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16th International Conference on Contemporary Computing, IC3 2024

作者： Gurbuxani, Shrey Gupta, Lakshay Madan, Kapil Department of Computer Science Engineering and Information Technology Jaypee Institute of Information Technology Noida India

ISBN: (纸本)9798400709722

An AI wellness coach is a software program that guides users through physical health routines by leveraging MediaPipe, OpenCV, and Python features. The program uses OpenCV computer vision techniques to monitor user progress and provide feedback on procedure and frame. To prepare the video data and provide real-time assessments, MediaPipe is used. Additionally, the app makes use of machine learning algorithms to provide users with tailored wellness recommendations and promote adoption. When these advances are combined, clients have an incredibly intelligent and practical way to advance their physical fitness. © 2024 Copyright held by the owner/author(s).

关键词： Python

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Centrality of Any Node in Social Network Analysis 2024

Centrality of Any Node in Social Network Analysis

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16th International Conference on Contemporary Computing, IC3 2024

作者： Srivastava, Milli Manju, Manju Department of Computer Science & Engineering and Information Technology Jaypee Institute of Information Technology Noida India

ISBN: (纸本)9798400709722

In the contemporary landscape of advanced mobile technology, social media platforms have emerged as prominent arenas for expression, fostering vast volumes of communication ripe for research and analysis. Social network analysis (SNA) stands as a pivotal tool in identifying influential individuals within microblogging platforms, notably Twitter, which serves as a catalyst for online dialogues, trends, and content virality. The applications of discerning influential users on Twitter are multifaceted, ranging from viral marketing and brand analysis to news dissemination, health awareness campaigns, political activism, and governance empowerment. In this study, we introduce a sustainable method, termed Weighted Correlated Influence (WCI), designed to capture the relative impact of both activity on a timeline and characteristics of online users that are trend-specific. Weighted Correlated Influence in social network analysis evaluates the significance of nodes by combining their connectivity and influence, considering both the weight and correlation of their relationships. This metric helps identify key influencers and the overall structure of the network, highlighting nodes with high influence and strong, correlated connections. Our methodology integrates profile activity with underlying network topology to assign influence scores to users, synthesizing their combined effect. To evaluate the efficacy of our proposed methodology, we focus on the Twitter trend #Coronavirus Pandemic and validate the results against another social media trend. Experimental findings demonstrate the superior performance of WCI over existing methods. © 2024 Copyright held by the owner/author(s).

关键词： Tweets

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Analytical study of the encoder-decoder models for ultrasound image segmentation

Analytical study of the encoder-decoder models for ultrasoun...

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作者： Srivastava, Somya Vidyarthi, Ankit Jain, Shikha Department of Computer Science Engineering & Information Technology Jaypee Institute of Information Technology Noida India

Accurate diagnosis and treatment planning for medical conditions rely heavily on the results of medical image segmentation. Medical images are available in many modalities like CT scans, MRI, histopathological, and ultrasound images. Among all, the real-time analysis of the ultrasound is the most complex as the internal organ’s visualization requires experience from the radiologist. Diagnosing the medical conditions and unavailability of experienced radiologists during an emergency requires automated segmentation which heavily depends on computer-aided diagnostic systems. The new generation CAD systems are found to incorporate advanced deep learning algorithms to produce accurate segmentation results. While most of the segmentation models relate to the encoder-decoder model as the base architecture and thus evolve a variety of modifications in its pipeline architecture. This paper presents the analytical study of the various Encoder- Decoder based models like UNet, Residual UNet (Res-U-Net), Dense UNet (DenseUNet), Attention UNet, UNet + +, Double UNet, and U2Net (U-Squared-Net) on ultrasound image segmentation. Further, the paper presents the various trade-offs, application areas, open challenges, and performance analysis of these models on benchmark datasets, namely the HC18 Challenge dataset, CUM dataset, and B-mode Ultrasound Nerve Segmentation dataset. The performance analysis of these models is presented using the six state-of-the-art metrics like Dice coefficient, Jaccard index, sensitivity, specificity, Mean Absolute distance, and Housdorff Distance. Based on the above parameters U2-Net (U-Squared-Net) outperformed all other neural network models for all three datasets. In terms of all four criteria (Dice Coefficient: 0.92, 0.89, 0.9, Jaccard Index: 0.81, 0.79, 0.81, Sensitivity: 0.86, 0.84, 0.86, Specificity: 0.97, 0.95, 0.96), the U2-Net (U-Squared-Net) model performed the best. Over the HC18 Challenge dataset, the CUM dataset, and the B-Mode Ultrasound ne

