International Journal of Research in Engineering, Science and Management
Call for Papers Publish in Multidisciplinary Journal Volume 8, Issue 11, November 2025 (In Progress) 7000+ Articles | 10,000+ Authors | 30+ Countries Publication Process Submit Manuscript ISSN (Online): 2581-5792 Publication Frequency: Monthly Subject/Scope: Multidisciplinary Areas Publication Format: Online CrossRef DOI is assigned to all published articles Free e-certificates for all authors Fast Publication: Within 3 Days Article Publication Fee (APC): $52 (Africa), $59 (Others), ₹2000 (India) International Journal of Research in Engineering, Science and Management, is an open-access International Journal for Paper Publication. To publish a paper, the authors can submit research papers, case studies, survey papers, academic project works, scholarly articles, academic articles, original or extended versions of previously published papers in conferences, and basic advances from all the areas of academic disciplines. With a broad scope, the journal is focused on multidisciplinary research, from the viewpoints in the advancement of research. The journal welcomes articles from all the academic disciplines. The journal aims to provide a platform for authors to publish research work online. Students at graduate and post-graduate levels are welcome to publish project papers. Academicians, and researchers, who carry out research can submit and publish research work in the IJRESM journal. The authors who wish to publish a paper in IJRESM, are advised to read the publication process and submit a paper for publication.
Innovative Technologies for Water Conservation in Warming Climate
Climate change is intensifying global water scarcity through rising temperatures, altered precipitation patterns, and increased evapotranspiration. This paper explores innovative technologies that offer sustainable solutions for water conservation in a warming climate. Key advancements include smart irrigation systems, atmospheric water harvesting, solar-powered desalination, precision agriculture, and advanced wastewater recycling. Through a review of recent case studies and performance evaluations, the paper highlights the potential of these technologies to enhance water-use efficiency, diversify supply sources, and build climate resilience. While the technologies show promise, successful implementation depends on factors such as cost-effectiveness, policy support, and local adaptability. An integrated, context-sensitive approach to technology adoption is critical to ensuring long-term water security in an era of climatic uncertainty.
Copyright (c) 2025 Vinayak S. Patil, Rahul N. Rane, Vishal D. Sutar, Sajid R. Shaikh, Vinayak D. Tambekar https://creativecommons.org/licenses/by/4.0
Optimization of Air Velocity and Fan Speed for Improved Outlet Temperature in Water–Air Heat Exchanger Drying Systems
The increasing demand for sustainable thermal energy solutions in food processing. House heating and other domestic applications has intensified interest in solar-assisted drying systems, particularly those integrating heat exchangers to deliver controlled drying air conditions. Efficient dehydration of agricultural products requires precise regulation of air temperature, humidity, and flow rate to preserve quality while minimizing energy consumption. However, determining the optimal combinations of these parameters remains a major challenge, especially for systems relying on variable renewable energy sources such as solar thermal input. This study develops a comprehensive mathematical model for a solar-powered food dryer incorporating a counter-flow water-to-air heat exchanger and a forced-convection drying chamber. The model describes heat and mass transfer dynamics using thermodynamic laws, fluid flow relationships, and heat exchanger effectiveness–NTU formulations. A detailed derivation of heat exchanger performance is presented, linking outlet air temperature to key variables including water inlet temperature, heat transfer area, overall heat transfer coefficient, air velocity, fan sweep area, and volumetric flow rate. By reformulating the number of transfer units (NTU) as a direct function of air velocity, an explicit expression for air-side control of outlet temperature is obtained. Simulations using experimentally realistic parameters show that air velocity, fan speed, and fan diameter exhibit inverse relationships with outlet air temperature; reducing air mass flow increases residence time within the exchanger, thereby improving thermal pickup and raising outlet temperatures. The drying chamber temperature evolution, and air–product interaction is regulated using a feedback-based control strategy to obtain robust drying conditions throughout the dehydration process, ensuring that food products are exposed to temperatures below their thermal degradation thresholds. Pontryagin’s Maximum Principle was used to determine the optimal drying air temperature, with respect to airflow velocity, and fan speed. Results demonstrate that a heat exchanger of area 2.827m2 with inlet water temperature at 000C flowing at Vl=1.128l/s, can transfer heat up to 75.60C of air temperature up from 250C working at efficiency of ε(v)=06826 and fitted with a fan of are Af=0.05m2 spinning at v=20 RPS. These parameters can be adjusted for a different desired output air temperature. The optimization model framework offers a tool for enhancing dryer performance, guiding design decisions, and reducing energy costs in solar-assisted food processing systems.
Copyright (c) 2025 Kenneth Korkoren, Titus Rotich, Samwel Rotich https://creativecommons.org/licenses/by/4.0
IoT-Enabled Autonomous Waste Segregation System with Real-Time Monitoring for Smart Cities
Urban waste management represents a critical challenge for modern smart cities, where traditional collection methods prove increasingly inadequate due to rapid population growth and environmental concerns. This research presents the development and implementation of an innovative IoT-enabled autonomous waste segregation system that integrates real-time monitoring capabilities for enhanced municipal waste management operations. The proposed system utilizes ESP32-based microcontroller architecture combined with multiple sensor technologies including ultrasonic distance sensors, load cells, and optical classification modules to automatically categorize waste into biodegradable, non-biodegradable, and hazardous categories. Through comprehensive experimental validation, the system demonstrates 92.4% classification accuracy while providing continuous waste level monitoring with alert generation capabilities. The implementation incorporates cloud-based data analytics and a centralized dashboard interface that enables municipal authorities to optimize collection routes and make data-driven operational decisions. Field testing across multiple deployment scenarios reveals significant improvements in collection efficiency, reducing unnecessary trips by 38% and operational costs by 24%. The system's modular design ensures scalability for city-wide deployment while maintaining low power consumption through optimized embedded programming techniques. Results indicate substantial potential for transforming conventional waste management practices through intelligent automation and real-time data insights, contributing to sustainable urban development goals.
