DSpace Community: Journal Articles

Implementing Competency-Based Education and training in Technical Colleges: A Realistic Approach to Producing Skilled Workforce for Sustainable Industrial Development

Fri, 01 Jan 2021 00:00:00 GMT

Title: Implementing Competency-Based Education and training in Technical Colleges: A Realistic Approach to Producing Skilled Workforce for Sustainable Industrial Development Authors: Eze, C. P.; Mojekwu, O. E.; Omeje, H. O.; Igwe, C. O.

Effect of spice-treated sundried bovine rumen digesta on performance, carcass characteristics and nutrient digestibility of finisher broiler chickens

Sat, 01 Apr 2023 00:00:00 GMT

Title: Effect of spice-treated sundried bovine rumen digesta on performance, carcass characteristics and nutrient digestibility of finisher broiler chickens Authors: Eniwaiye, Adenike A; Otu, Bisong O.; Kolo, Philip S.; Owolabi, Shina J.; Balogun, Muda A.; Ochiyan, Michael A. Abstract: The study was conducted to investigate the effects of feeding diets containing spice treated Sundried Bovine Rumen Digesta (SDBRD) on growth performance, carcass characteristics and nutrient digestibility of broiler chickens. A total of one hundred and fifty (150) day old broiler chickens were assigned to five (5) diets in triplicates containing ten (10) birds each in a completely randomized design. The diets were; T1, (control, 0% SDBRD), T2 (20% SDBRD without spice supplementation), T3 (20% SDBRD + 200 mg ginger), T4 (20% SDBRD + 200 mg garlic), and T5 (20% SDBRD + 200 mg thyme). Data were collected on growth performance, carcass characteristics and nutrient digestibility. The data were analysed using the Analysis of Variance (ANOVA) and differences among mean were separated with the Duncan Multiple range. The results showed that broiler chickens fed diets containing spices-supplemented SDBRD had significantly (p<0.05) higher weight gain and better feed conversion ratio (FCR). The live weight and dressing percentage were significantly (p<0.05) higher among birds fed spice-supplemented diets compared to the control and the un-supplemented SDBRD diet. However, digestibility for dry matter and crude protein was higher (p<0.05) on T1 and T2 than on spice supplemented diets. It was concluded that the combination of sundried bovine rumen digesta and spices such as garlic, ginger and thyme improve growth performance, carcass characteristics and nutrient digestibility, and can therefore be included in the ratio of broiler finisher at 20% level without any deleterious effect. Description: Effect of spice- treated sundried bovine rumen digesta on performance, carcass characteristics and nutrient digestibility of finisher broiler chickens

SYSTEMATIC LITERATURE REVIEW ON MALICIOUS COMMAND AND CONTROL: TYPES, TECHNIQUES, TOOLS, CHALLENGES AND RESEARCH DIRECTIONS

Sun, 01 Mar 2026 00:00:00 GMT

Title: SYSTEMATIC LITERATURE REVIEW ON MALICIOUS COMMAND AND CONTROL: TYPES, TECHNIQUES, TOOLS, CHALLENGES AND RESEARCH DIRECTIONS Authors: OJENIYI, Joseph Adebayo; CEPHAS, Anyigor Chigbo; SUBAIRU, Sikiru Olanrewaju; NOEL, Moses Dogonyaro; AHMAD, Suleiman; UDUIMOH, Andrews Abstract: Malicious Command and Control (C2) traffic is a critical enabler of modern cyberattacks, allowing remote management of compromised systems. This paper presents a systematic literature review (SLR) of 14 primary studies published between 2014 and 2025, identified via a structured PRISMA process across six databases (IEEE, ACM, EEE Xplore, etc.). The review synthesizes six dominant C2 models—centralized, P2P, DGA, fast-flux, cloud abuse, and encrypted traffic—and evaluates detection methods including DNS entropy and machine learning. Results indicate that while detection accuracy for P2P and DGA has improved, encrypted traffic and cloud-based C2 remain significant blind spots. We identify a critical need for explainable AI (XAI) and metadata-based analysis. This review provides a roadmap for researchers and practitioners to develop more resilient, automated threat detection frameworks.

SYSTEMATIC LITERATURE REVIEW ON MALWARE DETECTION AND CLASSIFICATION: TYPES, PLATFORMS, MITIGATIONS, LIMITATIONS AND OPEN ISSUES

Sun, 01 Mar 2026 00:00:00 GMT

Title: SYSTEMATIC LITERATURE REVIEW ON MALWARE DETECTION AND CLASSIFICATION: TYPES, PLATFORMS, MITIGATIONS, LIMITATIONS AND OPEN ISSUES Authors: OJENIYI, Joseph Adebayo; NWODO, Benita Chikodili; IDRIS, Ismaila; FASOLA, Olusanjo Olugbemi; NOEL, Moses Dogonyaro; AHMAD, Suleiman Abstract: This paper presents a PRISMA 2020–compliant systematic literature review of malware detection and classification studies published between 2023 and 2026. It synthesizes research across malware types, computing platforms, feature representations, detection architectures, and mitigation strategies from major digital libraries. The review identifies a significant shift toward deep learning and transformer-based models, which outperform traditional machine learning in capturing complex behavioral and structural patterns. Graph-based methods improve semantic relationship modeling, while federated learning enables privacy-preserving collaborative detection. Despite these advances, critical challenges persist, including dataset bias, temporal concept drift, adversarial vulnerability, and weak cross-platform generalization. Many studies rely on static datasets and random splits, leading to inflated performance estimates that do not reflect real-world conditions. Explainability, deployment feasibility, and adversarial robustness remain insufficiently addressed, limiting operational adoption in SOC environments. This review proposes a unified taxonomy and future research agenda focused on robustness-aware evaluation, temporal benchmarking, cross-platform generalization, and deployment-ready, adversary-aware detection frameworks.