MATHEMATICAL MODELLING AND OPTIMIZATION OF ORE EXTRACTION PROCESSES IN MINING ENGINEERING
Micho Vanoh, School of Mathematics and Computer Science, Papua New Guinea University of Technology, Lae, Morobe Province, Papua New Guinea.
John Lanta, School of Mathematics and Computer Science, Papua New Guinea University of Technology, Lae, Morobe Province, Papua New Guinea.
Raymond Kuna, School of Mathematics and Computer Science, Papua New Guinea University of Technology, Lae, Morobe Province, Papua New Guinea.
Mohsen Aghaeiboorkheili, School of Mathematics and Computer Science, Papua New Guinea University of Technology, Lae, Morobe Province, Papua New Guinea.
MSI Journal of AI and Technology | https://zenodo.org/records/20567576 | Page 01 to 13
Abstract
In this study we show a mathematical model in mining systems for the processes of ore extraction in relation to mining industries in Papua New Guinea. Major mining operations such as Ok Tedi Mine, Porgera Gold Mine and Newmont Lihir Gold Mine have over decades produced sustainable quantities of gold and copper with contributing more than 70% of Papua New Guinea’s export earnings in the recent years (Githiria, 2019). Regardless of this importance in economy, mining operations are affected frequently by variables such as equipment efficiency, reserve quantity, extraction rate and stochastic randomness that are a result of geological uncertainties are all integrated in the model. To optimize and predict the rate of ore extraction under geological and operational constraints we aim to develop a framework.
We formulate a system of differential equations to represent the depletion of ore over time (Øksendal, 2003) (Ross, 2014) and an additional stochastic component is then introduced to cater for random events in mining operations (Øksendal, 2003). Numerical simulations are conducted using Excel, to analyze system behavior under different extraction strategies, using an initial ore reserve of 1000 units with k=0.3, be the extraction coefficient. The deterministic model showed that from 1000 units the ore reserve went down exponentially to roughly 50 units after a span of 10 years. Whereas a fluctuating pattern was produced by the stochastic model with non-uniform ore quantities between 120 and 820 units which is due to the effect of uncertainty. By comparing aggressive, balanced and slow extraction strategies, the optimization simulation shows that the highest cumulative profit of K7710.00 was generated while extending the mine lifespan by more than 40% through the balanced extraction policy compared to the aggressive and slow extraction policy.
Findings indicate that optimal and well-designed extraction policies can improve recourse usage substantially while at the same time minimize operational cost (MacNeil & Dimitrakopoulos, 2017). The model illustrates that uncontrolled extraction leads to rapid depletion, on the contrary, sustainability is enhanced through controlled strategies.
This study enhances the role of applied mathematics in mining engineering by presenting a quantitative framework for making of decisions in ore extraction. The model can be calibrated using real data in mining to improve planning and operational efficiency in Papua New Guinea.
Keywords: Sustainable mining; Stochastic Differential Models; Exponential Decay; Depletion; Randomness; ore extraction; Mining in Papua New Guinea.
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INVESTIGATION AND IMPROVEMENT ON THE EARTH RESISTANCE OF THE POWER SUBSTATION IN AMBROSE ALLI UNIVERSITY, EKPOMA NIGERIA
IYERE SUNDAY FIDELIS, Department of Electrical and Electronic Engineering Ambrose Alli University, Ekpoma Edo State, Nigeria.
ODIA HOPE EHIMARE, Department of Electrical and Electronic Engineering Ambrose Alli University, Ekpoma Edo State, Nigeria.
