89 research outputs found

    Identity and Access Management System: a Web-Based Approach for an Enterprise

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    Managing digital identities and access control for enterprise users and applications remains one of the greatest challenges facing computing today. An attempt to address this issue led to the proposed security paradigm called Identity and Access Management (IAM) service based on IAM standards. Current approaches such as Lightweight Directory Access Protocol (LDAP), Central Authentication Service (CAS) and Security Assertion Markup Language (SAML) lack comprehensive analysis from conception to physical implementation to incorporate these solutions thereby resulting in impractical and fractured solutions. In this paper, we have implemented Identity and Access Management System (IAMSys) using the Lightweight Directory Access Protocol (LDAP) which focuses on authentication, authorization, administration of identities and audit reporting. Its primary concern is verification of the identity of the entity and granting correct level of access for resources which are protected in either the cloud environment or on-premise systems. A phased approach methodology was used in the research where it requires any enterprise or organization willing to adopt this must carry out a careful planning and demonstrated a good understanding of the technologies involved. The results of the experimental evaluation indicated that the average rating score is 72.0 % for the participants involved in this study. This implies that the idea of IAMSys is a way to mitigating security challenges associated with authentication, authorization, data protection and accountability if properly deployed

    Sparse Matrix Approach in Neural Networks for Effective Medical Data Sets Classifications

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    In this paper, a hybrid intelligent system that consists of the sparse matrix approach incorporated in neural network learning model as a decision support tool for medical data classification is presented. The main objective of this research is to develop an effective intelligent system that can be used by medical practitioners to accelerate diagnosis and treatment processes. The sparse matrix approach incorporated in neural network learning algorithm for scalability, minimize higher memory storage capacity usage, enhancing implementation time and speed up the analysis of the medical data classification problem. The hybrid intelligent system aims to exploit the advantages of the constituent models and, at the same time, alleviate their limitations. The proposed intelligent classification system maximizes the intelligently classification of medical data and minimizes the number of trends inaccurately identified. To evaluate the effectiveness of the hybrid intelligent system, three benchmark medical data sets, viz., Hepatitis, SPECT Heart and Cleveland Heart from the UCI Repository of Machine Learning, are used for evaluation. A number of useful performance metrics in medical applications which include accuracy, sensitivity, specificity. The results were analyzed and compared with those from other methods published in the literature. The experimental outcomes positively demonstrate that the hybrid intelligent system was effective in undertaking medical data classification tasks

    Assessment of Undergraduate Business Education Students' Usage of Social Networking as a Platform For Entrepreneurship Activities In North-West, Nigeria

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    The study assessed the undergraduate business education students' usage of social networking as a platform for entrepreneurship activities in North-west, Nigeria. Specifically, the study had five objectives, five research questions and five null hypotheses. The study anchored theory of Technology Acceptance Model of Ajzen and Fishbein's, (1980) and Division of Innovation Theory (DOI) of Rogers (1995). The study adopted a survey research design. The population of this study comprises of all the 407 final undergraduate business education 2019/2020 academic session in North-west Nigeria. The entire population was used for the study. The instrument for the data collection was a structured questionnaire. The instrument was validated by four experts, pilot tested and a reliability coefficient of 0.81 was obtained. The data were collected by the researcher assisted by four research assistants using personal contact method. Descriptive statistics of mean and standard deviation was employed to answer the research questions. The hypotheses were tested using Analysis of Variance (ANOVA) at the 0.05 level of significance. The results revealed among others that the level of students' awareness, perceived ease of use and perceived usefulness of social networking as a platform for entrepreneurship activities in tertiary institutions in North-west Nigeria was low. Based on these, it was concluded that the business education will not reap the benefit of social networking sites to searcher for business opportunities, venture into business and meet the needs of their technologically savvy customers. It was recommended among others that business education lecturers should create awareness on students on the role of social networking as a platform for entrepreneurship activities

