International Journal of Modern Developments in Engineering and Science
Call for Papers Publish in Multidisciplinary Journal Volume 4, Issue 11, November 2025 (In Progress) 1000+ Articles | 2,000+ Authors | 20+ Countries Publication Process Submit Manuscript ISSN (Online): 2583-3138 Publication Frequency: Monthly Subject/Scope: Multidisciplinary Areas Publication Format: Online Publication Time: Within 3 Days Publication Fee: $52 (Africa), $59 (Others), ₹2000 (India) CrossRef DOI to all published articles No Additional Author and Page Charges Free e-certificates to authors International Journal of Modern Developments in Engineering and Science, is online, open access, journal with a focus on engineering, science, and multidisciplinary areas. The modern developments to provide a solution to societal issues not only focus on engineering, and science alone, but also on multidisciplinary areas. The journal offers authors a to share their research with the audience of engineers, scientists, professionals, and other interested people across the globe. This International Journal of Modern Developments in Engineering and Science journal is a platform to publish research to anyone working in any area of engineering in academia, industry, or government, including engineers, scientists, consultants, policy-makers, government officials, economists, and corporate organizations. This journal welcomes articles from Engineering, Science, and Multidisciplinary topics.
Rethinking the Individual–Organization Relationship in the Public Sector: A Literature Review on the Impact of Organizational Change
Face within a rapidly changing world and fierce competition between companies, organisational change is becoming a source of stability and a key to adapting to external constraints, also it is part of organisational life, since it has become a central issue for organisations (Latortue, 2017). The methodology followed in this study is positivism adapted with a deductive hypothesis, in order to discover the renewal of the individual/organisation relationship in the context of organisational change within the public sector. We will begin by studying the key concepts of the article, then the description, and finally definition of the fundamentals of organisational change and the individual/organisation relationship. The results of our study show that the public sector lacks internal communication, whereas organisational change in this sector requires a strong individual/organisation relationship based on communication and information sharing.
Copyright (c) 2025 Dlimi Soumaya, Sibai Imane https://creativecommons.org/licenses/by/4.0
The twin prime conjecture inquires whether there are infinitely many prime (p) pairs of the form (p, p+2). This longstanding problem remains unresolved in number theory. Although the infinitude of prime numbers has been rigorously established, the question of infinitely many twin prime pairs has proven considerably more challenging as numerous proposed proofs have been refuted upon closer examination. In this paper, twin primes are classified into three categories according to their final digit. Patterns arising within each category are analyzed, and a proof addressing the infinitude of twin primes is presented.
Copyright (c) 2025 Kipkirui Rono, Michael Munywoki https://creativecommons.org/licenses/by/4.0
Hydrofiber Foam vs. Alginate Dressings: A Systematic Review of Wound Healing Outcomes
Wound healing is a complex physiological process requiring moisture balance, exudate control, and infection prevention. Advanced dressings such as alginate and hydrofiber foams are widely used in clinical practice for acute and chronic wounds. Alginate dressings have long been valued for their hemostatic properties and effectiveness in managing highly exudative wounds, while hydrofiber foams represent a newer innovation designed to optimize moisture retention, promote autolytic debridement, and reduce pain during dressing changes. This systematic review critically evaluates clinical evidence comparing alginate and hydrofiber foam dressings, focusing on wound healing efficiency, infection control, patient comfort, and cost-effectiveness. Evidence shows that while both dressings support wound healing, hydrofiber foams demonstrate superior exudate handling, longer wear time, and reduced pain. Alginate dressings remain preferable in wounds requiring strong hemostatic support. Dressing choice should therefore be individualized based on wound type and patient needs.
Copyright (c) 2025 Kothwala Deveshkumar, Lad Hirenkumar, Lad Sandip https://creativecommons.org/licenses/by/4.0
The Level of Factors Affecting Cockfighters Engagement in Illegal Sabong
This study investigates the factors driving participation in illegal cockfighting ("sabong") among residents of Cateel, Davao Oriental, Philippines. Utilizing a descriptive comparative research design, a survey questionnaire was administered to 60 respondents from three barangays, selected via snowball sampling. The demographic analysis revealed a predominantly male (100%) respondent pool, with the majority aged 35-42 years old and earning ₱5,001-₱10,000 monthly. A significant number (66.7%) had been involved in sabong for five years or more. Analysis of the influence of various factors on sabong engagement showed that economic factors (mean score 4.31), entertainment factors (mean score 4.45), and learning factors (mean score 4.23) all significantly influenced participation. While age showed no significant difference in engagement levels (p=0.675), a marginally significant difference was found in relation to years of experience (p=0.05), and a statistically significant difference was observed based on monthly income (p=0.033). The study concludes that the persistence of illegal sabong in Cateel stems from a complex interplay of socio-economic pressures, cultural acceptance, and the inherent thrill of the activity. The study draws upon existing literature on gambling behavior, Filipino culture, and the Theory of Planned Behavior to contextualize its findings.