MSI Journal of AI and Technology | https://zenodo.org/records/20280663 | Page 01 to 22
Abstract
Earthing of electrical appliances, installations and machinery is required to avoid the risk of electric shock to personnel as a damage to equipment. This is achieved by connecting the appliances or machinery through earth electrodes to the earth mass and connecting the electrodes together through low resistance conductors. In this project the earthing system of Ambrose Alli University 1000kVA MIKANO generator located in the power station was evaluated, Its earthing resistance was measured using Kyoritsu digital earth tester, It was discovered that the existing earthing system of the generator has degraded, which can endanger the life of the operating personnel and the generator. The earth resistance measured was 529 ohms thus, necessitating remediation measures. A pit 5 feet long, 3feet wide and 8 feet deep was excavated to place the earth electrode and earth mat. The earth mat was buried and galvanized earth rods of 6 fit with diameter of 32mm were driven into the ground at equidistant from each other. The pit was watered to increase the moisture content of the soil thereby enhancing its conductivity. The soil was treated with charcoal, magnesium sulfate salt, cow dung, poultry droppings. The combination of these materials enhanced conductivity of the earth electrode in the area around the earthing system. The mixture can also serves as an anti-corrosive agent, thereby ensuring longer life of the earth conductor owing to the fact that coal absorbs water and keeps the soil wet. Furthermore, coal is made up of carbon which is a good conductor, hence it minimizes earth resistance. Salt helps in forming electrolyte which increases the conductivity between the earth rod and ground. The resistance value was measured using a digital earth resistance tester. However, earthing resistance values varies with the time of the year; it is high during the dry season and low during rainy season. Lastly, the value of the earth resistance depends largely on the type and resistivity of soil. The measured minimum earth resistance of 10 ohms was used as a standard to evaluate the earthing resistances of the generator because of the high resistivity of the selected site.
Keywords: Earth, Electrode, Soil, Resistance, Continuity, Conductor, Lead
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Artificial Intelligence for public sector Governance: Implications for Monitoring and Evaluation and Policy Reform”
Dr. Addi Juma Faki, Zanzibar Planning Commission Zanzibar, Tanzania.
MSI Journal of AI and Technology | https://zenodo.org/records/19892337 | Page 01 to 25
Abstract
This review synthesizes research on “Application of AI in developing countries like Zanzibar, new roles for M&E professionals, and necessary policy reforms” to address the gap between AI’s potential and practical implementation in low-resource contexts. The review aimed to evaluate AI applications and challenges in Zanzibar’s context, benchmark AI-enhanced M&E methodologies, identify evolving M&E roles, analyze necessary policy reforms, and compare relevant case studies. A systematic analysis of multidisciplinary literature encompassing empirical studies, case reports, and policy analyses was conducted, focusing on African and island developing states. Findings reveal that AI significantly advances socio-economic development and public service delivery but is constrained by infrastructural deficits and digital literacy gaps. M&E professionals require new competencies in data science, ethical governance, and participatory approaches to manage AI integration effectively. Comprehensive, adaptable policy frameworks emphasizing capacity building, ethical safeguards, and inclusive governance are critical yet under-implemented in Zanzibar and similar settings. Ethical and capacity challenges, including data privacy and algorithmic bias, persist without robust operational frameworks. Collectively, these findings underscore the \
transformative potential of AI contingent on context-specific capacity building and policy reforms. The review highlights the necessity for inclusive, evidence-based governance models to ensure equitable AI adoption and sustainable development outcomes in developing countries.
Keywords: Artificial Intelligence, Monitoring and Evaluation, Data-Driven Decision Making, Socio-Technical Systems, Policy Reform
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EPISTEMOLOGY IN THE DIGITAL AGE: THE IMPACT OF INFORMATION TECHNOLOGY ON KNOWLEDGE
Obidike Charles Paul Chikelo, Department of Social Sciences School of General Studies Federal Polytechnic, Oko Anambra State, Nigeria.
Rev. Fr. Prof Samuel I. Nnoruka, Department of Philosophy Chukwemeka Odimegwu Ojukwu University, Igbariam Campus.
MSI Journal of AI and Technology | https://zenodo.org/records/19808991 | Page 01 to 20
Abstract
The digital age has transformed the conditions under which knowledge is produced, transmitted, validated, and contested. While information technologies promise unprecedented access to data and expanded epistemic participation, they also generate new challenges concerning credibility, authority, and the fragmentation of shared meaning. The central problem this article addresses is the epistemic instability produced by digital environments in which traditional mechanisms of knowledge validation such as expertise, communal verification, and institutional accountability are increasingly displaced by algorithmic curation, user-generated content, and rapid information diffusion. This epistemic shift raises fundamental questions regarding how knowledge is distinguished from misinformation, how trust is negotiated in digital spaces, and how human cognitive practices adapt under technological saturation. Employing a qualitative, interdisciplinary methodology that integrates philosophical analysis, media theory, and recent empirical studies in digital cognition, the article investigates how the structures of knowing are reshaped by networked technologies. It examines the epistemic implications of algorithmic bias, information overload, participatory media, and the decline of epistemic gatekeeping. It also evaluates how digital platforms alter the relationships among knower, knowledge-source, and knowledge-community. The findings reveal that digital technology neither democratises knowledge unconditionally nor destroys epistemic authority entirely. Instead, it creates a hybrid epistemic environment characterised by fluid authority, intensified contestation, and new forms of verification that rely on collective intelligence, technological mediation, and hybrid human–machine judgement. The study argues that understanding epistemology in the digital age requires rethinking classical epistemic categories such as justification, testimony, and expertise, and proposes an adapted system for sustaining reliable knowledge in technologically saturated societies.