    Modified PSO-Based Virtual Inertia Controller for Optimal Frequency Regulation of Micro-Grid

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    Owing to the growing need to address the energy crisis by the traditional sources (e.g. Thermal power plants), as well as the associated environmental concerns posed, the power system witnessed increased penetration of power electronics-based power sources like solar, wind, and energy storage in terms of battery technologies. Consequently, modern compared with traditional power systems have become more susceptible to large frequency fluctuations due to the emergence of stability issues. Prominent among these include the reduction of system properties such as damping and inertia which are significant characteristics of system stability. Insufficient inertia drives the grid frequency outside the acceptable range under severe disturbances and this may lead to an outage of generators and tripping, unscheduled shedding of load, system collapse, and in the severe scenario, an entire power blackout, this threatens the system dynamic security. To preserve the system's dynamic security, this paper proposes an alternative approach to frequency regulation built upon a PID-based Virtual Inertia Control (VIC) which imitates the inertia property. The proposed virtual inertia uses the frequency derivative to emulate virtual inertia. The optimality search capability of the Particle Swarm Optimization (PSO) technique is used to design the proposed controller. Evaluation of the robustness of the proposed controller is demonstrated through Time Domain Analysis, considering different system operating ranges for improving frequency stability and resilience. Improved performance of the proposed controller when paralleled with the traditional virtual inertia controller shows a 69.2% reduction in frequency nadir under the condition of reduced system inertia, 70% without RESs integration. Also, 50.7% and 44.4% improvement in the reduction of frequency nadir and maximum overshoot respectively were observed under the situation of nominal system inertia, 100%, and Renewable Energy Systems (RESs) penetration

    Adsorption of Chromium (VI) onto Metakaolin: Isotherms, Modelling and Optimization

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    This paper focuses on the application of metakaolin as an adsorbent for the removal of hexavalent chromium (Cr(VI)) from aqueous solution. Metakaolin was prepared and characterized using x-ray fluorescence spectroscopy (XRF), scanning electron microscopy (SEM), specific surface area and pH at point of zero charge analysis. Batch adsorption experiments were designed and conducted with the aid of the statistical central composite design in order to study the effects of pH (2–10), initial concentration of Cr(VI) (25–100 mg/L) and adsorbent dosage (2–10 mg/L). Adsorption of Cr(VI) onto metakaolin was described by a model quadratic equation. Analysis of variance revealed significance of the model quadratic equation. The predicted optimum values of the process variables were:  pH of 2.48, initial Cr(VI) concentration of 32.16 mg/L and adsorbent dosage of 7.08 g/L. The experimental percentage adsorption of Cr(VI) obtained under the predicted optimum conditions (34.43 %.) is very to the predicted value of 37.51 %. The adsorption equilibrium data were analyzed using Langmuir, Freundlich and Dubinin-Radushkevich isotherms. The adsorption equilibrium data is best described by the Freundlich isotherm. The maximum adsorption capacity (qmax) for Cr(VI) adsorption onto metakaolin  is 6.36 mg/g. The results showed that metakaolin is a promising adsorbent for the removal of hexavalent chromium from water

    Artificial Neural Network Logic-Based Reverse Analysis with Application to COVID-19 Surveillance Dataset

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    The Boolean Satisfiability Problem (BSAT) is one of the crucial decision problems in the fields of computing science, operation research, and mathematical logic that is resolved by deciding whether or not a solution to a Boolean formula exists. When there is a Boolean variable allocation that induces the Boolean formula to yield TRUE, then the SAT instance is satisfiable. The main purpose of this chapter is to utilize the optimization capacity of the Lyapunov energy function of Hopfield neural network (HNN) for optimal representation of the Random Satistibaility for COVID-19 Surveillance Data Set (CSDS) classification with the aim of extracting the relationship of dominant attributes that contribute to COVID-19 detections based on the COVID-19 Surveillance Data Set (CSDS). The logical mining task was carried based on the data mining technique of the energy minimization technique of HNN. The computational simulations have been carried using the different number of clauses in validating the efficiency of the proposed model in the training of COVID-19 Surveillance Data Set (CSDS) for classification. The findings reveals the effectiveness and robustness of k satisfiability reverse analysis with Hopfield neural network in extracting the dominant attributes toward COVID-19 Surveillance Data Set (CSDS) logic

