School-wide publications

Permanent URI for this collectionhttps://dspace.njala.edu.sl/handle/20.500.144402/182

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Start date: 2020

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    How Should Public Health Officials Respond When Important Local Rituals Increase Risk of Contagion?
    (American Medical Association, 2020) Mokuwa, Esther
    During the 2014-2015 Ebola epidemic in Sierra Leone, people were required by law to call a trained "safe burial" team to dispose of the body of a person who had died from Ebola. It took days for a team to arrive, however, due to limited resources and rural travel obstacles, so some villagers felt obliged to bury their loved ones themselves. Even with timely arrival of a team, there can be cultural priorities that deserve attention. One man's case discussed in this article suggests the need for Ebola responders to consider villagers' perspectives and possibilities for compromise.
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    Statistical Analysis on the Relationship Between Exports and Economic Growth in Sierra Leone (1990-2019)
    (Science Publishing Group, 2021) Turay, Matthew James
    In order to boost up the economic growth of any country, Exports should be considered as key factor as it contributes immensely in which Sierra Leone as a nation is no exception. Therefore, this research paper target to investigate the effect of export on the economic growth of Sierra Leone using time series data of exports and the gross domestic products ranging from 1990- 2019 which was source from the World Bank Indicators. In order to accomplish the aim of this paper, descriptive statistics, regression, correlation, Augmented Dickey- Fuller Unit root test, Johansen cointegration test, Vector Auto regression model, diagnostic test and the Pair- wise Granger causality test were the tools used to analyze the data. Based on the results from both regression analysis, it can be seen that export has a significant positive effect on the economic growth of Sierra Leone. Augmented Dickey-Fuller unit root test results shows existence of stationarity at first difference was detected, while the cointegration test results revealed that, there is no relationship between the exports and economic growth. However, the Vector Auto regressive model test revealed that, exports have a significant effect on the economic growth as well. Granger causality test, shows that both exports influence the Gross Domestic Product of Sierra leone.
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    Review of Knowledge Management in Optical Networks, Lambda Architecture using Database Technologies in Cloud Settings
    (International Journal of Scientific and Research Publications, 2021-08-24) Fofanah, Abdul Joseph
    In this paper, we present concepts, theories, and overview of knowledge management in an autonomous optical networks and Lamba Architecture in cloud related environment.This study presents some illustrative cases that has been used to illustrate the potential application of KM architecture and to evaluate the various policies for the knowledge sharing and integration algorithm.Here the knowledge is used at the optical transponder system level, sharing, and integration implemented at the node level and supervising and data analytics (SDA) controller level.The KM process has been evaluated by integrating on a metro-network situation in terms of model error convergence time and the data shared among agents.Indeed, the propagation and reinforcement actions illustrated by similar convergence time than data-based policies at various phases of the network learning process without compromising the convergence accuracy of the model prediction.The Lambda Architecture is the new model for Big Data and database research focus, that helps in data processing with a balance on throughput, latency, and fault-tolerance.To provide a complete solution and better accuracy, low latency, and high throughput, there exists no single tool.This introduced the idea to use a set of tools and methods to build a comprehensive Big Data approach.Although this paper does not provide a developed and working tool, however, provides an outline and the methods used by researchers to overcome some of the shortcomings of Lambda Architecture.The Lambda Architecture defines a set of layers to fit in a set of tools and methods rightly for constructing a comprehensive Big Data scheme: Speed Layer, Serving Layer, Batch Layer.Each layer satisfies a set of features and builds upon the functionality delivered by the layers beneath it.The Batch Layer is the place where the master dataset is warehoused, which is an unchangeable and add-only set of raw data.Also, the batch layer computes before the results using a distributed processing system like Hadoop, Apache Spark that can manage large amounts of data.The Speed Layer encapsulates new data coming in real-time and processes it.The Serving Layer comprises a parallel processing query steam engine, that takes results from both Batch and Speed Layers and responds to questions and requests in real-time with low latency.Stack Overflow is a Question-and-Answer forum with an enormous user community, millions of posts with rapid growth over the years.
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    Adoption of Technology-Driven Solutions Built on Strategic Decision Theories for Instructing Graduate Students in Applied Quantitative and Information Disciplines
    (2021-01-02) Sesay, Ibrahim
