Volume 11, Issue 9, September 2023 Edition - GSJ Journal Publication

[1]  [2]  [3]  [4]  [5]  [6]  [7]  [8]

ENERGY COST MINIMIZATION STRATEGIES IN CLOUD DATA CENTERS []


Cloud data centers play a pivotal role in modern computing, providing scalable and efficient infrastructure for a wide range of applications. However, the rapid growth of data centers has raised concerns about their environmental impact and operational costs. This research addresses the critical issue of energy consumption and cost optimization in cloud data centers through the application of Artificial Intelligence and Machine Learning (AI/ML) techniques. The central problem addressed in this study is the substantial energy consumption of data centers, which results in high operational costs and environmental consequences. To mitigate this challenge, we employ AI/ML algorithms to optimize the allocation of computational resources, cooling systems, and workload scheduling. Our methodology involves data collection, preprocessing, and the application of various AI/ML techniques, including predictive analytics, reinforcement learning, and optimization algorithms. Key findings of this research reveal significant reductions in energy consumption and associated costs within cloud data centers. Through the implementation of AI/ML-driven strategies, we achieved an average energy cost reduction of 30%, resulting in substantial financial savings for data center operators. Moreover, our approach enhances the sustainability of data center operations, contributing to reduced carbon emissions and improved environmental stewardship. The implications of this study extend to both the economic and ecological aspects of cloud data center management. By demonstrating the effectiveness of AI/ML techniques in energy cost minimization, this research offers valuable insights for industry practitioners and policymakers seeking to enhance the efficiency and sustainability of cloud computing infrastructure. The findings underscore the potential for AI/ML to drive transformative changes in data center operations, reducing their carbon footprint and aligning them with the principles of green computing. In conclusion, this research presents a promising pathway to address the growing challenges of energy consumption and cost management in cloud data centers. The application of AI/ML techniques provides a robust framework for achieving significant reductions in energy costs while advancing sustainability goals. As the demand for cloud computing continues to surge, the insights from this study are vital for creating more efficient and environmentally responsible data center ecosystems.

ANALYSIS OF DEMAND AND ACCESS TO CREDIT AMONG SMALL AND MEDIUM SCALE AGRIBUSINESS ENTERPRISES IN ABIA, STATE, NIGERIA []


The study analyzed the demand and anccess to credit among Small and Medium Scale agribusiness enterprises in Abia State, Nigeria. Multi- stage random sampling techniques were employed to select 120 respondents in the state. Primary data were collected with the use of well-stuctured questionnaires through the aid of enumerators. Relevant descriptive and inferential statistics such as frequencies, percentages, means and standard deviation. Hackman double hurdle model regression were used for data analysis. The results showed that a good proportion (52.50%) of the agribusiness small and medium scale operators in the study area were male with mean ages of 50years. Majority of the respondents were married (63.33%), while about (96.7%) were literate having acquired one level of education or the other. On avearage, the agribusiness operators have spent about 19 years in business. About 68.3% of them belong to cooperative society. The mean income of the respondents were #201,666.67% for an average small and medium scale operator. The results showed that the respondents obtained their credit from both formal and informal sources, with majority (53.33%) from informal sources, (46.67%) were from formal source. Also, majority (90.83%) demanded for short- time credit, while the mean and standard deviation of credit demanded were #199,916.67 and #103,601.10 respectively for an average small and medium scale operators. The Hackman double stage model showed that interest amount, years of education, experience, Enterprise' age, income and membership of association of the agribusiness operators were significant determinants of volume of credt. Result on performance of the agribusiness small and medium scale enterprises showed a total revenue and net profit were #201,166.67 and #35,814.54. Furthermore, simple linear regression mode on effect of demand of crediti on performance of small and medium scale enterprises showed there was a positive relationship between performance and credit access. Also result further showed that major constraints of credit access were burdensome collaterals (X=4.10), instability in government policy (X=4.02) and long protocols (X= 3.95). The study therefore recommend that policy should also focus on ways to attract and encourage not only experienced but younger people willing in agribusiness small and medium scale enterprises, who are agile and strong in business drive through of credit to them, this group of operators would be able to put in a lot at raising the current level of performance.

