University of Ibadan Journals
Not a member yet
794 research outputs found
Sort by
Development of Serial Number Extractor for Nigerian Currencies
Get PDFAbstract
The need to track currency movement and validate currencies in circulation are two cogent reasons for developing a real-time currency serial number extractor. Due to significant technical innovation over the past few decades, currency counterfeiting issues have gotten progressively worse all over the world and it is presently one of the main issues in Nigeria. Hence, financial institutions and the general public often desire to know the authenticity of cash. Also, Government and security agencies often desire to track cash for the purpose of apprehending notorious kidnappers after ransom collection. This calls for a fast and accurate serial number extraction from currencies. Automatic serial number extraction can be segmented into three (3) phases, which include currency classification, region of interest extraction, and character recognition. In this paper, an optimized object identification model was proposed for currency classification. A pre-trained denomination-based region of interest algorithm was then applied for the extraction of the serial number region. We further utilized three (3) existing optical character recognition models: Pytesseract, Easy OCR, and Keras OCR for the character recognition. Accuracy, Levenshtein Distance, Jaccard Similarity, Character Error Rate, and Damerau Distance metrics were employed in this study for recognition performance measure. The currency bill classification yielded a 100% accuracy while the best accuracy of 81% was obtained with the EasyOCR framework at the character recognition phase. The recognition model performance can be considered poor for the targeted application. Hence, the need for customization of the general character recognition architecture for Nigerian currency bill serial number recognition
WORK EXPERIENCE AND COMPETENCE AS INDICATORS OF PERFORMANCE EFFECTIVENESS OF EDITORS IN BOOK PUBLISHING FIRMS IN SOUTHWESTERN NIGERIA
No full textPerformance effectiveness of editors is critical to every publishing firm. For editors to discharge their duties efficiently, editorial competence is crucial. It is in the light of this that this study examined how work experience and competence indicate performance effectiveness of editors in book publishing firms in southwestern Nigeria. Descriptive survey research method was adopted, structured questionnaire tagged “WECIPEE” was the instrument, while four research questions were raised. The population of the study was the editorial staff of the 139 registered publishing firms in southwestern Nigeria while random sampling technique was used to select the editors of twenty-four publishing companies which constituted the study sample. The data collected was analysed using percentages and statistical mean. Findings show that publishers preferred editorial staff who have adequate experience, and that human capacity development enhanced performance effectiveness of editors. The study recommended that publishers should emphasise editors’ competence, ICT skills, and training
SCHOOL SUPPORT SERVICES, PRINCIPAL ADMINISTRATIVE SKILLS AND TEACHER JOB COMMITMENT IN PUBLIC SECONDARY SCHOOLS IN OGUN STATE, NIGERIA
No full textThis study investigated school support services, principal administrative skills and teacher job commitment in public secondary schools in Ogun State, Nigeria. The descriptive survey research design was adopted for the study. The population consisted of 3,587 teachers that were in 473 public secondary schools in Ogun State. The sample size for the study was 300 (teachers) respondents. Four hypotheses were formulated and tested. A self-structured questionnaire titled School Support Services, Principal Administrative Skills, Teacher Job Commitment Questionnaire (0.76). The data collected was analysed using inferential statistics of Pearson Product Moment Correlation and Multiple Regression analysis at 0.05 level of significance. The results showed significant relationship between school support services (library, health and mentoring) and teacher job commitment (library r= 0.410, P<0.05, health/medical r=0.447, P<0.05 and mentoring r=0.177, P<0.05). There was significant relationship between principal administrative skills (supervisory and communication skills) and teacher job commitment (supervisory skill r= 0.308, P<0.05, and communication skills r=0.341, P<0.05). There was significant relative contribution of school support services and principal administrative skills to teachers job commitment (ß = (0.425), t(298) = 7.799, p<0.05, ß = (0.298), t(298) = 2.789, p<0.05) and there was significant joint contribution of principal administrative skills and school support services to teacher job commitment (R= 0.459,(F(2,282) = 37.577, P = 0.000).Based on these findings, the study concluded that school support services and principal administrative skills are potent variables that could enhance or mar teacher job commitment. Therefore, the study recommended that teacher job commitment can be facilitated through school support services and high level of principals’ administrative skills
Housing Affordability of State Civil Servants in Calabar, Nigeria
