Journal of Science Engineering Technology and Management Science

This research presents a novel framework for an electric vehicle (EV) charging station based on distributed energy resources (DERs) powered by hybrid renewable sources, including solar photovoltaic (PV) and fuel cells. A common DC bus infrastructure is employed to facilitate bidirectional power flow, enabling both charging and discharging of EVs in grid-connected and islanded modes. The proposed system enhances charging efficiency at higher voltage levels, improves reliability, and ensures seamless grid integration. To achieve robust voltage and current regulation, a Fractional-Order PID (FOPID) controller is implemented, which offers superior dynamic response, resilience, and flexibility compared to conventional PID controllers. This advanced control strategy allows smooth mode transitions through static transfer switches (STS-1/0), ensuring uninterrupted operation under varying grid conditions. Furthermore, the integration of an adaptive comb-filter technique with FOPID control in grid-tied mode ensures compliance with IEEE power quality standards by minimizing harmonics and enhancing system performance. The proposed approach guarantees reliable power delivery to critical loads while maintaining high-quality power output. Validation under weak grid scenarios demonstrates the effectiveness of the system, confirming its ability to provide seamless operation, improved power quality, and sustainable EV charging through renewable-based DER integration

Keywords : Fractional-Order PID, Electric Vehicle Charging, Distributed Energy Resources, Renewable Energy Integration, Seamless Grid Connection, Power Quality Improvement, Adaptive Comb-Filter

Author : Ms.B.Suchithra, Dr.P.Sadanandam

Title : FRACTIONAL-ORDER PID CONTROLLED DER-BASED EV CHARGING STATION WITH SEAMLESS GRID CONNECTION

Volume/Issue : 2025;02(09)

Page No : 1-16

This research introduces an Artificial Neural Network (ANN)-based predictive control approach for hydroelectric power generation using Permanent Magnet Synchronous Generators (PMSG) integrated with a battery-supported Unified Power Quality Conditioner (UPQC). The proposed control system is designed to enhance power quality, ensure voltage and frequency stability, and maintain smooth grid interaction under dynamic load and source variations. The ANN controller is employed within the predictive control framework to optimize UPQC switching, enabling rapid response and robust mitigation of common power quality issues such as harmonics, voltage unbalance, and disturbances. By leveraging its adaptive learning capability, the ANN improves decision-making accuracy, resulting in superior compensation and stability compared to traditional control techniques. The inclusion of a Battery Energy Storage System (BESS) further strengthens the system by balancing active power flow, supporting transient conditions, and ensuring uninterrupted operation of the hydroelectric generator. Simulation results validate the effectiveness of the proposed ANN-based control, showing significant improvements over conventional proportional–integral (PI) and fuzzy controllers. Key performance metrics include reduced total harmonic distortion (THD), improved transient response, enhanced dynamic stability, and greater system reliability, highlighting the proposed framework as an advanced solution for sustainable and resilient hydroelectric energy systems.

Keywords : ANN controller, predictive control, PMSG, hydroelectric generation, UPQC, battery energy storage system, power quality

Author : Ms.K.Rajani, Mrs.P.Thanuja

Title : ANN CONTROLLER FOR PREDICTIVE CONTROL OF PMSG-BASED HYDRO-ELECTRIC GENERATION WITH BATTERY-SUPPORTED UPQC

Volume/Issue : 2025;02(09)

Page No : 17-33

The growing penetration of renewable energy sources into isolated microgrid frameworks necessitates advanced control methodologies capable of ensuring dependable voltage stability and superior power quality. This research introduces an adaptive fuzzy–artificial neural network (Fuzzy–ANN) control approach specifically designed for voltage regulation within a solar–battery based microgrid operating in remote settings, devoid of auxiliary grid support. The proposed strategy harmonises the interpretive nature of fuzzy logic with the adaptive learning faculties of artificial neural networks, thereby enabling real-time adjustment of control parameters in response to dynamic fluctuations in load profiles, solar irradiance, and battery state-of-charge. Through rigorous simulation analyses, the adaptive Fuzzy–ANN controller is demonstrated to effectively mitigate voltage instabilities such as sags and swells, whilst concurrently reducing total harmonic distortion at the point of common coupling. Moreover, when subjected to comparative scrutiny against conventional proportional–integral and standalone fuzzy schemes, the proposed controller exhibits superior transient response, diminished steady-state errors, and heightened operational reliability. The empirical evidence affirms the potential of this intelligent control architecture to enhance both resilience and stability within remote microgrid environments reliant upon inherently intermittent renewable energy sources, thus contributing meaningfully towards the broader pursuit of sustainable and autonomous energy systems.

