Abstract-This study investigated School Management Committee roles and the academic performance of pupils in selected government aided primary schools in Bulambuli Town Council, Bulambuli District. The study sought to; examine the relationship between the supervisory role of School Management Committees (SMCs) and academic Performance of pupils; examine the relationship between the supervisory role of School Management Committees (SMCs) and academic Performance of pupils; and examine the effect of the consultative role of School Management Committees (SMCs) on academic Performance of pupils. The study adopted a cross-sectional research design. Both simple random sampling and purposive sampling techniques were used to select the sample of respondents. The researcher studied a sample of 82 participants who included teachers, SMC members from selected government-aided primary schools, officials from DEO’s office and CCTs of selected schools in Bulambuli TC. Questionnaires and key informant interviews were used for data collection. Quantitative data from questionnaire was analyzed for both descriptive and inferential statistics using SPSS and Excel while qualitative data was analyzed thematically. The findings of this study were that; SMCs have significant influence on academic performance of pupils. The Pearson correlation coefficient shows that there is a significant positive relationship between the administrative role of SMCs and academic performance of pupils, r = 0.729, p = 0.000; supervisory role of SMCs influences the academic performance of pupils, r = 0.689, p = 0.000; and consultative role of SMCs has a significant positive relationship with academic performance of pupils, r = 0.648, p = 0.000. From the findings of this study, the researcher recommended that the SMCs should work with school administration to provide support such as academic intervention programs to struggling pupils so as to improve the academic performance of pupils; tighten regular monitoring and assessment of pupils’ progress to identify areas of improvement; and work closely with parents and other stake holders to support pupils’ learning. By involving the broader school community in academic initiatives, school will create a network of support that might help pupils thrive academically.

Abstract-This study examines the effects of interrupting versus continuing beta-blocker therapy in post-myocardial infarction patients. The ABYSS trial, a multicenter noninferiority study, found that interrupting beta-blocker therapy did not offer any advantages over continuation in reducing major cardiovascular events or improving quality of life. The interruption group experienced a slight increase in hospitalizations for coronary-related conditions. These findings challenge existing guidelines recommending beta-blocker discontinuation after one year for certain patients. The trial highlights the necessity for additional research to clarify the role of beta-blockers in modern post-MI care, especially for patients with preserved left ventricular function.

Abstract-Light fidelity (Li-Fi) technology is a wireless communication system that utilizes visible light spectrum to transmit data with high speed and secure manner compared to the traditional Wireless Fidelity (Wi-Fi) architecture. In this paper a smartphone is used in Li-Fi communication system. The aim of this proposed approach is to maximize the bit rate with high accuracy by using the flashlight of built-in smartphone camera as a source to send data and detect the effect of using a built-in smartphone ambient light sensor and external light detector sensors that is connected to Arduino UNO circuit to receive data. Four practical experiments were conducted to discover which light sensor accomplish higher data bit rate and tested the system performance under changing the distance between transmitter and receiver. The evaluation results demonstrated that the data bit rate is better with the proposed research than the others, where it reached more than 100 bps with accuracy 100%.

Abstract-Cloud Computing with field of emergence with frameworks with intelligent platform based on cloud which is designed with “reliability , availability “ with key deliverables with a specific and specialized platforms which are designed on methods for computing technology and service streamlined with pattern – self based analysis for Multimedia Management with Enterprise on Digital Platforms for reviewing Data Agents for digital Background for computing level of architecture format with a self-developing ecosystem for pattern recognition and texture delivering format.

Abstract-Ultrasound is simply sound whose frequencies are too high to be heard by the mortal observance, that’s to say the frequencies are above c 20 kHz. At the top end of the scale, ultrasound is used at frequentness up to several GHz. The main end of this system is to descry object that will be ahead of ultrasonic transducer. Utmost ultrasonic detectors are grounded on the principle of measuring the propagation time of sound between send and admit (propinquity switch). The hedge principle determines the distance from the detector to the glass (retro-reflective detector) or to an object (through- ray detector) in the measuring range. Ultrasonic detectors are grounded on the measured propagation time of the ultrasonic signal. They emit high- frequency sound swells which reflect on an object. The objects to be detected may be solid, liquid, grainy or in greasepaint form. It sends an ultrasonic palpitation out at 40 kHz which travels through the air and if there is a handicap or object, it will bounce back to the detector. By calculating the trip time and the speed of sound, the distance can be calculated. Ultrasonic detectors are a great result for the discovery of clear objects.