Get PDFThe global proportion of urban population has been on the increase since 1900 and it is expected to rise to 60% and 66% by 2030 and 2050 respectively. This high rate of population growth coupled with huge capital outlay required to develop housing made housing to be scarce and unaffordable. This paper examines rental housing affordability of civil servants in Calabar, Nigeria. The concept of affordability guided this study and cross-sectional survey research design was adopted. Secondary and primary data were used. A multi-stage sampling technique was used to sample 302 civil servants from the existing nine ministries and thirty-six parastatals in Cross Rivers state. A structured questionnaire was used to collect primary data. Data were analysed using descriptive and inferential statistics. The sex distribution of respondents indicates that male and female constituted 73.5% and 26.5% respectively. The middle-income brackets of between N40, 000 - N65, 000 and N65, 001 - N95, 000 jointly constitute 65.5% of the total respondents. The major factors that influence choice of rental housing according to 70.2% respondents were location, security, quality of housing, rent paid and neighbourhood characteristics. It was observed that between 2004 and 2017, rent increased, averagely on two years basis but salaries of civil servants were reviewed once (2013). The rent of a single room which stood at N16, 000 in 2004 increased to N32, 000 (an increase of 100%) in 2008 and further increased to N65, 000 in 2017. No civil servant earned enough housing allowance to pay his or her house rent. The percentages of mean annual rents paid as housing allowances for civil servants on grade levels 13 and 17 were 73.14% and 86.53% respectively. Housing allowances for workers on grade levels 10 to 13 range between 224,056.00 and 292,569.00 but to have access to 2 or 3-bedroom flats. There was significant difference between mean housing allowances and mean annual rents (t=-14.755). There was a very strong positive relationship (r=0.952) between ‘mean housing rent’ and ‘mean housing allowances’. House rents paid by most civil servants on grade levels 01- 14 were not adjudged to be affordable. These categories of workers spent between 37% and 87% of the salaries on rental housing. Civil servants on GLs 15 to 17 appeared to be the workers who can afford rental prices when juxtaposed with their annual incomes without considerations for other household expenditures. The growing problems of rental housing affordability among civil servants has brought into focus the need for housing researcher and policy makers to develop a better understanding of the operation of urban rental housing marke
Genetic Algorithm Based Space-Optimised Arrangement of Containers and Stability in Containerships
Get PDFAbstract
Space optimization in a container terminal to prevent space wastage and ensure the stability of containers is an optimization problem frequently experienced at container terminals. Ineffective planning of the arrangement of containers creates the problem of stability, loading and unloading containers from one port to another, leading to time wastage. In this research, the optimization of containers stowage in containership is achieved by using genetic algorithm processes of selection, crossover, mutation, and fitness in order to determine the optimal arrangement of containers in container ships. The objective function, the solution representation, and the constraints were set, and a fitness function determines how good a candidate solution is. The algorithm is able to optimize space, thereby ensuring stability and preventing time wastage that comes with loading and unloading at different ports.
The experiment was conducted six times on the population size of one hundred 20-feet containers and one hundred 40-feet containers. The results show that an average percentage space utilization of 98.55% and an average time of 17.73 seconds were achieved. The algorithm is efficient for arranging any type and size of containers on containerships
Enhancement of Intrusion Detection Dataset in Wireless Sensor Network using RNS - Feature Conversion with Stack Ensemble Technique
Get PDFThis research presents a feature selection and conversion technique for Wireless sensor network (WSN) for the enhancement of classification and detection of intrusions. There are many different approaches and datasets, but the performance of the current Intrusion detection systems (IDSs) does not seem to be sufficient because there are so many data volumes that need to be processed in a less ample time that it is beyond the capacity of the most widely used hardware and software tools. However, computational challenges and inadequate quality still exist in state-of-art of feature selection approaches in IDS. In order to effectively and optimally minimize the feature size of the data dimensions, the Particle Swamp Optimization (PSO) approach was presented, thereafter Residue Number System (RNS) was used to further convert the selected features from the dataset using moduli of {2(n+1) - 1, 2(n) - 1, 2(n)} to residues in order to reduce large weighted number to several small numbers andenhance the power consumption and improve the time complexity further. The outcomes demonstrate that Case 1; a composite of Z-Score, PSO, RNS, and Ensemble Classifier performed better than the case without the procedure of features conversion in Case2;(Z-Score + PSO+ Ensemble Classifier),in terms of the well-known UNSW-NB 15 dataset's classification accuracy, error rate, sensitivity, specificity, and training time. The classification accuracy shows the highest classification rate for CASE 1 to be 97.4736% and 95.3602% for CASE 2. The result shows a clear cut difference of over 2% in variation indicating the prominence of featureconversion in WSN dataset 
Use of White Shark Optimization for Improving the Performance of Convolution Neural Network in Classification of Infected Citrus
Get PDFCitrus plant diseases are major causes of reduction in the production of citrus fruits and their usage. Early detection of theonset of the diseases is very important to curb and reduce its spread. A number of researches have been done on the detectionand classification of the diseases, most of which have identified poor labelling of symptoms which result into improperclassification. Some researchers have also experimented on the effectiveness of convolution neural network and other deeplearning techniques, most of which results into a faster convergence but suffers from low accuracy, computational overheadand overfitting as fundamental issues. To reduce the effects of overfitting, this research developed a White SharkOptimization-Convolution Neural Network (WSO-CNN) technique to address the aforementioned problem by introducing aregularization strategy via feature selection which selects more useful and distinguishing features for classification. As aresult, the developed technique was able to detect and classify various types of citrus fruit diseases and label themaccordingly with low false positive rate, high sensitivity, specificity, increased accuracy and reduced recognition time, basedon all the experiments performed with the dataset used in the research. Hence WSOCNN performed better than CNN inclassifying citrus plant disease having a reduced FPR of 3.57%, 8.34%, 3.89% and 9.00% for black spot, greasy spot, cankerand healthy/non healthy dataset respectively
