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11th International Symposium on Electronic Systems Devices and Computing, ESDC 2023

作者： Singh, Himanshu Biken Singh, Moirangthem Pratik, Harsh Pratap, Ajay Department of Computer Science and Engineering Varanasi India

ISBN: (纸本)9781665455725

In recent years, automated (Intelligent) decision support systems have become prevalent in various smart city applications such as healthcare, transportation, energy management, and environmental monitoring. Internet of Things (IoT) and Unmanned Aerial Vehicle (UAV)-based smart sensing and actuation devices in agricultural events can change the sector from static and manual to dynamic and intelligent, resulting in increased production with minimal human efforts. In addition, soil measurements that are time-consuming can be collected using Unmanned Ground Vehicles (UGVs). However, to collect data efficiently from wireless sensors in agricultural fields, UAV and UGV need to follow an optimal path. Thus, in this paper, we formulate utility maximization problem using UAV and UGV by simultaneously minimizing energy consumption and maximizing data collection. To solve the formulated problem, we propose a modified Greedy Randomised Adaptive Search Procedure (GRASP) algorithm to predict an efficient path for UAV and UGV to collect data from the agricultural field. Moreover, the efficacy of the proposed algorithm is showcased theoretically and experimentally on real-world data and compared with other state-of-the-art methods. © 2023 IEEE.

关键词： Energy utilization

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StressSense: An IoT-Enabled Platform for Stress Level Prediction, Prevention, and Methods There of 6th

StressSense: An IoT-Enabled Platform for Stress Level Predic...

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6th International Conference on Recent Innovations in Computing, ICRIC 2023

作者： Gandhala, Santhosh Phanitalpak Joshi, Shubham Das, Sonali Saha, Upasana Department of Computer Science and Engineering Symbiosis Institute of Technology Pune India

ISBN: (纸本)9789819778614

As eloquently articulated by the esteemed sociologist and writer Chelsea Erieau, stress is a dynamic force, akin to an accelerator that exerts its influence, invariably driving individuals either forward or backward. This proposed project emerges as a beacon of hope, offering a sophisticated and highly effective solution for the detection and management of stress levels. It harnesses the power of cutting-edge physiological sensors, encompassing a pulse sensor (MAX30102), a Galvanic Skin Response sensor (GSR Grove v2.0), a body temperature sensor (DS18B20), and an array of other essential data sources like the smart watches (Apple Watch Ultra and Noise BT) for vitals. In conjunction with this, it introduces a user-centric application interface that has been meticulously crafted for the real-time analysis of sensor data, representing a revolutionary step forward in stress management. This interface leverages the prowess of advanced machine learning (ML) libraries and techniques, including TensorFlow and PyTorch for deep learning, regression models, and Scikit-learn for ensemble learning, as well as kNN models. It provides a dynamic and robust platform to monitor physiological responses and offer personalized recommendations. This user-centric approach empowers individuals to navigate the challenges of stress and achieve well-being. This innovative solution marks a significant shift toward personalized stress management, offering a lifeline to individuals seeking to mitigate the negative impacts of stress and lead a healthier, balanced life. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Physiological models

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Backpropagation-Based Deep Learning Model for Privacy-Preserving of Confidential Data 4th

Backpropagation-Based Deep Learning Model for Privacy-Preser...

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4th International Conference on Data, engineering, and Applications, IDEA 2022

作者： Soni, Mukesh Singh, Dileep Kumar Department of Computer Science and Engineering Jagran Lakecity University Bhopal India

ISBN: (纸本)9789819700363

Methods for neural network learning that rely on backpropagation are commonly used in fields including intrusion detection, bioinformatics, homeland security, and medical diagnostics. These application sectors extract trends and patterns from enormous volumes of complex information. In the application categories mentioned, protecting personal information and sensitive data is a critical concern. Most of the backpropagation neural network learning techniques now in use do not consider how to safeguard sensitive data during learning. This study suggests using a backpropagation neural network technique since it preserves privacy and works well with horizontally partitioned data. The network weight vector must be produced for the training sample set when building the neural network. Information is not made public to preserve the neural network learning model's privacy. In this study, it is suggested that the weight vector is divided among all participants, with a portion of its value going to each participant. Each layer of the neural network safely computes the final and intermediate weight vector values of the network utilizing a secure multi-party computing protocol. The learning model developed may be safely distributed across all participants, who can then use it to predict the output corresponding to their objective data. The experimental results show that the recommended method outperforms traditional non-privacy-preserving algorithms in speed and accuracy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Adversarial machine learning

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A Novel Approach for Channel Assignment Using Optimization Technique in Wireless Networks 6

A Novel Approach for Channel Assignment Using Optimization T...