A systematic review []


The occurrence of illnesses often requires the implementation of measures to control their spread, such, as quarantine. However long periods of quarantine can have an impact on people well-being. In this study, we examine the consequences on health that arise from quarantine in Ihiagwa, Owerri, a region located in southeastern Nigeria. Our research focuses on peer-reviewed studies, scientific reports, and relevant documents published between 2019 and 2023. We conducted a search across electronic databases and identified 25 studies that were relevant to our investigation. After screening and quality assessment we selected 12 studies for analysis. The findings indicate that extended periods of quarantine in Ihiagwa Owerri resulted in health challenges for the individuals involved. These challenges encompassed levels of stress, anxiety, depression well as feelings of isolation and loneliness. We also identified contributing factors including access to healthcare services, fear of infection financial difficulties, and uncertainty regarding the duration of the pandemic. This systematic review emphasizes the need for targeted interventions and support for health during prolonged periods of quarantine, in Ihiagwa, Owerri, and similar regions. It is crucial, for policymakers and healthcare authorities to give importance to the implementation of mental health programs. These programs will play a role in reducing the psychological effects caused by quarantine measures and will ensure the overall well-being of the population during public health emergencies. Additionally, there is a need for research to investigate interventions that align, with different cultures and assess long-term mental health outcomes in such situations.

Strategic Talent Management in the Digital Age: Leveraging Technology for Effective HR Strategies []


This study examines the relationship between Strategic Talent Management and the digital age, considering the rapid technological advancements, changing workforce dynamics, and increased market competition of the current era. The study revealed how technology has fundamentally transformed and enhanced HR strategies related to talent acquisition, development, and retention. This study aimed to identify the fundamental principles and components of Strategic Talent Management in the context of the contemporary digital environment. The findings indicated a significant change from traditional methods, introducing comprehensive strategies that prioritize ongoing learning and adaptability in organizational culture. Additionally, the notion of talent mobility has emerged as a crucial aspect that enables organizational agility through the lateral movement of employees. The investigation subsequently explored the transformative impact of technology on HR strategies. AI-driven recruitment platforms have improved talent acquisition by streamlining processes and utilizing data analytics, resulting in enhanced operational efficiency and decision-making. Talent development has incorporated technology through the utilization of e-learning platforms and AI-driven systems, which provide customized and readily available learning experiences. Technology has played a significant role in promoting employee engagement by facilitating a sense of belonging and providing immediate recognition, thereby improving the overall workplace atmosphere. The advantages and difficulties related to the integration of technology were thoroughly examined. The potential of technology to generate data-driven insights has been emphasized, leading to a transformative impact on decision-making processes. The study recognized the simultaneous concerns regarding data privacy and security, emphasizing the importance of adhering to regulations. This study yielded valuable practical insights and recommendations. Organizations were advised to invest in continuous learning platforms to enhance the skills and knowledge of their workforce through upskilling and reskilling initiatives. Strict data security and compliance measures were emphasized as crucial for utilizing technology in talent management. In conclusion, this study highlights the importance of effectively incorporating technology into HR strategies for organizations aiming to gain a competitive edge in the digital era. Organizations can achieve sustained success and adapt to the global business landscape by effectively managing talent.

KNOWLEDGE MANAGEMENT AND EMPLOYEE PERFORMANCE IN MANUFACTURING COMPANIES IN RWANDA: EVIDENCE FROM CIMERWA PLC []


This study aims to determine the relationship between knowledge management and worker performance in Rwandan manufacturing firms. In order to gather information for this study, the researcher used questionnaires. The sample size was 151 respondents, which was deemed to be representative of the entire population. The target populations were 244. To gather all the information required for this study, the researcher used primary and secondary data. After running the data through the Statistical Package for Social Sciences, the data was then analysed using descriptive and inferential statistics. Regression results indicated that the adjusted R2 is 0.600 representing 60.0%, indicating that Knowledge management components contribute 60.0% to the task accomplishment, while 0.400 representing 40.0% remaining comes from other variables that are not included in the model one. From ANOVA Table 24, the F- test of 29.482 is statistically significant with p < 0.05 indicating that the variables used in the model are good predictors of task accomplishment. Therefore, H01 which states that Knowledge management has no significant impact on task accomplishment at CIMERWA Plc; is not accepted at all levels of significance.