Copyright (c) 2025 Jatin Kadyan, Neetu Bala, Shubham Tanwar, Deepanshu Khudotia https://creativecommons.org/licenses/by/4.0
Effectiveness of Facilitated Tucking Position on Level Pain During Pentavalent Vaccination Among Infants at Selected Primary Health Centres, Bengaluru, Karnataka State
The pain associated with such injections is a source of distress for children, their parents and those administering the injections. If not addressed, this pain can lead to procedural anxiety in the future, needle fears and health care avoidance behaviors, including nonadherence with vaccination schedules. A true experimental study aimed to assess the effectiveness of facilitated tucking position on level of pain during pentavalent vaccination among infants in selected primary health centers, Bengaluru. Objectives: 1. To assess the level of pain during the pentavalent vaccination among infants in experimental and control group. 2. To assess the effectiveness of facilitated tucking position on level of pain during pentavalent vaccination among infants in experimental group. 3. To find out an association between the level of pain among infants receiving pentavalent vaccination with their selected demographic variables. Methods: A quantitative research approach, true experimental post- test only control group design was used, with non-probability purposive sampling technique. The sample size was 30 infants in experimental group and 30 infants in the control group. Data was collected from 60 infants using structured interview questionnaire which consists of the demographic, infant variables, maternal variables, clinical variables, parenting factors and Neonatal Infant Pain Scale Score checklist was used to assess the level of pain among infants. Facilitated tucking position was given during pentavalent vaccination to the experimental group and control group received vaccination without the intervention, post-test was scheduled during vaccination. Results: The findings of the analysis revealed that Mean pain score among the infants in the experimental group was 5.0 with SD of 1.37 whereas mean pain score of the infants in the control group was 5.7 with SD of 1.22. The mean difference score was 0.7. The calculated independent ‘t’ test value of t- value= 2.2, was found to be statistically significant at p< 0.05 level and the p- value= 0.03. which infers that there was evidence that facilitated tucking position was effective in reducing pain level among infants during pentavalent vaccination. Interpretation and conclusion: In the present study, the researcher analysed the effectiveness of facilitated tucking position among infants during pentavalent vaccination; the results infer that there was a subsequent reduction in the level of pain in experimental group. Hence it is proved that facilitated tucking position is effective in reducing the pain level among infants during pentavalent vaccination.
Copyright (c) 2025 Julice Varughese https://creativecommons.org/licenses/by/4.0
AI-Powered Automated Resume Screening and Job Matching System Using NLP and Machine Learning
Recruiters in today’s job market are frequently presented with the daunting challenge of screening thousands of resumes for one vacancy position, leading to inefficiency, bias, and lost opportunities. Conventional resume screening processes are not scalable and tend to overlook the best candidates, particularly when subtle skill sets and varying levels of experience are factors. To solve these issues, this paper suggests an automated resume screening system powered by AI that uses Natural Language Processing (NLP) and Machine Learning (ML) to simplify and improve the hiring process. The system is meant to scan unstructured resumes, extract key information like education, skills, experience, and certifications, and compare these features against pre-defined job descriptions. Employing sophisticated NLP methods, the system converts text data into semantic vectors and matches them with job requirement profiles based on similarity measures and classification techniques. It ranks candidates according to their relevance and categorizes them into groups like “fit,” “close fit,” or “not fit,” thereby helping recruiters make informed hiring decisions. In addition, the system features a web-based dashboard through which HR staff and recruiters can upload resumes, enter job specifications, and view candidate matching results in real-time. This easy-to-use interface not only minimizes the cognitive burden on recruiters but also shortens the recruitment cycle and enhances overall recruitment effectiveness. The suggested framework has been tested with real world resume datasets and exhibits high accuracy in matching and classification tasks. With potential uses across industries, this system is a major advancement toward intelligent, equitable, and scalable hiring solutions.
