Abstract:The processes and management of healthcare records are not trivial exercise; there is need for application of ICT to healthcare management system in order to meet globally accepted health care systems. Many healthcare systems have been designed and implemented, but they do not adequately incorporate nursing process. Also, most of them do not consider the needs and aspirations of patients. In this work, a modified framework based on Orlando's nursing process focuses on improvement in the patient's behavior by actions that are based on a patient's needs found through effective interaction with the patient was designed and proto type implemented. The design was implemented using Visual Basic.Net and SQL because of their supports for implementing web-based systems. The system was hosted on a website for a period of two months. Real life data in respect of medical practitioners' and patients were captured, analyzed and evaluated. Users interacted with the hosted system during the evaluation period. The system was evaluated using usability test and structured questionnaire. The result showed 93.10% participation efficiency, while ease of use, operational efficiency and data protection of Healthcare Information system scored more than 80%.This showed that the Healthcare Information Systems (HIS) is an effective life saving system that can influence and enhance health-workers' quality of services, timely precision decision making process and reduced cost of health care significantly through effective healthcare management. It is applicable in any healthcare environment irrespective of their social economic and technology settings. The application of the framework will prevents the spread of deadly diseases like Ebola Virus.
Depression is a serious illness that affects millions each year and if left untreated, it may lead to the deaths of many. It comes in many flavors that can be very different among people and this makes diagnosing it very difficult. A lot of artificial intelligence systems have been designed to diagnosing depression but they failed to perform feature selection and extraction on the dataset used in training the systems and this has a huge implication on the classification accuracy of the system. The objective of this research work is to develop a depression diagnosis system, that takes into consideration feature selection and extraction of dataset using Genetic-Neuro-Fuzzy techniques. Feature selection and extraction, will enable identification of key symptoms and hidden traits which are vital in diagnosis of depression. In this work, a Genetic Neuro-Fuzzy Model which is capable of handling feature selection and extraction on depression dataset was proposed and designed for diagnosing clinical depression. The GA component optimizes the clinical dataset which consist of series of diagnosed depression cases by performing feature selection and extraction, while ANFIS is used in training the optimized dataset obtained from the GA. The system had 92.5% prediction accuracy. This is a significant improvement over the best related model in literature that achieved a prediction accuracy of 92.4%. The system is recommended for psychiatrist hospital to aid in depression diagnosis. The research is limited to the diagnosis of clinical depression; future work should focus on the other forms of depression and treatments. The model has incorporated feature selection and feature extraction for the prediction of clinical depression with significant results established with performance indicators.
Multimodal teaching and learning via visual (video), sound (music), movement (amination), print-based text, and technology for students has great impact on content delivery if teachers teaching programming language realize its potency. Inclusion of multimodality in curriculum would enhance diversity of learning process. In this study, the author looked into the use of different modes of approaches (Multimodal Approaches) to produce desired result better more realistic and dynamic to the use of a single (monomodal) approach or mode. The study exposed students to the use of: video mode, game mode, practical mode and online classroom mode in learning a programming language. The degree students formed the target population. Data collection was done in three bases: paper data collection for videos and games, practical data for the practical classes while data was collected electronically for online classroom respectively. Quantitative analysis results of the data revealed that employing multiple modes (multimodality) for instructional supports to enhance learning programming language gave teachers opportunities to help them gain nuanced understanding of codes, powerfully express what they learned, and discover a psychological refuge. Importantly, multimodal teaching approach was found to enhance programming sense of accomplishment and self-esteem.
Abstract:This study appraised e-Government implementation in Ondo state government ministries, agencies and departments. It determined the availability of e-Government resources and infrastructure, the stage of e-government implementation and the challenges. Siau and Long, 2005 five phase of e-Government model was used for analysis. Survey design approach was adopted. Data were collected with a structured questionnaire administered to the Director of IT and administrators in the ministries, agencies and departments, result shows 96.42% participation. Collected data were structured into grouped frequency distributions. Findings revealed that Ondo state had made an entrance into e-Government. Resources and infrastructure for e-Governance were available and the State was found to be at the second phase (interaction) of eGovernment process and has not effectively demonstrated its capacity to progress towards the higher phases of e-government.The study indentified factors that inhibit the implementation of e-Government in Ondo state and recommended how egovernment implementation can be further improved in order to accomplished various present and future government programs and delivered the present and future expectation of citizen, Ondo state vision 20: 2020 and make it a truly Sunshine state. This research work is done using Ondo state as study case; it can be apply to any state in developing countries.
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