http://repository.unn.edu.ng/handle/123456789/203 Wed, 02 Sep 2026 18:32:41 GMT 2026-09-02T18:32:41Z http://repository.unn.edu.ng/handle/123456789/4928 An Algorithm for Mobile Location Estimation in a 3g Network Orah, Harris Onyekachi Locating the position of a mobile user with a high degree of accuracy is a trending research interest. It holds the key to a breakthrough in many service challenges faced by operators in the wireless communication industry. With a success in this field, it will be possible for call rates in mobile phones to be charged based on the location a subscriber is calling from; fighting crimes and delivering emergency services through the mobile network’s ability to detect the caller’s position will be possible. Many techniques have been proposed or developed for locating the position of a mobile station in a telecommunication network. Those in operation are mostly handset-based and each technique has its limitations. These ranged from the degree of accuracy of the location estimate and response time of the system, to the cost and ease of implementing the technique. The same goes for the various algorithms employed by these techniques. This work presents a novel network-based Time Difference of Arrival (TDOA) algorithm for use in estimating the position of a caller in a 3G mobile network. It is based on geometric principles and uses known network parameters to calculate the unknown positions of mobile users in the network. The algorithm improved the accuracy in the estimated position of a mobile user without incurring the mathematical complexities in hyperbolic trilateration methods conventionally used by TDOA techniques. From the results of the simulation, the improvement in the accuracy of the located coordinates of the mobile phone was up to 86.82% and 89.20% for the x and y coordinates respectively. The method adds no modification in the available cellular infrastructure and incurs no additional costs. Mon, 22 May 2017 00:00:00 GMT http://repository.unn.edu.ng/handle/123456789/4928 2017-05-22T00:00:00Z http://repository.unn.edu.ng/handle/123456789/4926 Biometric-Assisted Unique Patient Identifier Eke, Chima Stanley Over the years, healthcare institutions have relied on one or a combination of medical record number (MRN), demographics and issued documents such as name, sex, date of birth, social security number, and identity cards as patient identifiers. But all those have been proven unsuitable and inefficient as patient identifiers due to one or more of the following drawbacks: non-uniqueness, possessiveness, inability to establish the true identity of a patient, and limitedness of applicability to referencing of patients across healthcare systems. This project is geared towards solving the drawbacks of the earlier methods of patient identification by adopting a hybrid solution: a combination of a unique 15-digit numeric identifier and a patient’s biometric feature. A patient is expected to enroll their palm vein, with other basic information such as bio data and contact at an accredited healthcare facility, on their first visit and be assigned a unique 15-digit numeric identifier. The data are stored and maintained in a Master Unique Patient Identifier Index (MUPII). On the patient’s subsequent visits to any accredited healthcare facility, the unique code (called the unique patient identifier) is used to make an identity claim and verified by matching the patient’s palm vein pattern against the template in the MUPII. Furthermore, the identifier is useful for filing, labeling of laboratory specimens, recording, transferring and referencing of patients. In situations where the identifier is not handy (as a result of incapacitation or unconsciousness of the patient), the patient could still be identified, using just their palm vein feature alone. This solution will eliminate patient misidentification and identity theft in healthcare or, at least, reduce them to the minimum. Mon, 22 May 2017 00:00:00 GMT http://repository.unn.edu.ng/handle/123456789/4926 2017-05-22T00:00:00Z http://repository.unn.edu.ng/handle/123456789/4925 Real-Time Data Logging While Drilling Through Mud Pulse Telemetry Uwakwe, Crescentus Chukwuebuka This study investigated the influence of mud channel characteristics on real-time data logging while drilling. Drill string bore filled with flowing mud as the data transmission medium in mud pulse telemetry can have significant changes in its properties as a result of mud type (water-based mud or oil-based mud) which selection depends on the formation being drilled and depth penetrated. Logging data are transmitted to the surface modulated onto pressure pulses which amplitudes are greatly attenuated as drilling depth increases. This attenuation in severe cases can make logging data in the pressure pulse not to be decodable by the transducers. MATLAB Simulink communication blockset was used to model the arrival probability of logging data based on the time of arrival at the surface while drilling using Poisson distribution function. The rate of penetration and data acquisition sample rate were simulated by varying the slope of the ramp function for depth and intensity of data read block for data capture. It was observed that the transmitted pressure pulses propagate to the surface unaffected by depth except in amplitude. Also, lower frequencies were observed to be better carriers of signal in mud pulse telemetry than higher frequencies because attenuation in high frequency components is relatively higher than the low frequency components. It was further discovered that influences of both drilling fluid viscosity and volume fraction of gas in drilling fluids on transmitted pulse amplitude were more notable than that of internal diameter of drillpipe. Mon, 22 May 2017 00:00:00 GMT http://repository.unn.edu.ng/handle/123456789/4925 2017-05-22T00:00:00Z http://repository.unn.edu.ng/handle/123456789/4924 Algorithm Development for Fingerprint Image Enhancement Using Wavelet Processing Nwabunwanne, S.F.C Biometrics is a physical, electronic and biological means of providing dependable and accurate identification of people. It entails data acquisition, storage and subsequent matching at points of access or identification. Biometrics is an emerging technology that identifies people by their physical and/or behavioral characteristics and practically requires the person to be identified to be physically present at the point of identification. In this thesis, efforts to improve biometrics were made in developing an algorithm that will enhance fingerprint images for effective matching and rapid identification. The algorithm was based on wavelet processing which employed Daubechies’ wavelets for decomposition as well as reconstruction. Wavelet smoothing and denoising were also included in the algorithm. Mon, 22 May 2017 00:00:00 GMT http://repository.unn.edu.ng/handle/123456789/4924 2017-05-22T00:00:00Z