Copyright (c) 2025 Vernika Khatri, Vikas Kumar, Kapil Thakur, Vikash Kumar, Tanisha, Vani, Rishav Yadav https://creativecommons.org/licenses/by/4.0
Parenting Styles and Emotional Regulation in Adolescents
Background: Adolescents with poor emotional regulation often experience difficulties managing impulses, handling interpersonal relationships, and maintaining psychological stability. Research suggests that parenting styles play a pivotal role in shaping the emotional and behavioral development of children and adolescents. Both authoritarian and permissive parenting styles have been associated with emotional dysregulation, low self-esteem, and externalizing or internalizing behavioral problems. Objectives: This study aimed to investigate how various parenting styles contribute to the development of poor emotional regulation in adolescents. It further examined therapeutic approaches that focus on restructuring family communication, improving parental attunement, and promoting authoritative parenting practices to enhance emotional regulation in adolescents. Methods: A comprehensive literature review was conducted, synthesizing empirical findings and theoretical frameworks from studies by Baumrind (1967, 1991), Belsky (1984), Buboltz et al. (2007), and others. Additionally, qualitative research themes were analyzed to identify patterns related to family communication, parental modeling, emotional attunement, and therapy as a behavioral modeling tool. Results: Six major themes emerged: (1) characteristics of emotionally dysregulated adolescents, (2) ineffective communication in the family system, (3) parental modeling of poor emotional regulation, (4) lack of parental attunement, (5) therapy as a modeling technique, and (6) individual work with parents. Supplementary themes emphasized the use of specific therapeutic techniques, including communication training, mindfulness, and relaxation strategies, which correlated strongly with improved emotional regulation outcomes. Conclusion: The findings reinforce existing literature linking parenting styles to adolescent emotional regulation and extend current understanding by emphasizing the therapist’s role as a behavioral model. Integrating family-based interventions, mindfulness training, and authoritative parenting strategies can effectively promote emotional regulation and strengthen family relationships.
Copyright (c) 2025 https://creativecommons.org/licenses/by/4.0
The growing demand for efficient agricultural solutions has paved the way for smart plant monitoring systems. This research presents PMS—an IoT-based system that integrates the ESP8266 Wi-Fi module with soil moisture, temperature, and humidity sensors to enable real-time plant health monitoring. Data is stored in Google Firebase, while a mobile application provides farmers with remote access to plant conditions. A key feature of this system is its automated irrigation mechanism, which activates when soil moisture drops below a predefined threshold, thereby reducing water wastage and ensuring timely watering. This not only improves water efficiency but also minimizes human intervention in routine plant care. During implementation, challenges such as unstable connectivity and variations in sensor accuracy were observed. Despite these limitations, the results demonstrate that PMS can effectively automate irrigation, promote healthier plant growth, and enhance resource utilization. Its scalability and cost-effectiveness make it suitable for precision agriculture, while future enhancements may include AI-based predictive analytics and solar-powered operation for greater efficiency and sustainability.
Copyright (c) 2025 Shreeya Dinesh Rajput, Shrawani Mohan Patil https://creativecommons.org/licenses/by/4.0
Socio-Economic Conditions of Fishermen: A Sociological Study (With Special Reference to Tarikere Taluk)
Fisheries in India are an important sector of the Indian economy, contributing 1.07% of its GDP. The fisheries sector in India supports the livelihoods of over 28 million people in the country, particularly in coastal and vulnerable communities. India is the world's third-largest fish producer, accounting for 7.96% of global production, and the second-largest producer of fish through aquaculture after China. Total fish production in 2020–21 is estimated at 14.73 million metric tonnes. According to the National Fisheries Development Council, the fisheries industry generates export earnings of ₹334.41 billion. Centrally sponsored schemes are expected to boost exports by ₹1 lakh crore in FY5. Under these projects, 65,000 fishermen have been trained from 2017 to 2020. Freshwater fisheries constitute 55% of the total fish production.
Copyright (c) 2025 S. K. Mohana https://creativecommons.org/licenses/by/4.0
Applications and Energy Modelling of UAVs in Mobile Networks
Unmanned Aerial Vehicles (UAVs), commonly known as drones, have emerged as transformative tools for enhancing mobile network capabilities. With the rise of 5G networks and the impending implementation of 6G, UAVs play a crucial role in expanding coverage, enhancing connectivity, and facilitating communication in challenging environments. This paper reviews some of the applications of UAVs in mobile networks and, their significance in low-power communication systems. Further arithmetic modelling of energy consumption is also discussed, including ongoing research and technological developments.
Copyright (c) 2025 Arnav Sawant, Aryan Sawant https://creativecommons.org/licenses/by/4.0
Synthesis of Porous Carbons from the Valorization of Polyethylene Terephthalate Waste
Upcycling plastic waste for water remediation is a promising paradigm for enabling a circular economy. This study aimed at investigating the synthesis of porous carbons from waste polyethylene terephthalate (PET) bottles using potassium hydroxide and zinc chloride as activating agents at temperatures ranging from 700 to 800°C. The influence of different activating agents and activation temperatures on the characteristics of porous carbons was investigated. The morphological and structural characteristics of the resultant porous carbons were analyzed using scanning electron microscopy (SEM), Raman spectroscopy, and nitrogen physisorption surface area analysis. The SEM data revealed interconnected porous morphologies for all the porous carbons obtained. Raman spectra showed two distinct D and G bands at 1336-1347 cm⁻¹ and 1587-1599 cm⁻¹, respectively, indicating carbon graphitic structures. The ID/IG ratios revealed varying degrees of graphitization depending on the activation agent and temperature. The highest surface area obtained was 289 m²g⁻¹ at 800°C with porous carbons synthesized using KOH as the activating agent. This study demonstrates that waste PET is a viable and sustainable precursor for fabricating porous carbons.
