Volume 13 Issue 12

This study focused on a techno-economic modelling, simulation, and analysis approach, which was used to determine the techno-economic and environmental sustainability feasibility of Solar PV-BESS as the proposed case and an outright replacement of the existing fossil fuel power generation technology based on the load profile of the given location of study. The result from the technical analysis presented shows that the study area was able to utilize an annual solar radiation at 4.14 kWh/m2/d via horizontal positioning at 15⁰ inclination, which was optimal enough to meet the electrical power demand at 17,520,000kWh annually of the facility when the number of solar panels was increased to deliver 100% fraction of load, most especially in the low sunny days from May to October. Also, the economic analysis presented showed positive NPV and IRR on the proposed case. Although the initial cost of the proposed is quite high as already associated with renewable energy solutions but showed substantial payback results andoverall cost-benefit ratio at 1. The results showed that the proposed case eliminated 100% of the GHG emissions from the base case, with tremendous benefits for revenue generation from emission trading schemes. The study recommends that NUPRC and its stakeholders should form strategic partnerships with existing local solar panel manufacturing collaborators and manufacturers, in other to promote in-country production of solar PVs to reduce the initial cost of the solar projects.

The research focuses on the modeling and simulation of univariate and multivariate time series analysis by applying machine learning (ML) and deep learning (DL) techniques for accurate forecasting. The study includes the individuals and combined application of algorithms such as Support Vector Regression (SVR), Random Forest (RF), K-Nearest Neighbors (KNN), Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRU) in the context of neural networks. These techniques are evaluated for their analytical performance in a number of time series estimation settings. ML approaches are known for their simplicity and efficiency in small data sets. On the other hand, DL approaches require larger data sets and more computational resources, but offer higher accuracy and flexibility in demanding setups. The study concludes by highlighting the importance of choosing the right algorithm based on the nature of the data and the forecast object. The results provide valuable insights for applications in finance, energy, healthcare, and other fields where time series forecasting plays an important role. Future research may consider hybrid and interpretability-enhanced approaches to develop applications of these models in real-world settings. In this study, for the forecasting specification especially Univariate analysis, the demonstrations show the actual values ​​for the past 15 days and the forecasts for each model for the next 10 days.

This research work looks at the effects of incorporating technology (I.C.T) into the educational curriculum most especially in chemistry and how it affects the teaching and learning of the atomic structure in the senior high schools. The study made used of an experimental design in the data collection. The overall students for this study were eighty one (81) S.H.S Chemistry Students in Our Lady of Lourdes Girls' Senior High School but the researcher worked with fifty six (56) of them in the same year group. The sampling was done by using a shuffled list and assigning every second person to one group and the others to a different group. Multiples-choice and fill-in the blank questions were used for the data collection. The test was conducted before as pretest and after as posttest for the two groups respectively. From the mean, standard deviation and the t-test, (t-value of -3.434) there was a significant difference in the mean scores of the students taught using the I.C.T integrated method.  Per this findings, chemistry educators or teachers are encouraged to integrate I.C.T in the teaching and learning processes of the atomic structure.  Chemistry students should be challenged to use the internet and other technological mediums in their learning and doing of assignment especially in the topic, atomic structure. This will help them to be familiar with the use of I.C.T tools and how to use them in their learning processes. 

Poor indoor air quality (P-IAQ) poses significant challenges to public health, environmental sustainability, and socio-economic development, particularly in urban areas of developing countries. This issue aligns with the United Nations Sustainable Development Goal (SDG) 3 (Good Health and Well-being) and intersects with other SDGs. Despite the urgency of the problem, research exploring the interplay between urban air pollution, PIAQ, and health outcomes in healthcare settings remains limited. This study conducts a systematic literature review (SLR) of peer-reviewed articles published between 2020 and 2024 across major databases, including PubMed, Scopus, ScienceDirect, and Web of Science. It examines the impacts of P-IAQ on health outcomes in urban healthcare facilities in Nigeria, focusing on indoor environmental quality (IEQ) factors such as ventilation, thermal comfort, and air quality. The review identifies that improved indoor air quality significantly enhances patient recovery rates, reduces stress, shortens hospital stays, and boosts the performance of healthcare staff. The study further explores the disparities in health outcomes between purpose-built and retrofitted healthcare facilities, highlighting the combined effects of urban air pollution and IAQ dynamics. Based on these findings, an evidence-informed conceptual framework is proposed, integrating urban air pollution sources, IAQ determinants, and health outcomes. The framework also outlines actionable mitigation strategies, emphasizing the role of building design and urban policies in enhancing IAQ standards in healthcare facilities. The insights from this research provide a critical foundation for advancing sustainable building practices and informed policymaking aimed at mitigating P-IAQ and improving health outcomes in urban environments.

