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3rd IEEE International Conference of Electron Devices Society Kolkata Chapter, EDKCON 2024

作者： Santra, Soumen Majumdar, Dipankar Mandal, Surajit Deyasi, Arpan Techno International New Town Department of Computer Application Kolkata India RCC Institute of information Technology Department of Computer Science and Engineering Kolkata India B. P. Poddar Institute of Management & Technology Department of Electronics and Communication Engineering Kolkata India RCC Institute of Information Technology Department of Electronics and Communication Engineering Kolkata India

ISBN: (纸本)9798350374643

In this paper, novel cancer detection method using Kernel Based Fuzzy Simulation Model (KBFSM) represented with enhanced accuracy of 12%, considering MRI based breast cancer images. Developed framework, as suggested in this paper, Effectiveness and superiority of the suggested approach are proven by thorough testing on a variety of datasets and thorough assessment metrics, highlighting its capacity to produce accurate and nuanced segmentation results. Fuzzification and defuzzification of images using Fuzzy C means algorithm, speaks in favor of the proposed analysis, as tested over several dataset, owing to minute pixel intensity modification when associated with malignant tissues. Result is supported by histogram analysis, which paves the way of future research in the field of lung cancer using the same technique. © 2024 IEEE.

关键词： Lung cancer

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Enhancing Speech Emotion Recognition Combining Silence Elimination and Attention Model with a Novel CNN Architecture 8th

Enhancing Speech Emotion Recognition Combining Silence Elimi...

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8th International Conference on information and Communication technology for Intelligent Systems, ICTIS 2024

作者： Gawali, Piyush P. Takale, Dattatray G. Deshmukh, Gopal B. Kashid, Shraddha S. Mahalle, Parikshit N. Sule, Bipin Ashokrao, Patil Rahul Derle, Deepak R. Department of Computer Engineering Vishwakarma Institute of Information Technology SPPU Pune Pune India Department of Computer Engineering MIT ADT University Pune India Department of Artificial Intelligence and Data Sciences Vishwakarma Institute of Information Technology SPPU Pune Pune India and Humanities Vishwakarma Institute of Technology Pune India Department of Computer Science and Application KTHM College Nashik India

ISBN: (纸本)9789819766772

A natural interface for human–computer interaction is automatic speech emotion recognition, but it encounters challenges in handling non-emotional speech segments, especially silence, since it is non-emotional speech segmentation that requires recognition. Using a carefully designed attention model and a silence elimination approach, this paper proposes a novel method of enhancing emotion recognition performance by combining silence elimination with attention. In the present study, an enhanced Convolutional Neural Network architecture has been proposed, comprising of nine layers, utilizing a combination of convolutional 1D As a result of the research, CNNs have been employed in a revolutionary speech-emotion detection system that reaches an impressive 96.00% accuracy rate. There is great potential in this breakthrough to develop social robots and conversational robots capable of conveying nuanced human emotions. This breakthrough has marked a significant improvement in accuracy compared to prior models based on the same dataset. In addition to the broader classifications of positive, negative, and neutral emotions, the model's accuracy is evaluated across a wide range of emotion classes, such as anger, calmness, fear, happiness, and sadness for both genders. There is considerable evidence to suggest that combined noise cancellation and attention models are more effective than individual models of noise cancellation or attention. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Convolutional neural networks

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Performance Issues and Research Challenges in Designing a Secure IoT with Blockchain 3

Performance Issues and Research Challenges in Designing a Se...