Keywords: Epistemology; Digital Age; Information Technology; Knowledge Validation; Algorithmic Mediation
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A Sociological Analysis of Digital Health Technologies and Workforce Dynamics in Nigerian Healthcare Institutions
Edime YUNUSA, Department of Sociology, Faculty of Social Sciences, Prince Abubakar Audu University, Anyigba Kogi State – Nigeria.
Ejuchegahi Anthony ANGWAOMAODOKO, Department of Sociology, Faculty of Social Sciences, Prince Abubakar Audu University, Anyigba Kogi State – Nigeria.
Timothy Abayomi ATOYEBI, Ph. D, Department of Sociology, Faculty of Social Sciences, Prince Abubakar Audu University, Anyigba Kogi State – Nigeria.
MSI Journal of AI and Technology | https://zenodo.org/records/19642984 | Page 01 to 26
Abstract
This paper examined the growing integration of digital technologies into healthcare systems and its implications for the organization of work and professional relations, focusing on a sociological analysis of digital health technologies and workforce dynamics in Nigerian healthcare institutions. The paper was guided by four specific objectives exploring how digital health technologies shape work organization, assessed, the influence of digital health technologies on the roles, skills, and professional interactions of healthcare workers, identified associated challenges, and assessed their effects on workforce efficiency, job satisfaction, and institutional performance. Sociotechnical Systems Theory was adopted to explain the interdependence between technological innovations and social structures within healthcare settings. Analytical approach was employed, drawing on recent empirical literature and documented evidence from Nigerian healthcare institutions to interrogate patterns of digital health adoption and workforce transformation. The paper revealed that digital health technologies are restructuring clinical workflows through standardization and redistribution of tasks, while also redefining professional roles by requiring new digital competencies and fostering hybrid forms of practice. The paper further identified persistent challenges, including infrastructural deficits, limited digital literacy, financial constraints, and resistance to technological change among others, which constrain effective implementation. It also showed that while digital systems enhance efficiency and data management, their impact on job satisfaction and institutional performance remained uneven due to identified challenges. The paper concluded that the outcomes of digital health integration depend largely on the alignment between technological systems and the social organization of healthcare institutions. The paper recommended sustained investment in infrastructure, continuous workforce training, participatory implementation strategies, and the development of robust regulatory frameworks to support effective digital transformation.
Keywords: Digital Health Technologies, Workforce Dynamics, Healthcare Institutions, Sociotechnical systems, Nigeria.
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STRATEGIC MANAGEMENT OF GENERATIVE AI IN INSTITUTIONS OF HIGHER LEARNING: BALANCING INNOVATION AND ACADEMIC INTEGRITY
Oladele Olubukola Olabode, Ph. D, The Nigerian Baptist Theological Seminary, Ogbomoso.
MSI Journal of AI and Technology | https://zenodo.org/records/19450104 | Page 01 to 21
Abstract
Institutions of higher learning have traditionally served as centers of knowledge creation, intellectual inquiry, and character formation. The advent of generative artificial intelligence (AI) represents a paradigm shift in higher education, as these systems can independently produce essays, research summaries, programming scripts, and problem-solving frameworks, transforming traditional academic work. This rapid technological diffusion has generated institutional tensions, including faculty concerns over plagiarism and academic integrity, student dependence on AI for coursework, and administrative uncertainty in policy formulation and enforcement. Ethical questions regarding authorship, originality, and the boundary between human creativity and machine assistance further complicate the landscape. This paper argues that universities must adopt deliberate strategic frameworks for AI governance, integrating policy design, leadership foresight, risk management, and ethical oversight. By implementing intentional and adaptive governance structures, higher education institutions can harness the innovative potential of generative AI while preserving academic integrity and authentic learning.
Keywords: Strategic Management, Generative AI, Institutions of Higher Learning, Innovation and Academic Integrity.
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Cyber Security Threats and Risk Management in Modern Information Technology
Muhammad Faisal Nawaz, School of Computer Science, Jiangsu University, China.