The increasing global urban population and its accompanying increase in energy demands have intensified the need for energy-efficient building designs, particularly in tropical climates like Abuja. This study explores optimizing building envelope components—insulation, high-performance glazing, and green roofs—to mitigate cooling loads and enhance energy efficiency. A theoretical review methodology was employed, synthesizing recent literature to assess the thermal performance of envelope systems. Findings reveal that improvements in insulation, advanced glazing technologies, and green roof integration can significantly reduce cooling energy consumption while promoting sustainability. The study provides practical insights for architects, engineers, and policymakers aiming to achieve thermal comfort and energy efficiency in Abuja’s hot climate.

Plant diseases pose significant threats to agriculture, adversely affecting both crop yield and quality. This study offers a comprehensive overview of plant pathology, examining various types of diseases, their causative agents, and the intricate interactions between plants and pathogens. This study explored the integration of advanced deep learning and machine learning techniques. A dataset of plant leaf diseases, sourced from an online repository, was augmented with additional data featuring 11 West African plant species. The dataset underwent rigorous preprocessing to ensure compatibility with machine learning models. This study employed the ResNet50 Convolutional Neural Network (CNN) for feature extraction and XGBoost for classification, achieving a remarkable accuracy of 98.81% in differentiating between healthy and diseased plant leaves. The performance of the developed model was evaluated using key metrics, including accuracy, precision, recall, F1-score, confusion matrix, and ROC curve, and was found to outperform existing models in terms of accuracy. Furthermore, the model was successfully integrated into a mobile application, demonstrating efficient performance. This approach presents a scalable solution for precision agriculture, enhancing crop health management and boosting agricultural productivity.

This study identified the best-fit model for work engagement among public secondary school teachers in the Davao Region, Philippines, by examining the influence of organizational commitment, personality domains, and self-regulation. Using a stratified sampling technique, data were collected from 400 teachers and analyzed through Structural Equation Modeling (SEM). A non-experimental, quantitative, descriptive research design was employed, with statistical tools including mean, standard deviation, Pearson product-moment correlation, and SEM. The results revealed that the levels of organizational commitment, personality domains, self-regulation, and work engagement among teachers were all very high. Additionally, while no significant relationship was found between organizational commitment and work engagement or between self-regulation and work engagement, a significant relationship was observed between personality domains and work engagement. Furthermore, the study identified Model 3 as the best fit for explaining work engagement, highlighting the roles of organizational commitment, personality domains, and self-regulation as influenced by academic leaders and educational advocates in fostering work engagement. 

Due to economic circumstances and social demands the role of working women has changed in developing countries, like Bangladesh. For this reason, women have tremendous pressure to develop a career as strong as their male counterparts while sustaining active participation in personal life. The ever-increasing pressure in the workplace makes it completely difficult for women to get quality time for their family. This creates negative impact on women’s physical, emotional and social well-being. Thus, attaining work life balance is essential for working women to have a good quality of professional and personal life. This study attempts to explore the role of family support to balance the work life and reduce the job stress for female employees in Bangladesh. The study also focuses on the impact of family support to maintain work life balance and reduce job stress. The finding of the study reveals that family support is the most important issue for working women to continue a healthy professional as well as personal life especially in case of married women. It is also visible that family support has an opposite relationship with job stress.