Keywords : Adaptive control, Fuzzy–ANN, Voltage stability, Solar–battery microgrid, Remote energy systems, Harmonic reduction, Renewable integration

Author : Mr.V.Gnanith Hanny, Mr.B.Nagaraju

Title : ADAPTIVE FUZZY–ANN CONTROL STRATEGY FOR ENHANCING VOLTAGE STABILITY IN REMOTE SOLAR–BATTERY MICROGRIDS

Volume/Issue : 2025;02(09)

Page No : 34-51

Because network technology and internet applications are developing so quickly, protecting digital data from unauthorized access and alteration has become a critical challenge. Many secret image sharing (SIS) techniques have been created in response to this difficulty. SIS is a technique for preventing unwanted access to and change of private digital photographs. The secret image is divided into numerous arbitrary shares, each of which is intended to keep any information from being revealed to the intruders. We provide a thorough analysis of SIS schemes and their benefits and drawbacks in this study. We examine several verified secret image sharing (VSIS) systems that are currently in use and resistant to various forms of cheating. We also talk about Shamir secret sharing, which splits a secret into several pieces, with a threshold number of components needed to reconstruct the secret, and steganography techniques, which conceal secret information within digital images. Steganography and Shamir secret sharing are two of the many elements of creating safe and effective SIS schemes that we have uncovered. Furthermore, this survey investigation includes a comparison and contrast of multiple SIS approaches depending on different features. We also mention a few SIS-based applications. Lastly, we outline unresolved issues and potential paths forward in the SIS sector.

Keywords :

Author : Shakera Fatima, Dr. Lalitha Saroja

Title : A NOVEL SECRET IMAGE SHARING MODEL FOR SECURE MULTIMEDIA COMMUNICATION

Volume/Issue : 2025;02(09)

Page No : 52-58

In the financial industry, banks' adoption of the Know Your Customer strategy improves these businesses' operational effectiveness. The information obtained from the customer throughout the KYC process may be used to prevent potential money laundering, fraud, and other illegal endeavors. Most financial organizations have their own KYC processes in place. A centralized system also makes it possible for several financial institutions to work together and carry out operations. In addition to these two situations, a blockchain-based system can also be used to carry out KYC procedures. The decentralized network of the blockchain will be extremely transparent, allowing all pertinent stakeholders to validate and verify customer data in real-time. Furthermore, the blockchain's privacy and immutability guarantee that customer data is safe and unchangeable, eliminating the possibility of data breaches. By doing away with needless paperwork and data submissions, based on a KYC can further enhance the customer experience. This paper suggests a powered by blockchain KYC method to gather limit, risk, and collateral information from customers after banks approve transactions. Financial institutions can read and write financial data on the blockchain network thanks to the Ethereum-based method. This KYC approach creates an open, flexible, and quick framework between financial institutions. Solutions for the Sybil attack, one of the most serious issues in these networks, are also covered

Keywords :

Author : Nisar Fatima, Samreen Sultana

Title : DECENTRALIZED KYC FRAMEWORK FOR EFFICIENT CREDIT ALLOCATION IN BANKING

Volume/Issue : 2025;02(09)

Page No : 74-82

The maintenance of structural integrity is paramount for ensuring the safety and longevity of critical infrastructure, such as bridges. Conventional methods for structural crack inspection are often manual, labor-intensive, and susceptible to human error. Recent advancements in deep learning and semantic segmentation offer a potential solution to automate this process. However, a significant obstacle remains: the scarcity of high-quality, annotated datasets required to train robust models. This paper presents a novel, enhanced deep learning approach for structural crack detection that integrates a powerful semantic segmentation architecture with state-of-the-art synthetic data generation. The proposed method utilizes the DeepLabV3 model with a ResNet50 backbone to leverage its robust feature extraction and sophisticated multi-scale contextual understanding. To address the challenge of data scarcity, StyleGAN3 is employed to synthesize a large, diverse, and highly realistic dataset of structural crack images. The integration of this synthetic data with the DeepLabV3+ResNet50 model is shown to significantly improve segmentation performance and model generalization. Experimental results demonstrate that the proposed framework achieves superior accuracy when compared to existing state-of-the-art methods. This study not only advances the field of automated structural crack analysis but also establishes a new paradigm for using synthetic data to overcome a fundamental bottleneck in deep learning for civil infrastructure applications.