    Radiological and Toxicity Impact of Uranium (U-238) in Ground Water to Different Age Groups at Wurno, Sokoto State, Nigeria

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    One of the primary goals of the World Health Organization (WHO) is for every society to have an adequate supply of safe drinking water. This work aimed to assess the radiological and toxicity impact of ground water of Wurno Local Government Area. Uranium activity concentration from 45 water samples collected from different locations in the study area were determined using HpGe   detector, the result from the analysis was used to evaluate the annual effective dose due to ingestion of groundwater from the study area by the inhabitants.  Radiological and chemical toxicity risks were also calculated. High level activity was reported in Diggim while low activity level was reported in Nassarawa-Daje. The annual effective doses for adult, children and infants were estimated to be from 0.008 mSvy-1 to 0.32 mSvy-1. The highest risk cancer mortality value was found at Diggim with a value of 4.34 × 10-4 while the lowest value was observed at Nassarawa Daje with a value of 1.17 × 10-5. Chemical toxicity value ranged from 0.59 – 21. 79 µg.kg-1.day-1 with an average dose value of 5.12 µg.kg-1.day-1. The lifetime average daily dose (LADD) values were reported to be higher at Diggim and lower at Nassarawa-Daje with the values 21.79 µg.kg-1.day-1 and 0.59 µg.kg-1.day-1 respectively compared with 0.6 µg.kg-1.day-1 WHO limit standard. Significantly, the high activity level, and chemical toxicity risk reported from this study is an indication that the area may have developed some fractures of granitic strata in the subsurface geology that contributed to the wide distribution of radiation dose

    Terrace Soil Suitability for Highway Construction: Case Study in Lesser Himalaya (CPEC Project E-35), North Pakistan

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    In this study, terrace soil investigation was carried out in project E-35 (phase-I) China-Pak Economic Corridor, Lesser Himalayas, North Pakistan. The methodology in current research is based on tests that include sieve analysis, plastic index, proctor, California Bearing Ratio, Los Angeles, sand equivalent and specific gravity. The results of these tests for different layers were compared with AASHTO and NHA specifications. The results show that the embankment, subgrade and subbase layers were composed of silt, sand and gravel, respectively while the aggregate base coarse was composed of sand, aggregate and less amount of fine clay material. The sieve analysis test shows that soil and aggregate base coarse has less clay with high silt, sandy material and index plastic to low plastic, which is appropriate for the construction. The California Bearing Ratio shows that the soil and aggregate base coarse have high load-bearing capacity. The Los Angeles abrasion reveal that the sub base and aggregate base coarse are resistive. The sand equivalent shows that aggregate base coarse has high sand material. The specific gravity illustrates that aggregate base coarse material is denser. The current study shows that terrace soil is suitable for the construction of the road in project E-35 (phase-I) China-Pak Economic Corridor

    Smart Health Internet of Thing for Continuous Glucose Monitoring: a Survey

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    Health monitoring system allows patients to monitor the health-related problem to avoid further complications which could result in loss of life. Smart health is one of the categories of a health monitoring system that uses Smartphone’s and sensors to effectively monitor patient health status. However, the smart health internet of thing methods for glucose monitoring still does not provide accurate glucose reading. Hence, diabetes patient can easily loss life. To help understand this challenge, a comprehensive survey focused on smart health internet of thing methods for continuous glucose monitoring was conducted. The paper discusses the benefit and challenge of each method applicable to glucose monitoring. It was observed that several smart health methods required sensor to function. Smart vehicles and remote monitoring have less attention. However, when accommodates can provide future opportunities
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