The role of Home-based Communication on increase knowledge and practice regarding Utilization of Long-Lasting Mosquito Nets, Khartoum State, Sudan (2016 - 2018) []


Background: In the absence of a vaccine or effective and sustainable means of vector control, use of LLINs is an effective way to limit vector borne diseases. Objectives: The study aimed to assess the role of home-based communication in improving Knowledge and practice of nets owners and hence the LLINs utilization compared with the currently used BCC approaches in 2016 – 2018 in Khartoum state. Materials and methods: A community based quasi-interventional study that utilized both pre and post design, and case – control study design study was conducted in four villages two served as intervention in Bahri Locality and the other two were selected as a control villages in Omdurman Locality. A multistage random sampling technique was used in selecting the required samples for this study and a semi- structured questionnaire was used to collect required information. The intervention composed of home-based communication includes messages and printable materials about the LLINs importance adapted from the national malaria control as well as distributing LLINs and training the community on hanging LLINs.A total of 1250 participants were deployed and divided equally between both the experimental and control groups and were followed up for a period of one year with interval every 3 months. Results: There were no significant differences observed between the intervention and control groups concerning socio-demographic characteristics such as age, occupation and education level except for family monthly income, p-value > 0.05.The knowledge score about LLINs in the intervention villages was significantly increased for good knowledge in the dry season and wet season p-value= (0.001). This is most probably attributed to the four quarterly based follow-up visits, home based communication method has significant impact affecting bed net use compared to routine behavioral change communication (BCC) and It have great role in promoting the proper use and utilization of LLINs in the study villages during dry and wet season. Conclusion: The home-based communication is appearing effective in increase knowledge regarding utilization of nets. Therefore, it is suggested that there is a need to adopt by National Malaria Control Programme home-based communication during and after bed nets campaigns to enhance maximum utilization of LLINs. The study recommended adopting home-based BCC during and after LLINs campaigns and to a conduct more researches. Keywords: home based communication, knowledge, Khartoum state

An Empirical Study on SMEs Growth and Sustainability: A Case Study in Oman []


Purpose - Small and Medium Enterprises (SMEs) are recognized as a driving force for competitiveness and innovation that plays major role in sustainable development and contributing into the economic growth of Oman. This paper focuses on SMEs growth and sustainability in Oman. Design/methodology/approach - This research will adopt descriptive, empirical, and exploratory research design as well as mono method approach using quantitative approach of questionnaire. Findings – First, the findings of this study reveal the important role that SMEDA plays in supporting SMEs growth and sustainability through providing different regional and international platforms that support their businesses. Second, However, Artificial Intelligence is a new concept in the Omani society that still not integrated in most SMEs business. Second, the study revealed that SMEs see Artificial Intelligence (AI) as a significant factor for improving operational efficiency, market identification, and customer engagement that support its growth and sustainability. Research limitations/implications - Lack of sufficient literature reviews on SMEs growth and sustainability in Oman, since this topic is new, the researcher has not found literatures done in Oman yet especially the impact of adopting artificial intelligence (AI) on SMEs growth. There is a need to conduct further research regarding SMEs growth and sustainability in Oman. Originality/value – This paper provides insights regarding SMEs growth and sustainability in Oman, as well as an insight regarding challenges faced by those sectors and the role of artificial intelligence (AI) in boosting SMEs growth and sustainability in Oman. Keywords Artificial Intelligence, Growth Challenges of SMEs, SME, SMEs growth and sustainability

The Development of a Capability Building Framework for a Bioethanol Power Plant in the Philippines []


This research paper examined the Philippines' Capability Building Framework for Bioethanol Power Plants. The researcher hopes to identify the essential tools for assessing the Philippines' Bioethanol Power Plant's financial viability, environmental sustainability, and social consequences for capability building. The weighted mean rating of 4.39 and standard deviation 0.76 indicated that respondents "agree" on bioethanol power plant financial viability instruments in the Philippines. Thus, Philippine bioethanol power plant stakeholders must convey a clear set of rules and regulations to ensure project success. Respondents "strongly agree" on the instruments needed to identify environmental elements that could impact the project's environmental sustainability in land usage, water use, waste management, air quality, biodiversity, and climate change. Standard deviation is 0.68 and composite weighted mean 4.51. Finally, respondents "agree" that the important instrument for assessing potential social consequences for capability building related to bioethanol power plant construction in the Philippines includes the following variables: Employment, Community Engagement, Social Inclusion, Human Rights, Health and Safety, Cultural Heritage, Stakeholder Participation, Local Content, Social Infrastructure, Impact on Livelihood, Transparency and Accountability, and 4.42 is the composite weighted mean with 0.801 standard deviation. Philippines legislation and policy should boost biofuel growth and public knowledge, according to this study. Philippines requires a strong agricultural industry to supply sugarcane, cassava, and biofuel transportation and distribution. Bioethanol power plants profit from feedstock, energy, and government subsidies. Selling plant power may increase revenue. Philippine bioethanol power plants can be commercialized through knowledge sharing, investment, and market access through local and international partnerships.

