LAUTECH Journal of Engineering and Technology (LAUJET)
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THE STUDY OF ELECTRICAL AND MECHANICAL PROPERTIES OF MONTMORILLONITE CLAY POLYESTER NANO-COMPOSITE
Get PDFMontmorillonite clay polyester nano composite were successfully prepared by melt insertion method at 5wt%, 10wt%, 15wt%, 20wt% and 25wt% of Montmorillonite clay. The electrical and mechanical properties of the produced composites were studied. Five specimens for each test was analysed. Results obtained indicates that while a drastic decrease in the impact energy of 100 was observed, the maximum tensile strength and young’s modulus values of 50.27 MPa and 8.7 GPa respectively were obtained at 10% filler concentration. The compressive strength increases by 48% and 100% at 15wt% and 20wt% filler concentration respectively. An increase in dielectric strength ( 100%) and capacitance (32%) of the samples with each filler addition of up to 25% with 3 times increase in hardness at 25wt%. was observed
A SPATIAL MEASUREMENT AND RECOGNITION SYSTEM USING AUTONOMOUS MOBILE ROBOT
Get PDFIn this paper, an autonomous mobile robot (AMR) is designed to determine the lateral dimensions of an arbitrary enclosed space and to predict its area and shape. The robot operates in two modes, navigation and measurement modes. It uses the ultrasonic sensor to guide around obstacles in the navigation mode and also to calculate the area, in measurement mode, by determining the x-y dimensions. Communication with the robot is achieved by means of a Bluetooth connection to an android mobile phone. Extracted information from measurement times are found to be useful in tracking the path of the autonomous mobile robot
PERFORMANCE ANALYSIS OF ANTENNA TECHNIQUES ON WIRELESS COMMUNICATION SYSTEMS
Get PDFPerformance analysis of antenna techniques on wireless communication systems was the focus of this work.This was brought about as a result of the ever-increasing demand for higher communication channel capacityand baud rates resulting from the global technological revolution informed by increased number of users.Hence, there is urgent need to device technique(s) to effectively combat these and other related challenges.Measurement data was sourced from one of the network service providers in Lagos, Nigeria. Four channelcapacity enhancement of transmission schemes: Single Input Single Output(SISO), Single Input MultipleOutput (SIMO), Multiple Input Single Output (MISO) and Multiple Input Multiple Output (MIMO) wereinvestigated. Their performances in terms of capacity and bit error rates at the receivers’ outputs werecompared using a binary phase shift keying for Rayleigh fading channel. The results showed that MIMOantenna system have more capacity and higher reliability compared to other antenna systems. This is madepossible owing to the larger number of antennas in its design. Also, the BER values for the MIMO are muchlower than that of the other three antenna schemes, inferring better performances. Furthermore, betterperformance is observed as the number of antenna configuration increases on MIMO. Again, as the number ofantennas at both ends increased, the channel capacity increased while the Bit Error Rate (BER) decreased,leading to improved reliability over and above the use of a single antenna channel. The findings of this workwill be useful for network channel designers and mobile network service providers for 4G, 5G and Long TermEvolution (LTE) system
PRODUCTION OF BIODIESEL FROM SOME VEGETABLE OILS
Get PDFBiodiesel is becoming prominent among the alternatives to conventional petro-diesel due to economic,environmental and social factors. The quality of biodiesel is influenced by the nature of feedstock and theproduction processes employed. High amounts of free fatty acids (FFA) in the feedstock are known to bedetrimental to the quality of biodiesel. In addition, oils with compounds containing hydroxyl groups possesshigh viscosity due to hydrogen bonding. American Standards and Testing Materials, (ASTM D 6751)recommends FFA content of not more than 0.5% in biodiesel and a viscosity of less than 6 mm2/s. Thephysico-chemical properties of palm kernel oil and coconut oil were assessed for their potentials in biodiesel.The properties of palm kernel oil and coconut oil were compared with those of palm from literature whilethat of biodiesel were compared with petro-diesel, ASTM and European Standards (EN14214). Resultsshowed that high amounts of FFA in oils produced low quality biodiesel while neutralized oils with lowamounts of FFA produced high quality biodiesel. The quality of biodiesel from palm kernel oil and coconutoils was improved greatly by neutralising the crude oil
SELECTED ENGINEERING PROPERTIES OF PALM NUT (ELAEIS GUINEENSIS) REQUIRED IN THE DESIGN OF PALM KERNEL-SHELL SEPARATOR
Get PDFBased on high dependence of many companies on palm kernel products for soap making vegetable oil and body cream, an efficient palm kernel-processing machine is therefore not only necessary but also important to regenerate the production of palm kernel oil in order to meet up with the ever increasing demand for the industries. Therefore, the knowledge of engineering properties becomes very important in the design of suitable and appropriate palm kernel-shell separator. The parameters investigated were linear dimensions, arithmetic mean and geometric mean diameters, surface area, sphericity, true and bulk densities, angle of repose, drag coefficient and terminal velocity of palm nut and kernel at 7.19 % and 9.5 % (d.b.) moisture content, respectively. The results revealed that average arithmetic mean diameter, geometric mean diameter, sphericity, surface area, angle of repose, drag coefficient and terminal velocity were 20.88/12.55 mm, 20.08/12.41 mm, 0.69/0.84 %, 104.67/485.31 mm2, 19.33/19.17 °, 1.93/1.22 and 5.72/3.21s m/s, respectively for nuts/kernel seeds. Some of the properties of the palm nut have been determined and found useful in the design and construction of palm kernel shell separator. These properties were needed as input to models or predicting the behaviour of agricultural produce in pre-harvest, harvest, and post-harvest conditions, to aid better understanding of processing and design of machines
MODIFICATION OF LOG-NORMAL PREDICTION MODEL FOR HSPA NETWORK USING ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM
