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Design and Implementation of the Dynamic Spectrum Access on an Audio Stream in a Congested Environment
Get PDFThis paper aims to design and implement the dynamic spectrum access (DSA) on an audio stream in a congested environment. The test approach for the DSA protocol is based on the frequency of selection of five chosen stations and the size of the audio file saved. The implementation of the DSA protocol was done with an FM received coupled with the energy detector and channel selection algorithm using a non-coherent FM demodulation procedure and the register transfer level - software defined radio (RTL-SDR) in MATLAB environment (version 2018b). The analysis of the results for the DSA protocol implemented in the FM receiver showed that the 97.3MHz station is active compared to the remaining stations
Determination of best-fit isotherm model for the sorption of Lead (II) and Manganese (II) ions onto acid-activated shale using selected non-linear error functions
Get PDFThe focus of this research is to apply the selected error function equation to establish the equilibrium isotherm model that best describes the adsorption of Pb2+ and Mn2+ onto acid-activated shale. Data collected from the batch experiment were analyzed using selected isotherm models (Langmuir, Freundlich, Temkin, Dubinin-Radushkevich, Sips and Redlich-Peterson). To compute the isotherm parameters used in choosing the best-fit isotherm model, selected non-linear error functions, namely, error sum of the square, normalized standard deviation, hybrid error function, root mean square error and Marquardt’s percent standard deviation were employed. From the scanning electron microscope results, it was observed that the surface characteristics of the shale change considerably with calcination and acid treatment but the acid-treated shale shows better uneven porous surface characteristics. Error function computation shows that the Dubinin-Radushkevich isotherm model had the least sum of normalized error of 0.3623 for Pb2+ adsorption and 0.5465 for Mn2+ adsorption; hence, it was selected as the best isotherm model for explaining the sorption of Pb(II) and Mn(II) ions unto acid-activated shale
A Model for Stock Market Value Forecasting using Ensemble Artificial Neural Network
Get PDFArtificial Neural Network (ANN) is a model used in capturing linear and non-linear relationship of input and output data. Its usage has been predominant in the prediction and forecasting market time series. However, there has been low bias and high variance issues associated with ANN models such as the simple multi-layer perceptron model. This usually happens when training large dataset. The objective of this work was to develop an efficient forecasting model using Ensemble ANN to unravel the market mysteries for accurate decision on investment. This paper employed the Ensemble ANN modeling technique to tackle the high variations in stock market training dataset faced when using a simple multi-layer perceptron model by using the theory of ensemble averaging. The Ensemble ANN model was developed and implemented using NeurophStudio and Java programming language, then trained and tested using daily data of stock market prices from various banks, for a period of 497 days. The methodology adopted to achieve this task is the agile methodology. The output of the proposed predictive model was compared with four traditional neural network multilayer perceptron algorithms, and outperformed the traditional neural network multilayer perceptron algorithms. The proposed model gave an average to best predictive error for any day when compared with the other four traditional models
Evaluation and Performance of Path Profile Characteristics in Communication System
Get PDFThis study presents the evaluation and performance of path profile characteristics in communication system, to determine the path profile characteristics such as margin fade (dB), receiver power (dBm), 2-ray propagation model (dB), free space propagation model (dB), LOSMAX (km) and critical distance (km). Data were obtained from Network ‘A’, using three different links within a geographical location in Edo State. Receiver power is mathematic model, the sensitivity of the receiver, which depends on the bandwidth (data rate) (dBm) of antennas were considered in this analysis. All the path profile characteristics were determined, it was observed, that increase in path length distance of microwave line of sight, will necessitate the increase in transmitter power in decibel. The Path length distance and margin fade of the three basic mobile propagation links were determined. It was observed that path length distance characteristic as such the length of distance, obstacle, reflection, diffraction from ground, water bodies and atmosphere resulted to the pattern of radio margin fade signal obtained in receiver antenna. The margin fade determined are 28.83 dB, 12.95 dB and 21.24 dB for the three different links considered from Network ‘A’ in Auchi, Nigeria
Optimizing Hybrid Power Systems for Sustainable Operation of Telecommunication Infrastructure
No full textThe optimal system model comprising wind/photovoltaic hybrid power system with battery storage is designed by employing the energy-equilibrium strategy. The problem objective considered is in terms of cost but the energy system is constrained to reliably meet the power demand. Evaluation of the optimum sizing, cost and operation of the power system was carried out, utilizing 22-year meteorological datasets for a case study site (latitude 11°50.9′N and longitude 13°9.6′E) in Nigeria. The optimum design size comprising 1 kW wind turbine, 2.55 kW photovoltaic array, with 19.36 kWh battery storage system can reliably power the fourth-generation cellular site under study in a sustainable pathway at an energy cost saving of 94.4 %. This will enhance African cities’ decarbonization agenda by switching from conventional fossil fuel to a carbon-neutral energy system to benefit the immediate operational environment and the city at large. 