Copyright (c) 2025 Mark Raniel R. Darlo, Arnold L. Dela Luz, Darwin C. Lahaylahay https://creativecommons.org/licenses/by/4.0
This study explores structural and pattern-based factors influencing the validity of Frankl’s (Union-Closed Sets) Conjecture. By analyzing categorized families based on size, in- ternal structure, and symmetry, we assess how these characteristics impact the conjecture’s likelihood of holding. Particular focus is placed on families with high symmetry, dominant elements, or inherent union-closure. The results reveal consistent trends where certain configurations satisfy the conjecture trivially. These insights help pinpoint structural conditions that simplify the conjecture’s verification and highlight families that may present greater complexity.
Copyright (c) 2025 Muendo Joshua, Dorca Stephen, Michael Munywoki https://creativecommons.org/licenses/by/4.0
Assessment of Pesticide Usage by Kales Farmers in Kiegoi, the Upper Nyambene Carchement, Meru County, Kenya
Pesticides are widely used to protect crops from pests and diseases infestations. However, the use of pesticides in most developing countries poses serious environmental and food safety hazards. These chemicals often leave residues in vegetables post-harvest and may contaminate water sources through runoff and groundwater percolation. Given their intrinsic toxicity, the production, distribution, and use of pesticides require strict regulation and control. This study investigated the commonly used pesticides, analysed pesticides residues in kales samples. A total of 68 respondents were purposively sampled using structured questionnaire. Using a stratified random sampling method, 54 kale samples were collected and analyzed across wet and dry seasons. Samples were packed in labelled zip-lock bags, placed in a cool box, and transported to KEPHIS Analytical Chemistry Laboratory in Nairobi, Kenya where extracts were analyzed using MO301-GC-MS/MS. The Quick, Easy, Cheap, Effective, Rugged, and Safe (QuEChERS) protocol was followed for sample preparation and data processed using SPSS version 26. An independent t-test determined statistically significant differences in pesticide residue concentrations in kales and domestic water source between dry and wet seasons and compared to WHO's designated MRLs. The results indicated that 97.1% of farmers use pesticides to protect kale from pests and diseases. The most commonly used pesticides were Dithane M-45 (22.1%), Deltanex (14.7%), Nuvan (11.8%), and Captan 50 WP (11.8%). Other pesticides like Diazinol, Cyperkill, and Trophy each accounted for 7.4%, while Rufast and Roundup made up 4.4% and 1.5%, respectively. (80.9%) reported pesticide applications conducted on a weekly basis with Diazinol, Captan 50 WP, and Dithane M-45 being the most frequently applied pesticide while 16.2% of the respondents reported using Glyphosate (Roundup) on a monthly basis. 85.3% of respondents use diazinol, captan 50 WP and deltanex on their kale crops to combat aphids, leaf spot diseases, and powdery mildew and 5.9%, reported treating maize and potatoes with Dithane M-45 and Roundup. Residue analysis showed Captan concentrations ranged from 0.01533 mg/kg in the wet season to 0.04700 mg/kg in the dry season, showing a statistically significant difference (p=0.001). Deltamethrin residues ranged from 0.01467 mg/kg in the wet season to 0.04200 mg/kg in the dry season, with a significant difference (p=0.000). Diazinon concentrations increased from 0.01567 mg/kg in the wet season to 0.02567 mg/kg in the dry season (p=0.046). Dichlorvos and Diazinon residues exceeded their MRLs of 0.02 mg/kg and 0.01 mg/kg, respectively, while Dieldrin surpassed the WHO MRL of 0.05 mg/kg during the dry season, suggesting a potential food safety hazard. Mancozeb and Deltamethrin concentrations in water were found to be within the WHO MRLs of 0.02 mg/l and 0.5 mg/l, respectively. However, Diazinon and Dieldrin levels exceeded the WHO MRLs of 0.01 mg/l and 0.05 mg/l. According to the WHO classification of pesticides, Dieldrin is a Class 1a pesticide that is extremely hazardous and restricted for use. Cypermethrin, Acetochlor, and Acrinathrin levels were below their respective WHO MRLs of 0.1 mg/l, 0.3 mg/l, and 0.05 mg/l in both seasons.