Get PDFThe transmission of radio signals over a channel for proper path-loss prediction is a core aspect of planning in wireless communication. Some conventional path-loss prediction models such as Log-normal, Okumura-Hata and COST 231 models are not appropriate for predicting the path-loss values due to differences in frequencies of operation which, therefore, need adaptation before employing. This paper, therefore, modifies the Log-normal prediction model for High Speed Packet Access (HSPA) using Adaptive Neuro-fuzzy Inference System (ANFIS). The modification is carried out by measuring the Received Signal Strength (RSS) using drive test at Ayetoro area of Lagos, Nigeria on (Longitude 3.19647E and Latitude 6.59167 N). The drive test equipment consists of a computer system integrated with Test Equipment for Mobile System (TEMS) software, Ericson TEMS phone and Global Positioning System (GPS). Suitability of the conventional models is determined using Base Station (BS) parameters of the network after which the modification of Log-normal prediction model is carried out by obtaining the path-loss exponent. The path-loss exponent is used to determine the deviation for proper modification. The modified model is further enhanced using ANFIS model which is developed by training five layer ANFIS architecture for adaptation. The models are evaluated using path-loss values and Root Mean Square Error (RMSE) to determine the performances. The results obtained show that ANFIS, COST 231, and modified Log-normal models give the lowest RMSE values with their path-loss values closest to the measured values. Therefore, these models are suitable for predicting the HSPA signal in this area and can be used for future planning of wireless network
ANALYTICAL SOLUTION OF THE LINEAR AND NONLINEAR KLEIN-GORDON EQUATIONS
Get PDFIn this study, three powerful methods, the VIM, NIM and ADM were applied to find the solution of the linear and nonlinear Klein-Gordon equations. To illustrate the ability and reliability of the methods some examples were provided. In this study, we compare numerical results with the exact solution. The results show that the Variational Iteration Method, Adomian Decomposition Method and New Iterative Method are powerful and effective tools in solving the Klein-Gordon equations and can be used to solve other linear and nonlinear equations, ordinary and partial equations
IMPACT OF UNIVERSITY LIBRARY IN THE TEACHING AND LEARNING OF ENGINEERING: A CASE STUDY OF ADELEKE UNIVERSITY
Get PDFThe library is a resource center for providing a wide range of educational resources to supply information needs of staff and students. However, the use of academic library resources depends on the information literacy skills of staff members and students. The study investigated the university library's impact on the teaching and learning of engineering courses in Adeleke University, Ede, Osun State. Parameters measured include library usage, satisfaction, and implications for teaching and learning of engineering. The study used random sampling and survey research design with a population of 170 comprising members of staff and students of the engineering faculty. Descriptive statistics was used for data analysis and ANOVA was used to test the hypothesis at the 95% level of confidence. Findings revealed that 93% of Faculty of Engineering staff members and students utilize and consult the library regularly for teaching and learning purposes. The study concluded that the university library is instrumental, and it does have a positive impact on teaching and learning of engineering in Adeleke University. The study recommended that the university library should ensure a continuous provision and availability of library resources for effective teaching and learning of Engineering
ASSESSMENT OF NATURAL RADIONUCLIDE CONTENTS AND IMPACTS IN THE MUD SOIL OF IDO-IJESA, SOUTH- WESTERN NIGERIA
Get PDFThere has been great concern about the health risks associated with exposure to natural radioactivity present in soil and building materials, which could be traceable to either natural or artificial sources. Thus in this work, the natural radionuclide contents of the mud soil of Ido-Ijesa in South West Nigeria; which is commonly used as building material were analyzed . The analysis was carried out by means gamma ray spectrometry using NaI (TI) as the detector. The radioisotopes identified in the samples of the material include those of the series headed by 238U and 232Th as well as the singly occurring radioisotope 40K. The mean activity concentrations of the radionuclides were found to be 23.39±3.20, 19.37±2.60 and 165.14±7.10 Bq/kg for 226Ra, 232Th and 40K respectively. The activity index of this material was found to be 0.24±0.03. This is less than the requirement of 1 for material used in bulk amounts. Assessment of the radiological impact was made by calculating the radium equivalent activity, external and internal hazard indices and the annual effective dose equivalent and all were found to be within acceptable limit
DEVELOPMENT OF A NEURAL NETWORK MODEL FOR IDENTIFYING BULK COWPEA SEEDS VARIETY USING ITS ELECTRICAL PROPERTIES
Get PDFArtificial intelligence using machine leaning algorithms are modern trends in global industrialization. For agriculture to meet the global demand, the need to automate it processes are crucial. The objective of this study was to develop an artificial neural network model; that will be used to detect and identify variety of cowpea seeds in large storage facilities, using its electrical properties. Electrical properties of three variety of cowpea were generated; at five different moisture content, with five different current frequencies. A three-layer model was developed using multi-layer Perceptron method. It was trained and optimized using batch and scaled conjugate gradient methods respectively. Activation functions used were hyperbolic tangent and Softmax for the hidden and output layers; covariates in the input layer were standardized. The developed network model identifies 96, 97 and 93% varieties correctly during training, testing and validation respectively. Receiver Operating Characteristics (ROC) curve plotted for the model performance shows areas under the curve to be above 0.9 for all variety identified. This shows that the model performance was over 90% for predicting all varieties. The cumulative gain and lift charts were plotted to evaluate the model. Inductance was diagnosed to be the most important predictor to the model, while current frequency was the least. Pair t – test analysis at p<0.01, was done to further validate the model. This developed artificial neural network model can be used to program electrical sensors to identify cowpea seeds varieties during bulk storage, handling and processing. Such device can be used for quality control