In an era marked by escalating challenges such as climate change, resource scarcity, and social inequality, the imperative for sustainable leadership practices has intensified. This study explores the impact of sustainability leadership on staff performance in three major universities in Kano State Nigeria, and examines its influence on performance outcomes, societal impact, and environmental sustainability. Employing a descriptive survey methodology, the research investigates the relationship between sustainability leadership and organizational performance using two research instruments and formulating two hypotheses to test these relationships. Data collected from 150 staff members were analysed using the Pearson product-moment correlation coefficient to measure statistical associations between sustainability leadership and staff performance. The findings reveal significant and positive correlations, indicating that universities led by sustainable leaders exhibit higher levels of employee job performance. Additionally, substantial positive relationships were identified between sustainability leadership and the advancement of environmental, social, and economic sustainability goals within these institutions. These results underscore the critical role of sustainable leadership in enhancing organizational effectiveness and promoting sustainable development outcomes. Leaders who integrate sustainability principles into their practices are well-positioned to drive positive impacts on employee engagement, organizational reputation, and resilience amid global challenges. This study contributes to the understanding of how sustainability leadership influences organizational performance in the Nigerian context, advocating for the adoption of sustainable leadership strategies to achieve business success and broader societal benefits. Future research should further explore the mechanisms through which sustainable leadership practices can be effectively implemented and scaled across diverse organizational settings, ensuring sustained positive impacts on both organizational and societal outcomes.

Abstract- Growing urbanization and a tropical climate intensify the known environmental challenges of urban heat islands (UHIs) in the Philippines. UHIs are formed by human activity, infrastructure, and decreased vegetation, resulting in elevated temperatures in urban areas compared to their rural surroundings. This tendency exacerbates energy consumption, air pollution, and health concerns, posing significant issues for urban planners and policymakers. Geographic Information Systems (GIS) and remote sensing technologies provide efficient methods for evaluating and reducing UHIs. GIS enables the merging and examination of geographical data, providing a comprehensive understanding of urban settings. Remote sensing uses thermal data from satellites to provide a comprehensive understanding of land surface temperatures and heat distribution patterns. In the Philippines, these technologies are essential for detecting areas with high temperatures, assessing the elements that contribute to this, and creating specific policies for sustainable urban development. By utilizing GIS and remote sensing, urban planners can strategically create geographically accurate green spaces, optimize construction materials, and apply cooling measures, ultimately fostering a healthier and more resilient urban environment. This paper shows the significant utilization of these technologies to facilitate data-driven decision-making, which is crucial for mitigating the detrimental impacts of UHIs. This research can guide environmental planners on how to utilize GIS and remote sensing for a more scientific approach as urban areas continue to grow and science-based sustainable urban planning becomes more and more apparent. Evaluating UHIs using GIS and remote sensing is an essential step in the development of habitable, sustainable, and climate-resilient cities in the Philippines.

Abstract: An up-to-date review of erosion-corrosion from various literary sources, covering its origin, impacts, affecting factors, occurrence areas, experimental measuring devices, and research advances, is reported. From the review, erosion-corrosion is a mechanically caused action by impinging fluid, usually liquid, slurry abrasion, suspended particles in fast-flowing fluids, bubbles, droplets, cavitations, etc., under complex synergistic effects of the natural electrochemical corrosion. It is affected by many factors that still need to be fully understood, so it is very challenging to accurately find its rates for controlling it. It is a very costly problem that is common in power plants, water, oil, gas, metallurgy, mining, and other industrial sectors that utilize mechanical equipment as well as structural components in hydraulic environments. Its effects are predominant in petroleum pipelines and heat exchange industries, as well as marine equipment or structures. Its rates, time scale, and capacity to degenerate material components to failure are much more alarming than most other corrosion types. This corrosion type is highly detestable, so much attention has been drawn to it, as attested by many research outputs on it to date, with a pressing need for ways, including emerging technologies, of minimizing its impacts. Forty-six of the research outputs have been recapitulated and presented, and they focus on developing and/or testing alternative material components, coatings, measuring devices, and application of artificial intelligence, for better erosion-corrosion resistances or rate measurements and control under various fluid conditions. The paper provides integrated, up-to-date information on erosion-corrosion for easy accessibility for the needful basic knowledge for research progress towards reducing its impacts.