Thermodynamic Studies on the Sorption of Lead (II), Chromium (III) and Manganese (II) ions onto Acid-Activated Shale
Get PDFShale mineral in its raw form was collected, processed, calcinated and activated using tetraoxosulphate (VI) acid. The microstructural arrangement and chemical composition of the raw, calcinated and acid-activated shale was determined using x-ray fluorescence and scanning electron microscope to verify its ability for the removal of Pb2+, Cr3+ and Mn2+ from wastewater. Batch experimental method was used to study the effect of different adsorption parameters on the sorption efficiency of shale. The effect of temperature on the sorption of Pb2+, Cr3+ and Mn2+ on acid-activated shale was investigated at varied temperature of 15 – 40 . The calculated value of enthalpy () was 12.50 kJ/mol for Pb2+ adsorption, 5 kJ/mol for Cr3+ and 11 kJ/mol for Mn2+ adsorption. The calculated values of Gibbs free energy () varies from -6.576 kJ/mol to 1.358 kJ/mol for Pb2+ adsorptions, from -2.696 kJ/mol to 0.192 kJ/mol for Cr3+ adsorptions, and -4.994 kJ/mol to 1.870 kJ/mol for Mn2+ adsorptions. The entropy () range is 38.68 – 60.946 kJ/mol for Pb2+ adsorptions, 16.69 – 24.58 kJ/mol for Cr3+ adsorptions, and 31.70 – 51.10 kJ/mol for Mn2+ adsorptions. The positive value of shows that the adsorption of Pb2+, Cr3+ and Mn2+ onto acid-activated shale was an endothermic process. The values of are negative at temperature of 298 K and above for the three metal ions studied, which confirmed that the adsorption of Pb2+, Cr3+ and Mn2+ on acid-activated shale was a spontaneous process. The decline in with increasing adsorption temperature showed that adsorptions of Pb2+, Cr3+ and Mn2+ onto acid-activated shale became better at higher temperature while the positive value of for all metal ions studied showed the amplified arbitrariness at the solid-solution interface during the fixation of the adsorbate on the active site of acid-activated shale
An Integrated Model for Monitoring Nodes in Computer Networks
Get PDFMonitoring complex computer network environment is now a very challenging task for network administrators despite the various existing monitoring applications for networks that are faced with the issues of centralized monitoring, which causes network traffic, reduces network bandwidth, and are unable to concurrently run two or more network services. This research paper was designed to tackle the problems exhibited by the existing network monitoring application by integrating different network monitoring services in a single model using the power of agent’s distributed processing and monitoring services. Data about the existing and proposed model was gathered using key informant interview approach, and observation of the existing software. Iterative software model was adopted as the software development life cycle based on its strengths and suitability. The proposed model was developed using use-case and sequence diagrams. Suitable programming languages and development environment such as Java, JavaScript, Hypertext Preprocessor, Hypertext markup language and MySQL were used in coding the software prototype. The functionality of the proposed system was tested and results showed that the proposed system has 100% anomaly network intrusion detection rate and better functional features as compared to the existing network monitoring applications observed
CANFIS based DSTATCOM modelling for solving power quality problems
Get PDFDevolution of the power grid into smart grid was necessitated by the proliferation of sensitive load profiles into the system, as well as incessant environmental challenges. These two factors culminated into aggravated disturbances that cause serious havoc along the entire system structure. The traditional proportional-plus-integral-plus-derivative (PID) solution offered by the distribution synchronous compensator (DSTATCOM) could no longer hold. As such, this paper proposes some soft-computing framework for redesigning DSTATCOM to automatically deal with power quality (PQ) problems in smart distribution grids. A recipe of artificial neural network (ANN) and coactive neuro-fuzzy inference systems (CANFIS) was fabricated for the objective. The system was modelled, simulated, and validated in MATLAB/Simulink SimPowerSystems environment. The performance of the CANFIS against adaptive neuro-fuzzy inference systems (ANFIS), ANN and fuzzy logic controllers’ algorithms proved superior in handling PQ issues like voltage sag, voltage swell and harmonics
Comparative of Ziegler Nichols, Fuzzy Logic and Extremum Seeking Based Proportional Integral Derivative Controller for Quadcopter Unmanned Aerial Vehicle Stability Control
Get PDFUnmanned aerial vehicle is potentially recognized in autonomous sectors where intelligence gathering, surveillance, reconnaissance missions, power line inspection, aerial video, search and rescue monitoring devices are required. It is essential in modern era control and monitoring especially a rotary unit where quadcopter performed a crucial task. However, the flight behavior of a quadcopter is determined by the synchronous speed of each of the motors as the speed changes with load torque variations. The dynamics model equation of the system, external disturbances and its parameters variation of the motor makes it difficult for the manual tuning techniques employed into the system to perform its stability operation. The purpose of this work is to employ adaptive controllers to enhance the stability performance so as to prevent the risk of human lives and financial implication that may arise from improper monitoring of the system. Therefore, Ziegler Nichols, fuzzy logic and extremum seeking controllers were employed to auto-tuned the parameters of proportional integral derivative (PID) gains controller to optimize and give a satisfactory performance of motor speed control at different operating condition. The altitude, pitch, roll and yaw parameters of the quadcopter are simulated using the x-plane II flight simulator MATLAB tools. The simulation results presented in this work show better performance for extremum seeking-PID in terms of decrease in rise time, settling time and overshoot relative to Zigler-Nichols-PID and Fuzzy-PID controllers
Analysis of unsymmetrical faults based on artificial neural network using 11 kV distribution network of University of Lagos as case study
Get PDFThe occurrence of faults in any operational power system network is inevitable, and many of the causative factors such as lightning, thunderstorm among others is usually beyond human control. Consequently, there is the need to set up models capable of prompt identification and classification of these faults for immediate action. This paper, explored the use of artificial neural network (ANN) technique to identify and classify various faults on the 11 kV distribution network of University of Lagos. The ANN is applied because it offers high speed, higher efficiency and requires less human intervention. Datasets of the case study obtained were sectioned proportionately for training, testing, and validation. The mathematical formulations for the method are presented with python used as the programming tools for the analysis. The results obtained from this study, for both the voltage and current under different scenarios of faults, are displayed in graphical forms and discussed. The results showed the effectiveness of the ANN in fault identification and classification in a distribution network as the model yielded satisfactory results for the available limited datasets used. The information obtained from this study could be helpful to the system operators in faults identification and classification for making informed decisions regarding power system design and reliability