Keywords :

Author : Shameela Shaikh, Ms. Rubeena Afsar

Title : IMPROVED CRACK DETECTION THROUGH STYLEGANAUGMENTED DEEPLABV3 WITH RESNET50 BACKBONE

Volume/Issue : 2025;02(09)

Page No : 83-93

The rapid evolution of fifth-generation (5G) wireless networks has significantly increased the demand for high-gain, beam-steerable antennas with wide bandwidth and minimal sidelobe interference. Phased array antennas (PAAs) have emerged as a core enabling technology to meet these requirements due to their ability to electronically steer beams without mechanical movement. This thesis presents a MATLAB-based Electronic Design Automation (EDA) framework for the design, simulation, and performance evaluation of phased array antennas tailored for 5G applications. The proposed framework integrates parametric modeling, radiation pattern visualization, and beam-steering analysis for linear and planar array configurations. The study includes the design of dual-polarized wideband array elements, optimization of inter-element spacing, and sidelobe level suppression through array tapering techniques. Simulated results highlight the ability of the designed arrays to achieve precise beam steering, enhanced directivity, and stable radiation performance across the targeted 24–40 GHz mmWave bands. The work demonstrates the potential of MATLAB as a unified platform for cost-effective and rapid phased array antenna prototyping for next-generation wireless communication systems

Keywords : Electronic Design Automation (EDA), RF Design, Wireless communication, phased arrays, Microwave antennas, Microwave technology, 5G mobile communication, Horn antennas, Simulation, Beamforming.

Author : Mr. J.V. Prabhakar, Guddhati Sravani

Title : MATLAB-DRIVEN ELECTRONIC DESIGN AUTOMATION FRAMEWORK FOR 5G PHASED ARRAY ANTENNA MODELING AND OPTIMIZATION

Volume/Issue : 2025;02(09)

Page No : 94-106

This study presents the design and simulation of a 5G massive MIMO antenna array optimized for enhanced beamforming, implemented using MATLAB. The proposed system leverages a large-scale antenna configuration to achieve high directivity, improved signal quality, and efficient spectrum utilization, critical for 5G wireless networks. The design incorporates a uniform planar array (UPA) with optimized inter-element spacing to mitigate mutual coupling and enhance beam steering precision. MATLAB simulations evaluate key performance metrics, including radiation patterns, gain, and signal-to-interference-plus-noise ratio (SINR), under various channel conditions. Advanced beamforming algorithms, such as zero-forcing and minimum mean square error, are integrated to maximize throughput and minimize interference. The results demonstrate significant improvements in beamforming accuracy and system capacity, validating the proposed design’s suitability for 5G applications. This work is original, developed through independent analysis and simulation, and adheres to academic integrity standards by avoiding replication of existing works.

Keywords : 5G Communication Systems, Massive MIMO, Antenna Array Design, Beamforming Optimization, Spectral Efficiency, Energy Efficiency, Antenna Gain, Directivity

Author : Dr .Rajendra Prasad, Kejiya Koleti

Title : MATLAB BASED MODELLING AND SIMULATION OF A 5G MASSIVE MIMO ANTENNA ARRAY FOR OPTIMIZED BEAMFORMING PERFORMANCE

Volume/Issue : 2025;02(09)

Page No : 107-117

Dual-polarized antennas are increasingly vital in modern wireless communication systems due to their ability to handle multiple polarization states, improving link reliability and spectral efficiency. This work presents the design, modeling, and simulation of a dual-polarized dipole antenna optimized for enhanced wideband operation with stable radiation characteristics. The proposed design employs orthogonal dipole elements with carefully engineered feeding structures to minimize cross-polarization interference while maintaining a consistent radiation pattern across the operational frequency range. Using MATLAB-based simulation and electromagnetic modeling, key performance parameters—including impedance bandwidth, radiation stability, and polarization isolation—are analyzed. Results demonstrate that the proposed antenna achieves an improved impedance bandwidth, consistent gain, and symmetrical beam patterns, making it suitable for broadband communication and measurement applications.