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6th IEEE International Conference on Emerging Smart Computing and Informatics, ESCI 2024

作者： Sheenam Chadha, Raman Chandigarh University Department of Computer Science and Engineering Punjab Mohali India

ISBN: (纸本)9798350306613

Due to their adaptable deployment options and complementary communication features, Wireless Mesh Networks (WMNs) have experienced an exponential rise in popularity in recent years. WMNs, a crucial component of next-generation wireless networking, have great promise for both the academic and commercial worlds. However, the best routing protocols are lacking in the present WMNs. Instead, a lot of WMNs use ad hoc network routing methods, which have various network characteristics as a result, routing is now the most pressing issue that must be addressed as soon as possible. The proposed model used the Ant-In-Mesh routing algorithm and its upgraded version is being developed in this paper to deal with the demanding traffic needs of WMNs. This algorithm was influenced by the conventional Ant Colony Optimization (ACO) approach, which provides an optimum path for best routing in dynamic networks by using Ant colony optimization and improves network performance by removing and reconnecting dead paths in mesh networks. © 2024 IEEE.

关键词： Ant Colony Optimization channel assignment route selection wireless mesh network

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Addressing Power Grid Stability With Grid-Forming Converters in Future Energy Systems

Addressing Power Grid Stability With Grid-Forming Converters...

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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Saxena, Kumud Vijay, Sandip Kamalraj, R. Noida Institute of Engineering and Technology Department of Computer Science Engineering Uttar Pradesh Greater Noida India Tula's Institute Department of Computer Science and Engineering Dehradun India Department of Computer Science Bangalore India

ISBN: (纸本)9798350357769

Synchronous generators (SGs) have been a major component of the power system's historical reliance on inertia and grid stability. However, since there is a visible lack of inertia with the growing integration of power-electronics-interfaced clean energy sources, the grid's stability has faced issues during the last ten years. Now, grid-following (GFL) converters are mostly used on the presumption that inertial stimuli are enough to control system stability. However, this assumption turns out to be insufficient for the future low-inertia grids that are projected. Grid-forming (GFM) converters, which emulate the functions of conventional synchronous machinery, have emerged as a possible approach to overcome these issues and enable low-inertia grids. Although the literature provides information on small-signal instability performance study of GFM converters, large-signal instability research is still lacking. Moreover, a multitude of topologies and variations of GFM conversion have been put forward;nevertheless, a thorough comparative analysis that encompasses all GFC variants and specifically addresses large-signal stability concerns is noticeably lacking. By consolidating and contrasting all currently available GFM control techniques from the perspective of large-signal stability concerns, this work aims to close this gap. The goal is to set the stage for further study and development of GFM mode converters designed particularly for large-signal stability analysis and stabilization in the next low-inertia grids. This thorough analysis not only resolves the existing shortcomings that have been highlighted but also lays the groundwork for furthering our knowledge of and use of GFM conversions in the dynamic world of power systems. © 2023 IEEE.

关键词： Grid-Following Converters Grid-Forming Converters Large-Signal Stability Inertia Power Grid and Renewable Energy Small-Signal Stability

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Enhanced Brain Tumor Detection via ResNet50 Classification and Residual U-Net Segmentation 2

Enhanced Brain Tumor Detection via ResNet50 Classification a...

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2nd International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2025

作者： Saeed, Abdullah Dhanda, Namrata Kumar Gupta, Kapil Department of Computer Science and Engineering Amity University Uttar Pradesh Lucknow India

ISBN: (纸本)9798331530389

AI-driven dual-model system for brain tumor detection in MRI scans, combining classification and segmentation techniques. A ResNet50-based convolutional neural network (CNN) identifies the presence of tumors, while a ResUNet architecture ensures precise segmentation for accurate localization. To enhance localization, ResUNet architecture is employed for pixel-wise segmentation, providing precise tumour boundaries within the MRI images. By incorporating transfer learning techniques, the models benefit from pre-trained weights, significantly improving performance and reducing training time. Innovative use of Focal Tversky loss addresses data imbalance, improving segmentation accuracy for irregular tumour shapes. Experimental results demonstrate superior performance with 9 5 % classification accuracy and a Dice score of 0.91 for segmentation. This dual-model pipeline offers a robust solution for early detection and precise localization of brain tumours, which is critical for timely medical intervention and improved patient outcomes. © 2025 IEEE.

关键词： Convolutional neural networks

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Suitability of Blockchain Smart Contracts for Securing the Internet of Things 5th

Suitability of Blockchain Smart Contracts for Securing the I...