关键词： Deep neural networks

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High Utility Periodic Frequent Pattern Mining in Multiple Sequences

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computer Modeling in engineering & sciences 2023年第10期137卷 733-759页

作者： Chien-Ming Chen Zhenzhou Zhang Jimmy Ming-Tai Wu Kuruva Lakshmanna College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao266590China Department of Information Technology Vellore Institute of TechnologyVellore632014India

Periodic patternmining has become a popular research subject in recent years;this approach involves the discoveryof frequently recurring patterns in a transaction sequence. However, previous algorithms for periodic patternmining have ignored the utility (profit, value) of patterns. Additionally, these algorithms only identify periodicpatterns in a single sequence. However, identifying patterns of high utility that are common to a set of sequencesis more valuable. In several fields, identifying high-utility periodic frequent patterns in multiple sequences isimportant. In this study, an efficient algorithm called MHUPFPS was proposed to identify such patterns. To addressexisting problems, three new measures are defined: the utility, high support, and high-utility period sequenceratios. Further, a new upper bound, upSeqRa, and two new pruning properties were proposed. MHUPFPS usesa newly defined HUPFPS-list structure to significantly accelerate the reduction of the search space and improvethe overall performance of the algorithm. Furthermore, the proposed algorithmis evaluated using several *** experimental results indicate that the algorithm is accurate and effective in filtering several non-high-utilityperiodic frequent patterns.

关键词： Decision making frequent periodic pattern multi-sequence database sequential rules utility mining

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Vehicle Accident Detection and Reporting System using Internet of Things 5

Vehicle Accident Detection and Reporting System using Intern...

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5th International Conference on Electronics and Sustainable Communication Systems, ICESC 2024

作者： Goyal, Atul Gupta, Priyansh Pandey, Kavita Jaypee Institute of Information Technology Department of Computer Science & Engineering and Information Technology Noida India

ISBN: (纸本)9798350379945

The rising number of vehicles on the road has led to a concerning increase in accidents, as reported by the Indian Government's Ministry of Road Transport and Highways. In many cases, prompt medical assistance can save lives. While numerous solutions exist to address this issue, most are limited to two-wheelers. In contrast, this research study presents a vehicle-independent solution that employs sensors to detect accidents in any vehicle type, making it highly effective and cost-efficient. The proposed model automatically identifies and report accidents in real-time, enhancing the road safety. It utilizes advanced sensors and communication technology to promptly notify emergency services and relevant authorities for timely response and assistance. © 2024 IEEE.

关键词： Vehicle detection

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Hybrid Approach for Cost Efficient Application Placement in Fog-Cloud Computing Environments

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computers, Materials & Continua 2024年第6期79卷 4127-4148页

作者： Abdulelah Alwabel Chinmaya Kumar Swain Department of Computer Sciences College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of Computer Science and Engineering Institute of Management and Information TechnologyCuttackBPUTOdishaIndia

