static preprogramming of the threshold values show that the proposed method outperforms the existing method.Item Experimental investigation of the effect of change in ambient air temperature on power consumption of domestic refrigerators,(Faculty of Engineering, University of Ilorin, 2012) Olorunmaiye, John; Awolola; Opadiji, JayeolaOne of the manifestations of climate change is increase in ambient temperature usually referred to as global warming. For sustainable development in a country, there is need to identify impacts of climate change and the necessary adaptation and mitigation strategies to adopt. To simulate the effect of global warming on the power consumption of refrigerators, a (model No. 150) THERMOCOOL refrigerator filled with twenty-five 75cl packaged ware was run in an air-conditioned room, in a room with the air-conditioner switched off and near an oven in a bakery. The electric power consumption of the refrigerator was measured using "Watts up!.net" watt meter and the ambient temperature was measured using FLUKE temperature/humidity meter. The average hourly energy consumption of the refigerator operating at mean ambient temperatures of 25.4C, 30.7C, 38.8C were 93.844Wh, 100.32Wh, 105.08Wh, respectively. Some possible ways to reduce the increase in power consumption of refrigerators due to global warming include using compressors of higher efficiency and condensers of greater effectiveness.Item Genetic algorithm-based precision tuning of digital P-I-D controller for second-order systems(Faculty of Engineering, University of Ilorin, 2011) Opadiji, Jayeola; Ajiboye, AyeTuning of the PID controller is often done by trial and error which is tedious, time consuming and relatively inefficient. A more reliable and efficient approach of tuning the PID controller is presented using genetic algorithm. The scope of this work is limited to obtaining control parameters of a digital PID controller for a second-order system, given the desired time-response parameters.Item Improved energy detection algorithm for cognitive radios in cooperative spectrum sensing(Published by Faculty of Communication and Information Science, University of Ilorin, Ilorin, Nigeria, 2019-05) Fajemilehin, Temitope; Olatunji, Samuel; Opadiji, JayeolaBackground: The performance of algorithms used in white space detection in cooperative spectrum sensing is largely dependent on the sensitivity of the cognitive radios used. The sensitivity of the radios is measured in terms of the probability of missed detections and probability of false alarms. Aim: This work is aimed at improving on the detection sensitivity of the Conventional Energy Detection (CED) algorithm while preserving its simplicity. Method: The detection performance of the CED was improved by avoiding the misdetections caused by instantaneous signal energy drops through the use Modified Energy Detection (MED) and Improved Energy Detection (IED) algorithms in cooperative spectrum sensing. Results: The IED scheme proposed reduces the false alarm ratio of the MED scheme while preserving the detection performance improvement attained with respect to the CED method. With a probability of false alarm at 0.1, the MED algorithm increases the CED detection probability from 0.2 to 0.4, while the IED algorithm increases the probability of detection to 0.8, in poor channel conditions where the CED performs unreliably. This fulfils the objective of improving the sensitivity of energy detection in cooperative spectrum sensingItem Improving pedagogy in a digital signal processing course using computer-Aided learning systems(Published by IEEE Nigeria, Computer Science Section., 2011) Opadiji, Jayeola; Ajiboye, Aye; Ayeni, Adeseko; Olatunji, SamuelThe development and deployment of a computer-aided learning tool which serves as a learning aid for undergraduate course in digital signal processing is presented. We have carefully outlined the construction of the algorithm and the implementation process of the software with the aim of improving the level of understanding and assimilation of the concepts that make up the course. It also inspires software development at undergraduate level. Although the scope of this project was limited to fundamental principles of Digital Signal Processing, it was found to inspire software development among undergraduate students.Item Introduction to Computer Engineering(Faculty of Engineering and Technology, University of Ilorin, Ilorin, Nigeria, 2018) Opadiji, Jayeola; Olatunji, SamuelItem Market-based strategic procurement planning in convergent supply networks(Institute of Systems, Control and Information Engineers, Japan., 2009) Opadiji, Jayeola; Kaihara, ToshiyaConvergent manufacturing supply networks facilitate the flow of complementary resources which make the application of competitive equilibrium algorithms difficult. In this work, we present a market-based decentralized approach which uses a market-oriented programming algorithm to obtain Pareto-optimal allocation of resources traded among agents which represent enterprise units in a supply network. It is assumed that every enterprise have unique preferences for suppliers in the markets in which they trade. Description of