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Wavelet scattering and scalogram visualization based human brain decoding using empirical wavelet transform

International Journal of Information Technology (Singapore) 2023年第3期15卷 1699-1708页

作者： Lakshmipriya, B. Jayalakshmy, S. School of Computer Science Engineering Vellore Institute of Technology Chennai Campus Chennai India Department of Electronics and Communication Engineering IFET College of Engineering Villupuram India

A prediction model to decode the human brain activities from brain signals is proposed in this work. The existing works available in the Neuroscience field are higher in the classification of brain related diseases like brain tumor, Alzheimer’s etc. whereas only very few works are done to understand the cognitive state of the human brain. In this work, decoding of brain signals is performed by analysing the time frequency representations of the signal using wavelet scattering and scalogram coefficients. The proposed approach decomposes the brain signals captured using functional near-infrared spectroscopy (fNIRS) into several intrinsic mode functions (IMFs) obtained through Empirical Wavelet Transform (EWT). Subsequently, the time frequency representations obtained from the wavelet scattering and scalogram coefficients of every IMFs are given as input to a popular transfer learning architecture, GoogLeNet for training and testing. The classification results obtained for every IMFs are compared and contrasted with the existing works. Wavelet scalogram representation of filter bank 2 of IMF 3 coefficients records better classification accuracy of 91.67%. © 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's institute of computer Applications and Management.

关键词： Brain decoding Empirical wavelet transform GoogLeNet Mental arithmetic Scalogram Wavelet scattering transform

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Enhanced Archimedes Optimization Algorithm for Clustered Wireless Sensor Networks

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computers, Materials & Continua 2022年第10期73卷 477-492页

作者： E.Laxmi Lydia T.M.Nithya K.Vijayalakshmi Jeya Prakash Kadambaajan Gyanendra Prasad Joshi Sung Won Kim Computer Science and Engineering Vignan’s Institute of Information Technology(Autonomous)Andhra Pradesh530049India Department of Computer Science and Engineering K.Ramakrishnan College of EngineeringTiruchirappalli621112India Department of Electronics&Communication Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesChennai600025India Department of Electronics&Communication Engineering Kalasalingam Academy of Research and EducationKrishnankoil626128India Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea Department of Information and Communication Engineering Yeungnam UniversityGyeongsan-siGyeongbuk-do38541Korea

Wireless sensor networks(WSN)encompass a set of inexpensive and battery powered sensor nodes,commonly employed for data gathering and tracking *** energy utilization of the nodes in WSN is essential to capture data effectively and transmit them to *** latest developments of energy efficient clustering techniques can be widely applied to accomplish energy efficiency in the *** this aspect,this paper presents an enhanced Archimedes optimization based cluster head selection(EAOA-CHS)approach for *** goal of the EAOA-CHS method is to optimally choose the CHs from the available nodes in WSN and then organize the nodes into a set of ***,the EAOA is derived by the incorporation of the chaotic map and pseudo-random ***,the EAOA-CHS technique determines a fitness function involving total energy consumption and lifetime of *** design of EAOA for CH election in the WSN depicts the novelty of *** order to exhibit the enhanced efficiency of EAOA-CHS technique,a set of simulations are applied on 3 distinct conditions dependent upon the place of base station(BS).The simulation results pointed out the better outcomes of the EAOA-CHS technique over the recent methods under all scenarios.

关键词： Wireless sensor network CH selection energy efficiency clustering lifetime

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E-waste management in the digital era: A sustainable computing approach

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IEEE Potentials 2024年第2期43卷 30-36页

作者： Ramasamy, Rajkumar Gopi, Rahul Sanmugam Palanisamy, Rohini Vel Tech Rangarajan Dr. Sagunthala R and D Institute of Science and Technology Department of Electronics and Communication Engineering Chennai600062 India Vel Tech Rangarajan Dr. Sagunthala R and D Institute of Science and Technology Department of Computer Science and Engineering Chennai600062 India

In the digital era, the proliferation of electronic devices has led to a surge in electronic waste (e-waste), posing significant environmental and health challenges. This article proposes a sustainable computing approach to e-waste management. The article explores the complexities of e-waste management and recycling frameworks within the context of sustainable computing and applications. It delves into the challenges posed by the rapid advancement of technology and the resultant surge in electronic waste. Strategies to mitigate e-waste are discussed, including approaches in product design. The article emphasizes collaborative efforts to address these challenges effectively. By adopting sustainable computing practices and leveraging innovative solutions, the aim is to create a more sustainable approach to managing electronic waste and its environmental impacts. © 1988-2012 IEEE.