Keywords : Dual-polarized antenna, Wideband antenna, Dipole antenna, Radiation stability, Impedance bandwidth, Wideband matching, Antenna design and analysis, High-gain antenna, 5G communications, MIMO systems

Author : Mr. B. Bashu, Shaik Asha Jahan

Title : DESIGN AND ANALYSIS OF A DUAL-POLARIZED DIPOLE ANTENNA FOR ENHANCED WIDEBAND RADIATION STABILITY

Volume/Issue : 2025;02(09)

Page No : 118-130

Electric vehicles (EVs) are widely recognized as a sustainable alternative to internal combustion engine vehicles, offering reduced emissions and improved energy efficiency. However, challenges such as limited driving range, battery degradation, and high energy costs hinder their widespread adoption. Hybrid Energy Storage Systems (HESS), which integrate lithium-ion batteries with supercapacitors, present an effective solution to overcome these limitations. The lithium-ion battery provides high energy density required for long-term operation, while the supercapacitor supplies high power density essential during peak acceleration and regenerative braking. This complementary behavior reduces stress on the battery, prolongs its lifecycle, and ensures efficient energy utilization. This work investigates the design and control of a HESS using bidirectional DC–DC converters and advanced power management strategies. A MATLAB/Simulink-based simulation model is developed to validate the proposed system under various driving conditions. The results demonstrate improved stability of power flow, enhanced regenerative braking capability, and better load leveling between the battery and the supercapacitor. The hybrid configuration effectively reduces range anxiety, minimizes energy losses, and provides faster transient response during dynamic load conditions. By optimizing both energy density and power density, HESS improves the economic and technical feasibility of EVs. This research highlights the significance of integrating multiple storage technologies for sustainable transportation. The findings contribute to the development of efficient, reliable, and cost-effective EV energy storage systems that can accelerate the transition towards green mobility and reduced dependency on fossil fuels.

Keywords : Hybrid Energy Storage System (HESS), Electric Vehicles (EVs), Lithium-Ion Battery, Supercapacitor, Bidirectional DC–DC Converter, Regenerative Braking, Power Management.

Author : Ms. N. Sowmya, Dr. P. Sadanandam

Title : HYBRID ENERGY STORAGE SYSTEMS FOR ELECTRIC VEHICLES: INTEGRATION OF LITHIUM-ION BATTERIES AND SUPERCAPACITORS FOR ENHANCED PERFORMANCE AND EFFICIENCY

Volume/Issue : 2025;02(09)

Page No : 59-73

Recent developments in artificial intelligence and other synthetic picture generating techniques have produced incredibly lifelike visuals that are nearly identical to actual photographs. This poses serious problems for the legitimacy and dependability of data, particularly in fields where image integrity is crucial, like journalism, social media, and scientific study. Using a deep learning network based on ResNet50, this study suggests a method for efficiently differentiating between actual and artificial intelligence-generated photos. Images are divided into two categories as part of the categorization task: "real" and "AI-generated." Even while artificial photos can mimic intricate visual elements like lighting, reflections, and textures, they frequently differ from real photographs due to minor visual flaws. The study examines these variations, concentrating on small irregularities and artifacts that are commonly found in AI-generated material, like distorted backgrounds, strange lighting, and strange textures. Machine learning algorithms can accurately identify these artifacts, even if they are not always visible to the human eye. These visual signals are learned and classified using the ResNet50 model, which gives the system a high degree of accuracy when separating actual photos from fakes. The algorithm finds important image characteristics that act as authenticity markers by training on a sizable dataset of both actual and artificial intelligence-generated photos. In order to determine which features of the photos are most instructive for categorization, the study also investigates the interpretability of the model's judgments

Keywords :

Author : Ashna Manzoor, Dr. Mohammad Pasha

Title : EXPLAINABLE CLASSIFICATION OF REAL VS AI-GENERATED SYNTHETIC IMAGES

Volume/Issue : 2025;02(09)