Copyright (c) 2025 Judy K. Mwiti, Martin Magu, Bridget K. Mutuma, Dickson Andala https://creativecommons.org/licenses/by/4.0
Link Prediction and Cascading within Subreddits
Reddit is a social news aggregation and discussion website, where members post content like text, posts, images etc. Posts are organized by subject boards called “communities” or “Subreddits”, which cover various topics such as news, politics, science, movies, video games etc. “Subreddits” become a channel of propagation of information when a post at one subreddit is linked or tagged in another subreddit. We formulate this network as a Graph, where each node is a “Subreddit” and edges are existing hyperlinks between them. Given a pair of nodes (“Subreddits”) in that graph, we wish to predict the probability that of one subreddit hyperlinking or tagging a post in the other subreddit.
Copyright (c) 2025 Sunjeet Jena, Aayush Sharma, Oluwaseun Talabi, Ankit Sharma, Akhil Mittal, Rajath Manjunath https://creativecommons.org/licenses/by/4.0
Assisting Visually Impaired People to Detect Objects Using Machine Learning
Navigating the world poses significant challenges for the visually impaired, compounded by the limited availability of suitable technological solutions. Traditional aids often fall short in providing real-time assistance and fail to address the nuanced complexities of everyday tasks. Our project aims to bridge this gap by introducing a comprehensive solution tailored to the unique needs of visually impaired individuals. By capturing live footage of their surroundings, our system offers immediate access to visual information previously inaccessible to the user. Through an advanced image processing module, the captured images are analyzed and interpreted in real-time, enabling the identification of objects, obstacles, and spatial cues. This information is then seamlessly converted into spoken feedback using a text-to-speech module, empowering users with clear auditory guidance to navigate their environment confidently. With a focus on usability and effectiveness, our project represents a significant step forward in enhancing the independence and quality of life for the visually impaired community. By leveraging cutting-edge technology, we aspire to create a more inclusive world where everyone has equal access to information and opportunities.
Copyright (c) 2025 Harditya Shah, Sahil Nannaware, Rohit Singh, Jyoti Ramteke https://creativecommons.org/licenses/by/4.0
Development and Characterization of Magadiitic Aluminosilcate Nanozeolite Adsorbent Using Magadi Salt from Lake Magadi, Kenya
A Magadiitic Aluminosilicate nanozeolite (AP-05-02) was developed from Lake Magadi’s Magadi salt, Kenya, as a cost-effective water adsorbent, confirmed by XRD, EDX, FT-IR, XRF and SEM analysis to possess a porous aluminosilicate structure for water pollution reduction. Its aluminosilicate nature was verified by FT-IR analysis showing characteristic framework vibrations, and its chemical composition determined by XRF, revealed high SiO₂ (77.282 %), Al₂O₃ (12.400 %), and K₂O (7.469 %) contents, while SEM showed a rough surface with agglomerated particles and interconnected pores. The provided data described a nonparticulate material (around 21 nm) with a well-developed porous structure, characterized by a high surface area (285.88 m²/g BET, 895.80 m²/g, Langmuir), signifying total pore volume (0.231 cm³/g), notably high volume of micropores (0.242 cm³/g) and ultra-micropores (0.044 cm³/g). The pore distributions, including ultra-micropores suitable for molecular sieving and mesoporous average pore diameter (32.3–78.3 Å) adding to the material versatile adsorption capabilities and further will enhance its functionality in specific separation application.
Copyright (c) 2025 Janes Bochaberi Omoko, Njagi Njomo, Deborah A. Abong’o, Dickson M. Andala https://creativecommons.org/licenses/by/4.0
Zakat Institution: A Study on its Contribution to Community Development in Talipao, Sulu
The institutionalization of zakat in Talipao is not accurately and highly specialized, but it is only suitable to the ability and power that could be done by the people of Talipao as a zakat institution, though not highly institutionalized. It is only appropriate to the level standard of the adat (tradition) of the community. Fortunately, it could give realization to the mind of the individual Muslims in Talipao. Furthermore, zakat institution had already been materialized some developments in Talipao, Sulu that the people of said community can at least be having a suitable comfort in terms of worship in the masjid and knowing Islam in the madrasah. In addition, there is also a dividend from zakat institution given to the needy and poor individuals as their suitable livelihood assistance. The Da'wah Al-Islamiyyah is also conducted in the Talipao community; the people have learned more Islamic knowledge and understanding that can lead them to worship Allah (SWT) alone properly in a manner of the Prophetic Sunnah. They have seen the reality of Islam that is being glittered under the teaching process of Da'wah Al-Islamiyyah. Under the development in Talipao, individual students have learned Islamic science under the principle of Islamic education which is conducted in a madrasah created in Talipao. However, they use Islam in a way that can lead them to comfortable living amd support their Islamic morality. This principle has served them as their wisdom and philosophy in their life. Even the zakat institution has faced challenges such as management, organization, process and mostly war between the MNLF and GRP during the Marcos regime in the early 1970s. However, with all the challenges that zakat institutions have faced, the institution has a prospect beyond Talipao, Sulu. It dreams to remain in touch with its goals and objectives of the future of the Talipao through one generation after another. It has been aiming to remain steadfast and determined to continue the mission of past forefathers and to the future progress in Talipao Sulu. The researcher is recommending that the zakat institution in Talipao must maintain the good outlook of the organization, management and process of the zakat institution so that it can provide strong resistance of the organization including its program objectives that are being carried out in the process of the implementation of its plan and development in the Talipao community as a whole. It should be doing its obligation and duties on every activity being done. Its tendency is that it can maintain its determination to survive along the process in all its objective with all constituents including all inhabitants of Talipao and their necessities throughout life. This must be done correctly in light of Islamic principles and teachings as well as its wisdoms.