Copyright (c) 2025 Kennedy Kemboi Chumar https://creativecommons.org/licenses/by/4.0
Adiabatic Logic and Subthreshold CMOS Circuit Design Using Opensource Software
Adiabatic circuits use a varying voltage source allowing for the energy to flow back and be reused, reducing power consumption. A subthreshold circuit is a circuit which operates at below transistor threshold voltages, which is the voltage it takes for the transistor to switch on. Multiple blocks using subthreshold CMOS and adiabatic were designed and simulated in ltspice and Xscheme using the opensource Skywater 130nM PDK. These blocks include baseline subthreshold D Flipflop, 1 Mhz subthreshold integrated oscillator, sub adiabatic modulo 10 divider (order of magnitude lower power than conventional Boolean approach), adiabatic phase generator, low power relaxation oscillator. These blocks can be combined to form a lower power system.
Copyright (c) 2025 Avijit Jutla, Justin Xu, Yinxuan Qiao, Daniel Abreu, Ziyuan Zheng, James T. Doyle https://creativecommons.org/licenses/by/4.0
A Comparative Study on Career Readiness and Career Identity Among Undergraduate Students: Influence of Gender, Medium of Instruction, and Academic Background
This study investigates the factors influencing career readiness and career identity among undergraduate students, focusing on demographic, educational, and contextual variables. The readiness and stronger career identity and commitment compared to their male counterparts. Similarly, students instructed in English exhibit significantly greater career readiness and stronger career identity than those taught in Tamil. However, no statistically significant differences were found across academic streams (Arts, Commerce, and Science), suggesting uniformity in career preparedness across disciplines. Additionally, neither residential area (rural, semi-urban, urban) nor college location had a significant impact on career readiness or career identity, although slight trends favoring semi-urban areas were observed. The type of school attended and students’ preferred career paths did not significantly affect their career readiness or identity, despite marginally higher scores among private school students and those aspiring for higher education. These findings underscore the importance of targeted interventions that account for language and gender-based disparities while supporting holistic career development across diverse student populations.
Copyright (c) 2025 C. Dhayanand, S. Archana https://creativecommons.org/licenses/by/4.0
A MERN Stack and Next.js Based Freelancer Marketplace for Local Services with Secure Authentication, Profile Management, and Booking System
Freelancing has become a popular career choice for those individuals who are seeking flexibility, independence, and opportunities to work on projects which perfectly suit their interest and align very well with the skills they possess. Yet, local freelancers find it hard to attract clients locally because of a shortage of specialized platforms. This paper outlines the design and implementation of a localized freelancer marketplace built using the MERN stack and Next.js. The platform aims at bridging the gap between local freelancers and clients by offering secure authentication, customizable and personalized freelancer profiles, and a real-time booking system. It tries to address key limitations which are there in the existing global platforms by focusing on locality, security, and seamless user experience. The proposed system emphasizes secure transactions, smooth communication and helps people find nearby services, making it simple for clients and service providers to connect and work together.
Copyright (c) 2025 Prince Kumar, Harshit Pandey, Jatin Salhan, P. Sree Ram, Naman Swarup, Sarvesh Chopra https://creativecommons.org/licenses/by/4.0
Implementation, Success, and Challenges of LGU San Jose Disaster Risk Reduction and Management
This descriptive study investigated the extent of implementation, success, and challenges of DRRM strategies of LGU San Jose, Occidental Mindoro by using stratified random sampling among 154 respondents who are members of the Barangay Disaster Risk Reduction and Management Councils (BDRRMCs). This covered the implementation in terms of prevention and mitigation, preparedness, response, and rehabilitation and recovery; level of success in reduction in disaster impact, community awareness and participation and resilience and quick recovery; and extent of challenges in education and information, manpower, equipment and facilities, and institutional coordination. This also analyzed the relationship between implementation, success, and challenges of the DRRM of LGU San Jose. Weighted mean and correlation analyses were utilized in the study. The research instrument is a survey questionnaire crafted by the author and validated by experts. The study revealed that the extent of implementation of DRRM is high in all areas but highest in rehabilitation and recovery phase. In addition, the level of success is high in all indicators but highest in reduction in disaster impact. However, the level of challenges is also high in all factors and highest in the equipment and facilities. Lastly, the study found out that there is a significant relationship between all the variables which demonstrates that as the DRRM strategies are implemented, the level of success also elevates, however the level of challenges also increases which is inherent in implementation.