The adoption of Building Information Modelling (BIM) has transformed the architecture, engineering, and construction (AEC) industry by providing a digital platform for integrating project lifecycle information. While BIM has been widely recognised for improving project efficiency, reducing costs, and enhancing communication, its implementation faces persistent challenges that hinder its full adoption, particularly in Malaysia. This study aims to identify the challenges of BIM implementation in construction projects within Klang Valley and to recommend strategies for improving its adoption in construction projects. A mixed-method approach was employed, involving a questionnaire survey distributed to 55 AEC professionals and in-depth interviews with three key stakeholders. The findings highlight that high costs, skill gaps, time constraints, preference for conventional practices, and limited awareness and training are the primary challenges hindering BIM adoption in construction projects, underscoring the need for financial support, capacity-building initiatives, cultural shifts, and improved education to foster wider acceptance and implementation. These challenges highlight the need for targeted initiatives to bridge knowledge gaps, enhance training programmes, and promote the value of BIM to stakeholders. Addressing these issues is crucial to ensuring the successful integration of BIM across construction projects, enabling the industry to maximise its potential benefits. Effective BIM adoption in construction projects requires a combination of comprehensive training, phased implementation, government support, standardisation, and technological advancements, underpinned by national strategies to address challenges, enhance education, and demonstrate BIM’s tangible benefits. This study aims to provide insights that can guide policymakers, industry leaders, and practitioners in overcoming the barriers to BIM adoption, paving the way for a more advanced and efficient construction sector.

Abstract: Increased urbanization in many cities of the world brings with it the problem of multiplied impervious surfaces on infrastructure like roads. Using pervious instead of impervious surfaces will address these concerns, the use of palm kernel shell (PKS) to replace granite in the matrix will further address the cost and environmental worries. A Pervious Concrete walkway was constructed on an unpaved, waterlogged stretch using agricultural waste product-Palm Kernel Shell (PKS) to replace conventional granite in the concrete matrix. The initial laboratory tests were carried out in accordance with BS 812, Part 101 from 1984 to 1990, and Parts 110 and 112 from 1990. The batching process was weighted, with aggregate percentages for partial replacement set at 10%, 20%, 30%, 40%, and 50% PKS. The mix of 70% granite and 30% palm kernel shell produced the highest compressive strength, with values of 5.33 MPa, 6.19 MPa, and 7.36 MPa at 7, 14, and 28 days, respectively. The incorporation of PKS into the pervious concrete walkway effectively reduced waterlogging in the area while posing no environmental concerns..

Abstract: This study assessed background ionizing radiation (BIR) levels in six markets across Ile-Ife and Modakeke, Southwestern Nigeria, to evaluate potential health risks. Annual effective dose rates (AEDR) were measured and analyzed using a handheld Geiger Counter. Results showed AEDR values ranging from 0.67 mSv/y at Texaco Market to 2.52 mSv/y at Sabo Market. The average AEDR across all markets was below the global population average exposure of 2–3 mSv/y. The findings suggest that BIR exposure in these markets is primarily due to naturally occurring radionuclides in the soil and rocks, with no significant anthropogenic contributions. This study concludes that the BIR levels in these markets pose no significant health risks to users.

Abstract: The objective of this study was to explore the key factors influencing the role of Fintech in promoting financial inclusion in Bangladesh with special focus on the barriers, drivers and opportunities offered by digital financial services. Based on the study findings, it is evident that Fintech has a huge potential to bridge the financial inclusion gap in Bangladesh, but certain challenges need to be overcome to achieve a widespread and comprehensive impact. Financial awareness, a fundamental component of economic growth and poverty reduction, remains a significant challenge in many developing countries, including Bangladesh. Fintech has emerged as an innovative tool to bridge the financial gap with innovative technologies and solutions. Taking into account Bangladesh's interesting socio-economic environment, this study explores the factors influencing the role of Fintech in promoting financial awareness in Bangladesh. Key factors examined include technology infrastructure, management systems, financial literacy, trust, transparency, and fairness. The study also highlights challenges facing fintech adoption, including limited internet access, cybersecurity concerns, and resistance to change. Using both subjective and quantitative methods, the study explores how fintech platforms, such as mobile financial services, digital payment systems, and microcredit platforms, can help increase access to financial services for the unbanked and underbanked. The findings suggest that fintech has made great strides in promoting financial inclusion in Bangladesh, but targeted interventions in planning, training, and infrastructure are essential to maximize its impact. The study provides key insights for policymakers, fintech providers, and development organizations to leverage fintech for inclusive financial development in Bangladesh.