enterprise agents and the interaction protocol used to generate procurement plans for the enterprise units are presented.Item Microeconomic Characterization of Supply Network Integration in a Multi-product Manufacturing Environment(Japan Society of Precision Engineers, Japan, 2006) Opadiji, JayeolaThis paper presents a theoretical framework for supply network integration in a multi-product manufacturing economy making use of the walrasian market system. We propose a method of dissolving a supply network into a competitive market and then applying the theory of Computable General Equilibrium (CGE) to find an optimal allocation of resources. Agents in the supply network are represented using the Cobb-Douglas (CD) function with a constant return-to-scale. A simulation program based on Market-Oriented Programming (MOP) was developed to mimic the trading environment in order to search for a pareto-allocation of resources in the network. The experimental results presented reveal that this framework can be adapted for use in drafting a holistic picture of a supply network in a multi-product manufacturing environment.Item A model for capturing the effects of Macroeconomic indicators on aggregate planning in a supply network(Tokyo Institute of Technology, Japan., 2006) Opadiji, Jayeola; Kaihara, ToshiyaAs competition in the global market is getting tougher, firms are turning to their supply networks in order to improve their competitiveness. This is done by improving the performance of some components of the supply network while not violating the requirements of the other components. This is undoubtedly a difficult task to achieve considering the autonomous nature of these units of the network and also their distributed topology. Within the last few years, firms have resulted into a globalization of their industrial workspace in order to put a lid on cost as well as harness the opportunities of new markets. The globalization of these workspaces however introduces new challenges to the supply chain of these firms in the form of impediments to trade across national borders. We present a model for estimating the effects of some of these macroeconomic indicators on a firms supply network. We define the supply network as a virtual enterprise network which has the ability of taking advantage of the technology provided by existing telecommunication networks including the internet, to conduct transactions and also provide for easy reconfiguration across enterprise boundaries. In this model, enterprise units are represented as trading agents operating within a competitive market structure to arrive at a paretoallocation of resources in the network. We first describe a process of trading among the agents within a Walrasian market structure and then we consider the effects of two macroeconomic variables – per-capital income and interest rates – on the pareto-allocation of resources in the virtual enterprise network.Item Optimal Resource Allocation in Supply Network with Competitive Market Concept(CIRP International Seminar on Manufacturing Systems, University of Liverpool, UK, 2007) Opadiji, Jayeola; Kaihara, ToshiyaWe propose a competitive market-based model which uses price mechanism in an economy to determine an optimal allocation of resources among a set of trading agents. A supply network is represented by a set of production agents, which make use of the resources available to them in the market to produce an output defined by their technologies and demand agents seeking to maximize returns based on manufacturing budget. We take into consideration, changes in quantity of primary production factors – capital and labour – at facility locations. The resource allocation table obtained from simulation is a measure of value of market resources and facility capacities in the supply network.Item Optimizing Energy Utilization in Unequally Spaced Linear Array for Smart Antenna(Faculty of Engineering, University of Maiduguri, 2019) Fajemilehin, Temitope; Opadiji, Jayeola; Olatunji, SamuelRadiation in unwanted patterns, energy wastage and reduction are caused by high side lobe levels in a radiation pattern. This in turn affects the overall performance of the antenna. The purpose of this work is to improve the performance of a smart antenna by optimizing the radiation pattern using genetic algorithm. Optimal antenna parameters that would minimize side lobe level were obtained using genetic algorithm. Simulations were carried out to determine the impact of the increase in inter-element spacing on array factor and beamwidth using the optimal antenna parameters. The optimal arrangement of inter-element spacing and number of elements in unequally spaced antenna elements were then considered. The array factor model for a uniform linear array of elements was used with the aim of obtaining the optimum weights that would give a radiation pattern with reduced side lobe level. It was observed from the results for unequally spaced linear arrays, using all the possible configurations, that non-tapered arrangement gave the best improvement in the side lobe level. The outcome of this improvement is an optimized radiation pattern which is expected to aid the reduction of radiated power wasted in the side lobes of linear arrays in antenna systems.Item Performance evaluation of equally spaced linear array antenna by optimizing the radiation pattern using two optimization techniques(Published by IEEE Nigeria, Computer Science Section, 2019) Opadiji, Jayeola; Fajemilehin, Temitope; Olatunji, SamuelHigh side lobe levels in a radiation pattern often lead to unwanted patterns of radiation, energywastage 10 and reduction in the overall performance of the antenna. This research work aims to improve 11 theperformance of a smart antenna by optimizing the radiation pattern usingvarious approaches. This was 12 done by obtaining the optimum weights that givea radiation pattern with reduced side lobe level (SLL). 