Muhammad Hasnain, University of Agriculture, Pakistan.
MSI Journal of AI and Technology | https://zenodo.org/records/19382148 | Page 01 to 17
Abstract
The pervasive integration of information technology (IT) into the fabric of modern society, from critical national infrastructure to personal consumer devices, has created an expanded and complex digital landscape. This digital transformation, while driving unprecedented innovation and efficiency, has concurrently introduced a sophisticated and evolving array of cyber security threats. This research article provides a comprehensive analysis of the contemporary cyber security threat landscape and evaluates the corresponding frameworks for risk management within modern IT environments. The study begins with an examination of the evolution of threats, moving from simple malware to advanced persistent threats (APTs), ransomware-as-a-service (RaaS), supply chain attacks, and the emerging risks associated with artificial intelligence (AI) and the Internet of Things (IoT). Through a systematic literature review, this paper synthesizes existing academic and industry knowledge on threat vectors, vulnerability management, and the principles of risk assessment. The methodology section outlines a qualitative approach, leveraging case study analysis of major security incidents and a critical review of established risk management frameworks, including the NIST Cybersecurity Framework (CSF) and ISO/IEC 27001. The results and discussion section presents key findings, highlighting a significant gap between the rapid proliferation of threats and the often-siloed, reactive nature of traditional risk management practices. It argues for a paradigm shift towards a proactive, continuous, and integrated risk management strategy that embeds security into the DevOps lifecycle (DevSecOps) and leverages predictive analytics. The article concludes that effective cyber security in the modern era is not merely a technical challenge but a fundamental business risk that requires strategic alignment, continuous adaptation, and a culture of shared responsibility to ensure organizational resilience.
Keywords: Cyber Security, Risk Management, Threat Landscape, Advanced Persistent Threats, Ransomware, Supply Chain Attacks, NIST Cybersecurity Framework, DevSecOps.
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AI - AUGMENTED LEADERSHIP AND EMOTIONAL INTELLIGENCE MODELLING IN AFRICAN INDUSTRIAL SETTING
Yahaya Segun ALILU, Ph. D, Department of Political Science, Faculty of Social Sciences, Prince Abubakar Audu University, Anyigba, Kogi State – Nigeria.
Timothy Abayomi Atoyebi, Ph. D, Department of Sociology, Faculty of Social Sciences, Prince Abubakar Audu University, Anyigba, Kogi State – Nigeria.
Edime YUNUSA, Department of Sociology, Faculty of Social Sciences, Prince Abubakar Audu University, Anyigba, Kogi State – Nigeria.
MSI Journal of AI and Technology | https://zenodo.org/records/19371541 | Page 01 to 30
Abstract
The accelerating convergence of Artificial Intelligence (AI) and organizational leadership is reshaping productivity across industries, yet African contexts remain insufficiently theorized, particularly regarding the integration of AI with human-centred leadership constructs. This paper examined the interface between AI-augmented leadership and Emotional Intelligence (EI) in driving adaptive performance and sustainable competitiveness in African industries. It advances a context-sensitive integrative framework that explains how the synergy between AI capabilities and EI competencies enhances leadership effectiveness. To achieve this aim, the paper evaluated the extent to which AI-augmented analytics improves leaders’ decision-making processes, examined the interaction between EI and AI systems in shaping organizational performance, and developed a framework for implementing AI-augmented emotionally intelligent leadership within African settings. The paper was anchored on Transformational Leadership Theory and Goleman’s Emotional Intelligence framework, offering a dual perspective that integrates technological augmentation with relational competencies. Methodologically, a systematic analytical review approach was adopted, drawing on secondary data to synthesize existing empirical and conceptual insights. Findings indicated that leaders who effectively integrate AI into their practices while demonstrating high EI exhibit greater adaptability, reduced organizational conflict, and improved employee engagement. These outcomes highlight the complementary relationship between AI-driven analytics and emotionally intelligent leadership. The paper concluded that AI is unlikely to replace human leadership; rather, when strategically integrated, it enhances leaders’ effectiveness and emotional capacity. The paper recommended among others that African organizations should institutionalize leadership development programmes that combine AI literacy with emotional intelligence to support data-driven and human-centred decision-making.
Keywords: Artificial Intelligence, Emotional Intelligence, AI-Augmented Leadership in African Industries, Organizational Performance.
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