Abstract: Nanoparticles are small particles with distinctive characteristics of chemical, biological and physical properties as compared to the bulk matter. Great interest to explore the potential and application of this nanoparticles have gain momentum in the field of science. This research in particular was designed to explore alternative way of producing these nanoparticles. Green synthesis used in this research was prefer as the materials are readily available, the method is ecofriendly and potentially efficient. The study utilized croton megalocarpus leaves extract as reducing and capping agent of gold solution (1 mM gold (III) chloride trihydrate).Formation of AuNPs was done using Uv vis spectrophotometer while characterization was done using HRTEM,the active biomecules present in the plant extract was screened using FTIR. From the results the stirring time was six minutes and the color of the solution turned from right yellow to dark brown. The uv vis spectrophotometer surface plasmon resonance (SPR) was λmax 545 nm with the intensity of 1.0 after six minutes. The HRTEM results indicated that the resultant nanoparticle were mostly spherical with non-uniform surface with an average diameter of 26.5±1.2nm. The FTIR indicated O-H stretching at 3273.26 cm-1+ absorbance peak which corresponds to alcohol and phenol, carbonyl (C=O) groups stretching at an absorbance peak of 1637.59 cm-1 corresponding to carbonyl-containing organic species. The nanoparticles produced showed great antimicrobial properties especially on gram negative bacteria, with E.coli having highest inhibition of 15 ±0.41nm  the least affected was B.sabtilis a gram positive bacteria with 8.5 ± 0.73 and E.feacalis which was resistant to AuNPs inhibition. Synergistic antimicrobial effect was observed on E.feacalis where coating an inhibition of 16.5nm as compared to drug alone which had an inhibition of 14.5nm. These findings suggest that AuNPs synthesized from Croton megalocarpus could be valuable in the development of nanotechnology-based antimicrobial drugs.

Abstract: Cognitive radio (CR) is a promising solution to resolve the crisis of spectrum underutilization. Spectrum sensing is an indispensable aspect of CR network (CRN). Energy detection method is being recognized as a simple and reliable step for spectrum sensing. The significant factor of the energy detector (ED) is threshold, whose optimum value depends on signal to noise ratio (SNR). However, in a wireless environment, where the received signal is severely degraded due to the uncertain noise, reliable spectrum sensing is not guaranteed. The key metrics of the CRN are total spectrum sensing error probability, throughput, and energy efficiency. For each SNR value, there exists an optimal threshold that minimizes total spectrum sensing error probability and maximizes throughput as well as energy efficiency. Therefore, the threshold of ED should be adaptive in CRN. This paper presents an optimal adaptive threshold by utilizing spectrum sensing errors for each metric in CRN.

Abstract: The superiority of composite (blended/multiple materials) baseball bats over wood bats, bolstering  10-15% higher exit velocity is attributed to the trampoline effect (bounciness) resulting from advanced materials, deliberate breaking, reduced sting vibrations, balanced weight, and an expanded sweet spot. This article systematically examines (B7: Bolstering (enhanced), Blended (composite) Baseball Bats with Bounciness, Bang (sound), and Banishment (safety), focusing on the comparative superiority of composite bats over wood bats for 12U players, where they are permitted.  In a controlled environment (70 oF), the average exit velocity of a ball on the composite bat are >10% superior to those of a wood bat when hitting balls off the tee, while >15% superior when hitting balls pitched at a speed of 50 MPH. Experimentally, metal bats produced a louder (102 to 106 dB), high-pitched “bang” due to their hollow structure, while composite and wood bats emitted a quieter (91 to 95 dB), low-pitched sound, when measured close to the batter. The variation in decibels was influenced by ball speed, impact point, and bat design, affecting player perception. Composite bats gain power over time as they break in, enhancing performance but also introducing inconsistency and potentially increasing injury risk. Authors shed light on the importance of baseball safety gear for players on the diamond, helping them avoid possible injuries.

Abstract: Tomato cultivation (Solanum lycopersicum L.) is highly significant due to its considerable economic value, high consumer demand, and critical role in supporting the livelihoods of farmers in Bangladesh. However, the majority of Bangladeshi farmers rely on traditional, manual methods for detecting tomato leaf diseases, relying on visual inspection and personal experience. Limited resources and a lack of awareness about advanced technologies further hinder the adoption of efficient disease detection methods. Computer vision, a cutting-edge technology, enables the automated identification and classification of tomato leaf diseases, holding significant promise for improving agricultural productivity and farmers’ livelihoods. This study focuses on developing a robust disease detection framework involving image acquisition, preprocessing, and feature extraction using a VGG16-CNN hybrid model, integrated with smartphone applications for real-time detection. To address the limitations faced by local farmers and plant enthusiasts unfamiliar with such technology, a diverse dataset of approximately 16,824 images was created, comprising field images and online sources. The proposed method leverages VGG16 for feature extraction, achieving enhanced performance through additional fine-tuned layers that form a hybrid model. This approach delivers an accuracy of 98%, with an F1 score of 98%. These findings highlight the potential of the proposed system to significantly mitigate the impacts of tomato leaf diseases, thereby improving tomato cultivation and production outcomes.

