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Ejeh, Patrick
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Computer Science & IT Decision Sciences, Operations Research & Management

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Knowledge Advancement and Application in E-business for SME’s in Nigeria: An Epilogue (A Case of Delta State) Omede, Nduka Kenneth; Ejeh, Patrick
Management Analysis Journal Vol 9 No 3 (2020): Management Analysis Journal
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/maj.v9i3.38738

Abstract

SMEs continuously seeking for knowledge advancement to improve their performance and keep pace with the new ways of doing business, the acquisition of knowledge equip SMEs to come to terms with the realities of the new order. This study examined knowledge advancement and application in e-business for SMEs in Nigeria. To achieve these laudable objectives two hypotheses were formulated to establish whether or not there is a relationship existing between the two intervening variables i.e. knowledge advancement and application in e-business and the growth and development for SMEs in Nigeria in general and Delta state in particular. Survey research design was adopted, while data were obtained from structured questionnaire and analyzed using Pearson’s product-moment coefficient of correlation. From the analysis, the results indicated that there is an existing relationship between the variables. Based on the findings it was concluded that for SMEs to stand the test of time, the need to continue to seek for new ways of doing business and innovation becomes imperative. Among others, the study recommended that SMEs should embark on intensive training, skill acquisition and development exercise to keep pace with the new order.
Knowledge Advancement and Application in E-business for SME’s in Nigeria: An Epilogue (A Case of Delta State) Omede, Nduka Kenneth; Ejeh, Patrick
Management Analysis Journal Vol 9 No 3 (2020): Management Analysis Journal
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/maj.v9i3.38738

Abstract

SMEs continuously seeking for knowledge advancement to improve their performance and keep pace with the new ways of doing business, the acquisition of knowledge equip SMEs to come to terms with the realities of the new order. This study examined knowledge advancement and application in e-business for SMEs in Nigeria. To achieve these laudable objectives two hypotheses were formulated to establish whether or not there is a relationship existing between the two intervening variables i.e. knowledge advancement and application in e-business and the growth and development for SMEs in Nigeria in general and Delta state in particular. Survey research design was adopted, while data were obtained from structured questionnaire and analyzed using Pearson’s product-moment coefficient of correlation. From the analysis, the results indicated that there is an existing relationship between the variables. Based on the findings it was concluded that for SMEs to stand the test of time, the need to continue to seek for new ways of doing business and innovation becomes imperative. Among others, the study recommended that SMEs should embark on intensive training, skill acquisition and development exercise to keep pace with the new order.
An Ensemble-based Adaptable and Privacy-aware Threat Detection Mechanism for Wireless Sensor Network in Healthcare Systems Afonne, Emmanuel Iheanacho; Ejeh, Patrick; Aworonye, Linda Chioma
Scientific Journal of Computer Science Vol. 1 No. 2 (2025): December
Publisher : PT. Teknologi Futuristik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64539/sjcs.v1i2.2025.328

Abstract

Recently, wireless sensor networks (WSNs) have been widely integrated in critical applications such as environmental monitoring, smart cities, and modern healthcare for remote patient monitoring and data collection. This makes WSNs increasingly susceptible to security threats, including eavesdropping, jamming, sybil, data injection, routing, senor node capture, malicious intrusion attacks etc., therefore maintaining integrity, confidentiality, and availability of sensitive data and preserving privacy become a challenge. Existing mechanisms do not integrate threat detection, privacy preservation, and adaptability to evolving threats leading to security breaches in the left-out security requirements. This paper proposes an ensemble-based threat detection mechanism (FAL-ELeM-IDS) with privacy-awareness and adaptability to evolving threats for WSNs-based healthcare systems. The ensemble consists of Online Random Forest, Online AdaBoost, Support Vector Machine, Neural Network, and XGBoost to ensure detection high accuracy and low false-positives. Federated Learning combined with ensemble technique to provide confidentiality and a combined Online Adaptive Boosting and Online Random Forests algorithms to provide adaptability. The proposed model trained on a real-world healthcare sensor dataset demonstrates its superiority in performance compared to conventional models. An accuracy of 97.8%, a recall of 97%, precision of 98%, and F1-score of 97.5%, was achieved outperforming individual models by significant margins, showing that the model is accurate and reliable in detecting threats. This mechanism implies enhanced system security and privacy, timely threat mitigation ensuring patient safety, and boost in public acceptance for sensor-based healthcare services. Overall, this work contributes a scalable, privacy-aware, and adaptive threat detection mechanism suitable for integration in the sensitive healthcare applications.
Co-Authors Afonne, Emmanuel Iheanacho Aworonye, Linda Chioma Omede, Nduka Kenneth