    This study investigates the adoption of technology-driven instructional solutions grounded in strategic decision theories for graduate education in applied quantitative and information disciplines. The increasing complexity of modern data-centric fields such as applied mathematics, data science, and information systems has necessitated the integration of advanced pedagogical technologies that are not only computationally sophisticated but also strategically aligned with institutional decision-making frameworks. This research proposes a conceptual and operational model that integrates strategic decision theories, including bounded rationality, game theory, and multi-criteria decision-making, with educational technologies such as adaptive learning platforms, intelligent tutoring systems, and analytics-driven instructional design. A structured mixed-methods approach is adopted, combining theoretical synthesis, system design modeling, and pedagogical analysis. The study explores how strategic decision frameworks influence the deployment, optimization, and effectiveness of educational technologies in graduate-level instruction. Findings suggest that aligning instructional technologies with structured decision models significantly improves learning efficiency, conceptual mastery, and student engagement in computationally intensive disciplines. Furthermore, the integration of decision-theoretic principles enhances institutional adaptability in curriculum design and resource allocation. The study also highlights the role of data-driven feedback loops in optimizing teaching strategies and improving learner outcomes. It demonstrates that strategic alignment between educational technologies and decision sciences creates a robust ecosystem for graduate education that is both adaptive and scalable. The research contributes to the growing body of literature on intelligent education systems by positioning strategic decision theory as a foundational framework for instructional innovation in higher education.
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    Adaptive Neuro-Fuzzy Inference System with Non-Linear Regression Model for Online Learning Framework
    (RELX Group (Netherlands), 2021-10-01) Fofanah, Abdul Joseph
    In this paper, we present a combined hybrid of an adaptive neuro-fuzzy inference system with an adaptive online learning model (ANFISAOLM) using a non-linear regression machine learning technique to construct the Neural Network. We proposed ANFIS-AOLM for learning by modeling and controlling imprecise defined, uncertainty system with a significant role of the neuro-fuzzy method. The various simulation exercise was conducted with define input and output values, define rules and the dataset was created and trained the Neural Network. Exploration of the dataset was tested for ANFIS-I using “Grid Partitioning”; ANFIS-II using “Subtractive Clustering”; and ANFIS-III using “Fuzzy Clustering Means”. The study was conducted in order to explore the effectiveness of the combined hybrid learning opportunities using ANFIS and Non-linear Regression models. The study was experimented using MATLAB programming language for the adaptation of the online learning framework with learner’s capability to learn from the existing information and adapt accordingly in the learning environment. The results obtained from the analysis shows that with a membership function of 20 and 25 an average of 97.7% accuracy was achieved. However, as the number of membership functions increases the better the performance of the ANFIS and the higher the computational response time. The non-linear regression model also indicated that the relationship of the ANFIS system and the proposed technique is adequate for learner’s adaptation and the decision made through learning mechanism.
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    Experimental Exploration of Evolutionary Algorithms and their Applications in Complex Problems: Genetic Algorithm and Particle Swarm Optimization Algorithm
    (2023-04-18) Fofanah, Abdul Joseph
    The primary aim of this study was to experiment and compare the empirical evidence of evolutionary algorithms and their applications using the Genetic Algorithm (GA) and Particle Swamp Optimization (PSO) algorithm. The objectives of the study included reviewing recent scholarly scientific research papers and practices, and algorithms with existing genetic algorithm techniques, identifying the need for lessons learned and leveraging best health practices garnered from the existing problems of optimization, reviewing and identifying the technological tools used in the healthcare domain, algorithms, and the effectiveness of GA and PSO techniques and to develop and analyse GA algorithms using datasets to predict and determine which of the two algorithms performs better. Evolutionary algorithms which are normally viewed as components of both evolutionary computing and bio-inspired computing use mechanisms inspired by nature and are indeed capable of solving problems through processes that emulate the behaviours of living organisms. Genetic algorithms (GAs), evolution strategies (ESs), differential evolution (DE), and particle swarm optimization (PSO) are typical examples. Therefore, evolutionary algorithms are typically used to provide good, estimated solutions to problems that cannot be solved easily using other techniques, and as such numerous optimization problems fall into this category. This work aims to provide a systematic evaluation of the literature on contemporary PSO methods for knowledge discovery in the area of illness detection. Although the major objective is to present recommendations for future enhancement and development in this field, the systematic analysis reveals the possible study topics of PSO techniques as well as the research gaps. The essential ideas, theoretical underpinnings, and traditional application domains are covered in this study. It is fervently anticipated that the findings will help researchers to thoroughly examine PSO algorithms for disease diagnosis. According to the current state of PSO strategies in healthcare, several difficulties that can be taken on to advance the sector are mentioned.
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    Personalized learning through artificial intelligence: Revolutionizing education
    (GSC Online Press, 2024-12-20) Dumbuya, Emmanuel
    Personalized learning, powered by Artificial Intelligence (AI), is reshaping education by addressing diverse student needs, bridging learning gaps, and enhancing academic outcomes. This paper explores how AI technologies, such as adaptive learning platforms, predictive analytics, and intelligent tutoring systems, contribute to more equitable and efficient education. Emphasizing the potential of inclusive access to AI tools, it highlights the role of technology in democratizing education globally. The research concludes with recommendations for integrating AI into educational practices to ensure broad, equitable impacts. This paper examines the applications, benefits, and challenges of AI-driven personalized learning systems and proposes strategies for their effective integration into educational frameworks.
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    Exploring the Landscape of Open Access Fibre Optic Cable Network in Sierra Leone
    (RELX Group (Netherlands), 2024) Monson, Fred Konneh Songa