Copyright (c) 2025 Czarina Maye P. San Jose https://creativecommons.org/licenses/by/4.0
Enhancing Power Prediction in Digital VLSI Circuits Using Diffusion Models: Synthetic Data Generation and Performance Evaluation
Accurate power forecasting plays a crucial role in optimizing the performance of digital VLSI circuits, particularly as design complexities continue to grow. This research delves into the use of diffusion models to create synthetic data aimed at improving the accuracy of power predictions in machine learning frameworks. Running simulations within the HSPICE environment and using advanced CMOS nodes yielded realistic datasets that were employed to train the proposed models. The synthetic data not only resembled real-world data closely but also effectively complemented limited datasets, leading to a significant improvement in power prediction performance metrics. This study underscores the potential of using data augmentation through diffusion models as an innovative strategy in VLSI design.
Copyright (c) 2025 Sinchan Roy, Sanket Jain, Satwik Khattar, Deva Nand https://creativecommons.org/licenses/by/4.0
The Impact of Police Brutality on Human Rights in India
Creating a dependable and skilled police force is essential for ensuring public safety and addressing concerns effectively. India lacks a police force of this calibre, as supported by concrete evidence from many committees, human rights commissions, media reports, and firsthand experiences of residents who have witnessed crimes. It is widely acknowledged that the police force is in dire need of essential reforms. Two separate components of police reform must be executed at the same time. reform must be implemented concurrently.
Copyright (c) 2025 Pahal Srivastava https://creativecommons.org/licenses/by/4.0
Independence is a fundamental right for every individual, including those living with visual impairments. With rapid advancements in technology over the past decades, significant efforts have been made to develop tools that assist disabled individuals in achieving autonomy. This study introduces a smart assistive system specifically designed to enhance the mobility of blind individuals by providing real-time information about their surroundings. The proposed solution employs the You Only Look Once (YOLO) object detection algorithm for high-speed and accurate identification of various objects within video streams. The system is implemented using OpenCV and Python and operates on the Raspberry Pi 3 platform, a low-cost and portable computing device. Results from the implementation show that the system is capable of recognizing multiple types of objects with high accuracy and delivering audio-based feedback to the user. This enables the visually impaired to navigate both indoor and outdoor environments with greater confidence and safety.
Copyright (c) 2025 Pramod Kumar Sagar, Anant Mishra, Akhilendra Mishra https://creativecommons.org/licenses/by/4.0
Redefining Masculinity and Feminity in Matriarchal Societies
This paper examines the way in which matriarchal societies challenge the dominant patriarchy by redefining feminist and masculinity via alternative gender power structures. Using sociological and ethnographic case studies-including the Khasi and Garo tribes of India, and the Mosuo of China, this study argues that gender roles are not natural or predetermined but socially constructed and shaped in regards to circumstances. In these cultures, women inherit property and hold household authority, while men take up the supportive, communal and ritualistic roles. These arrangements in the society displace hegemonic masculinity and promote balanced and cooperative gender identities. This paper underlines the cultural fluidity of gender and presents insights into how equitable gender relations can be sustained. The paper is a contribution to ongoing sociological debates on gender, power and cultural variation.
Copyright (c) 2025 Sunidhi Sangwan https://creativecommons.org/licenses/by/4.0
Voice assistants are software agents that can interpret human speech and respond via synthesized voices. Apple's Siri, Amazon's Alexa, Microsoft's Crotona, and Google's Assistant are the most popular voice assistants and are embedded in smart phones or dedicated home speakers. Users can ask their assistants questions, control home automation devices and media playback via voice, and manage other basic tasks such as email, to-do lists, and calendars with verbal commands. This paper will explore the basic workings and common features of today's voice assistants. Digital installation provides new opportunities to simplify everyday life using auxiliary technology tools. Amazon Alexa, Apple Siri, Microsoft Cortana, are examples of voice assistant. Voice assistant is a software that utilize artificial intelligence to take input in form of voice and then do the task accordingly. We use Various methods to convert speech into text (STT), then after processing of the text, it converts into speech (TTS). However, the smart personal assistant's study is vast. It is divided into separate branches, e.g. A computer-related environment, personal interaction with a computer as well Information systems. Various python packages are used in this project. In this paper, we have tried to present a descriptive and detailed review to provide strong support for future research. We use NLP instead of pattern identification strategies for recognizing contextual based text. It works online and offline. Python programming language is used in voice assistant. Data is stored in the app itself; it reduces the complexity of time and space.
