University of Ibadan Journals
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ADULT EDUCATION AS A PREDICTOR OF DIGITAL SOCIETY GOAL ACHIEVEMENT IN OYO METROPOLIS
Get PDFThis study examined the adult education as a predictor of digital society goal achievement in Oyo metropolis. Descriptive survey research design was adopted for the study. The population comprised of the two colleges of education in Oyo metropolis - Emmanuel Alayande College of Education and Federal College of Education (Special), Oyo. A total of 2,071 of 300 level students in the two colleges of education served as the total respondents. The study used purposive sampling technique to select 120 students each from the two colleges making a total of 240 sampled respondents. Data for the study were collected using the researchers’ self-designed questionnaire titled ‘Adult Education and Digital Society Questionnaire’. Analysis was done using simple percentages, Pearson’s Moment Correlation Coefficient and regression. All the hypotheses were tested at a 0.05 level of significance. The results from the analysis revealed that literacy (p - value of 0.003 and r value of -0.194) and further education (p - value of 0.025 and r value of -0.145) had weak negative significant influence on the goal achievement of digital society but no significant correlation was established between professional education (p - value of 0.124 and r value of -0.099) and achievement of goal of digital society. Also, there was no joint influence of literacy, further and professional education and goal achievement of digital society (F(4,235) =3.183, p < 0.05). The result revealed that literacy education was relatively significant while further education and professional education were not relatively significant to the achievement of goals of digital society. It is therefore concluded that only two aspects of adult education (literacy and further education) play crucial role in the growth, development, promotion and goal attainment of digital society. Based on the findings and conclusion, it was recommended that government and other stakeholder should encourage citizens of the Oyo metropolis to acquire functional literacy skills needed for the achievement of goal of digital society
Software Development for Crime Management in Nigeria
Get PDFAn onsite observation conducted at Nigerian police stations indicated that criminal records are managed manually in a crime diary or ledger. This technique is prone to time waste in searching criminal records and fire disasters. To address this problem, this study, a web-based Graphical User Interface (GUI) application was designed to aid Nigerian police in capturing criminal records across various Police Stations. This study adopted Object Oriented Analysis and Design (OOAD) approach by employing Unified Modeling Language (UML) tools. In the implementation stage, Mongo Database (Mongo DB) was used at the backend and Python programming language was chosen to design the user interface at the frontend. The results indicate that user’s authentication, criminals’ biometric capturing, criminal data entry and criminal information updates were successfully implemented. Besides, a module is also implemented to extract features from the crime database and export extracted crime datasets into Python for further data analytics
Assessment of Diurnal Signal Strength Penetration of Mobile Signals through Ceiling Materials
Get PDFCommunication has been much easier since the onset of the global system for mobile communication (GSM). However, despite the advancement and several upgrades been deployed in GSM communication, it is also a known fact that signal loss is still being experienced in some buildings due to the different materials utilized in their construction including those of the roofing and ceiling. Hence, this work was aimed at analyzing the Mobile network signal strength penetration through three (3) of the most commonly used ceiling materials (POP, Hardboard and Glass) and the free Air column as control in Nigeria. An In-situ signal strength software installed on an android phone was used for signal strength measurement on the signal reception in buildings during the 09th, 12th, 15th, and 18th communication hours for twelve consecutive days. The data obtained were modelled using the Log distance model for path loss in wireless communication to estimate the pathloss exponent (n) of the signal and the penetration signal (attenuation) loss through for all the ceiling materials. The GSM service providers operating at frequencies 2120 MHz, 2130 MHz, 2140MHz and 2150MHz respectively were used for analysis. The results showed the penetration loss and Path loss exponent ( n) for Glass; a maximum value of 9.25 dB and n of 3.61 for 09HR, 3.92dB and n of3.63 for 12HR, 12.22dB and n of 3.40 for 15HR and 0.91dB and n of 3.52, for POP; a maximum value of 13.15 dB and n of 3.68 for 09HR,3.96 dB and n of 3.57 for 12HR, 14.82dB and n of 3.70 for 15HR and 6.07dB and n of 3.79 , for Hardboard; a maximum value of 11.38 dB and n of 3.58 for 09HR, 3.01dB and n of 3.61 for 12HR, 13.41dB and n of 3.79 for 15HR and 4.21 dB and n of 3.60 for frequencies 2120 MHz, 2130 MHz, 2140MHz and 2150MHz respectively. The mean penetration loss obtained for glass was lowest at 18HR 12HR, and high at 09HR and 15HR, with value 0.63dB, 3.04dB and 3.41dB and 3.81 dB, POP with value 2.54dB, 2.547dB and 4.68dB and 6.25 dB and hardboard with value 1.93dB, 2.26dB and 4.90dB and 6.1081 dB respectively. It could be concluded that for all ceiling materials 18HR and12HR were best time to roam calls and to prevent data packet loss during the day