关键词： electronic waste Recycling Green computing Metals Maintenance engineering Soil Regulation Water pollution Energy efficiency Resource management

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Enhancing IoT-Enabled Healthcare with Genetic-based Encryption and Authentication for Secure and Efficient wireless Data Transmission 7

Enhancing IoT-Enabled Healthcare with Genetic-based Encrypti...

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7th International Conference on Inventive Computation Technologies, ICICT 2024

作者： Padhy, Satyanarayan Vijaya Lakshmi, T.R. Ahmad, Shahnawaz Sophia, S. Senthilkumar, G. Natrayan, L. Centurion University of Technology And Management Department of Electronics And Communication Engineering Odisha India Mahatma Gandhi Institute of Technology Department of Electronics And Communication Engineering Telangana Hyderabad India Bennett University School of Computer Science Engineering And Technology Uttar Pradesh Greater Noida India Karunya Institute of Technology And Sciences Department of Computer Science And Engineering Tamil Nadu Coimbatore India Panimalar Engineering College Department of Computer Science And Engineering Tamil Nadu Chennai India Saveetha School of Engineering SIMATS Department of Mechanical Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350359299

The Internet of Things' incorporation with healthcare systems has enabled new prospects in patient monitoring and healthcare management. This research work offers a new Internet of Things (IoT) enabled healthcare system that integrates modern sensor technology with genetically-based authentication, and encryption methods. The proposed model is designed to improve healthcare sector wireless data transfer security, and efficiency in order to allow seamless remote monitoring, and timely intervention. The proposed system offers a comprehensive real-time health monitoring protocol through integration of pressure, temperature, and electrocardiogram (ECG) sensors. Genetically-based encryption and authentication schemes are employed to address the pressing requirement for robust security in healthcare systems, and data security. Performance tests including, doctor visualization time, sensor data transmission rate, and authentication time show an overall efficiency of 98.45% proving the effectiveness of the system over a multitude of parameters. This research work presents a complete solution to real-time monitoring, and data security in secure and efficient IoT enabled healthcare systems, and makes an important addition to this field. As demonstrated through the findings, such technology can potentially revolutionize remote patient monitoring and healthcare delivery. © 2024 IEEE.

关键词： Internet of things

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EDSA-Ensemble: an Event Detection Sentiment Analysis Ensemble Architecture

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IEEE Transactions on Affective Computing 2024年第2期16卷 1-18页

作者： PETRESCU, Alexandru TRUICA, Ciprian-Octavian APOSTOL, Elena-Simona PASCHKE, Adrian Computer Science and Engineering Department Faculty of Automatic Control and Computers National University of Science and Technology Politehnica Bucharest Bucharest Romania Fraunhofer Institute for Open Communication Systems Berlin Germany

As global digitization continues to grow, technology becomes more affordable and easier to use, and social media platforms thrive, becoming the new means of spreading information and news. Communities are built around sharing and discussing current events. Within these communities, users are enabled to share their opinions about each event. Using Sentiment Analysis to understand the polarity of each message belonging to an event, as well as the entire event, can help to better understand the general and individual feelings of significant trends and the dynamics on online social networks. In this context, we propose a new ensemble architecture, EDSAEnsemble (Event Detection Sentiment Analysis Ensemble), that uses Event Detection and Sentiment Analysis to improve the detection of the polarity for current events from Social Media. For Event Detection, we use techniques based on Information Diffusion taking into account both the time span and the topics. To detect the polarity of each event, we preprocess the text and employ several Machine and Deep Learning models to create an ensemble model. The preprocessing step includes several word representation models: raw frequency, TFIDF, Word2Vec, and Transformers. The proposed EDSA-Ensemble architecture improves the event sentiment classification over the individual Machine and Deep Learning models. Authors

关键词： Sentiment analysis

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Principles and Potentials of F5G: The Fifth Generation Fixed Network 1

Principles and Potentials of F5G: The Fifth Generation Fixed...