Copyright (c) 2025 Alphata Jairi Untih https://creativecommons.org/licenses/by/4.0
Artificial Intelligence in Transactional Data Analysis: A Data-Centric Analysis of Customer Behavior in the U.S.A.
The rapid expansion of digitalization in the financial services sector has changed the relationship way of customers with banks while creating new opportunities and challenges regarding the understanding of transactional behavior. This work will explore Artificial Intelligence in Transactional Data Analysis: A Data-Centric Analysis of Customer Behavior using composite models that represent demographic, temporal, and geographic context along with predictive modeling. The study utilizes descriptive statistics, ANOVA, clustering unity, and time-series forecasting on data from U.S. bank customers on Kaggle, contributing clarification to multiple dimensions with more than 2,500 observations supplemented by Federal Deposit Insurance Corporation (FDIC) and Federal Reserve data. The life-cycle patterns are evident that the middle-aged have classified as the highest balances and volumes, whereas transactions with students are numerous but lower in value and seniors are still heavily branch dependent. Temporal patterns reveal daily transactions that take place between Tuesday and Thursday are higher than other days of the week and the seasonal peaks in August-September. While urban centers have demonstrated the most successful adoption and integration of digital technologies, rural populations remain excluded. Predictive models estimate a churn risk as around 20% and indicate that the problem is associated with the inactive customers, whereas clustering analysis isolates a pattern of four different behavioral groups of customers that have their own managerial relevance. The study uses smart ideas about the Life-Cycle Hypothesis, Technology Acceptance Model (TAM) and Behavioral Economics to show how AI can be used to analyze banking transactions. It also focuses on making sure the AI is ethical that it is fair, easy to understand, and works for everyone. This makes the research useful both for scholars and for practical use in the real world. These results provide banks with data-driven metrics by which to improve retention, improve the investment between digital and physical channels, and incorporate best practices for the deployment of responsible AI that builds customer trust and helps financial inclusion.
Copyright (c) 2025 Kazi Shakhawat Hossain, Faysal Ahmed, Maksuda Akter, Md. Belayet Hossain https://creativecommons.org/licenses/by/4.0
The Effect of Reciprocal Mentoring on the Performance of the Kenya Defence Forces: The Moderating Role of Organizational Culture
This study evaluated how organizational culture moderates the relationship between multigenerational techniques and the organizational performance of the Kenya Defence Forces (KDF), with a particular focus on reciprocal mentorship. The design used was an explanatory sequential mixed-methods design. 193 KDF personnel at Isiolo Barracks were chosen by stratified random sampling, and quantitative data was gathered from them using a standardized questionnaire. Multiple regression analysis, correlation, and descriptive statistics were performed. The quantitative results were enhanced by qualitative information gleaned from interviews. A 5% significance level was used for testing the hypotheses. According to the study, reciprocal mentoring significantly improved organizational performance (β=0.468, p<0.05). A supportive culture increased the success of multigenerational methods, as evidenced by the substantial, significant positive moderating effect of organizational culture (β=0.8339, p<0.05). Generalizability was limited by the study's geographic focus on a single barrack. The study recommended that various KDF units should be longitudinally included in future studies. The results suggested that in order to fully use its intergenerational workforce, KDF leadership should establish formal reciprocal mentoring programs and actively foster an inclusive workplace atmosphere. This study bridged the gap in the literature by providing real data from an African military setting on the connection between performance, organizational culture, and reciprocal mentorship.
Copyright (c) 2025 George Katumpe https://creativecommons.org/licenses/by/4.0
School Heads’ Competencies in the Lens of VUCA: Basis for Strategic Management Plan
This study aimed to explore the management competencies of school heads in the lens of VUCA (Volatility, Uncertainty, Complexity, Ambiguity). It assessed the school heads’ level of management competencies in terms of personnel development, financial and resource management, classroom instructional support, project and program implementation, and stakeholders’ engagement. Additionally, the research investigated the differences on the school management competencies among school heads in the three Schools Division Offices (SDOs) in Quezon province. Furthermore, the study identified the issues and challenges encountered by the school heads in managing schools in the province of Quezon. The study used the descriptive multi-methods design with a researcher-made survey questionnaire as the primary data-gathering instrument, which was substantiated by interviews and a focus group discussion with the participants. Results revealed that school heads possess management competencies across most indicators to a great extent. It was also revealed that there is no significant difference among the school heads’ management competencies. The study identified challenges and issues in school management such as insufficient funding, lack of classrooms and other school facilities, incomplete learning materials such as books, teachers’ inability to use modern instructional equipment and applications effectively, teachers’ lack of training in inclusive education, stakeholders’ limited opportunities, and resources to participate in implementing school projects, programs, and activities. Based on the key findings, a strategic management plan was designed to enhance the school heads’ competencies in handling challenges and issues brought by the VUCA environment.