Copyright (c) 2025 Akshay Awasthi, Karan Dwivedi, Nilesh Mani Tripathi, Vaishali Rastogi https://creativecommons.org/licenses/by/4.0
Credit Card Fraud Detection Using Machine Learning
The fraud done to credit cards has become a critical issue affecting financial institutions and consumers globally, leading to significant financial losses. This paper presents machine learning approach is employed to identify fraudulent credit card transactions by analyzing transaction patterns and behaviors. Several supervised learning algorithms, such as Random Forest, Sup-port Vector Machine, and Decision Tree, are assessed for their ability to detect fraudulent activities effectively. The study ad-dresses challenges such as data imbalance and evolving fraud tactics through feature engineering and model optimization. Experimental results demonstrate that ensemble methods pro-vide superior accuracy and reduce false positive rates, enhancing the reliability of fraud detection systems. The proposed approach contributes to strengthening financial security and protecting users from unauthorized transactions.
Copyright (c) 2025 Avinash Dua, Vishal Akash Gahlaut https://creativecommons.org/licenses/by/4.0
Pet Breed Classification and Diet Recommendation Using Deep Learning
The rising popularity of domestic pets has generated a new demand for more personalized care systems, especially regarding diet and exercise recommendations based on breed. In this paper, we present a new Pet Care Recommendation System which uses deep learning and advanced image processing techniques to identify pet breeds from images and make breed appropriate recommendations. The model utilizes EfficientNetB5, which provides a high degree of efficiency with 95% classification performance. The accuracy is a result of the design architecture, as well as being trained on a dataset that encompasses a variety of animal breed sets. After breed recognition, the model provides categorized diet plans, which outline recommendations for morning, afternoon, and evening meals per pet breed, along with a recommended walking schedule that fits the individual needs and expectations of a particular breed based on exercise knowledge. The recommendations are made specifically to enhance and/or improve a pet’s health and overall well-being. Additionally, the model can be used within a Flask application for real-time user engagement and convenience for pet owners. Through an automated pet identification process and recommendations, the user no longer searches manually, and also saves time while providing scientifically driven findings to enhance a pet’s health status. The scalability and flexibility of the application are viable solutions to the demands of the growing pet care industry. Future consideration involves extending the model for multiple types of pets, expanding health monitoring capabilities, and using multiple language options to provide for a broader global client base.
Copyright (c) 2025 Prince Raj, Richa Sharma, Ramanjit Singh, Abhishek Raj, Swetabh Shekhar https://creativecommons.org/licenses/by/4.0
Effect of Aerobic Exercise on Polycystic Ovarian Syndrome: A Narrative Review
Purpose: Polycystic ovarian syndrome is a hormonal disorder that occurs in female during reproductive age. It is characterized by irregular menstrual periods, hyperandrogenism and multiple cyst ovaries. PCOS leads to metabolic, psychological and reproductive risks by increasing obesity. The first line of treatment of PCOS is lifestyle intervention which includes diet, exercise and behavioral management. This review of articles discusses the use and effects of aerobic exercises in polycystic ovarian syndrome to motivate self- management and adherence to exercises. Methods: Many electronic databases were searched such as google Scholar, and PubMed. The articles which were showing the effects of exercises especially aerobic on Polycystic ovarian syndrome with other interventions from year 2018 to 2023 were included. The project’s prospects for future study are highlighted. Results: There is significant evidence that the exercises provided in polycystic ovarian syndrome, seems beneficial in females. The advantages include its convenience and accessibility, health and lifestyle management, adherence and compliance of exercise and quality of life. Conclusion: These reviewed articles showed that there are limited studies in India that showed the effect of the exercises, mainly aerobic, approach in treating women with polycystic ovarian syndrome. It promotes self- management and adherence to exercises. So thus, exercises tend to decrease the risks and complications in PCOS.
