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  <title>DSpace Community: Journal Articles</title>
  <link rel="alternate" href="http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/1" />
  <subtitle>Journal Articles</subtitle>
  <id>http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/1</id>
  <updated>2026-07-11T00:34:58Z</updated>
  <dc:date>2026-07-11T00:34:58Z</dc:date>
  <entry>
    <title>Implementing Competency-Based Education and training in Technical Colleges: A Realistic Approach to Producing Skilled Workforce for Sustainable Industrial Development</title>
    <link rel="alternate" href="http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31809" />
    <author>
      <name>Eze, C. P.</name>
    </author>
    <author>
      <name>Mojekwu, O. E.</name>
    </author>
    <author>
      <name>Omeje, H. O.</name>
    </author>
    <author>
      <name>Igwe, C. O.</name>
    </author>
    <id>http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31809</id>
    <updated>2026-07-10T00:54:25Z</updated>
    <published>2021-01-01T00:00:00Z</published>
    <summary type="text">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.</summary>
    <dc:date>2021-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Effect of spice-treated sundried bovine rumen digesta  on performance, carcass characteristics and nutrient  digestibility of finisher broiler chickens</title>
    <link rel="alternate" href="http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31808" />
    <author>
      <name>Eniwaiye, Adenike A</name>
    </author>
    <author>
      <name>Otu, Bisong O.</name>
    </author>
    <author>
      <name>Kolo, Philip S.</name>
    </author>
    <author>
      <name>Owolabi, Shina J.</name>
    </author>
    <author>
      <name>Balogun, Muda A.</name>
    </author>
    <author>
      <name>Ochiyan, Michael A.</name>
    </author>
    <id>http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31808</id>
    <updated>2026-07-09T14:37:10Z</updated>
    <published>2023-04-01T00:00:00Z</published>
    <summary type="text">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 &#xD;
Rumen Digesta (SDBRD) on growth performance, carcass characteristics and nutrient digestibility of broiler chickens. A &#xD;
total of one hundred and fifty (150) day old broiler chickens were assigned to five (5) diets in triplicates containing ten (10) &#xD;
birds each in a completely randomized design. The diets were; T1, (control, 0% SDBRD), T2 (20% SDBRD without spice &#xD;
supplementation), T3 (20% SDBRD + 200 mg ginger), T4 (20% SDBRD + 200 mg garlic), and T5 (20% SDBRD + 200 mg &#xD;
thyme). Data were collected on growth performance, carcass characteristics and nutrient digestibility. The data were &#xD;
analysed using the Analysis of Variance (ANOVA) and differences among mean were separated with the Duncan Multiple &#xD;
range. The results showed that broiler chickens fed diets containing spices-supplemented SDBRD had significantly &#xD;
(p&lt;0.05) higher weight gain and better feed conversion ratio (FCR). The live weight and dressing percentage were &#xD;
significantly (p&lt;0.05) higher among birds fed spice-supplemented diets compared to the control and the un-supplemented &#xD;
SDBRD diet. However, digestibility for dry matter and crude protein was higher (p&lt;0.05) on T1 and T2 than on spice&#xD;
supplemented diets. It was concluded that the combination of sundried bovine rumen digesta and spices such as garlic, &#xD;
ginger and thyme improve growth performance, carcass characteristics and nutrient digestibility, and can therefore be &#xD;
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</summary>
    <dc:date>2023-04-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>SYSTEMATIC LITERATURE REVIEW ON MALICIOUS COMMAND AND CONTROL: TYPES, TECHNIQUES, TOOLS, CHALLENGES AND RESEARCH DIRECTIONS</title>
    <link rel="alternate" href="http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31807" />
    <author>
      <name>OJENIYI, Joseph Adebayo</name>
    </author>
    <author>
      <name>CEPHAS, Anyigor Chigbo</name>
    </author>
    <author>
      <name>SUBAIRU, Sikiru Olanrewaju</name>
    </author>
    <author>
      <name>NOEL, Moses Dogonyaro</name>
    </author>
    <author>
      <name>AHMAD, Suleiman</name>
    </author>
    <author>
      <name>UDUIMOH, Andrews</name>
    </author>
    <id>http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31807</id>
    <updated>2026-07-09T11:40:29Z</updated>
    <published>2026-03-01T00:00:00Z</published>
    <summary type="text">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,&#xD;
allowing remote management of compromised systems. This paper presents a systematic&#xD;
literature review (SLR) of 14 primary studies published between 2014 and 2025, identified via&#xD;
a structured PRISMA process across six databases (IEEE, ACM, EEE Xplore, etc.). The review&#xD;
synthesizes six dominant C2 models—centralized, P2P, DGA, fast-flux, cloud abuse, and&#xD;
encrypted traffic—and evaluates detection methods including DNS entropy and machine&#xD;
learning. Results indicate that while detection accuracy for P2P and DGA has improved,&#xD;
encrypted traffic and cloud-based C2 remain significant blind spots. We identify a critical need&#xD;
for explainable AI (XAI) and metadata-based analysis. This review provides a roadmap for&#xD;
researchers and practitioners to develop more resilient, automated threat detection&#xD;
frameworks.</summary>
    <dc:date>2026-03-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>SYSTEMATIC LITERATURE REVIEW ON MALWARE DETECTION AND CLASSIFICATION: TYPES, PLATFORMS, MITIGATIONS, LIMITATIONS AND OPEN ISSUES</title>
    <link rel="alternate" href="http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31806" />
    <author>
      <name>OJENIYI, Joseph Adebayo</name>
    </author>
    <author>
      <name>NWODO, Benita Chikodili</name>
    </author>
    <author>
      <name>IDRIS, Ismaila</name>
    </author>
    <author>
      <name>FASOLA, Olusanjo Olugbemi</name>
    </author>
    <author>
      <name>NOEL, Moses Dogonyaro</name>
    </author>
    <author>
      <name>AHMAD, Suleiman</name>
    </author>
    <id>http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31806</id>
    <updated>2026-07-09T11:29:15Z</updated>
    <published>2026-03-01T00:00:00Z</published>
    <summary type="text">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&#xD;
detection and classification studies published between 2023 and 2026. It synthesizes research&#xD;
across malware types, computing platforms, feature representations, detection architectures,&#xD;
and mitigation strategies from major digital libraries. The review identifies a significant shift&#xD;
toward deep learning and transformer-based models, which outperform traditional machine&#xD;
learning in capturing complex behavioral and structural patterns. Graph-based methods&#xD;
improve semantic relationship modeling, while federated learning enables privacy-preserving&#xD;
collaborative detection. Despite these advances, critical challenges persist, including dataset&#xD;
bias, temporal concept drift, adversarial vulnerability, and weak cross-platform generalization.&#xD;
Many studies rely on static datasets and random splits, leading to inflated performance&#xD;
estimates that do not reflect real-world conditions. Explainability, deployment feasibility, and&#xD;
adversarial robustness remain insufficiently addressed, limiting operational adoption in SOC&#xD;
environments. This review proposes a unified taxonomy and future research agenda focused&#xD;
on robustness-aware evaluation, temporal benchmarking, cross-platform generalization, and&#xD;
deployment-ready, adversary-aware detection frameworks.</summary>
    <dc:date>2026-03-01T00:00:00Z</dc:date>
  </entry>
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