Classification of Depression through Social Media Posts Using Machine Learning Techniques
Get PDFAbstractMachine Learning has been applied to solve several problems in various areas of life such as medicine, sciences and industries. Depression is a major problem across the globe and is becoming a serious challenge in the health sector. Millions of people suffer from depression, at different levels, but only few take preventive measures and get appropriate treatment, due mainly to the fact that early detection of depression may be cumbersome. A deep study of an individual’s behaviour could led to early detection and some of these behaviours can be gotten through social media platforms. This study seeks to analyse users’ tweets gotten from twitter and classify depressive contents into four levels, rather than the usual two-tier depression classification. Users’ tweets were extracted using twitter API and a web scrapping tool called ‘Twint’. Bag of words model, Term Frequency-Inverse Document Frequency and a text pre-processing tool provided by Keras framework, were used to quantify and comparatively evaluate how different models influenced the classification of tweets. Three machine learning algorithms; Naïve Bayes, Random Forest and Decision Tree were used for the classification. The result reveals that Random Forest best classifies the tweets into the four categories of depression
An Improved Ensemble Model Using Random Forest Branch Clustering Optimisation Approach
Get PDFAbstractThe world of technology is growing faster and helping organisations to repositioning their focus and vision for business. The introduction of Internet of Things (IoTs) devices has contributed in no small measure to business values and the world livelihood. The need for efficient Machine Learning Algorithms (MLAs) to drive these devices to perform to optimal or near optimal has been a serious challenge. The inadequacies of these MLAs has resulted in loss of trust and sometimes led to legal litigation against Artificial Intelligent (AI) organisations.Hence, we introduced a novel approach to improving traditional Random Forest RF, an ensemble model, which is known to be high performance classifier using branch clustering Random Forest (BCRF) technique in Decision Tree Forests (DTFs). The sensitivity, specificity and F-score values as well as extra pruning of pessimistic after Entropy and Information Gain Ratio (IGR) were used to isolate the weaker groups for model improvement. The model produced more accurate results with a better speed of execution when used on the same dataset as Naïve Bayes, RandomForest and K-nearest Neighbour
The Enhanced Mayfly Optimization Algorithm with Roulette Wheel Selection
Get PDFIn the year 2020, the Mayfly optimization method was proposed. It is a modification of particle swarm optimization and it combines major advantages of particle swarm optimization, genetic algorithm, and firefly algorithm. Mayfly flight and mating activity were the inspiration for this piece. Simulated in many tests using various benchmark functions, all of which were found to be capable of optimization, although some drawbacks, like a sluggish or premature convergent rate, and a probable imbalance between exploration and exploitation, haveyet to be handled, necessitating modification for improved performance. The Mayfly Algorithm hasn't been used much for feature selection problems, to the author's knowledge. In this study, the Mayfly algorithm was enhanced with the Roulette Wheel Selection method been the most common and straightforward method of fitness proportionate selection, free of bias, because each individual is given a fair chance of selection, preserving diversity. On the constructed database, the evaluation is based on the force acceptance rate, force rejection rate, recognition accuracy, and recognition time. The created database is mainly for purpose of this study. Five hundredand seventy images (570) of face and iris were acquired via digital camera, three hundred and forty-two (342) face and iris images were used for training which equals 60% of the total dataset and two hundred and twenty-eight (228) face and iris images which are equivalent to 40% of the total dataset were used for testing. Both unimodal and multimodal recognition systems were used in the stimulation trials. The optimal result was achieved on a fused recognition system at a threshold of 0.76. The findings reveal a 1.79% force acceptance rate, 2.92% force rejection rate, 97.36% recognition accuracy, and 181.52 sec recognition time for enhanced Mayfly algorithm (EMA) as against 3.51% force acceptance rate, 5.26% force rejection rate, 95.18% recognition accuracy, and 215.75 sec recognition time for original Mayfly algorithm (MA). Obtained results showed that the enhanced algorithm would indeed increase the capability of the original Mayfly algorithm
ASSESSING BENEFICIARIES OF TERTIARY EDUCATION IN THE MANAGEMENT OF SOCIO-ECONOMIC AND POLITICAL EMANCIPATION OF OYO STATE, NIGERIA