Fog computing has recently developed as a new paradigm with the aim of addressing time-sensitive applications better than with cloud computing by placing and processing tasks in close proximity to the data ***,the majority of the fog nodes in this environment are geographically scattered with resources that are limited in terms of capabilities compared to cloud nodes,thus making the application placement problem more complex than that in cloud *** approach for cost-efficient application placement in fog-cloud computing environments that combines the benefits of both fog and cloud computing to optimize the placement of applications and services while minimizing *** approach is particularly relevant in scenarios where latency,resource constraints,and cost considerations are crucial factors for the deployment of *** this study,we propose a hybrid approach that combines a genetic algorithm(GA)with the Flamingo Search Algorithm(FSA)to place application modules while minimizing *** consider four cost-types for application deployment:Computation,communication,energy consumption,and *** proposed hybrid approach is called GA-FSA and is designed to place the application modules considering the deadline of the application and deploy them appropriately to fog or cloud nodes to curtail the overall cost of the *** extensive simulation is conducted to assess the performance of the proposed approach compared to other state-of-the-art *** results demonstrate that GA-FSA approach is superior to the other approaches with respect to task guarantee ratio(TGR)and total cost.

关键词： Placement mechanism application module placement fog computing cloud computing genetic algorithm flamingo search algorithm

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Automatic emotion recognition using deep neural network

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Multimedia Tools and Applications 2025年 1-30页

作者： Sujatha, R. Chatterjee, Jyotir Moy Pathy, Baibhav Hu, Yu-Chen School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India Department of CSE Graphic Era University Dehradun India School of Electrical Engineering Vellore Institute of Technology Vellore India Department of Computer Science Tunghai University Taichung City Taiwan

Emotions are a vital semantic part of human correspondence. Emotions are significant for human correspondence as well as basic for human–computer cooperation. Viable correspondence between people is possibly achieved when both the importance and the emotion of the correspondence are perceived by all groups included. Understanding the significance of language has generally been concentrated on in natural language processing (NLP) as a semantic examination. In NLP, the text can be handled appropriately for classification. Emotion detection from facial emotion is the subfield of social signal processing applied in a wide assortment of regions, explicitly for human and PC collaboration. Many researchers have proposed various approaches, generally utilizing machine learning concepts. Automatic emotion recognition (AER) is significant for working with consistent intuitiveness between a person and a smart device toward fully acknowledging an intelligent society. Many researchers examined cross-lingual and multilingual speech emotion as a stage toward language-free emotion acknowledgment in natural speech. In the present work, we are proposing a deep learning-based AER system using four openly accessible datasets, namely Basic Arabic Vocal Emotions Dataset (BAVED), Acted Emotional Speech Dynamic Database (AESDD), Urdu written in Latin/Roman Script (URDU), and Toronto Emotional Speech Set (TESS), by utilizing the Jupyter notebook and a Python library for music and audio synthesis named Librosa. The experimental results exhibited that the proposed approach achieves better than the existing approaches, i.e., the accuracy of the proposed system with the URDU dataset is 96.24%, the TESS dataset is 99.10%, the AESDD dataset is 65.97%, and the BAVED dataset is 73.12%. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Semantics

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Modelling a Learning-Based Dynamic Tree Routing Model for Wireless Mesh Access Networks

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computer Systems science & engineering 2023年第2期44卷 1531-1549页

作者： N.Krishnammal C.Kalaiarasan A.Bharathi Department of Computer Science and Engineering Sri Shakthi Institute of Engineering and TechnologyCoimbatoreIndia School of Engineering Presidency UniversityBengaluruIndia Department of Information Technology Bannari Amman Institute of TechnologySathyamangalamIndia

