Browsing by Author "Jimoh, R. G."

Now showing 1 - 7 of 7
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    A semantic framework for e-commerce using web ontology language 2
    (the Faculty of Natural and Applied Sciences, Al-Hikmah University, Ilorin, 2017) Jimoh, R. G.; Kinssinger, S.; Agbo, F. J.; AbdulRaheem, M.; Tomori, R. A.; Salimonu, I. R.
    Several web applications have been deployed by business enterprises through which their products would not only be made available on the internet, but also enable their prospective consumers to be able to follow some procedures to make their purchases online. This is normally achieved with the help of some technologies provided by the Semantic Web, namely Resource Description Framework (RDF), Resource Description Framework Schema (RDFS), DARPA Agent Markup Language (DAML) plus Ontology Inference Layer (OIL) and Web Ontology Language (OWL1). The Present study leverages on some of the Semantic Web technologies mentioned in the previous sentence in order to design a Semantic framework for enhancing Business to Consumer (B2C) e-commerce applications. In this paper, the researchers developed OWL 2 ontology rich in more expressive OWL constructs for rich entailments. Qualified Cardinality Restriction (QCR) which OWL 2 is known for, is also applied to the ontology. Also in this paper, the researchers compared two popular reasoners in querying the underlying ontology in a programmatic way. The overall aim of this research is to provide a more efficient framework for B2C through the right choice and combination of some Semantic Web languages.
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    Design of intelligence gathering model: A semantic web based approach
    (the Faculty of Natural and Applied Sciences, Al-Hikmah University, Ilorin, Nigeria, 2018) Jimoh, R. G.; Agbo, F. J.; Kinssinger, S.; AbdulRaheem, M.; Tomori, R. A.; Salimonu, I. R.
    Intelligence information gathering, investigation and analysis are vital components of security management in any given society. The ability to know what, where and when events occur is a key element of investigation process especially in a large dataset. This is a thematic, spatial and temporal (TST) reporting issue. Semantic Web technologies such as Resource Description Framework (RDF), Resource Description Framework Schema (RDFS) and Web Ontology Language (OWL) have been discovered to be a good approach to solving this problem. In this study, the researchers proposed a semantic web based intelligence gathering model for TST using OWL ontology, which has more expressive constructs than RDF. The study further demonstrated the use of Semantic Query-enhanced Web Rule Language (SQWRL), Semantic Web Rule Language (SWRL), Jess and OWL APIs for ontology reasoning and inferences. The model presents university ontology, which could be applied in implementing security intelligence gathering in university community. Thus, this paper established the possibility of gathering intelligence information that satisfied TST through semantic web based tools.
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    Iris Feature Extraction for Personal Identification using Fast Wavelet Transform (FWT)
    (International Journal of Applied Information Systems, 2014) Abikoye, O. C.; Sadiku, J. S.; Adewole, K. S.; Jimoh, R. G.
    Iris is the annular region of the eye bounded by the pupil and the sclera(white of the eye) on either side. The iris has many interlacing features such as stripes, freckles, coronas, radial furrow, crypts, zigzag collarette, rings etc collectively referred to as texture of the iris. This texture is well known to provide a signature that is unique to each subject. All these features are extracted using different algorithms i.e features extraction is the process of extracting information from the iris image. Iris feature extraction is the crucial stage of the whole iris recognition process for personal identification. This is a key process where the two dimensional image is converted to a set of mathematical parameters. The significant features of the iris must be encoded so that comparisons between templates can be made. In this study the feature of the iris is extracted using Fast Wavelet Transform (FWT). The algorithm is fast and has a low complexity rate. The system encodes the features to generate its iris feature codes.
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    Office Application in Digital Skill Acquisition, GNS 312,
    (General Studies Division, University of Ilorin, 2017) Jimoh, R. G.; Ahmed, M. I.,; Mabayoje, M. A.; AbdulRaheem, M.; Salihu, S. A
    GNS NOTE
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    A review of algorithm for fingerprint image acquisition, preprocessing and minutiae extraction
    (Ilorin Journal of Science, 2015) Adewole, K. S.; Jimoh, R. G.; Abikoye, O. C.
    Biometric recognition distinguishes between individuals using physical, chemical or behavioral attributes of the person. These attributes are called biometric identifiers or traits, and include fingerprint, palmprint, iris, face, voice, signature, gaint, and DNA among others. Fingerprint recognition is one of the oldest and most reliable biometric used for personal identification. Fingerprint has come a long way from tedious manual fingerprint matching. The ancient procedure of matching fingerprints manually was extremely cumbersome and time-consuming and required skilled personnel. In this paper, a review of algorithms for the various stages involved in fingerprint recognition such as fingerprint image acquisition, segmentation, normalization, ridge orientation estimation, ridge frequency, Gabor filtering, binarization, thinning, minutiae extraction, template generation, and template matching is presented. It was established that minutiae features of a person fingerprint truly make fingerprint of individual to be unique.
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    Stepwise biometric procedures for managing student attendance in higher institution of learning
    (2015) Adewole, K. S.; Jimoh, R. G.; Abikoye, O. C.; Ajiboye, A. R.
    Data and information security are very important issues in computing environment. Security of data prevents unauthorized users from accessing individual personal information. Biometric is one of the authentication methods used in a wide range of application domains such as airline and banking environment to secure confidential data. This technique is more reliable and capable of distinguishing between an authorized person and an impostor than traditional methods such as passwords. Large numbers of higher academic institutions in the developing countries are still using the process of manual attendance for both lecture and examination for students' authentication and authorization, hence, the need for automated system that can assist in this area. In this paper, stepwise biometric procedures for managing students' attendance for both lectures and examinations are presented. The various stages involved in student attendance management are discussed and simulated. These include enrollment, fingerprint matching and attendance management. The results show that the proposed system is able to identify those students who are qualified to sit for an examination.
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    Stock trend prediction using regression analysis–a data mining approach
    (ARPN Journal of Systems and Software, 2011) Abdulsalam, S. O.; Adewole, K. S.; Jimoh, R. G.
    Organizations have been collecting data for decades, building massive data warehouses in which to store the data. Even though this data is available, very few of these organizations have been able to realize the actual value stored in it. The question these organizations are asking is how to extract meaningful data and uncover patterns and relationship from their databases. This paper presents a study of regression analysis for use in stock price prediction. Data were obtained from the daily official list of the prices of all shares traded on the stock exchange published by the Nigerian Stock Exchange using banking sector of Nigerian economy with three banks namely:- First Bank of Nigeria Plc, Zenith Bank Plc, and Skye Bank Plc to build a database. A data mining software tool was used to uncover patterns and relationships and also to extract values of variables from the database to predict the future values of other variables through the use of time series data that employed moving average method. The tools were found capable technique to describe the trends of stock market prices and predict the future stock market prices of three banks sampled.