A Collaborative Service Provider Platform For Handyman Services
Get PDFAbstract
Nigeria's population is growing at an unprecedented pace of 2.4 percent yearly, boosting the demand for a handyman. Although Nigeria has a thriving informal sector comprised of part-time or freelance handypersons, the country's economy needs to be structured at the national level to offer users excellent service. The unorganized informal sector has made access to handyperson services more challenging, specifically when traveling or moving to a new location. Service providers are spread out over different locations and provide varied pricing, quality, and types of services. Existing solutions to this issue need to be more cohesive, offering contacts spread throughout the internet, some of which need to be more genuine and wind up being fraudsters acting as handyman providers. Hence, this research aims to develop a platform where all handyman service providers can showcase their services, and clients can quickly request and hire one. To achieve the work, an iteration model was employed, the design was created using Draw.io, HTML, CSS, BOOTSTRAP, and JAVASCRIPT to develop the application layer, business logic was constructed using PHP, and Mysql was used for the back end. The application was hosted and deployed for evaluation. Questionnaires were used to capture users' opinions after interacting with the application, and the results proved that the application provides accessible communication between the handyman and those requiring their services
TEAM COHESION AS IMPERATIVE FOR SCHOOL MANAGEMENT IN ENHANCING EFFECTIVE SERVICE DELIVERY IN EDUCATIONAL INSTITUTIONS
Get PDFThis paper looked at school management with a focus on team cohesion with a view to achieving effective service delivery in educational institutions. This was for the purpose of determining appropriate strategies for improving the quality of service delivery system in Nigerian educational system. The paper submits that team cohesion is very important to the success of any organization. People are referred to as a team because they have similar objectives and determined to pursue them together as a team to achieve the desired results. The paper also examined the ability of school administrators/teachers to organize classrooms and manage the behaviour of their students which is considered critical to achieving positive educational outcomes and build cohesion among the staff as well as the students. Problems within a team are unavoidable, hence, the paper as well focused on strategies for handling problems within the team before they escalate so as to ensure effective service delivery. There is no doubt that cohesive groups offer advantages in terms of social support for group members, they also present some risks, such as lack of cooperation among team members, lack of reward and recognition for individual contributions to accomplish team goals as well as selfish interests on the part of team members. The paper, therefore, recommended that all team members should embrace the spirit of togetherness for successful task accomplishments regardless of individual differences among members; and that classroom-management strategies should be executed effectively such that teachers minimize the behaviors that impede learning for both individual students and groups of students, while maximizing the behaviors that facilitate or enhance learning and promote team cohesion and effective service delivery
ASSESSMENT OF STUDENTS’ AWARENESS AND UTILISATION OF OPEN EDUCATIONAL RESOURCES IN EDUCATION IN SELECTED NIGERIAN UNIVERSITIES
Get PDFThis research examined the level of students' awareness, utilisation and challenges of using open educational resources (OERs) for learning in Nigerian universities. The descriptive survey research design was adopted for the study. Multi-stage sampling technique was used to select two (2) universities (both federal and state-owned) that are running open and distance learning programmes in each of the six (6) geographical zones of Nigeria, and to select a total of two thousand nine hundred and eight-seven (2,987 students). To guide the study, three research questions were raised and answered, while three hypotheses were formulated and tested at 0.05 level of significance. Data obtained were analysed using descriptive statistics of mean, standard deviation and inferential statistics of ANOVA. The main structured research questionnaire used in the study was titled: “Student’s Use of OERs Questionnaire” (SUOER; r=0.78). The findings revealed that students had a high level of awareness (? = 2.92; SD = 1.02) of open educational resources for learning and also aware of the effect (? = 2.58; SD = 0.98) of the use of OERs on their academic achievements also with a range of identified challenges of the proper use of OERs for education. Findings also established significant institutional affiliation differences in the levels of students’ awareness (F(11,2986) = 14.15; p = 0.00 < 0.05), perceived effect of the use of OERs on academic achievements (F(11,2986) = 32.97; p = 0.00 < 0.05) and perceived challenges (F(11,2986) = 15.85; p = 0.00 < 0.05) towards the utilisation of OERs for education. Implications to meeting the global challenges were discussed. It was recommended among others that modalities to provide free access to data within the campus environments needed to be worked out for the students