Copyright (c) 2025 Nilo C. Villamin https://creativecommons.org/licenses/by/4.0
Delineation of Aquifer Fluids for Groundwater Prospecting Using a Digital-Analogue Terrameter in Rumuosi, Rivers State
Groundwater remains the most reliable source of potable water in the Niger Delta due to inadequate public supply and increasing urbanization. This study focuses on the delineation of aquifer fluids for groundwater prospecting in Rumuosi, Rivers State, using a digital–analogue terrameter. The aim was to characterize subsurface aquifer zones, evaluate fluid properties, and recommend viable groundwater prospects. Electrical resistivity surveys were conducted using the Schlumberger configuration for Vertical Electrical Sounding (VES) and selected 2D profiles. Data acquisition involved systematic electrode expansion to probe shallow and deeper subsurface horizons, with resistivity inversion applied to generate geoelectric models. The results revealed shallow conductive zones (0–20m) associated with contaminant plumes and clay-rich sediments, overlying more resistive aquiferous layers between 22–45m. Productive confined aquifers were delineated at depths beyond 45m, with the most promising horizons occurring between 50–110m and extending laterally up to 90m horizontal spread. These resistive zones correspond to freshwater aquifers with high porosity and permeability, suitable for sustainable borehole development. However, vulnerability was noted in areas where conductive plumes migrate downward, threatening aquifer integrity in the long term. The study concludes that deeper confined aquifers in Rumuosi remain viable for groundwater exploitation, provided protective casing and monitoring are implemented. This research demonstrates the effectiveness of resistivity methods in aquifer fluid delineation, supporting sustainable water resource planning in the Niger Delta.
Copyright (c) 2025 Rorome Oghonyon, Victoria Okereke, Titus Romanus https://creativecommons.org/licenses/by/4.0
Student Knowledge, Consumption Patterns and Health Effect of Using the ‘Fortified Food’: A Cross-Sectional Study Among Rural and Urban Areas College Students
Background: Food fortification is a key nutritional intervention aimed at preventing and controlling micronutrient deficiencies globally. By adding essential nutrients, such as vitamins and minerals, to improve their nutritional value. These nutrients may be lacking in natural foods due to various factors like soil depletion, processing and cooking. Fortification helps prevent nutrient deficiencies, promotes overall health, and supports specific bodily functions. Fortified foods play a crucial role in maintaining public health, particularly in regions where access to nutrient-dense foods is limited. Fortified foods are enriched with various nutrients, including – Iron, Calcium, Zinc, Folic acid, Potassium, Vitamin-D, Vitamin-A, Vitamin-B12, Omega-3-fatty acids etc. These nutrients are added to various food products to enhance their nutritional value and help to prevent deficiencies of different micronutrients like iron (deficiency of which results anaemia), vitamin D (deficiency of which results rickets and osteomalacia), vitamin A (deficiency of which results xerophthalmia), calcium & vitamin D (deficiency of which results osteoporosis) etc. Objective: The study aimed to determine the knowledge, consumption and effect on health towards the usage of fortified food among rural and urban areas college going students. Methods: This was a cross-sectional study conducted in the college students having the age group between 19 – 24 years. The study was carried out by random sampling among 100 students. This survey study was carried out through questionnaires method and a face-to-face interview among those students.
Copyright (c) 2025 Baisakhi Ghosh, Debalina Mukherjee https://creativecommons.org/licenses/by/4.0
Dynamic Multi-Scale Quantization: A Quantization Technique for Efficient Large Language Model Compression
Quantization techniques are crucial for reducing the computational and memory requirements of large machine learning models, particularly large language models (LLMs). Existing quantization methods often tradeoff between accuracy and efficiency, with limitations in adaptability to diverse workloads and hardware environments. This paper introduces Dynamic Multi-Scale Quantization (DMSQ), a framework combining adaptive precision scaling, per-layer calibration, and workload-aware optimization to address these challenges. We present the mathematical foundations of DMSQ, detail its implementation, and demonstrate its effectiveness through experimental evaluation. DMSQ achieves significant compression while maintaining high accuracy, making it suitable for deployment on resource-constrained devices.
Copyright (c) 2025 Ayush Bodade, Bhavesh Chaudhari, Akshat Biniwale, Sudhir Dhage https://creativecommons.org/licenses/by/4.0
Boosting Performance with Data-Driven Dashboards
In the current context of significant challenges faced by businesses, particularly in the pharmaceutical sector, human resources management becomes crucial. This article focuses on the strategic role of the Human Resources Dashboard (HR Dashboard) as a tool for improving performance within a pharmaceutical company. The HR Dashboard is presented as an essential instrument for guiding, coordinating, and monitoring activities related to human resources (Alazard and Separé, 2007). The aim of this research is to delve into various aspects of the HR Dashboard, from its theoretical foundations to practical application, emphasizing its central role in effective human capital management. The adopted methodology relies on a qualitative approach, featuring a single case study within a pharmaceutical company, safeguarding data confidentiality. Information gathering was conducted through semi-structured interviews with key stakeholders. The article is structured into two parts: a theoretical exploration of the HR Dashboard, covering its specific design within the pharmaceutical context, and a practical analysis of results obtained from the case study. The findings of the case study conducted within the pharmaceutical company demonstrate the effectiveness of the HR Dashboard as a decision-making tool, enabling specific corrective actions for continuous performance improvement. This study contributes to understanding the impact of the HR Dashboard on performance in the pharmaceutical sector.
