DSpace Community: SICT

Android-Based Mobile Text-to-Speech Enabled Malaria Diagnosis System

2019-12-01T00:00:00Z

Title: Android-Based Mobile Text-to-Speech Enabled Malaria Diagnosis System Authors: Yahaya Mohammed Sani, Yahaya Ibitoye Emmanuel Olarewaju and Mamman Adamu Abstract: Android-Based Mobile Text-to-Speech enabled malaria diagnosis system is a research work that is focused on the design and im plementation of a text-to-speech enabled medical diagnosis sys tem that is capable of reading out diagnosis process and report to the user of the system in English text/speech or its translation from English to Hausa, Igbo and Yoruba speeches depending on the language option selected by the user. This research is targeted at solving the problem of communication barrier that exist amongst patients who do not have a good understanding of Eng lish language experienced when they visit hospital to get diag nosed and treatment for malaria by a doctor or medical expert. The system was developed with the following: Android studio and Java programming language for the development of the application, NetBeans and Java programming language was used to build the communication between the system and the server that host the knowledge base of the disease symptoms that is capable of translating and reading out the diagnosis process and report to the user and the database was implemented with MYSQL.. The implemented system will help to overcome the communication barriers between doctors and the patients who do not have good understanding of English language pass through when they go to see a doctor for medical diagnosis and attention and thereby help in reducing the scourge of Malaria in Nigeria.

The Perceived Role of Artificial Intelligence (AI) in Library and Information Science in Tertiary Educational Institutions of Kwara State, Nigeria

2026-04-10T00:00:00Z

Title: The Perceived Role of Artificial Intelligence (AI) in Library and Information Science in Tertiary Educational Institutions of Kwara State, Nigeria Authors: Busari, Suebat A.; Babalola, G. A.; Mohammed, Adamu B.; Yusuf, Ibrahim O. Abstract: The integration of artificial intelligence (AI) into library operations has become increasingly important, yet its perceived role in academic libraries in Kwara State, Nigeria, remains underexplored. This study examined the perceived role of AI in cataloguing, its influence on book indexing, and its contribution to abstracting processes in tertiary educational institutions. A descriptive survey research design was adopted. The population comprised library staff and library students from eight public tertiary institutions (excluding the monotechnic), from which 200 respondents (25 staff and 175 students) were selected using purposive sampling technique. Data were collected through a structured questionnaire whose validity and reliability were established prior to administration. Descriptive statistics (frequency counts and percentages) were used to address the research objectives, while the chi-square test was employed to test the corresponding hypotheses at the 0.05 level of significance. The findings revealed that a majority of respondents perceived AI as enhancing cataloguing efficiency, improving indexing accuracy, and facilitating abstracting processes. Inferential analysis indicated statistically significant relationships between AI utilization and cataloguing (χ² = 12.96, p < .05), indexing (χ² = 19.36, p < .05), and abstracting (χ² = 10.24, p < .05). The study concludes that AI has a significant positive influence on library functions and recommends increased funding and strategic adoption of AI technologies in academic libraries.

Rbust network Anomaly Detection through meta-Ensemble Learning Comparative Evaluation of Eight Classifier's

2026-02-20T00:00:00Z

Title: Rbust network Anomaly Detection through meta-Ensemble Learning Comparative Evaluation of Eight Classifier's Authors: Ngozi Ukamaka Okonkwo, Calistus Tochukwu Ikwazom; Grace Amina Onyeabor, Jane Ada Ukaigwe; Temple Okeahialam C Abstract: Effective detection of network anomalies is crucial when it comes to security of computer networks, but traditional methods tend to fail when used to address a wide range of traffic and dynamiiccaly changing conditions. This paper provides a systematic review of Eight Ensemble algorithms such as the random Forest, Extra Trees Bagging, AdaBoost, Staking and voting on a dataset of 4,998 samples and 35 features where statistics of network traffic model's based on straightfied 10- Ford cross - Validation.

Development of an IOT Based of Drowning detection system for private swmining pools

2025-03-01T00:00:00Z

Title: Development of an IOT Based of Drowning detection system for private swmining pools Authors: Anunso Justice C, Mustapha Hafiz Nwado; Innocent Chika, Aba Ojoinimi king; Thomas Alhassa Mamma, Okeahialam Temple C; C T Ikwazom Abstract: Drowning among the top three leading causes of Unintentional death world wide, accounting for over 8% of all injury- related deaths, Annually, over 22,000 deaths occure due to Drowning in adults, teenagers, and children. The highest rate is among children ages 0- 15 year's available solutions to this murder ( drowning) involve traditional fencing of swmining pools.