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3rd International Conference on Issues and Challenges in Intelligent Computing Techniques, ICICT 2022

作者： Hemani Singh, Dayashankar Dwivedi, Rajendra Kumar Madan Mohan Malaviya University of Technology Department of Information Technology and Computer Application Gorakhpur India

ISBN: (纸本)9781665482684

Now a day, Internet of Things (IoT) are being used in several areas such as vehicular systems, smart city, healthcare, and supply chain management. Sensor data is stored in the cloud in an IoT system. Therefore, there is always a security concern with this data. There are several techniques for maintaining security, but most of them work in a centralized manner. However, blockchain is an emerging technology that works in a distributed manner and is based on peer-to-peer computing. Security can be enhanced using blockchain in any system. Blockchain technology offers decentralised security and privacy. Sensors used in loT systems are resource constrained. Therefore, implementing blockchain in any loT system creates several research challenges. This paper provides a discussion on such performance issues and research challenges while integrating blockchain with loT. The paper also gives some insights to overcome such issues. © 2022 IEEE.

关键词： Smart contract

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Inception and LightGBM-based Model for Poly-Cystic Ovary Syndrome Detection with CNN in Ultra-sound Images 4

Inception and LightGBM-based Model for Poly-Cystic Ovary Syn...

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4th IEEE Asian Conference on Innovation in technology, ASIANCON 2024

作者： Puri, Shalini Soni, Akanksha Choudhary, Vishal Manipal University Department of Information Technology Rajasthan Jaipur India UIT-RGPV Department of Electronics Communication & Engineering Bhopal India Lovely Professional University Department of Computer Application Punjab India

ISBN: (纸本)9798350354218

Nowadays, a common hormonal condition that affects women of reproductive age and frequently results in infertility is Poly-Cystic ovary syndrome. Recognizing the Poly-Cystic ovary syndrome early is essential for symptom management and mitigating associated health risks. The traditional methods are used for diagnosis, encompassing high androgen levels, anovulation, and Poly-Cystic ovaries observed via ultra-sound. However, the challenging aspect of manually assessing Poly-Cystic ovaries observed via ultra-sound through follicle counting and thickness determination by medical professionals persists. In addition to addressing patient symptoms, clinicians must rely on a combination of biochemical and clinical indicators, lacking standardized diagnostic procedures. To alleviate these diagnostic challenges, this paper presents a hybrid Poly-Cystic Ovary Syndrome Detection model using a convolutional neural network comprising an ensemble inception model and a light gradient-boosting machine on ultra-sound Images. It significantly improves the detection of the Poly-Cystic ovaries observed and achieves an accuracy of 98.4%, surpassing InceptionV3's 96.3%. This study substantiates this performance gain through comprehensive quantitative effectiveness assessment metrics. This study proposes a promising model for accurate and efficient Poly-Cystic ovary syndrome diagnosis, aiding clinicians in providing timely and targeted care to affected individuals. © 2024 IEEE.

关键词： Deep neural networks

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Evolution of AVS video coding standards: twenty years of innovation and development

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Science China(information Sciences) 2022年第9期65卷 50-73页

作者： Siwei MA Li ZHANG Shiqi WANG Chuanmin JIA Shanshe WANG Tiejun HUANG Feng WU Wen GAO Institute of Digital Media School of Computer Science Peking University Bytedance Inc. Department of Computer Science City University of Hong Kong CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China

Ever since the founding of the Audio and Video Coding Standard(AVS) Workgroup of China in 2002, it has been dedicated to advancing and innovating the digital audio-video industry with highly efficient and economical encoding/decoding technologies. Three representative generations of video coding standards have been finalized and published, consistently improving the coding performance in the past two *** series of AVS standards establish solid foundations for ubiquitous video applications in the areas including acquisition, coding, production, delivery, integrated system, public service, general screen content, and mixed reality media. Along with the standardization process, an extensive amount of studies have been carried out on efficiency-aware designation, algorithm optimization, and hardware implementation of these innovative video coding techniques. This paper explains how those developed techniques provide a lasting impact on the video coding community, extensively, technologically, and systematically. In particular, we provide a comprehensive survey of the three generations of the standards, and timely and in-depth summarize the efforts of the AVS video coding standards in the twenty years. The rate-distortion performance comparisons,in particular in terms of the 8K ultra-high-definition(UHD) contents, reflect the elegant design of the state-of-the-art AVS3 standards. We have also elaborated on a variety of well-established and promising applications, including commercial level real-time 8K encoder, high-frame-rate decoder chip for cell phone,and live streaming solution for sports. In addition, the China Central Television(CCTV) of China Media Group(CMG), the state television of China, has officially launched the first 8K broadcasting channel(CCTV-8K) since 2021 using AVS3. Given the significant success realized by the AVS standards, it is envisioned that a new era of 8K UHD video is arriving.