Copyright (c) 2025 Sakshi Jaiswal, Shivpriya Sharma https://creativecommons.org/licenses/by/4.0
Sea-Fastening of Cargos on a Platform Support Vessel Using Lashing Method
This study examines the critical aspects of sea-fastening methodologies for securing cargo on Platform Support vessels, integrating theoretical principles, practical load plan results, and equipment certification. The methodology emphasizes a systematic approach encompassing data collection, force calculation, lashing plan design, execution, and verification, all crucial for ensuring cargo stability and vessel safety during maritime transport. The theoretical framework, rooted in Newton's laws of motion, analyzes static, dynamic (induced by vessel motions like roll, pitch, and heave), and environmental forces acting on cargo. Basic equations for inertial force, frictional force, overturning moment, and righting moment underpin the design and analysis of securing arrangements. The load plan results for twelve distinct loads reveal calculated maximum forces ranging from 10.1229 N to a critical high of 205.7179 N for specific loads (4 and 7). Correspondingly, lashing tensions were applied based on these forces, utilizing both single and dual belts at 50% (12500 N) and 75% (18750 N) of their strength, demonstrating a risk-adjusted securing strategy. The relatively consistent maximum acceleration values (around 0.10-0.11 m/s²) across loads indicate the significant influence of vessel motion on the forces experienced. The certification of a cargo lashing belt with a capacity of 2500 daN (25000 N) and the visual confirmation of such belts in practical application underscore the importance of using inspected and compliant equipment. The analysis highlights the necessity of addressing critical high-force loads with enhanced securing measures, as evidenced by dual lashings. Integrating a robust methodology, informed by theoretical calculations and validated through practical application with certified equipment, is paramount for ensuring the safe and secure cargo transportation at sea, mitigating risks to the vessel, crew, and the cargo itself. This study emphasizes the interplay between meticulous planning, accurate force assessment, and the appropriate application of securing equipment to achieve effective sea-fastening.
Copyright (c) 2025 Olusegun Samuel Dare, Eferebo Sylvanus Ibietela https://creativecommons.org/licenses/by/4.0
Artificial Intelligence Applications in Undergraduate Engineering Education: A Literature Review
Artificial Intelligence (AI) is rapidly transforming undergraduate engineering education, offering new tools to personalize learning, improve feedback, and scale instruction. This literature review synthesizes recent developments across five key application areas: intelligent tutoring systems, adaptive learning platforms, AI-assisted assessment, virtual laboratories, and AI-driven career and communication support. These technologies have shown promise in enhancing student engagement, tailoring content delivery, and supporting data-informed teaching practices. However, their integration also raises concerns about ethical use, data privacy, algorithmic bias, and faculty preparedness. The review identifies six critical gaps in current research, including the lack of longitudinal studies, limited focus on higher-order thinking skills, and underrepresentation of certain engineering fields. It concludes by outlining strategic directions for responsible AI integration, emphasizing ethical design, inclusive access, and stronger support for educators. As AI continues to evolve, its thoughtful implementation holds the potential to significantly enrich engineering education and better prepare students for future challenges.
Copyright (c) 2025 Thanh Tung Pham https://creativecommons.org/licenses/by/4.0
The Concept of Digital Marketing: Benefits and Techniques
The main purpose of this paper is to provide a better knowledge of the Digital Marketing. This paper begins with an introduction of digital marketing and then it highlights the mediums of digital marketing, the difference between traditional and digital marketing, and the pros, cons, and importance of digital marketing in today’s era. The world is shifting from analog to digital and marketing is no exception. As technology development is increasing, the use of digital marketing, social media marketing, search engine marketing is also increasing. Internet users are increasing rapidly and digital marketing has profited the most because it mainly depends on the internet. Consumer’s buying behaviour is changing and they are more inclined towards digital marketing rather than traditional marketing.
Copyright (c) 2025 Sumit Kumar Singh, Guneet Kumar, Gurwinder Singh https://creativecommons.org/licenses/by/4.0
The Concept of OSI Model and TCP/IP Model
Layered approaches to networking are possible. Network architects categorize protocols in order to simplify their designs. Each layer has its own protocol for talking to the outside world. Every component of the network implements some of the nth layer. Messages are sent back and forth between these parts. Layer n protocol data units are the official name for these transmissions. The OSI model is a framework for developing and implementing network-based software applications. It also serves as a basis for the development of new networking protocol hardware, and architectures. This document compares and contrasts the OSI Reference Model seven layers with those of the TCP/IP Model four. There are distinct roles at each successive level. All Internet communication duties may be traced back to the TCP/IP reference model.