Abstract: The study highlights the potential of Asaba clay for producing high-quality ceramic wares by examining the physicochemical characteristics of clay mineral using advanced analytical techniques such as X-ray fluorescence (XRF), X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), and atomic absorption spectrophotometry (AAS). Results obtained reveal that the sample was kaolinite with SiO2 (43.63%), Al2O3 (16.65%), and Fe2O3 (4.87%) as the most predominant elements. The identified minerals include Quartz (SiO2), Orthoclase (KAlSi2O3), Kaolinite (Al2O3•2SiO2•2H2O), and Albite (NaAlSi2O3). Wavenumbers ranges from 3697.51913 - 685.83016, while the high intensities of the hydroxyl-related peaks at 3421.70 cm⁻¹, 3622.97 cm⁻¹, and 3697.52 cm⁻¹ suggest that Asaba clay has properties similar to kaolinitic. Elemental composition indicates that the elements (Co, Cr, Cu, Fe, Mn, Ni, Pb, Cd, Zn and Ca) are in acceptable concentration levels. The study therefore revealed that the clay from Asaba has kaolinite characteristics, is environmentally safe and is therefore suitable for porcelain insulator production.

Abstract: This study explores the role of YouTube as a mediating variable between enhancing knowledge (independent variable) and job performance (dependent variable) for records personnel in Putrajaya. A total of 97 respondents (out of 118) from various public sector organizations participated in this study. Data was collected via a structured questionnaire, and statistical analysis was conducted using SPSS to examine descriptive statistics, reliability tests, and regression analysis. The results revealed a negative relationship between YouTube’s role in enhancing knowledge and job performance. Although YouTube was found to be useful for knowledge acquisition, its role did not significantly translate into improved job performance for records personnel. The study emphasizes the need for more tailored and formalized training approaches to bridge the gap between knowledge enhancement and job performance.

Abstract: This study investigates the determinants of job performance, specifically focusing on work stress, social support, and emotional intelligence.   Data were acquired from 326 police officers in Johor. The results indicate a significant correlation between work stress, social support, emotional intelligence, and police job performance. Furthermore, the regression analysis demonstrates that emotional intelligence emerged as the most influential predictor of job performance. The implication of this study highlights the significance of emotional intelligence in improving job performance among police personnel in Selangor. The report continues by emphasizing the need for future research to provide a more thorough investigation into forecasting job performance, specifically within the setting of Malaysia.

Abstract: According to F. Furtado and A. Singh (2021), movie recommendation systems aim to assist viewers by suggesting movies to watch, thereby avoiding the time-consuming and complex process of selecting from a vast library of movies, which can number in the thousands or even millions. This article seeks to reduce human effort by recommending movies based on user interests. To address these challenges, we propose a technique that combines content-based and collaborative approaches. This method produces more precise results than systems that rely solely on content-based methods. Content-based recommendation systems are limited to individual preferences and do not recommend items outside the user’s immediate interests, restricting exploration. To overcome these limitations, we developed a system that addresses these concerns. The proposed movie recommendation system uses Cosine Similarity to suggest movies like the one chosen by the user. While existing algorithms generate recommendations, they often fail to answer the critical question, “Is this a film worth watching?” To enhance the overall experience, our system incorporates sentiment analysis of selected movie reviews using machine learning techniques. This study employs two supervised learning approaches, Naïve Bayes (NB) and Support Vector Machine (SVM), to improve accuracy and efficacy. A comparison of the two methods reveals that SVM achieved an accuracy score of 98.63%, while NB scored 97.33%, as reported by N. Pavitha et al. (2022). The project integrates a sentiment analysis module into the movie management system to enhance decision-making and user experience. The Naïve Bayes approach is used to classify and evaluate user reviews and feedback into positive, negative, and neutral categories. This analysis provides insights into audience preferences, overall satisfaction, and movie reception. The system utilizes this information to refine movie recommendations, analyze trends, and enhance content selection, all of which contribute to a more personalized user experience. The system is evaluated using the ISO 25010 framework, focusing on functionality, reliability, usability, effectiveness, and robustness. Findings show that respondents actively participated in the review process across multiple domains. Key results indicate high satisfaction levels in terms of ease of use, interface design, and system performance. Feedback also highlighted areas for improvement, such as optimizing loading times and enhancing specific features for a smoother user experience. Overall, the findings reflect positive engagement with the system, demonstrating its effectiveness in meeting user needs while identifying opportunities for future enhancements.