关键词： video coding AVS standards video applications intelligent coding

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Remote Sensing Target Recognition Model Based on Small Sample Image Generation 4

Remote Sensing Target Recognition Model Based on Small Sampl...

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4th International Symposium on computer Engineering and Intelligent Communications, ISCEIC 2023

作者： Chen, Lei Sun, Liting Space Engineering University School of Space Information Beijing China Beijing Institute of Computer Technology and Application General Department of Network and Information Security Beijing China

ISBN: (纸本)9798350306323

In recent years, remote sensing object recognition methods based on deep learning have received extensive attention. Deep learning methods need to use a large number of labeled data to carry out network training. However, the cost of labeling remote sensing image data is very high. Therefore, how to use a small number of labeled target images to train the remote sensing target classifier with high performance is an urgent problem to be solved. In view of the above problems, this paper has carried out the following work. Firstly, based on WGAN-GP, this paper optimizes the constraint conditions of neural network and proposes a depth generation model, namely CCWGAN-GP, for remote sensing image generation. Secondly, this paper proposes a remote sensing target classification model SCLNet, which makes full use of the original one-hot label and the generated soft classification label to train the neural network. Experimental results show that the proposed model can generate highly similar images to real images, and can significantly improve the performance of the classifier under training conditions with only a few labels. © 2023 IEEE.

关键词： Remote sensing

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An Enhanced Explicit Port Forwarding Solution for Improving Video Delivery over Software-Defined Networks

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Journal of Internet technology 2023年第2期24卷 313-321页

作者： Ke, Chih-Heng Lo, Yu-Wen Chen, Yeong-Sheng Chen, Hung-Pai Department of Computer Science and Information Engineering National Quemoy University Taiwan Master of Information Technology and Application National Quemoy University Taiwan Department of Computer Science National Taipei University of Education Taiwan The Graduate School of Arts and Humanities Instruction National Taiwan University of Arts Taiwan

In order to improve video delivery, an Enhanced Explicit Port Forwarding (EEPF) solution is proposed. Data are divided into ordinary packets and video packets using a packet identification mechanism. Traditional mechanisms transmit packets through routing table lookup. As the size of the routing table often becomes excessively large, this lookup can be time-consuming. While the EEPF solution directly includes the transmission path in the video packet, which can reduce the transmission time. And by setting header flags/fields in video packets, the transmission can be further optimized. For example, to reduce the amount of duplicate data to be transmitted for broadcast packets are not replicated until they arrive at the destination switch;to avoid packet loss caused by disconnection, the transmission path can be monitored and rerouting can be initiated immediately in the event of disconnection;to increase the chance of successful delivery, packets can be replicated before they are transmitted via a path with high packet loss risk;and to prevent video packets from being discarded, the switch queue status can be monitored and managed. The testing results have shown that the EEPF solution can effectively shorten the time of video packet transmission and improve the quality of transmitted video. © 2023 Taiwan Academic Network Management Committee. All rights reserved.

关键词： Packet loss

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A Comprehensive Study of a Conversational AI-Driven Healthcare Bot with Pose Estimation for Precision Fitness Monitoring and Personalized Guidance

A Comprehensive Study of a Conversational AI-Driven Healthca...