Get PDFTertiary education serves as eye opener, helps in the development of latent skills, discovery of self, development of initiatives of beneficiaries, innovations and global competiveness in the world of work. The benefits of tertiary education are far beyond the individual beneficiaries to the state, nation and the world at large. This study assessed the impact of beneficiaries of tertiary education towards the management of socio-economic and political emancipation in Oyo State. The design adopted was descriptive survey. The entire 33 local governments in Oyo State formed the total population. Stratified sampling technique was used to group the local governments into three, based on senatorial district. Five of the local governments were chosen from Ogbomoso zone, four local governments from Oyo zone and Oke-ogun zone respectively using stratified sampling technique.The purposive sampling technique was used to select 180 civil servants who had tertiary education. A total of 900 respondents were used. Questionnaire which consisted of forty statements and tagged “Assessing Beneficiaries of Tertiary Education Questionnaire” (ABTEQ) was used. The research instrument was tested through test-re-test method and reliability index of 0.78 was obtained. Simple percentage Analysis was used to answer the three research questions. Findings revealed that there was significant relationship between the impact of beneficiaries of tertiary education and management of political emancipation Averagely, 73% respondents supported the option), management of socio emancipation (Averagely, 78% respondents supported the option) and management of economic emancipation (Averagely, 72% respondents supported the option). The paper recommended among others, that tertiary education should be made compulsory for all qualified citizens of the state, tertiary institutions should change the orientation of their students from job seeking to job creation through necessary modification in their curricular and method of instruction and that tertiary institution should ensure the political participation in Student Union Government is inclusive of all students and the union must serve as a model of exemplary government even to the larger society
INTERACTIVE PEDAGOGY AND CLINICAL LEGAL EDUCATION (CLE) IN THE TEACHING OF REPRODUCTIVE AND SEXUAL HEALTH LAW TO 2ND YEAR LAW STUDENTS
Get PDFReproductive and sexual health rights education in Nigeria is poor. With the alarming increase in sexual abuse and other forms of reproductive and sexual health rights violations, the knowledge of reproductive and sexual health law to would-be lawyers becomes imperative for effective protection and promotion of reproductive and sexual health rights as human rights. Recently, National Universities Commission and Council for Legal Education approved clinical legal education (CLE) as a method of teaching in law faculties. This paper presents an observational study of CLE cum interactive pedagogy methodologies in the teaching of reproductive health law to law students at the University of Ibadan. The combination of CLE and interactive pedagogy proved to be more effective than traditional theoretical based teaching. Clinical legal education using interactive pedagogy should be made mandatory in legal education
EXAMINING THE MIXED-METHODS ANALYSIS OF STUDENTS’ SKILL LEVEL IN THE USE OF COMPUTER-BASED TECHNOLOGY (CBT) IN NIGERIAN UNIVERSITIES
Get PDFThe use of technological tools in traditional education has advanced teaching and learning in the area of education globally. This study explored the gender, student’s prior knowledge in the use of Computer Based Technology (CBT) and classified the CBT skill level of students in selected Nigerian Universities. A descriptive survey research design with the use of mixed-methods was adopted and 3,000 undergraduate students received questionnaires. A total of 2,327 valid questionnaires were returned and used for the data analysis. A sub sample valid returned questionnaire participated in an in-depth focus group interview. The results revealed that females were marginally more interested and willing to use CBTs (50.9%). Additionally, students with greater prior knowledge in the use of CBT were most motivated to engage in blended learning (65.5%). Challenges were identified and included - computer laboratory were not accessible and there was power outages on campus, which prevented access to the internet. Consequently, students had to rely on their personal computers, mobile phones and data purchases, as well as cybercafés. While many students expressed dissatisfaction with this situation, they were at least able to develop their skill level and complete online assignments. Those without access to personal resources were placed at a major disadvantage. It was recommended that University Management should ensure that all students have access to up-to-date CBT facilities with back-up power supply and a conducive environment where they can develop the skills needed. The use of CBT should be integral to teaching and learning in all Nigerian universities
Development of Smart Intelligent Walking Aid 3rd Eye for the Blind Using Ultrasonic Sensor
Get PDFLaser canes, traditional white canes, guide dogs, Mowat sensor, talking signs and sonar systems have been used by those who are visually impaired (blind) but possess some drawbacks. The main focus of this research is to develop a device meant for the blind to navigate nearby obstacles called the “Third eye” that will notify the blind of any obstruction ahead by signaling a beep or vibration with design, experimental and implementation analysis. Third Eye is a wearable device based on five modules that is built from an Arduino Pro Mini 328- 15/16MHz board equipped with ultrasonic sensors, a vibrating motor, a buzzer, a power bank, a battery, etc. The device was subjected to test on a visually impaired person. Findings revealed that as the distance between the blind and obstacles decreases, the intensity of the vibration and the device’s beeping rate increases. Third Eye device proved effective, requires little training to use and enhances the confidence of the user thereby giving it an edge.