Copyright (c) 2025 Prakash Kumar Verma, Ravneet Kaur, Pritam Singh https://creativecommons.org/licenses/by/4.0
The Future of Cloud Computing: Benefits and Techniques
The main purpose of this paper is to provide to the better knowledge of the cloud computing as well as to suggest relevant research paths in this growing to the field And Paths. And also, we will go through the future benefits of cloud computing. The Cloud computing are offers to the wide range of architectural configurations, and including to the number of processors and memory. It defines the benefits, various tools, and techniques used in cloud computing. The Cloud computing is ready to the changed the way we store and it is expected to continue to the future of information technology. The Cloud computing enables organizations to scale their IT resources up or down quickly and easily, without the need for costly hardware upgrades. The study aims to provide insights into how cloud computing enhances efficiency, and fosters innovation in different industries.
Copyright (c) 2025 Priyam Kumar Tiwari, Amit Puri, Komalpreet Kaur https://creativecommons.org/licenses/by/4.0
Geographic Influence on the Life Cycle Assessment of a 12W Polycrystalline Solar Photovoltaic Module in Southwest Nigeria
This study examined the geographic impact on the life cycle environmental performance of a 12W polycrystalline solar photovoltaic (PV) module installed in six designated locations throughout Southwest Nigeria: Ogbomosho (Oyo State), Ikeja (Lagos State), Abeokuta (Ogun State), Osogbo (Osun State), Akure (Ondo State), and Iworoko (Ekiti State). As the demand for renewable energy technologies escalates, comprehending the geographical influences on the sustainability of solar PV systems is essential for maximizing its implementation. Nevertheless, there is a paucity of localized data regarding the environmental performance of small-scale photovoltaic modules across Nigeria's varied climatic zones. This study filled the gap by assessing life cycle indicators including cumulative energy demand (CED), energy payback time (EPBT), global warming potential (GWP), greenhouse gas payback time (GHG-PBT), greenhouse gas emission rate (GHG-ER), CO₂ emission rate, and CO₂ payback time. The method considered a system boundary encompassing the pre-manufacturing and manufacture stages in China, transit logistics from China to Nigeria, as well as the installation, operation, and end-of-life phases at six locations in Nigeria. The data indicated that CED values are uniform across sites, varying from 1231.86 MJ in Ikeja to 1232.10 MJ in Iworoko, with manufacturing accounting for around 97% of overall energy demand. EPBT values exhibit considerable variation owing to disparities in solar irradiation, with Ikeja documenting the highest value at 17.62 years and Iworoko the lowest at 15.95 years. GWP values varied from 66.31 kgCO₂eq in Akure and Osogbo to 136 kgCO₂eq in Ogbomosho, mostly affected by transportation distances and factory emissions. Correspondingly, GHG-PBT fluctuated from 5.66 years in Iworoko to 11.72 years in Ogbomosho, whilst GHG-ER ranged from 0.1031 to 0.2137 kgCO₂eq/kWh. The results underscore the environmental benefits of installing solar modules in high-irradiance regions and stress the significance of sustainable manufacturing processes and localized photovoltaic production to mitigate carbon footprints.
Copyright (c) 2025 Oloruntobi S. Olatide, Emmanuel O. Sangotayo, Abdullateef. B. Muraina, Abdulfatai O. Sulaiman https://creativecommons.org/licenses/by/4.0
Driver Drowsiness Detection Using Artificial Intelligence and Machine Learning
Drowsiness greatly contributes to the prevalence of road accidents where drivers can get injured or lose their lives. This paper provides a solution to the driving drowsiness issue with the Driver Drowsiness Detection System which tracks a driver's alertness levels to provide warnings when needed. The detection system captures the driver’s eye movements, blinking frequency, and head tilting angles through a camera placed on the front dashboard and analyzes them using computer vision techniques. Drowsiness levels are detected using drowsiness detection algorithms or existing frameworks through input signals from the camera. Once the driver exhibits signs of fatigue, the system alerts the driver using visual or audio signals to allow the driver to act upon it. The system is developed with a preventative measure against accidents to improve safety on roads and reduce the number of accidents related to driver exhaustion.