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2024 IEEE International Conference on Big Data and Machine Learning, ICBDML 2024

作者： Sinha, Anurag Kumar, Biresh Kundu, Roumo Sharma, Amit Sharma, Mukesh Raza, Asif ICFAI University ICFAI Tech School Computer Science Department Jharkhand Ranchi India Amity University Department of Computer Engineering and Application Jharkhand India Amity Institute of Information Technology Amity University Jharkhand Jharkhand Ranchi India Lovely Professional University Department of Computer Science Phagwara India Amity University Department of Master of Computer Application Jharkhand Ranchi India

ISBN: (纸本)9798350374100

This research investigates a new healthcare paradigm through the analysis of a conversational AI-powered healthcare bot that has posture estimation capabilities for accurate fitness tracking and customized recommendations. User motions during workout routines are accurately and thoroughly assessed thanks to the incorporation of powerful posture estimation technology. With the help of individualized exercise advice, this thorough study explores the capabilities of the system and shows how it may transform wellness practices. The healthcare bot provides an innovative method of fitness tracking by using conversational AI and accurate posture prediction to customize recommendations based on user requirements. This novel combination promises to enhance wellbeing and provide consumers with a more efficient and customized workout experience. The study emphasizes this point. © 2024 IEEE.

关键词： Health care

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Distributed Aperture Coherent Synthesis Method based on Two-stage Compensation 2

Distributed Aperture Coherent Synthesis Method based on Two-...

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2nd IEEE International Conference on Signal, information and Data Processing, ICSIDP 2024

作者： Liu, Zhongwei Zhou, Dongming Xiang, Rongrong Chen, Jie Wu, Tianhang Ding, Tianyu Liu, Xiaochuan Gao, Hongwei Beihang University School of Electronic and Information Engineering Beijing China School of Information and Electronics Beijing Institute of Technology Radar Research Lab Beijing China Beijing Institute of Computer Technology and Application Department of Data Technology and Application Beijing China Beijing Institute of Radio Measurement Radar R&d Center Beijing China

ISBN: (纸本)9798331515669

To solve the problem that it is difficult to accurately estimate the coherent parameters of distributed aperture radar under the condition of low signal-to-noise ratio, a distributed coherent synthesis method based on two-stage compensation is proposed in this paper. This method utilizes prior information such as system layout, beam pointing, and inertial navigation station location to perform coarse alignment of echoes at the first stage in time, and then uses cross-correlation method to estimate coherent parameters of delay and phase within a small range, and perform precise compensation of time and phase at the second stage, so as to realize the coherent synthesis of multiple radar echoes. Experimental results show that the proposed method can effectively realize distributed coherent synthesis processing under low signal-to-noise ratio. © 2024 IEEE.

关键词： Signal to noise ratio

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Big Data Privacy: A Survey Paper

Big Data Privacy: A Survey Paper

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2023 International Conference on IoT, Communication and Automation technology, ICICAT 2023

作者： Gupta, Manish Kumar Rai, Ashok Kumar Pandey, Bipin Gupta, Anurag Verma, Vipul Kumar Madan Mohan Malaviya University of Technology Department of Information Technology & Computer Application UP Gorakhpur273010 India Madan Mohan Malaviya University of Technology Department of Computer Science & Engineering UP Gorakhpur273010 India

ISBN: (纸本)9798350302820

Big Data (BD) has grown in popularity as a research subject in recent years. The likelihood of violating personal privacy also rises with the growth of big data. Distributed systems are used because BD calls for a lot of processing capacity and storage. These systems increase the danger of privacy violation because numerous parties are involved. Numerous PP techniques have been created to safeguard privacy at various stages of the BD life cycle, including data generation, storage, and processing. This paper aims to give a thorough overview of the privacy preservation mechanisms in BD and the difficulties of current mechanisms. In this paper, we present BD infrastructure and cutting-edge privacy in a different phase of the BD life cycle. Furthermore, a comparative analysis also provided for different PP techniques. This paper also discusses related works in terms of review and research. The paper is summed up with the conclusion and future work. © 2023 IEEE.

关键词： Big data

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