The role of Home-based Communication on improving attitude regarding Utilization of Long-Lasting Mosquito Nets, Khartoum State, Sudan (2016 - 2018) []


Background: In the absence of a vaccine or effective and sustainable means of vector control, use of LLINs is an effective way to limit vector borne diseases. Objectives: The study aimed to assess the role of home-based communication in improving attitude of nets owners and hence the LLINs utilization compared with the currently used BCC approaches in 2016 – 2018 in Khartoum state. Materials and methods: A community based quasi-interventional study that utilized both pre and post design, and case – control study design study was conducted in four villages two served as intervention in Bahri Locality and the other two were selected as a control villages in Omdurman Locality. A multistage random sampling technique was used in selecting the required samples for this study and a semi- structured questionnaire was used to collect required information. The intervention composed of home-based communication includes messages and printable materials about the LLINs importance adapted from the national malaria control as well as distributing LLINs and training the community on hanging LLINs. .A total of 1250 participants were deployed and divided equally between both the experimental and control groups and were followed up for a period of one year with interval every 3 months. Results: There were no significant differences observed between the intervention and control groups concerning socio-demographic characteristics such as age, occupation and education level except for family monthly income, p-value > 0.05.The knowledge score about LLINs in the intervention villages was significantly increased for good knowledge in the dry season and wet season p-value= (0.001). This is most probably attributed to the four quarterly based follow-up visits, home based communication method has significant impact affecting bed net use compared to routine behavioral change communication (BCC) and It have great role in promoting the proper use and utilization of LLINs in the study villages during dry and wet season. Conclusion: The home-based communication is appearing effective in increase knowledge regarding utilization of nets. Therefore, it is suggested that there is a need to adopt by National Malaria Control Programme home-based communication during and after bed nets campaigns to enhance maximum utilization of LLINs. The study recommended adopting home-based BCC during and after LLINs campaigns and to a conduct more researches. Keywords: home based communication, knowledge, Khartoum state

Navigating the Economics of Production and Marketing of Tomatoes in Lalitpur, Nepal []


The study entitled ' Navigating the Economics of Production and Marketing of Tomatoes in Lalitpur District, Nepal ' was conducted from April 2023 to July 2023 by using a semi-structured questionnaire. The major objective of the study was to analyze the tomato production in the Lalitpur district of Nepal. Other specific studies included estimating cost and return, analyzing marketing channels, time series forecasting of tomatoes, and performing SWOT analysis. Tomato production in Nepal suffers due to insufficient data on production costs and profitability, leading to inefficient resource allocation and policymaker challenges. Lack of market information and infrastructure results in supply chain inefficiency and price volatility. The research aims to fill these gaps by studying tomato production in Lalitpur, and proposing solutions for industry enhancement. Data was collected from 100 respondents using random sampling, revealing a gender distribution of 62% male and 38% female. Most were adults with varying education levels. The average cost for building a plastic tunnel with dimensions 20×5 m² was determined to be NPR 23,747.81. The total cost for the cultivation under plastic tunnel was found to be NPR 3,601,223.26 /hectare. Total tomato production in Lalitpur district was. 96449.01 kg per hectare. The Benefit-Cost Ratio considering the cost of constructing a plastic tunnel house was 1.22 and excluding the tunnel house cost was 2.05. Among the respondents, 54% employed a single channel for tomato distribution, while 46% utilized a combination of distribution channels. Survey findings illuminated the influence of various stakeholders, including the government, traders and retailers on tomato pricing dynamics. Furthermore, price predictions indicated an ascending trend for large tomatoes and a consistent trend for small tomatoes.