Abstract-Innovation in robotic arm control has been sparked by the development of Arduino-based technology, which provides both experts and enthusiasts with an affordable and user-friendly platform. The creation of robot arm control with an Arduino controller is presented in this work. The project entails integrating sensors and Arduino microcontrollers to provide dynamic and accurate control over a robotic arm. Four servo motors—which rotate left, right, front, and back—control the suggested robot. The study lays the groundwork for future developments in this emerging topic by discussing the difficulties faced during the development process and offering solutions. The demonstrated robotic arm control system has the potential to increase access to robotics education and promote automation innovation due to Arduino’s broad availability and low cost.

Abstract-This research examines the impact of artificial intelligence (AI) and machine learning (ML) on improving human resource (HR) decision-making procedures, with an emphasis on the years from 2015 to 2025. Employing a bibliometric approach, the study uncovers trends, obstacles, and prospects related to artificial intelligence and machine learning usage in human resource management. The results depicted in Figure 1 (“Document by Year”) indicate a marked rise in research activity after 2020, emphasizing an increasing interest in the incorporation of AI and ML in HR practices. Figure 2 (“Document by Area”) illustrates that computer science (45%) and business studies (30%) lead in research contributions, highlighting the technical and strategic aspects of these technologies. The geographic analysis shown in Figure 5 (“Document by Country”) reveals that 40% of the studies come from the United States, while European and Asian nations account for 30% and 20%, respectively. Institutional contributions, shown in Figure 7 (“Document by Affiliation”), indicate that 60% of research originates from academic institutions, while corporate research centers account for 25%. Figures 3 and 4 underscore the variety of sources and funding, showing a balance between academic integrity and practical uses, with government funding representing 50%. The research highlights the revolutionary impact of Artificial intelligence and Machine learning in human resource management, especially concerning talent acquisition, employee engagement, and workforce management. Nevertheless, ethical issues, biases in algorithms, and privacy threats present significant challenges. By combining technological advancements with ethical guidance, as illustrated by the trends shown in the figures, organizations can develop adaptable, inclusive, and effective HR systems that meet the changing needs of the workforce.

Abstract-Heart attacks remain a critical global health issue, necessitating accurate predictive models to identify at- risk individuals and support preventive care. This project, titled “Heart Attack Risk Assessment Using Deep Learning with Feature Optimization,” applies deep learning techniques to assess the likelihood of a heart attack. The study utilizes a Fully Connected Neural Network (FCNN) model enhanced by feature optimization methods, ensuring that the most relevant predictors are prioritized. Additionally, the project incorporates risk visualization, enabling clear and actionable insights for early detection and management of heart attack risks.

Abstract-This journal discuss in detail on a suggested medication reminder device that will be made for senior citizens based on their problems. This study’s background is explained in the report, and its primary goal is to guarantee that the medication reminder device will be resolving issues that older people have. The problems that have been discovered are mostly focused at the elderly and are meant to address the problems that they encounter on a daily basis, particularly with regard to medication use. In order to design a better device, the study will also examine similar implemented devices and systems to determine the advantages and disadvantages of other pertinent devices and systems. This portable and economical system would be helpful to every age group also.

Abstract-Microglia, the principal immune cells within the central nervous system (CNS), are essential for maintaining neuronal homeostasis. Nonetheless, the chronic activation of microglia has been associated with the development of neurodegenerative diseases, notably Alzheimer’s Disease (AD) and Parkinson’s Disease (PD). This review investigates the mechanisms underlying microglial activation, the dual functions of microglia in neuroprotection and neurotoxicity, and the implications for therapeutic strategies. By examining contemporary research, we aim to clarify the molecular pathways that link microglial activation to the progression of these diseases and identify potential approaches for modulating microglial responses to alleviate neurodegeneration.