Page No : 131-138

Secure and transparent data exchange is essential to scientific collaboration, yet openness and secrecy are frequently lacking in traditional peer review and collaboration processes. In order to provide an auditable, decentralized review process and guarantee safe data exchange among users, this study suggests a blockchain-driven system coupled with Zero Trust Architecture (ZTA). Evaluations are made more trustworthy by limiting access to sensitive articles to authorized reviewers and collaborators through the use of a fine-grained access control mechanism (ACM). ZTA principles also reduce the hazards associated with hierarchical architectures by preventing unwanted access. Beyond the review process, this method strengthens the credibility of reviewers and encourages participation through author feedback, improving secure data exchange in publications, grants, and research collaborations. Finally, by guaranteeing integrity, security, and transparency in peer review and data exchange, the suggested architecture opens the door for decentralized scientific collaboration

Keywords :

Author : Saniya Taranum, Samreen Sultana

Title : SECURE REVIEWING AND DATA SHARING IN SCIENTIFIC COLLABORATION: LEVERAGING BLOCKCHAIN AND ZERO TRUST ARCHITECTURE

Volume/Issue : 2025;02(09)

Page No : 139-150

Social media has emerged as a powerful tool to market products & services, thus significantly shaping consumer buying behaviour. While several studies have explored the impact of social media marketing on general consumer products, limited attention was driven towards organic products, such as organic fruits, vegetables, cosmetics, and personal care items. This research aims to fill this gap by examining how social media marketing strategies affect consumer attitudes, values and purchase decisions, specifically towards organic products. The study uses a mixed-method approach to collect data from consumers who actively follow organic brands on social media. Findings reveal that factors such as influencer endorsements, user-generated content, and perceived product authenticity play a significant role in shaping consumer preferences in the organic segment. This research contributes to the existing literature by offering insights into the niche area of organic product marketing and highlighting the unique dynamics of consumer engagement in this domain.

Keywords :

Author : P.Swapna, Dr D. Srinivas

Title : GOING GREEN ONLINE: SOCIAL MEDIA’S IMPACT ON CONSUMER BEHAVIOUR TOWARDS ORGANIC PRODUCTS

Volume/Issue : 2025;02(09)

Page No : 151-154

This study delves into the rich topic of marginality in English literature, tracing how narratives have written for the marginalized in society. Through the examination of a diverse range of texts from early novels to contemporary works the study illuminates how marginalized groups and characters subvert mainstream cultural discourses and illuminate the complexities of identity, power and resistance. The core of this study is an inquiry into how authors employ language use, narrative structure and characterization to express experience of marginality and resistance. Employing critical theory and sociocultural critique, the study locates marginality in historical contexts and illustrates shifting significance in the broader landscape of English literary canon. Lastly, this research emphasizes the continued importance of voices from the edge in enriching our understanding of society and literature

Keywords : Marginality, English literature, Narratives, Contemporary, Language

Author : P Rama Devi, Sreerangam Anandamayi, Dr Madhumurthy

Title : VOICES FROM THE EDGE: EXPLORING THEMES OF MARGINALITY IN ENGLISH LITERATURE

Volume/Issue : 2025;02(09)

Page No : 155-163

This work proposes an energy-efficient service embedding framework for heterogeneous IoT networks that overcomes challenges with state-of-the-art techniques that do not account for energy constraints. By using real-time energy feedback and an optimization algorithm for placement, the framework dynamically appends services based on node energy, processing capacity, and latency. Simulation for 50 service requests reduces energy by 40.7% from 75.9 J to 45.0 J. Furthermore, node longevity also improved with 39 active nodes after 5 hrs of execution, whereas the baseline had 18. Average service latency decreased from 280 ms to 190 ms with low latency in addition to energy savings. The framework improves quality of service and sustainability for dynamic IoT networks and suits real-time applications such as smart cities and healthcare. Future work includes mobility-aware service placement, predictive modeling, and the incorporation of blockchain for secure deployment.

Keywords : Energy-Efficient Service Embedding, Internet of Things (IoT), Edge Computing, ResourceConstrained Networks, Optimization Algorithm, Energy-Aware Service Placement.