Abstract: This study aimed to explore how Ghanaian construction firms manage payroll, scrutinize existing internal controls, and assess their effectiveness. This inquiry is critical due to the significant and growing role of labour costs, and the need to ensure company growth aligns with its intended objectives. The study employed a descriptive survey research design. Data were collected using questionnaires that were disseminated among construction workers in Ghana. These participants were selected via purposive and convenience sampling techniques. The collected data was then analysed using SPSS version 23. The analysis revealed several key insights. Firstly, it was observed that proper payroll practices were generally in place among the construction companies surveyed. Secondly, the study found that these companies were implementing effective internal control practices. Lastly, the study found a positive correlation between the effectiveness of internal controls and the payroll process in Ghanaian construction companies. The findings of the study underline the crucial role of internal controls in the payroll process within construction companies. Given their proven effectiveness in the surveyed firms, the study recommends that these controls should be more widely adopted. Policymakers should consider implementing regulations to encourage construction companies to integrate internal controls into their payroll processes. This not only ensures correct payroll practices but also boosts the overall growth and development of the organization.

Abstract: Mix Aluminium-Iron (80:20) pillared clay was prepared through pillarization method, after purification using standard method to reduce the amount of Quartz present. The procedures involved were purification, preparation of the pillaring solution, hydration of parent clay, calcinations, intercalation of Aluninium and Iron metal oxides as pillars. BET N2 absorption technique was employed in order to determine the surface area, pore volume and micropore volume which was found to be 6.929 (Å) 139.669 m2/g, 0.057 cc/g, 0.074 cc/g, respectively. The XRD analysis was also carried out to determine the minerals obtainable in the sample, which montmorillonite (Na,Mg and AlO3) and Quartz peak were observed at a relative intensity of 49.15 and 100% with d-spacing of 0.3073(Å) and 0.1023(Å) respectively.

Abstract: This paper aims to evaluate the current safety practices and their impact on the reduction of accidents and fatalities in construction sites in North-West Nigeria tertiary institutions. To achieve this aim, the study, through a survey design, draws a sample of forty-two respondents comprising a chief builder, director of works, physical planners and project supervisors using a convenience sampling technique. To obtain pertinent data, a 5-point Likert scale questionnaire was administered to participants and the collected data were analyzed using the relative importance index using the Statistical Package for Social Science (SPSS) version 17. However, findings from the analysis show that; the adoption of comprehensive and sustainable safety practices at construction sites significantly mitigates risks, safeguards the well-being of their workers, enhances project efficiency, and bolsters their overall reputation. Hence, there is a need for continuous improvement in safety standards, emphasizing proactive measures such as robust safety training and strict adherence to safety protocols. More so, integrating safety considerations into all phases of project management emerges as crucial for achieving sustainable safety outcomes.

Abstract: This systematic review of literature bears the objective of exploring the potential of transformative novel blockchain technology, its regulation, and the substantive impact it bears on renewable energy firms' competitive advantage. The study provides a minutiae of the current trends in research, their implications, and blockchain implementation and innovation between 2019 to 2024. The methodology comprised a comprehensive search of scholarly databases, selection, and analysis of the relevant research studies. The findings revealed that Blockchain is essential based on its transparency, traceability, data privacy, and decentralization features which enhance trust, transparency, and traceability across the supply chain. Furthermore, blockchain technology is relevant in the renewable energy sector in Kenya ranging from p2p trading platforms, digitization by IoT, E-mobility, and decentralized trading platforms. The distributed ledger technology is a promising disruption for a wide area of service and product management in the energy sector ranging from the producers, transmitters, regulators, and distributors involved. The review concludes with future research recommendations and the practical implications for the industry players and the regulators.