Copyright (c) 2025 Dlimi Soumaya, Fazroun Abir https://creativecommons.org/licenses/by/4.0
Utilizing the Exploration-Adventure Approach for Junior High School Students Toward Mastery of Exponents
The objective of this research was to assess the effectiveness of the Exploration-Adventure Approach toward mastery of exponents. The study used a quasi-experimental design of research. The participants were 44 Grade 9 learners. A researcher-made test and a survey questionnaire were the main data-gathering instruments. Statistical tools include frequency distribution, dependent t-test, weighted mean, and composite mean. The results indicated that the Exploration-Adventure Approach significantly elevated students' mathematical proficiency from an initial stage characterized by a low mean percentage score in exponents to a proficient level, underscoring the effectiveness of the intervention in enhancing their mathematical skills. Moreover, there is a significant difference in the level of performance of junior high school students in mathematics focusing on exponents before and after the utilization of the exploration-adventure approach. Thus, the exploration-adventure approach effectively facilitates positive changes in the students' mathematical proficiency related to exponents. The findings also revealed that the students, through the exploration-adventure approach, were able to improve their understanding of exponent concepts, delve deeper into the study of exponents, boost their confidence in tackling exponent problems, and promote collaboration with peers in tackling exponent-related challenges.
Copyright (c) 2025 Jeffrey R. Abad https://creativecommons.org/licenses/by/4.0
Building Bridges to Excellence: Enhancing Research Competencies Among Lucsuhin National High School Teachers Through Project SERYE
This study aimed to enhance the research competencies of junior high school teachers at Lucsuhin National High School through Project SERYE (Systematic Engagement in Research Yielding Educational Excellence). A mixed-method research approach was employed, combining descriptive and phenomenological designs, with data collected through documentary analysis, a researcher-made survey questionnaire, and interviews. The study involved 81 junior high school teachers, selected through random sampling. The sample size was determined using the Raosoft Sample Size Calculator, with a five percent margin of error. Statistical tools used in the analysis included frequency distribution, weighted mean, composite mean, and a dependent t-test. Additionally, thematic analysis was applied to the qualitative data. The results revealed a significant increase in teacher participation in the Division Conference of Basic Education Researchers, with participation rising from 7.29% in SY 2023-2024 to 32.29% in SY 2024-2025. Moreover, there was a marked improvement in teachers' research competencies across various stages of the research process, from formulating research backgrounds to drawing conclusions and recommendations, highlighting the effectiveness of Project SERYE in enhancing their research competencies. Statistically significant improvements across all stages led to the rejection of the null hypothesis. Teachers' responses further indicated that Project SERYE not only transformed their attitudes toward research but also enhanced their competencies and confidence in conducting and applying research, thereby fostering their professional growth and deepening their understanding of research processes.
Copyright (c) 2025 Jeffrey R. Abad, Simeona Rechie C. Ojales https://creativecommons.org/licenses/by/4.0
Integration of Cloud Computing in eHealth
The integration of cloud computing into healthcare is transforming the delivery of medical services by improving data accessibility, scalability, and collaboration. However, for non-commercial and developing healthcare systems, selecting optimal cloud models that ensure security, affordability, and usability remains a critical design challenge. This study adopts a qualitative case study approach to evaluate the integration of cloud computing into an eHealth service initiative. Through architectural modeling and stakeholder-oriented analysis, the study proposes a multi-tier Software as a Service (SaaS) architecture deployed on a public cloud platform, aligned with key principles of cost-effectiveness, accessibility, and regulatory compliance. The proposed model facilitates real-time access to patient records, supports interoperability between healthcare providers, and enhances user experience for both patients and physicians. A detailed assessment identifies SaaS as the most appropriate service delivery model, supported by a multi-tier architecture and public cloud deployment strategy. Benefits include reduced infrastructure costs, improved disaster recovery, enhanced collaboration, and scalable expansion potential. Data security and regulatory compliance emerge as the primary risks, addressed through encryption, access control, and standards-based interoperability. Cloud computing, when carefully architected and contextually aligned with healthcare needs, offers a robust framework for eHealth transformation. The findings provide a scalable model for national-level deployment, offering strategic insights into designing cloud-based systems that balance performance, privacy, and stakeholder needs in resource-constrained environments.
Copyright (c) 2025 Deborah Chimuanya Ugwuorah, Gabriel Eigbe, Esther Ronke Ogbonna, Moses Udoisoh https://creativecommons.org/licenses/by/4.0
Floristic Diversity and Ecological Significance of the Malvaceae Family in Madhya Pradesh, India
The Malvaceae family, known for its significant ecological and economic roles, exhibits remarkable floristic diversity in Madhya Pradesh, India. This paper examines the taxonomy, phylogenetic classification, chemical diversity, historical presence as documented in fossil records, and ecological distribution of Malvaceae in the region. With biodiversity hotspots such as the Satpura and Vindhya ranges, the state provides a vital refuge for endemic and medicinally important species. The study also addresses contemporary threats such as habitat loss and climate change while underscoring the relevance of conservation strategies grounded in floristic assessments. This work integrates current botanical research with regional ecological data to provide a comprehensive understanding of the diversity, importance, and conservation needs of the Malvaceae.