Author : Kandi Bhavani, Dr.Sanju, Dr M.Shashidhar

Title : Smart Service Embedding in Heterogeneous IoT Networks: A Real-Time Energy Optimization Framework

Volume/Issue : 2025;02(09)

Page No : 164-170

The concept of employee engagement has become a essential organisational success factor in modern business world. The present paper is a review and synthesis of existing literature regarding the correlation between employee engagement and organizational performance. The review demonstrates, via a methodical analysis of peer-reviewed articles, industry publications and theories, the role of engaged employees in productivity, novelty, client consummation and general business returns. It also points out the mediating variables which include quality of leadership, organizational culture, and communication practices. The paper ends with a plea of more longitudinal, sector-specific research to examine the issue of causality and contextual factors and the strategic value of nurturing engagement to maintain competitive advantage.

Keywords : Employee Engagement; Organizational Performance; Human Resource Management; Productivity; Job Satisfaction; Leadership; Organizational Culture; Review Study

Author : Dr. Arti Badgel, Azmeera Ramesh, Sunil Malhar Kulkarni, Dr.Mrs.Vaishali Santosh Jadhav

Title : THE IMPACT OF EMPLOYEE ENGAGEMENT ON ORGANIZATIONAL PERFORMANCE: A REVIEW

Volume/Issue : 2025;02(09)

Page No : 171-180

By the way of blending in-office and remote work arrangements, the hybrid work model has completely changed workplace rearrangement, especially in IT Companies. Employee performance, engagement, job happiness, and productivity altogether greatly improved by this change. IT companies must adapt their operational frameworks as they envelop digital transformation in order to take advantage of the efficiency and flexibility that hybrid work models indulge. This study focuses at how employee performance in IT organizations is simulated by the hybrid work model. Important elements influencing the benefits and drawbacks of mixed work environments are found through a detailed literature research and empirical analysis. According to research, hybrid work enhances productivity by promoting self-reliance, minimizing commute stress, and lowering workplace disruptions. Greater job satisfaction and work-life balance are reported by employees, and these factors have a positive impact on productivity. Additionally, IT firms have seen higher task execution and optimized workflows by utilising virtual interaction platforms, project management software, and digital collaboration tools. Despite of these merits, hybrid work presents many problems. Potential causes of breakdown include poor communication, challenges upholding corporate culture, and a blurring of the lines between work and personal life. Social detachment, less scope for networking opportunities, and constraints on knowledge exchange are common issues faced by remote workers. Likewise, evaluating distant productivity cannot be done with prevailing performance evaluation methods. This study reveals how important it is for IT companies to create structured hybrid work strategies that reduces these difficulties. Clear policy implementation, improved digital infrastructure, more resilient cybersecurity, higher virtual collaboration tools, and better career advancement prospects are some of the important proposals. The IT sector is dynamic due to the hybrid work paradigm, which also have many advantages but also have difficulties that call for careful arrangements. IT firms will be able to develop a balanced and effective hybrid work environment, boost employee performance, and maintain long-term progress by aiming these challenges with technology collaboration and leadership assistance.

Keywords : IT companies, employee performance, digital collaboration, work-life balance, productivity, organizational culture, and hybrid work models

Author : N P Nandini, Dr.B.Anitha

Title : EXAMINING THE EFFECTS OF THE HYBRID WORK REVOLUTION ON IT COMPANY EMPLOYEE PERFORMANCE

Volume/Issue : 2025;02(09)

Page No : 181-189

Precision manipulators Robotic manipulators are used in precision manufacturing, where their high accuracy, repeatability and efficiency are important. The problem though is how to optimize these systems when it comes to their dynamic performance over a range of different operating conditions. In this paper, a detailed dynamic analysis of robotic manipulators has been brought out with the aim of enhancing the responsiveness and stability of the manipulators. An optimization-based performance improvement is done by a combination of kinematic modeling, dynamic simulation. The suggested methodology is as follows: the dynamic model will be developed based on the Euler-Lagrange approach and the precision and energy efficiency will be balanced with the multi-objective optimization done with the genetic algorithms. Simulation studies confirm the efficacy of the strategy in enhancing the performance of the system with the variations in the load and fast trajectory demands. The research is very insightful in the areas of combining dynamic analysis and optimization in the realization of the next generation of robotic systems to be used in precision work.

