Vehicle Accident Alert and Locator (VAAL)

An emergency is a deviation from planned or expected behaviour or a course of event that endangers or adversely affects people, property, or the environment. This paper reports a complete research work in accident (automobile) emergency alert situation. The authors were able to programme a GPS / GSM module incorporating a crash detector to report automatically via the GSM communication platform (using SMS messaging) to the nearest agencies such as police posts, hospitals, fire services etc, giving the exact position of the point where the crash had occurred. This will allow early response and rescue of accident victims; saving lives and properties. The paper reports its experimental results, gives appropriate conclusions and recommendations

Analysis of Capacity Limitation in Nigerian GSM Networks and the Effects on Service Providers and Subscribers

The performance of GSM network is measured in terms of KPIs (Key Performance Indicators) based on statistics generated from the network. The most important of these performance indicators from the operators’ perspective are BER (bit error rate), the FER (frame error rate) and the DCR (dropped call rate). The Dropped Call Rate (DCR) is a measure of the calls dropped in a network as it gives a quick overview of network quality and revenues lost. This makes it one of the most important parameters in network optimization. At the frame level in the NMS (Network Management System), the DCR is measured against the Slow Associated Control Channel (SACCH) frame. If the SACCH frame is not received, then it is considered to be dropped calls. For this work data was acquired form the Network Management System of various GSM operators in Nigeria (e.g. MTN, Celtel, Globacom etc.). The acquired data was analyzed to statistically illustrate the extent of revenue that is lost as a result of dropped calls and the consequent impact on the customers/subscribers

On the Power Spectral Density of the GSM Signaling Scheme

In this paper, the Power Spectral Density of encoded Gaussian Minimum Shift Keying (GMSK) which is the Signaling Scheme of the Global System for Mobile Communication (GSM) is derived by a combined approach of the autocorrelation method and Markov Process. In the analysis, the Amplitude Modulated Pulse decomposition proposed by P. Laurent is employed to ease computation. Encoding of the message data utilizes Convolutional Code of rate1/2. Results are for both the uncoded and coded waveform comparing variation in power spread over a range of frequency

Development of e-SIWES Portal: A Web based Platform for Student Industrial Work Experience Scheme (SIWES) Management

We developed the e-SIWES portal in order to enhance the manual task of carrying out SIWES activities such as registration, dissemination of information, filling of log book for students’ day-to-day activities and supervision/assessment by lecturers and industry based supervisors. The portal is web-based and allows all tasks to be carried out using the personal computer and the Internet. We digitized the SIWES logbook and assessment forms for filling by students and grading by the supervisors electronically. This will allow supervisors to be assigned immediately the students commence their industrial training and facilitate their monitoring in real-time. With the e-SIWES portal, important messages can be broadcast to all students at once and on a prompt and regular basis

Estimating An Optimal Backpropagation Algorithm for Training An ANN with the EGFR Exon 19 Nucleotide Sequence: An Electronic Diagnostic Basis for Non–Small Cell Lung Cancer(NSCLC)

One of the most common forms of medical malpractices globally is an error in diagnosis. An improper diagnosis occurs when a doctor fails to identify a disease or report a disease when the patient is actually healthy. A disease that is commonly misdiagnosed is lung cancer. This cancer type is a major health problem internationally because it is responsible for 15% of all cancer diagnosis and 29% of all cancer deaths. The two major sub-types of lung cancer are; small cell lung cancer (about 13%) and non-small cell lung cancer (%SCLC- about 87%). The chance of surviving lung cancer depends on its correct diagnosis and/or the stage at the time it is diagnosed. However, recent studies have identified somatic mutations in the epidermal growth factor receptor (EGFR) gene in a subset of non-small cell lung cancer (%SCLC) tumors. These mutations occur in the tyrosine kinase domain of the gene. The most predominant of the mutations in all %SCLC patients examined is deletion mutation in exon 19 and it accounts for approximately 90% of the EGFR-activating mutations. This makes EGFR genomic sequence a good candidate for implementing an electronic diagnostic system for %SCLC. In this study aimed at estimating an optimum backpropagation training algorithm for a genomic based A%% system for %SCLC diagnosis, the nucleotide sequences of EGFR’s exon 19 of a noncancerous cell were used to train an artificial neural network (A%%). Several A%% back propagation training algorithms were tested in MATLAB R2008a to obtain an optimal algorithm for training the network. Of the nine different algorithms tested, we achieved the best performance (i.e. the least mean square error) with the minimum epoch (training iterations) and training time using the Levenberg-Marquardt algorithm

National Hospital Management Portal (NHMP): a framework for e-health implementation

Health information represents the main basis for health decisionmaking process and there have been some efforts to increase access to health information in developing countries. However, most of these efforts are based on the internet which has minimal penetration especially in the rural and sub-urban part of developing countries. In this work, a platform for medical record acquisition via the ubiquitous 2.5G/3G wireless communications technologies is presented. The National Hospital Management Portal (NHMP)platform has a central database at each specific country’s national hospita

Managing and Improving Upon Bandwidth Challenges in Computer Network

Managing the bandwidth of a computer network is always faced with great challenges. This research was necessitated by the urgent need to manage the University network currently experiencing congestion in both the local LA� and on the internet backhaul with a view to improving network performance and reduce the huge recurrent on the WA� link. However, there exists various ways that have been deployed towards solving these problems. In this paper we examined existing bandwidth management, effect of limited bandwidth on the network performance and profound solutions of techniques that enhanced or improved the bandwidth efficiency. Also, included in this research work are the studies of the effect of limited bandwidth on work load, type of protocol used and the effect of network congestion on the quality of service of a Wide Area �etwork (WA�). By comparison, from the modeling of the effect of work load and limited bandwidth on the throughput of a wide area network based on experimental simulation and real time simulation scenarios, some observations were made and recommendation of solutions were given from the analyzed results

Automatic Electrical Appliances Control Panel Based on Infrared and Wi-Fi: A Framework for Electrical Energy Conservation

-Today, proprietary home automation targets very specific applications which operate mostly on a cable based infrastructure. In contrast to that, our implementation builds on a wireless platform for the automatic control of house hold electrical appliances. The nodes gather sensor readings in a home and transmit them to a central automation server. There, the readings are matched against a list of script statements. When there is a match, a specific action is performed. An important property of the system is that the control of all home appliances is done by means of the ubiquitous Infrared and Wi-Fi wireless technologies. This way, the co-operation between manufacturers is not a necessity in order to connect devices to the home automation network