Copyright (c) 2025 Rohit Kumar, Santosh Kumar Agnihotri https://creativecommons.org/licenses/by/4.0
Impact of Management Style on Organizational Culture in Public Institutions: A Study of Moroccan Public Sector Dynamics
Objective: Management style has a significant impact on organizational culture. The type of leadership adopted by managers influences not only the work environment but also the values, norms, and behaviors that prevail within the organization. This descriptive study examines the role of managerial style in shaping the organizational culture of public institutions. Methods: A cross-sectional survey was conducted among 500 officials from four public institutions in Morocco between July 2024 and October 2024. Data were collected using an online questionnaire, measuring factors related to management quality and satisfaction with organizational culture. Results: The study revealed that management style plays a crucial role in shaping and sustaining organizational culture in the public sector. Participative management styles are particularly effective in fostering a positive and dynamic culture. Specifically, it is essential that leaders in the public sector adopt management practices that promote participation, recognition, and continuous development to optimize employee performance and satisfaction. Discussion/ Conclusions: Understanding the relationship between organizational culture and the roles assumed by managers in public institutions, based on their management style, provides valuable insights for enhancing employee performance and equipping leaders with the necessary tools to adapt their management practices to employee behaviors and expectations.
Copyright (c) 2025 Dlimi Soumaya, Sibai Imane https://creativecommons.org/licenses/by/4.0
Artificial intelligence (AI) has the potential to revolutionize the drug discovery process, offering improved efficiency, accuracy, and speed. However, the successful application of AI is dependent on the availability of high-quality data, the addressing of ethical concerns, and the recognition of the limitations of AI-based approaches. In this article, the benefits, challenges, and drawbacks of AI in this field are reviewed, and possible strategies and approaches for overcoming the present obstacles are proposed. The use of data augmentation, explainable AI, and the integration of AI with traditional experimental methods, as well as the potential advantages of AI in pharmaceutical research, are also discussed. Overall, this review highlights the potential of AI in drug discovery and provides insights into the challenges and opportunities for realizing its potential in this field.
Copyright (c) 2025 J. Rekha Rani, Roshan Kumar, Muskan Shaikh, Prerana Prayasi, Zaid Naik, Mousumi Mondal https://creativecommons.org/licenses/by/4.0
Thermal Performance Optimization of Shell and Tube Heat Exchangers Using Simulation Based Design Enhancements
Shell-and-tube heat exchangers are critical components in petrochemical processing, where efficient thermal exchange directly impacts energy consumption and product quality. This study investigates the thermal performance of a legacy heat exchanger used for naphtha cooling, employing Aspen HYSYS v14 and the Exchanger Design and Rating (EDR) module to simulate and optimize heat transfer characteristics. By varying tube length, baffle spacing, and flow rates, the study identifies configurations that enhance heat duty by up to 18% while maintaining acceptable pressure drops. The optimized design demonstrates improved temperature profiles, reduced fouling risk, and enhanced energy recovery, offering a scalable retrofit strategy for industrial heat exchangers.
Copyright (c) 2025 Noble Aggrey Efemena, Peter Odiboroghene Muwarure https://creativecommons.org/licenses/by/4.0
AI-Powered Precision Agriculture for Sustainable Yield and Resource Efficiency in African Farming
This research examines the transformative potential of AI-driven precision agriculture technologies, including autonomous drones, AI-powered sensors, and advanced machine learning analytics, in enhancing agricultural productivity, resource efficiency, and sustainability among smallholder farmers in Africa. Employing predictive models based on sophisticated machine learning algorithms such as ARIMA, Random Forest, XGBoost, and LSTM, the study forecasts significant yield enhancements, improved market price predictions, and notable resource savings in water, fertiliser, and energy usage from 2022 to 2030. The findings demonstrate considerable improvements, including increased yield accuracy, optimised resource utilisation, and heightened economic viability compared to traditional farming methods. Moreover, the study identifies key barriers and opportunities that influence technology adoption, suggesting that strategic investments and targeted policy interventions are essential components for successfully scaling these innovations. Ultimately, this research provides critical insights and practical recommendations to drive sustainable agricultural development and economic empowerment across African agrarian communities.
Copyright (c) 2025 Rukayat A. Olawale, Owoade O. Odesanya, Peter T. Oluwasola, Elizabeth A. Adeola, Adeyinka G. Ologun https://creativecommons.org/licenses/by/4.0
Automated Thread Depth Verification System for Gamor Tapping Machines Using Proximity Sensors
This paper describes an automated depth gauge monitoring system for GTR-200 pneumatic tapping machines (100 PSI/6.9 BAR. The system utilizes an Omron E2E-X5D1-N inductive proximity sensor (30–60 mm range) in conjunction with a new L-shaped flag mechanism to ensure robust detection in hollow parts. Sensor data is processed by a programmable logic controller to realize threshold-based counting (99.95% accuracy), automatic batch reset after 10 cycles, and real-time error detection (under/over-depth conditions). Experimental testing over M4–M10 thread sizes shows 86% fewer defects than manual inspection, with a 17-day payback on the $185 implementation cost. No machine retooling is needed, and the system performs well in oily industrial settings (IP67-rated parts) with a user-friendly HMI display for real-time viewing. Size-variable thresholds (M4–M10 compatibility) and non-contact sensing that does not compromise tool integrity are the main innovations. This technology solves key industry problems in aerospace (AS9100D compliance) and automotive manufacturing by delivering high precision (±0.3mm), low cost (<$200), and simplicity of integration—making it perfect for small-to-medium-sized businesses looking to automate quality inspection in tapping processes.
Copyright (c) 2025 B. D. Mohan, V. Sanjaya Kumar https://creativecommons.org/licenses/by/4.0