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5th International Conference on Advances in Information Communication Technology and Computing, AICTC 2024

作者： Khichi, Deepika Sharma, Ajay Kumar Patel, Mayank Rathore, Narendra Singh Department of Computer Science Engineering GITS Udaipur India GITS Udaipur India

ISBN: (纸本)9789819761050

Due to its core characteristics, blockchain research has gained attention (Alrubei et al, in Ethereum blockchain for securing the Internet of Things: practical implementation and performance evaluation. IEEE, 2019 [1]). This is because it provides anonymity, security and integrity and is independent from the reliable 3rd party organizations. Blockchain technology could initially only be employed with currency. However, applications outside of crypto currencies are already being created and investigated thanks to the emergence of Ethereum, which enables the development and how smart contracts are executed (miniature computer programmes that operate on blockchain technology). The fact is that an enormous progress has been made for the improvement of the technology of blockchain and stress is given on smart contracts (Zhaofeng et al, in IEEE Trans Ind Inform 16(3):2013–2021, 2019 [2]). It was found that few descriptive studies on the application of smart contracts for security of IoT and Internet are present. The purpose of this research project is to locate and evaluate scholarly works on smart contracts based on blockchain for securing the Internet. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Smart contract

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Improved-Equalized Cluster Head Election Routing Protocol for Wireless Sensor Networks

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computer Systems science & engineering 2023年第1期44卷 845-858页

作者： Muhammad Shahzeb Ali Ali Alqahtani Ansar Munir Shah Adel Rajab Mahmood Ul Hassan Asadullah Shaikh Khairan Rajab Basit Shahzad Department of Computer Science Institute of Southern PunjabMultan5932Pakistan College of Computer Science and Information Systems Najran UniversityNajran61441Saudi Arabia Department of Computer Skills Deanship of Preparatory YearNajran UniversityNajran61441Saudi Arabia Department of Engineering National University of Modern LanguagesIslamabad44000Pakistan

Throughout the use of the small battery-operated sensor nodes encou-rage us to develop an energy-efficient routing protocol for wireless sensor networks(WSNs).The development of an energy-efficient routing protocol is a mainly adopted technique to enhance the lifetime of *** routing protocols are available,but the issue is still *** is one of the most important techniques in the existing routing *** the clustering-based model,the important thing is the selection of the cluster *** this paper,we have proposed a scheme that uses the bubble sort algorithm for cluster head selection by considering the remaining energy and the distance of the nodes in each ***,the bubble sort algorithm chose the two nodes with the maximum remaining energy in the cluster and chose a cluster head with a small *** proposed scheme performs hierarchal routing and direct routing with some energy *** simulation will be performed in MATLAB to justify its performance and results and compared with the ECHERP model to justify its ***,the simulations will be performed in two scenarios,gate-way-based and without gateway to achieve more energy-efficient results.

关键词： Bubble sort algorithm gateway energy thresholds wireless sensor networks

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Non-Contact Vital Prediction Using rPPG Signals 1

Non-Contact Vital Prediction Using rPPG Signals

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1st IEEE International Conference on Contemporary Computing and Communications, InC4 2023

作者： Madhu, Meghna Gurudas, V.R. Manjunath, Chinthakunta Naik, Praveen Kulkarni, Praveen School of Engineering and Technology Department of Computer Science and Engineering Bangalore India Dayananda Sagar University Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350335774

In this paper, we present the clinical significance of various cardiac symptoms with the use of heart rate detection, ongoing monitoring and present emotions. The development of algorithms for remote photoplethysmography has drawn a lot of interest during the past decade (rPPG). As a result, using data gathered from the video feed, we can now precisely follow the heart rate of individuals who are still seated. rPPG algorithms have also been developed, in addition to technique based on hand-crafted characteristics. Deep learning techniques often need a lot of data to train on, but biomedical data frequently lacks real-world examples. The experiment described in this work, we looked at how illumination affected the rPPG signals' SNR. The findings show that the SNR in each RGB channel varies depending on the colour of the light source. Paper describes development in video filtering for recognising the comprehending human face emotions. In our method, emotions are deduced by identifying facial landmarks and analysing their placement. © 2023 IEEE.

关键词： Photoplethysmography

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Simplifying code translation: Custom syntax language to C language transpiler 2

Simplifying code translation: Custom syntax language to C la...

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2nd International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2025

作者： Lalith, Pecheti Charan Goel, Sujal Kakkar, Misha Sharma, Seema Department of Computer Science and Engineering Amity University Uttar Pradesh Noida India

ISBN: (纸本)9798331530389

In today's world, programming has become a very essential skill as it is used everywhere, from creating software's for operating systems to analysis of patients' health care data in biomedical engineering. Programmers usually face a lot of difficulties to understand beginner level coding languages having low-level syntax. The proposed study "Simplifying Code Translation: Custom Syntax Language to C Language Transpiler", targets the specified problem and provides the solution in a form of transpiler that converts the newly developed custom language (made up of high-level syntax) to C language. The developed tool minimizes the overall cost incurred during the code designing process. This transpiler consists of 4 main parts: preprocessor, lexer, parser and emitter. It first starts by creating preprocessor which handles preprocessor directives such as 'define' and 'include'. This preprocessed code is then passed onto lexer which tokenizes the code. The parser is responsible for creating Abstract Syntax Tree (AST) using the tokens provided. The final AST is then transformed to C program by the emitter. Then output C code maintains proper syntactic and semantic structure of the original custom syntax language code. © 2025 IEEE.

关键词： C (programming language)

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