4 research outputs found
Application of hybrid non-dominated sorting genetic algorithm-II and self-organizing map technique to interference management in homogenous frequency demand cellular network
No full textDEVELOPMENT OF CROP WATER PRODUCTION MODEL IN A RAINFED TROPICAL MAIZE CROP CULTIVATION
Get PDFCrop production, which is one of the sources of food for human and animal sustenance is a function of the availability of adequate quantity of water. The rainfall being seasonal is the main source of water for agricultural production in Nigeria. Maize production is majorly through rainfed agriculture in Nigeria and the irregularity of which affect the yield. This research work was to develop crop-water production model in tropical rain fed maize crop cultivation using maize yield and rainfall data from Oyo state. One of the major problems of food production in attempting to determine the relative future roles of irrigated and rain-fed agriculture is the lack of sufficient ground and accurate tool on a localized basis. Hence, the essence of this research works. Using correlation and full quadratic regression analysis, the effects of some rainfall indices (monthly and annual rainfall, raindays, and rainfall onset and rainfall cessation) on maize yield in Oyo State were examined. The results of the correlation statistics showed that cessation has the strongest association (r= - 0.284) with maize yield. The analysis also showed that early maize and late maize suffer moisture deficiency in March and November respectively while excessive rainfall of June/July and September also have implication for maize yield. It was also observed that the rainfall characteristics jointly contributed 96.7% in explaining the variations in the yield of maize per hectare. Conclusively, a model was development for predicting maize yield in Oyo State. The study also recommends the use of state own yield so as to harmonize with state rainfall data, application of appropriate moisture conservation management practices that ensured efficient use of water and use of drought resistance crop species with shorter growing periods as adaptive measures to the changing rainfall pattern within the study area
Improving the detection of intrusion in vehicular ad-hoc networks with modified identity-based cryptosystem
Get PDFVehicular ad-hoc networks (VANETs) are wireless-equipped vehicles that form networks along the road. The security of this network has been a major challenge. The identity-based cryptosystem (IBC) previously used to secure the networks suffers from membership authentication security features. This paper focuses on improving the detection of intruders in VANETs with a modified identity-based cryptosystem (MIBC). The MIBC is developed using a non-singular elliptic curve with Lagrange interpolation. The public key of vehicles and roadside units on the network are derived from number plates and location identification numbers, respectively. Pseudo-identities are used to mask the real identity of users to preserve their privacy. The membership authentication mechanism ensures that only valid and authenticated members of the network are allowed to join the network. The performance of the MIBC is evaluated using intrusion detection ratio (IDR) and computation time (CT) and then validated with the existing IBC. The result obtained shows that the MIBC recorded an IDR of 99.3% against 94.3% obtained for the existing identity-based cryptosystem (EIBC) for 140 unregistered vehicles attempting to intrude on the network. The MIBC shows lower CT values of 1.17 ms against 1.70 ms for EIBC. The MIBC can be used to improve the security of VANETs
Improvement of Multiple Antenna Sensing Technique for Detecting the White Space in a Spectrum Sharing System
No full textExact detection of White Space (WS) is one of the actions in a Spectrum Sharing System (SSS) to determine unused spectrum for proper utilization. However, exact detection of WS is being affected by channel impairments, resulting in harmful interference. The Existing Multiple Antenna Spectrum Sensing (EMASS) technique used in addressing this effect is characterized with noise uncertainty leading to low detection rate due to setting of thresholds that is based on noise variance. Hence, this paper proposes an Improved Multiple Antenna Spectrum Sensing (IMASS) for detecting the WS in a SSS. Various copies of licensed user’s signals are received through the unlicensed user antennas over different antenna configuration. The received signals are combined using a modified equal gain combiner and energy of the combined signal is determined using Parseval’s relation for a discrete time signal. The received signal is used to form a square matrix which is converted to covariance matrix. Characteristic equation is obtained from covariance matrix to determine the minimum eigenvalue. The ratio of energy to minimum eigenvalue of the received signal is obtained and used as test statistics. The IMASS technique is evaluated using Probability of Detection (PD) and Total Error Probability (TEP) by comparing with EMASS. The proposed IMASS technique gives better performance with higher PD and lower TEP values than EMASS at all different antenna configurations
