EXPERT SYSTEM FOR DIAGNOSIS OF MALARIA AND TYPHOID

An expert system is a computer program designed to solve problems in a domain that has human expertise. The knowledge built into the system is usually obtained from experts in the field. Based on this knowledge, an expert system can replicate the thinking process of the human experts and make logical deductions accordingly. Malaria and Typhoid are major health challenge in our society today (Nigeria), its symptoms can lead to other illness which include prolonged fever, fatigue, headaches, nausea, abdominal pain and constipation or diarrhea. People in endemic areas are at risk of contracting both infections concurrently. According to the world malaria report 2011, there were about 216 million cases of malaria and typhoid and estimated 655,000 deaths in 2010. (WHO report, 2011). The main challenging issue confronting the healthcare is lack of quality of service at minimal cost implying from diagnosing to predicting patients correctly. This issue can sometimes lead to an unfortunate clinical decision that can result in devastating consequences that are unacceptable. Although many studies were carried out by different researchers in the medical domain using various data techniques. In this research work, an efficient expert system that diagnoses patients with malaria and typhoid was developed. A secondary data was collected from university of Maiduguri teaching hospital for the period of four years which ranges from 2017 to 2020. The work explored the potential benefits of proposing a new model for prediction and diagnosis of malaria and typhoid using symptoms. The model adopted the Naive bayes and was implemented using the python. The system diagnoses a patient in real time (within 30 minutes) without necessarily visiting the laboratory for a test. Three algorithms were used these are, Support vector machine, Artificial neural network and Naïve bayes. From our finding, it is observed that Naïve bayes and support vector machine give the best result which is 100% in terms of accuracy of diagnosis. Keywords: Diagnosis, Prediction, Expert System, Typhoid, Malaria

APPLICATION OF GENETIC ALGORITHM FOR IMAGE TRANSFER

For images transfer, different embedding system exist which works by creating a mosaic image from the source image and recovery from the target image using some sort of algorithm. In current study, a method is proposed using the genetic algorithm for recovery of image from the source image. The algorithm utilized is genetic algorithm which is a search method along with another additional technique for obtaining higher robustness and security. The proposed methodology works by dividing the source image into smaller parts which are fitted into target image using the lossless compression. The mosaic image is recovered at retrieving side by the permutation array which is recovered and mapped using the pre-select key.

PROPOSED CLUSTER BASED ALGORITHM FOR MOBILE AD HOC NETWORK

Mobile ad hoc networks use the wireless network and have wider applications especially in emergency situation, military combat zones, and the mobility vehicles. The mobile ad hoc network especially poses the problem of security and efficiency as the network is often subject to internal and external attacks. To overcome such problems, different protocols are proposed. In this study, an improved protocol is proposed which makes use of hexacol cluster method and thus provide greater efficiency and security to the network. For validating the proposed method, a stimulation was performed and results were compared with other protocols. The results indicate that the proposed method showed improved performance compare to the other protocol.

FLOOD FORECASTING MODEL USING THE COMBINATION APPROACH

This paper reviews the qualities of a good flood forecasting model such as timeliness, accuracy, and reliability. The article reviews the current forecasting models which are based on fuzzy logic, artificial neural network, as well as combination. The combination approach is gaining popularity and is found to be more flexible, accurate, reliable, and highly efficient in terms of development and output.

IMPROVING TRAFFIC FLOW AT INTERSECTION USING INTELLIGENT TRAFFIC MANAGEMENT SYSTEM

In this study, a proposed intelligent traffic management system is presented making use of the wireless sensor network for improving traffic flow. By making use of the clustering algorithm, VANET environment is utilized for the proposed system. The components of the proposed system include sensor node hardware, vehicle detection system through magnetometer, and UDP protocol for communication between the nodes. The intersection control agent receives the information about the vehicles and by making use of its algorithm, it dynamically changes the traffic light timings. By making use of the greedy algorithm, the system can be enhanced to a wider area by connecting multiple intersections.

