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Author Archives: Kajal Tripathi

Employing Swarm Intelligence for Optimizing Latency and Energy Consumption for Routing in WSNs

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Employing Swarm Intelligence for Optimizing Latency and Energy Consumption for Routing in WSNs/strong>
Authors:-Khushboo Parmar, Professor Ruchika Pachori

Abstract- Efficient routing is crucial for many practical applications in wireless sensor networks. Nevertheless, they encounter the unavoidable obstacle of restricted energy resources, which underscores the need of developing data transmission mechanisms that optimize the allocated energy to enhance the longevity of the networks and minimize the system’s latency. Implementing efficient clustering and energy management strategies can enhance the longevity of the network while concurrently decreasing the observed delay. The present study introduces a two-tier methodology for reducing unnecessary transmissions in conjunction with particle swarm optimization (PSO). The objective is to minimize the distances inside clusters in order to reduce both latency and energy usage. The evaluation parameters for the proposed method include the delay in the first hop, the latency in the network, and the energy usage. This empirical method has been employed to determine the optimal fitness function so as to optimize latency and energy consumption in WSNs.

DOI: 10.61137/ijsret.vol.10.issue6.386

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Examining the Acceptance of Mobile Marketing by Customer of Small and Medium Scale Enterprises

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Examining the Acceptance of Mobile Marketing by Customer of Small and Medium Scale Enterprises/strong>
Authors:-Sopheap Suon

Abstract- In this study we try to explore the concept of mobile marketing in a holistic context. The main focus of the research is on consumer’s behaviour towards mobile marketing. The research is conducted through a primary methodology. Both quantitative and qualitative methodology were used. Surveys were conducted from customers of SMEs and interviews were conducted from the managers of those SMEs. The result shows various consumer attitudes towards mobile marketing, which organisations can understand and attract customers.

DOI: 10.61137/ijsret.vol.10.issue6.385

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Validation Testing of Digital Blood Pressure Monitoring Devices for the Upper Arm According to the ISO 81060-2:2018/ AMD 1:2020 Protocol

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Validation Testing of Digital Blood Pressure Monitoring Devices for the Upper Arm According to the ISO 81060-2:2018/ AMD 1:2020 Protocol/strong>
Authors:- Saheb Singh, Deepak Sinha

Abstract- The purpose of the study was to ascertain the accuracy of blood pressure monitors commonly available in the market. Six devices were chosen including one professional BP monitor for home, clinical and hospital use, manufactured by Mann Electronics India Private Limited, Kota from the market. These devices did not have accessible validation testing results. The subjects for assessment were adults from the general population with varied age groups and sex. The objective was to establish whether the devices conform to the requirements of ISO 81060-2:2018/AMD1: 2020 protocol

DOI: 10.61137/ijsret.vol.10.issue6.384

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Educational Data Mining on University Management Information System for Measuring Performance of Students

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Educational Data Mining on University Management Information System for Measuring Performance of Students/strong>
Authors:- Pankaj Shrimali, Dr. Tarun Shrimali

Abstract- Data mining techniques are used in the numerous industries alongwith the IT sector, Agriculture and education system. Massive technical advancements and opportunities from past decades change the approach and lifestyle of the people. Although data mining techniques are used in the several industries but it is new approach in the Academics. The education system has not greatly profit from the potential of data mining techniuqes. A substantial amount of information are required for the better performance of the students in the academics. There is a vast amount of data are available which can help to find the performance of the students. The role of the data mining technology is to find out the performance of students in academics, the factors also find out which affects the academic performance and also other issues like financial, family background etc. how it effects the performance, how semester wise results so that students aware about the performance and also gender wise how it affects.

DOI: 10.61137/ijsret.vol.10.issue6.383

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Multimodal Emotion Recognition Using BERT and ANN: A Hybrid Deep Learning Approach

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Multimodal Emotion Recognition Using BERT and ANN: A Hybrid Deep Learning Approach/strong>
Authors:- Research Scholar Avasheen Shishir Temurkar, Professor Anuradha Purohit

Abstract- Emotion recognition plays a vital role in enhancing human-computer interaction systems by enabling empathetic and context-aware AI solutions. This study introduces a hybrid deep learning architecture that integrates BERT for extracting contextual text features and an Artificial Neural Network (ANN) for processing MFCC-based acoustic features. By combining textual and audio modalities, the proposed model effectively addresses the limitations of single-modality approaches. The model is evaluated on the USC-IEMOCAP dataset, encompassing six emotion categories: ‘Happy’, ‘Sad’, ‘Angry’, ‘Neutral’, ‘Frus- trated’, and ‘Excited’. It achieves competitive performance with a weighted F1-score of 0.91 and an accuracy of 86%, outperforming several state-of-the-art methods. The fusion of text and audio features enhances the model’s ability to capture subtle emotional nuances, demonstrating the potential of multimodal learning for robust emotion classification. This research underscores the value of hybrid architectures in advancing emotion recognition for real- world applications.