13 Least Mean Squares (LMS) Algorithm and Genetic Algorithm (GA) were used to determine the optimal 14 antenna parametersthat would minimize side lobe level. Simulations were carried out to determine the 15 effect ofincrease in inter-element spacing on array factor and beamwidth using the optimal 16 antennaparameters. It was observed from the results, that for the same number of elements, LMS gave the 17 better outcome in form of a more reduced beamwidth while GA performed better for the reduction of the 18 side lobe level. This translates to the reduction of radiated power wasted in side lobes for linear arrays in 19 antenna systems.Item A Proposal on agent-based production planning in integrated supply network(Elsevier Ltd., 2008) Opadiji, Jayeola; Kaihara, ToshiyaWe propose models that focus on the improvement of flexibility in manufacturing supply networks by enabling a tighter information coupling between the various planning levels without tampering with the autonomy of enterprises which are geographically distributed. The problem is approached from the perspective of social network planning using a community of agents. These agents have unique properties which they exhibit at different planning levels. Characterization of agents in the models is discussed.Item Reduction of Computational Time for Cooperative Sensing Using Reinforcement Learning Algorithm(Published by IEEE Nigeria, Computer Science Section, 2019) Olatunji, Samuel; Fajemilehin, Temitope; Opadiji, JayeolaCooperative spectrum sensing in cognitive radio systems is characterized by high computational time for decision making due to the fusing of individual decisions of cognitive radios involved in the cooperative scheme. This increases the communication overhead of the network. In this paper, an adaptive cooperative spectrum sensing algorithm is developed with improved detection algorithm. Reinforcement learning is thenincorporated to improve the decision making efficiency of the cooperative spectrum sensing such that less time is required to make a decision at the fusion centre. Three temporal difference learning techniques were compared in order to select the most efficient to reduce sensing and decision delays. Appropriate learning rate was utilized in the sensing and decision making algorithm to enhance the performance ofthe adaptive cooperative spectrum sensing. Results reveal significant reduction in the computation time required in cooperative spectrum sensing and decisions. This permits greater efficiency in dynamic spectrum management as the limited electromagnetic spectrum is being utilized for telecommunication services.Item A study on resource allocation optimization in a multi-commodity virtual enterprise network(Published by the Graduate School of Science and Technology, Kobe University, Japan., 2007) Opadiji, Jayeola; Kaihara, ToshiyaFinding an optimal solution to various constrained optimization problems in the supply network of organizations is clearly a Herculean task considering the fact that some of the objectives to be optimized have conflicting requirements. A popular method used in tackling issues aimed at improving the performance of a supply network is to focus on a particular planning horizon and explore activities where improvements can be made. Optimization problems within a supply network vary from strategic to operational domains and a number of models have been developed to address these issues including probabilistic models, mathematical algorithms and some meta-heuristic methodologies. We propose a strategic decision support model based on Multi-Agent System (MAS) paradigm to find a pareto-optimal resource allocation among a group of trading agents in a multi-commodity market scenario. We employ the price mechanism model in microeconomics to create a trading floor for a set of reactive agents to search for a solution to a resource allocation problem in a virtual enterprise network. While the concept of Competitive General Equilibrium (CGE) is not new in the neo-classical economic domain, its application to solving resource allocation problem within a supply chain structure may not be as common. We first study some existing algorithms for CGE based on the Walrasian market model and then introduce an adaptation of the Market-Oriented Programming (MOP) paradigm to the supply network problem. We compare the performance of these algorithms and discuss application areas of the competitive market based approach.