AN EXPERIMENTAL STUDY OF FACE RECOGNITION METHOD

The increased use of face recognition techniques leads to the development of improved methods with higher accuracy and efficiency. Currently, there are various face recognition techniques based on different algorithm. In this study, a new method of face recognition is proposed based on the idea of wavelet operators for creating spectral graph wavelet transformation. The proposed idea relies on the spectral graph wavelet kernel procedure. In this proposed method, feature extraction is based on transformation into SGWT by means of spatial domain. For recognition purpose, the feature vectors are used for computation of selected training samples which makes the classification. The decomposition of face image is done using the SGWT. The system identifies the test image by calculating the Euclidean distance. Finally, the study conducted an experiment using the ORL face database. The result states that the recognition accuracy is higher in the proposed system which can be further improved using the number of training images. Overall, the result shows that the proposed method has good performance in terms of accuracy of the face recognition

EXPERIMENT STUDY OF AUTONOMOUS SYSTEM FOR INTRA-ROW WEED CONTROL

The study is used to propose and test by experiment a procedure for autonomous hoeing system for intra-row weed control. The proposed system utilizes the RTK-GPS navigation system. The system consists of autonomous vehicle equipped with side-shifting frame and cycloid hoe. The navigation of the system is controlled using a pre-specified plan and implemented in the system internal computer. The internal computer is also attached to a field station using the wireless local area network (WLAN). The performance of the system was measured through an experiment consisted of making rows having small plants and soil conditions similar to the actual field. The results based on chi-square shows that transverse deviation had normal distribution indicating the performance of the side-shift control. The results related to the longitudinal deviation distance between plants and the nearest line trajectories showed good chi-square fit which is an indication of performance of the cycloid hoe control. The result shows that the system is promising and can be used at larger level with suitable adjustments

ENERGY CONSUMPTION SOLUTION IN MOBILE AD-HOC NETWORK

The current study was motivated because of higher energy consumption in the current mobile-ad hoc network especially the dynamic system routing. A solution was proposed consisted of nodes energy and traffic load and distance during the route discovery phase. Later, a simulation was performed to make comparison between DSR and MP-DSR. The results states that the proposed MP-DSR outperformed the DSR in all three tests including packet delivery fraction, end-to-end delay, and average energy consumption.

COMPUTER BASED ENGLISH SPEAKING TEST BASED ON ARTIFICAL NEURAL NETWORK

English testing is a most common test conducted around the world for evaluating an individual’s English capabilities in mostly reading, writing, speaking, and listening domain. With increased cost and higher subjective assessment attached in some tests, there is required to change the test from traditional method to computer based. In this study, a proposed method for conducting speaking test for English based on objective assessment method. The proposed system is able to identify different dialects based on unit analysis of syllable along with phonetic errors. The proposed system is based on pronunciation parameters and neural network for evaluation purpose. The PSO algorithm is used for training the artificial neural network. The experiment result conducted for validating the proposed system shows promising performance

PILOT PROJECT FOR ELECTRONIC REIMBURSEMENT SYSTEM FOR PHYSICIANS IN INDONESIA

A healthcare department in remove community of Indonesia aimed for reducing paperwork and improving the electronic system. As part of a pilot project, one aspect was replaced from manual to the electronic format. The proposed system was use of electronic form for claiming for fee reimbursement made by the physicians. The design of the system is intranet based and consisted of two separate portals. The first portal is for physicians and second portal is for billing clerk. The interface is user-friendly and packed with pre-defined codes set in several of its fields and sub-fields. The electronic form is also linked to a centralized database from which a physician can copy the existing patients record. For improving the system variance from individual needs, decision support algorithm is used. Whereas, for improving the system performance, machine learning algorithm is used. For data query, database query was designed. The relationship of columns in the database is displayed as a tabulated form to the user. In situation where a user selects a particular column, a filtered display mechanism displays those columns which satisfying the portion of the query already constructed. For obtaining data from the tabulated database, the SQL query is adapted. Rule-based knowledge inference model is utilized for reasoning about terminology and required domain knowledge. The inference used is algorithmic and helpful in performing all necessary tasks under the suitable billing circumstances. A survey is conducted with 35 physicians for judging their perception towards the system. Results of the survey indicate that most participants find the system suitable and better than the paper-based system in terms of several dimensions such as user friendliness, time saving, reducing errors, and accuracy.