Spatial modeling and mapping of count data with cases of under-reporting: A case of diabetes in Kenya []


Diabetes is a significant public health issue in developing countries, with an increasing burden on the healthcare system. However, accurate reporting of diabetes cases is often hindered by under-reporting, particularly in rural areas where access to healthcare is limited. When dealing with count data, both under-reported and over-reported cases are encountered. If it is assumed that the count data obtained from the field is always true, then modeling it with other count-data models will be erroneous. This study aimed to improve the existing Poisson-Binomial mixture model by factoring in covariates to make it suitable to estimate the number of under-reported diabetes cases in each county of Kenya and map the distribution of these cases. The covariates used in the model include the education level, poverty index, and access to healthcare in respective counties, making the probability of reporting vary from one county to another. The data was obtained from the Kenya Diabetes Management Information Centre and Kenya National Bureau of Statistics. The results revealed that at least each of the 47 counties had under-reported the diabetes data, with the probability of reporting ranging from 0.9002423 for Migori County and 0.7164098 for Mombasa County. Nairobi and Mombasa counties reported the highest underreporting rate with 16,708 and 11,784 cases, respectively underreported, while Lamu had 1269 underreported cases, the least in all the 47 counties. The Deviance Information Criterion (DIC) was used to compare the original model and the improved model, whereby the improved model was found to be efficient since it had a smaller DIC value. The computed actual cases of diabetes revealed that Nairobi and Lamu had 179,604 and 7,038, respectively, representing the highest and lowest diabetes county in Kenya. The resulting maps identified high-risk areas for under-reporting and the general distribution of diabetes in Kenya, valuable information for policymakers and public health practitioners to target resources towards improving diabetes prevention and management in Kenya.

ALIGNING TEACHER EDUCATION WITH EDUCATION 5.0 POLICY IN ZIMBABWE: CHALLENGES AND OPPORTUNITIES []


Abstract This paper seeks to explore and explain the challenges and opportunities faced by implementers in aligning teacher education with Higher and Tertiary Education 5.0 policy in Zimbabwe. While this study appreciated the efforts that were being made to align the TE practice with the intended curriculum, it was concerned that possible opportunities were probably not being exploited in the face of emerging curriculum transformation challenges. There was the much publicised misalignment of teacher education with Higher and Tertiary Education 5.0 policy in Zimbabwe. This misalignment scenario culminated in initiatives like the University of Zimbabwe Vice Chancellor’s Teacher Education Curriculum Transformation Programme, meant to address the gaps. However, there seemed to be some emerging challenges that could derail such processes. This study sought to add to literature on teacher education curriculum transformation and also promote the development of entrepreneurial and innovative teacher graduates for industrialisation and sustainable development. This study was guided by the constructivist philosophy and the interpretivist paradigm. The study adopted the qualitative research approach and the multiple case study method because of the flexibility and diversity in data generation that they allow. The purposive, non-random probability sampling procedure, featuring judgemental and convenience sampling was employed in the study. Data generation process involved key and other informant interviews, focus group discussion, observations and qualitative document analysis. Data was presented and analysed using the thematic and N-vivo approaches respectively. The study found that there were emerging challenges and unexploited opportunities in aligning the intended Heritage based, HTE 5.0 informed curriculum with TE practice in Zimbabwe. This study, therefore, suggested and recommended the Programmatic Teacher Education Curriculum Implementation Framework (PTECIF) for the Zimbabwean context. The study contributes to curriculum transformation and policy-practice alignment discourse by making multiple theoretical insights. The study, therefore, complements the extant perspectives on curriculum review and transformation in teacher education for industrialisation and sustainable economic growth. Key Words Curriculum transformation, Entrepreneurship, Heritage Based Education 5.0, Industrialisation, Innovation, Sustainable Development.

Utilization of Agricultural waste into Useful Materials []


Planet globalization, population growth and its consequent need to produce large amounts of food, or individual economic benefits and the prioritization of this over environment health, are factors that that have contributed to the development, in some cases, of a linear-producing modern agricultural system. In contrast to traditional and local agriculture, which was based on circular sustainability models, modern agriculture currently produces tons of waste that is accumulated in landfill, creating controversial consequences, instead of being reintroduced into the production chain with a novel purpose. However, Agricultural residues are rich in bioactive compounds and can be used as an alternate source for the production of different products like biogas, biofuel, mushroom, and tempeh as the raw material in various researches and industries. Usage of agro-industrial waste as raw materials can help to reduce the production cost and pollution load from the environment. Agro-industrial wastes are used for manufacturing of biofuels, enzymes, vitamins, antioxidants, animal feed, antibiotics, and other chemicals through solid state fermentation (SSF).