Abstract: Sign language recognition (SLR) has arisen as a major area of research in recent years, attempting to bridge the communication gap between the deaf and hard-of-hearing community and the hearing world. This research study addresses the construction and implementation of a manual alphabet recognition system utilising deep learning techniques, notably convolutional neural networks (CNNs). The work focuses on establishing an efficient and accurate system for converting Nigerian Sign Language manual alphabets into text. By integrating computer vision and machine learning methods, the proposed system seeks to overcome the communication gap between deaf and hearing individuals. The paper explains the technique adopted, including data collection, preprocessing, model architecture, and deployment using web-based tools. The system achieves a 95% success rate in recognizing static hand motions, proving its potential for real-world applications. However, issues in identifying dynamic motions and generalizing across varied user populations are observed. The report finishes with recommendations for future research, emphasizing the need for combining temporal analysis and expanding the system's capabilities to word and phrase recognition.

Abstract: Given that death is a natural occurrence, disposing of the dead especially corpses is an unavoidable and necessary part of human life. In order to appropriately dispose of the deceased, land use planning is crucial since improper handling could jeopardize environmental, psychological, and human health. In Nigeria, planning laws have not stopped urban growth due to urbanization and shifting societal attitudes. Public authorities usually only consider residential, commercial, industrial, and institutional land uses like schools, hospitals, and stadiums when allocating state land directly or through state agencies, despite the fact that the country's population has grown from 70 million in 1973 to nearly 200 million in recent years. The matters of death and burial require consideration from both a general and an urban management and planning standpoint. The development and execution of environmental policy on the disposal of the deceased should be localized, taking into account the characteristics of residents in certain areas. This evaluation determined that the living's planning for the disposal of the deceased encompasses creating a comfortable environment for the ultimate resting place, appropriately interring the remains, and ensuring that the subsequent management and maintenance of the designated resting area is conducted with dignity and hygiene. From a municipal standpoint, interring the deceased is regarded as an essential and obligatory public service.

Abstract: This research article examined the correlation between natural gas usage by power generation firms and economic growth in Nigeria. The study analyzed many factors, including liquefied petroleum gas usage, industrial gas consumption, and gas consumption for electricity production, and their effects on gross domestic product (GDP). Data on a quarterly basis from 2010 to 2020, sourced from reputable entities such as the Central Bank of Nigeria, Gas Exporting Countries Forum, and the United Nations, were employed for the analysis. The study investigation utilized the Nonlinear Autoregressive Distributed Lag (NARDL) approach. The results indicated that gas usage substantially affected Nigeria's GDP in short term and long run. The research indicated that a 1% growth in gas utilization by electric power plants and LPG usage positively correlated with a 1.04% and 16.64% rise in Nigeria's GDP, respectively. A 1% reduction in industrial gas usage would result in a 19.95% decline in Nigeria's GDP. The findings demonstrated that augmenting gas use in power generating influenced the GDP. Based on the study, it is advised that the Nigerian government undertake steps to increase the consumption of LPG and natural gas for industrial applications and electricity generation to foster economic growth.

Abstract: Access to safe and clean drinking water is essential but  underground water contamination by some (heavy) metals poses a serious threat to water quality in many areas. This research focus was to analyze the concentration of various metals in underground water samples obtained from different locations in Malete, Kwara State, Nigeria. The metals of interest include lead (Pb), chromium (Cr), manganese (Mn), uranium (U), and cobalt (Co), which are associated with adverse health and environmental effects, such as cancer and other forms of diseases. Through atomic absorption spectrophotometry (AAS), the samples collected from Westend 1, Westend 2, Yidi road, New Yidi road, and School Road were analyzed to assess the concentration of some metals that can pose health risks. The results showed that the average lead (Pb) concentration across samples was 0.07 mg/L, chromium (Cr) was 0.02 mg/L, the average manganese (Mn) concentration was 0.16 mg/L, Uranium (U) averaged at 0.02 mg/L  and Cobalt (Co) was found at an average concentration of 0.03 mg/L. The results  were compared with the World Health Organization (WHO) drinking water quality standards. Chromium (Cr) concentration was below the WHO  standard of 0.05 mg/L suggesting a low risk of chromium toxicity. while other metals were above the standard. Hence ,the results identified potential sources of metal contamination and represents a significant step toward addressing the environmental and health challenges posed by some metals contamination in Malete.