Link asymmetry in wireless mesh access networks(WMAN)of Mobile ad-hoc Networks(MANETs)is due mesh routers’transmission *** is depicted as signiﬁcant research challenges that pose during the design of network protocol in wireless *** on the extensive review,it is noted that the substantial link percentage is symmetric,i.e.,many links are *** is identiﬁed that the synchronous acknowledgement reliability is higher than the asynchronous ***,the process of establishing bidirectional link quality through asynchronous beacons underrates the link reliability of asym-metric *** paves the way to exploit an investigation on asymmetric links to enhance network functions through link ***,a novel Learning-based Dynamic Tree routing(LDTR)model is proposed to improve network performance and *** the evaluation of delay measures,asymmetric link,interference,probability of transmission failure is *** proportion of energy consumed is used for monitoring energy conditions based on the total energy *** learning model is a productive way for resolving the routing issues over the network model during *** asymmetric path is chosen to achieve exploitation and exploration *** learning-based Dynamic Tree routing model is utilized to resolve the multi-objective routing ***,the simulation is done with MATLAB 2020a simulation environment and path with energy-efﬁciency and lesser E2E delay is evaluated and compared with existing approaches like the Dyna-Q-network model(DQN),asymmetric MAC model(AMAC),and cooperative asymmetric MAC model(CAMAC)*** simulation outcomes demonstrate that the anticipated LDTR model attains superior network performance compared to *** average energy consump-tion is 250 J,packet energy consumption is 6.5 J,PRR is 50 bits/sec,95%PDR,average delay percentage is 20%.

关键词： Wireless mesh access networks mobile ad-hoc network reinforcement learning multi-objective constraint asymmetric link

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SWIFT: Swarm Intelligence Driven ESL Synthesis for Functional Trojan Fortification 10

SWIFT: Swarm Intelligence Driven ESL Synthesis for Functiona...

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10th IEEE International Symposium on Smart Electronic Systems, iSES 2024

作者： Sengupta, Anirban Chaurasia, Rahul Indian Institute of Technology Department of Computer Science and Engineering Indore India Indian Institute of Information Technology Department of Computer Science and Engineering Bhopal India

ISBN: (纸本)9798331533229

This paper presents a novel Swarm Intelligence driven Electronic System-Level (ESL) synthesis-based security methodology for functional Trojan fortification (called 'SWIFT'). Backdoor functional Trojan covertly inserted in the reusable hardware designs is a major concern for ensuring reliability functionality of consumer electronics (CE) systems and also for ensuring consumer trust. Erroneous computed output due to malicious functional Trojan can cause malfunctioning of such reusable IP cores. Therefore, the proposed methodology introduces a framework that integrates triple modular redundancy (TMR) along with a unique multi-vendor allocation that enables the generation of Trojan fortified (resistant) reusable hardware intellectual property (IP) designs capable of countering functional Trojan, if present and producing the correct output. The proposed approach integrates the swarm intelligence-based design space exploration (DSE) process with Trojan fortification design process to optimize any possible design overhead incurred due to TMR design. Results of the experimental evaluation prove that the proposed approach can generate low-cost Trojan fortified IP designs at meagre exploration time and at the expense of nominal overhead compared to prior work (that handle Trojan detection only). Further, the presented approach can handle a several potential vulnerabilities in the DSP design, which shows its robust security strength. © 2024 IEEE.

关键词： Swarm intelligence

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Secure Accelerated Computing: High-Level Synthesis Based Hardware Accelerator Design for CNN Applications 10

Secure Accelerated Computing: High-Level Synthesis Based Har...

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10th IEEE International Symposium on Smart Electronic Systems, iSES 2024

作者： Chaurasia, Rahul Sengupta, Anirban Indian Institute of Information Technology Department of Computer Science and Engineering Bhopal India Indian Institute of Technology Department of Computer Science and Engineering Indore India

ISBN: (纸本)9798331533229

This paper introduces a novel methodology for designing secure hardware accelerator tailored for convolutional neural network (CNN) applications, leveraging security-aware high-level synthesis (HLS). The methodology outlined offers comprehensive security measures, including hindrance against reverse engineering (RE) and intellectual property (IP) piracy concerns through architectural transformations and embedded biometric palmprint constraints, respectively. Key contributions of this methodology include: i) robust hindrance against RE attack, ii) robust piracy detection with no additional design overhead, iii) definitive proof of IP ownership by achieving significantly lower probability of coincidence (P), indicating lower probability of false positive, and iv) enhanced tamper tolerance (TT) and resilience against brute force attacks compared to recent methodologies. © 2024 IEEE.

关键词： High level synthesis

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