Copyright (c) 2025 Dhaval Rane, Rohit Danavale, Abhijit Rathiya, Shwet Pawar https://creativecommons.org/licenses/by/4.0
Hygienex – A Next Gen Smart Toilet is an intelligent sanitation system designed to enhance hygiene and optimize maintenance in public restrooms, particularly in high-traffic areas such as transport hubs, hospitals, and educational institutions. The system employs an infrared sensor to dispense a biodegradable seat cover and activates ultraviolet disinfection after each use to ensure cleanliness. It features an MQ2 gas sensor for continuous air quality monitoring, tracks flush counts to trigger automatic cleaning liquid release, and monitors seat cover availability to prompt timely refills. An LCD display provides user guidance, while an ESP32 Wi-Fi module enables real-time data transmission to a cloud dashboard. Additionally, Fast2SMS integration delivers instant maintenance alerts to janitorial staff. By combining automated cleaning, smart sensing, and proactive maintenance, Hygienex offers a cost-effective and efficient solution for improving public restroom hygiene and user experience.
Copyright (c) 2025 Harsh Hemant Patole, Amaan Abdul Qadir Rakhangi, Samiksha Rajendra Kobal, Rhea Dinkar Bagul, Shubhangi Verulkar https://creativecommons.org/licenses/by/4.0
The Profound Effects of Data Science on Business and Society
This paper looks into the unique impacts of data analytics through the eyes of its integration with information technology systems and business and social operations. The adoption of digital technologies has created an unprecedented surge in data storage, which is critical to gaining insights that can guide changes in organizations and society. Communities have been provided with new employment opportunities by researchers who focus on important data generation and interpretation; simultaneously, businesses are changing their strategies to operational frameworks. This research contends that the lives of people in the society have been impacted immensely owing to new data analytics technologies and that organizations are now able to assess and devise plans in a far more nuanced and tactical manner. Hence, this paper seeks to highlight a research gap that attempts to study and explain the fundamental shifts in societal frameworks and business structures that have been advanced by innovation in data analytics.
Copyright (c) 2025 Priyanjli Singh Deo https://creativecommons.org/licenses/by/4.0
A Study on Employee Engagement and Work Culture in Coimbatore with Reference to Textile Industry
Employee engagement and work culture play a crucial role in the success of any organization, particularly in labor-intensive industries such as textiles. This study examines the relationship between employee engagement and work culture in the textile industry of Coimbatore, a major hub for textile manufacturing in India. The research aims to assess how various organizational factors, including leadership, communication, job satisfaction, and workplace environment, influence employee engagement levels. A quantitative approach is employed, gathering data from textile industry employees through structured surveys and interviews. The findings of the study highlight key drivers of engagement, challenges faced by employees, and the impact of organizational culture on workforce productivity and retention. The results will help textile companies in Coimbatore implement better employee-centric strategies, fostering a more motivated and committed workforce.
Copyright (c) 2025 S. Soundariyan, E. Dhanasekar https://creativecommons.org/licenses/by/4.0
The project introduces SmartScribe, an innovative AI-powered PDF note-taking solution designed to enhance user interaction with digital documents. SmartScribe streamlines the process of reading and extracting insights from lengthy PDFs by employing intelligent summarization and note extraction features. It empowers students, professionals, and researchers to efficiently organize and manage document content. With a user-friendly interface, secure data handling, and multi- language support, SmartScribe represents a significant advancement in productivity tools for document management.
Copyright (c) 2025 Nishchal Vyas, Manan Atal, Manvi Choudhary, Niraj Jain, Rohan Jadoun https://creativecommons.org/licenses/by/4.0
Mobile Cloud Computing (MCC), which merges mobile computing and cloud computing, has become a significant topic in the IT industry since 2009. As MCC is still in its early stages of development, it is crucial to gain a comprehensive understanding of the technology to guide future research directions. This paper reviews the background and principles of MCC, its characteristics, recent research efforts, and anticipated future trends. It begins with an overview of the evolution from mobile computing to cloud computing, followed by a discussion of MCC's defining features and recent research initiatives. The paper further analyses the infrastructure and functionalities of mobile cloud computing. Additionally, it addresses the challenges associated with MCC, summarizes relevant research projects, and highlights promising avenues for future research.
Copyright (c) 2025 Akash Kumar, Aanchal Madaan, Manisha Kumar https://creativecommons.org/licenses/by/4.0