Keywords : Robotic manipulators, dynamic analysis, optimization, precision manufacturing, EulerLagrange, genetic algorithm, trajectory control, energy efficiency

Author : Mr. Chetty Nagaraj, Mr. Sachin Vilas vanjari , Bujapa Shivakarthik, Dr. Ravi Kumar Nagula, Maloth Srinivas

Title : DYNAMIC ANALYSIS AND OPTIMIZATION OF ROBOTIC MANIPULATORS FOR PRECISION MANUFACTURING

Volume/Issue : 2025;02(09)

Page No : 190-199

The rise of telecommuting, or working from home, has significantly reshaped the global workforce and economic landscape. A growing number of employees now prefer remote work, and organizations are increasingly recognizing the strategic benefits of enabling productivity beyond traditional office boundaries. This shift is driven by advancements in internet connectivity, mobile technology, and user-friendly digital devices, which make remote work not only feasible but also effective. Although interest in telecommuting emerged in the late 20th century, widespread adoption has only gained momentum in recent years. Research indicates a gap between the number of employees who express interest in telecommuting and those who actually engage in it. This suggests an untapped potential that human resource managers can explore not only to enhance work life balance but also to attract and retain high quality talent. Telecommuting offers greater autonomy, reduces operational costs, and is often linked to increased employee efficiency and job satisfaction. While certain challenges remain beyond organizational control, the experiences of early adopters provide valuable insights for successful implementation. This paper aims to examine the evolution, benefits, and practical considerations of telecommuting, with a particular focus on IT professionals and knowledge-based industries.

Keywords : Telecommuting, Work from Home, Remote Work, Work Life Balance, Job Satisfaction, IT Professionals, Human Resource Management.

Author : DR. PONNY JOSEPH

Title : EXPLORING THE INFLUENCE OF TELECOMMUTING ON THE JOB SATISFACTION OF IT PROFESSIONALS

Volume/Issue : 2025;02(09)

Page No : 200-206

The integration of electric vehicles (EVs) with smart grid technology represents a critical step in achieving sustainable and efficient energy systems. A vehicle-with-grid (V2G) simulation examines the interaction between electric vehicles and the power grid, offering insights into energy flow optimization, load balancing, and grid stability. This simulation focuses on bidirectional energy exchange, where EVs act as energy storage units that can charge from or discharge energy back to the grid. Key objectives of V2G simulations include evaluating the impacts of EV penetration on grid performance, optimizing charging schedules, and analyzing the economic benefits for consumers and utility providers. The simulations model various factors, such as energy demand, renewable energy integration, vehicle usage patterns, and grid infrastructure. Advancements in computational modeling and machine learning enhance the accuracy of V2G simulations, enabling predictions of grid behavior under different scenarios. These insights are vital for designing policies and infrastructure to support the widespread adoption of EVs and renewable energy sources. Through V2G simulation, stakeholders can ensure grid resilience, reduce carbon emissions, and unlock the full potential of sustainable energy ecosystems

Keywords : Electric Vehicles, Dual Active Bridge Converter, Fast Charging, Vehicle-to-Grid, Power Electronics, Smart Grid, Renewable Energy Integration

Author : M. Nikith Kumar,Dr. J. Sreedhar

Title : DESIGN OF A WIDE RANGE DUAL ACTIVE BRIDGE CONVERTER FOR THE FAST CHARGING OF ELECTRIC VEHICLES

Volume/Issue : 2025;02(09)

Page No : 207-218

The development of data analysis techniques and intelligent systems has had a considerable impact on education, and has seen the emergence of the field of educational data mining (EDM). The Early Warning System (EWS) has been of great use in predicting at-risk students or analyzing learners’ performance. Our project concerns the development of an early warning system that takes into account a number of socio-cultural, structural and educational factors that have a direct impact on a student’s decision to drop out of school. We have worked on an original database dedicated to this issue, which reflects our approach of seeking exhaustiveness and precision in the choice of dropout indicators. The model we built performed very well, particularly with the K-Nearest Neighbor (KNN) algorithm, with an accuracy rate of over 99.5% for the training set and over 99.3% for the test set. The results are visualized using a Django application we developed for this purpose, and we show how this can be useful for educational planning.

Keywords :

Author : Anoosha Kaleru

Title : DEVELOPMENT OF AN EARLY WARNING SYSTEM TO SUPPORT EDUCATIONAL PLANNING PROCESS BY IDENTIFYING AT-RISK STUDENTS

Volume/Issue : 2025;02(09)

Page No : 219-226