DOI: 10.61137/ijsret.vol.10.issue6.382

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The Role of Data Science in Business Intelligence: Use Cases and Implementation Challenges

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The Role of Data Science in Business Intelligence: Use Cases and Implementation Challenges
Authors:-Priyanshu Tripathi

Abstract-Data Science has become a pivotal element in the evolution of modern Business Intelligence (BI), transforming the way organizations process and analyze vast amounts of data to uncover actionable insights. By leveraging advanced techniques such as machine learning, statistical modeling, and data visualization, businesses can enhance decision-making processes and gain a competitive edge. This report delves into the synergistic integration of Data Science within BI frameworks, illustrating its practical applications through diverse use cases including predictive analytics for forecasting trends, customer segmentation for personalized marketing strategies, and fraud detection to safeguard organizational integrity.While the potential benefits are immense, the implementation of Data Science in BI is not without its challenges. Key hurdles include ensuring data quality and consistency across sources, overcoming integration complexities with legacy systems, and addressing skill gaps in data literacy among employees. These challenges require strategic planning, investment in technology, and workforce training to be effectively mitigated.The report also explores emerging trends shaping the future of BI, such as the increasing adoption of artificial intelligence, real-time analytics, and the use of natural language processing for intuitive data interactions. Finally, it provides actionable recommendations for organizations to build robust and scalable BI strategies, emphasizing the importance of fostering a data-driven culture, prioritizing ethical data practices, and continuously evolving with technological advancements.

DOI: 10.61137/ijsret.vol.10.issue6.433

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Assessing Model Misspecification in Stochastic Linear Regression Analysis

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Assessing Model Misspecification in Stochastic Linear Regression Analysis/strong>
Authors:-Research Scholar Siddamsetty Upendra, Research Scholar R. Abbaiah

Abstract-This paper studies misspecification tests for stochastic linear regression models, including the Durbin-Watson test, Ramsey’s regression specification error test, Lagrange’s multiplier test, and UTTS’ rainbow test. Specification errors arise when there are deviations from the underlying assumptions of a stochastic linear regression model, impacting associated inferences. Specifically, errors may occur in specifying the error vector ( ) and the data matrix ( X ). Common causes of specification errors involve including irrelevant independent variables or excluding relevant ones in the stochastic linear regression model. Previous research by Ivan Krivy et al. (2000) presented two stochastic algorithms for estimating parameters in nonlinear regression models. In a 1984 paper, Russell Davidson et al. developed a computational procedure for a variety of model specification tests. Ludger Ruschendorf et al. (1993) constructed nonlinear regression representations of general stochastic processes, focusing on specific representations for Markov chains and certain m-dependent sequences. This study contributes to the understanding of misspecification in stochastic linear regression models, utilizing a range of tests to identify errors in model assumptions and parameter estimation. The insights gained from these tests can enhance the accuracy and reliability of regression model inferences.

DOI: 10.61137/ijsret.vol.10.issue6.432

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Review on Performance Parameter of MOSFET and FinFET Transistor

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Review on Performance Parameter of MOSFET and FinFET Transistor/strong>
Authors:- Assistant Professor Madhvi Singh Bhanwar, Associate Professor Dr.Nidhi Tiwari, Professor Dr. Mukesh K Yadav

Abstract- In modern world technologies are grooming very fast day by day along with the world semiconductor industry the world of IC is also grooming and enhancing the technologies day by day as we know according to Moore’s law the number of transistors will be double on a chip in every eighteen months that means the size of components will be reducing day by day in the same way types of transistors were introduced like MOSFET and FinFET. FinFET replaced MOSFET, FinFET resolved all the challenges of MOSFET and helped in compact designing of electronic devices, FinFET is widely used in various modern electronic devices because of its structure, fast switching speed, low power consumption and less leakage current.

DOI: 10.61137/ijsret.vol.10.issue6.381

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Comprehensive Study of Mobile and Web Applications for on-Demand Services

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Comprehensive Study of Mobile and Web Applications for on-Demand Services/strong>
Authors:-Aditi Pradeep, Akshara Vijay, Jerom Jo Manthara, K S Abhishek, Jithy John

Abstract-With the rapid growth of digital solutions, on- demand service applications have emerged as valuable tools for addressing daily needs, such as home maintenance and freelancing tasks. This survey paper provides a comprehensive review of ten existing mobile and web-based applications designed to connect customers with service providers across a range of sectors. By examining each system’s features, user experience, and limitations, this study highlights the commonalities and distinct approaches used to facilitate service matching. Key findings reveal that, while these applications effectively streamline access to services, they often face challenges such as limited service categories, regional restrictions, and issues with pricing transparency and real-time availability. Through a comparative analysis, this paper identifies trends, limitations, and potential improvements for future on-demand service platforms.

DOI: 10.61137/ijsret.vol.10.issue6.430

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AI-Driven Vehicle Assistance Platform with Geolocation Services

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AI-Driven Vehicle Assistance Platform with Geolocation Services/strong>
Authors:-Rakesh Jaiswal, Kuldeep Yadav, Deepak Singh Purviya

Abstract-It often has brought inconveniences of unsafe situations and discomfort to its customers owing to vehicular breakdown. Typical roadside assistant applications that come out face problems such as high response times, small cover-up areas, and lack of real-time diagnostic capabilities among other problems. This research proposal intends to establish an innovative, web-based platform called Repair that has AI and LBS technologies integrated to provide real-time assistance for vehicles. The core feature of Repair is an AI-powered chatbot that can troubleshoot the most common vehicle issues independently. Advanced NLP techniques are applied to guide users through the diagnostic steps and provide solutions to problems such as flat tires, dead batteries, or other engine issues. When the problem exceeds the capabilities of the chatbot, the system uses Geolocation API technology to pinpoint the user’s exact location and dispatch the nearest available towing service. This seamless integration of AI and geospatial technology ensures faster response times, reducing user waiting periods and improving service efficiency.

DOI: 10.61137/ijsret.vol.10.issue6.429

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