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1st International Conference on Circuits, Power, and Intelligent Systems, CCPIS 2023

作者： Routray, Sudhir K. Javali, Abhishek Sharmila, K.P. Pappa, M. Jha, Mahesh K. Sarangi, Susanta K. Cmr University Department of Computer Science and Engineering Bangalore India Cmr Institute of Technology Department of Electronics and Communication Engineering Bangalore India University Department of Electronics and Communication Engineering Bhubaneswar India

ISBN: (纸本)9798350315769

In general, 5G is understood to be the fifth generation of mobile communications. However, there is also a fifth generation of wired communications which is led by the optical fiber technologies. This technology too has several attractive features like the wireless mobile 5G. In this article, we present the basic concepts of Fifth Generation Fixed Network (F5G). We show its characteristics and explain how it is going to change the communication landscape. We present the key benefits of F5G and show the main motivations behind its development. There are several applications of F5G and many emerging applications are also being introduced every year. Therefore, this newly developed technology has a lot of commercial importance in the modern world. In addition to the above, F5G is going to be one of the main rivals of 5G in the fixed environment. It is expected that F5G will outperform all its contemporary access area technologies in the fixed domain in the next few years. In this article, we briefly present its applications and future economic prospects. © 2023 IEEE.

关键词： Optical fibers

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Improved Deep Matrix Factorization for Signal Recovery in Random Frequency Diversity Array Radar 2

Improved Deep Matrix Factorization for Signal Recovery in Ra...

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

作者： Guo, Dayan Lin, Zijian Huang, Tianyao Qi, Yue He, Jie Zhang, Xiao-Ping Wang, Xueqian Li, Gang University of Science and Technology Beijing School of Computer & Communication Engineering Beijing China Tsinghua Shenzhen International Graduate School Institute of Data and Information Shenzhen China Tsinghua University Department of Electronic Engineering Beijing China

ISBN: (纸本)9798331515669

Motivated by the success of recent deep learning researches on radar, we consider a deep learning based matrix factorization method for suppressing the high range-angle side-lobes in random frequency diversity array (FDA) radars. While the existing deep matrix factorization approach is designed for real-valued situations and signals of FDA radars are complex-valued cases, we propose two methods to extend the existing approach into complex-valued framework: 1) adjusting the neural network structures and activation functions for complex-valued operations, and 2) constructing a real-valued representation of the original complex-valued input. Simulation results demonstrate that the proposed methods outperform traditional ones in multi-target scenarios. © 2024 IEEE.

关键词： Matrix factorization

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Causal Digital Twins for Physical System Control 59

Causal Digital Twins for Physical System Control

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59th Annual Conference on Information Sciences and Systems, CISS 2025

作者： Mohseni-Sehdeh, Saeed Saad, Walid Sakaguchi, Kei Yu, Tao Virginia Tech Bradley Department of Electrical and Computer Engineering AlexandriaVA22305 United States Institute of Science Tokyo Department of Electrical and Electronic Engineering Tokyo Japan

ISBN: (纸本)9798331513269

Digital twins (DTs) are virtual representations of physical systems, replicating their behavior, dynamics, and interactions with the environment. Hosted on computational platforms, DTs have access to more extensive information and computational power than their physical counterparts (PTs), making them suitable for control applications. This paper proposes a novel DT-based control architecture that leverages causal learning to achieve autonomous control. In this framework, the DT employs causal inference to determine the desired system behavior and, subsequently, instructs the PT accordingly. By incorporating causal learning, a DT can gain self-training capabilities, enabling it to generate and analyze hypothetical scenarios based on cause-and-effect relationships. Simulation results show that DT-based control outperforms the traditional local control method by 49% in terms of the tracking performance measured through the mean squared error. Additionally, causal learning demonstrates 16% better tracking performance over statistical learning in a self-training scenario, as measured by the mean squared error. © 2025 IEEE.

关键词： Digital elevation model

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An Adaptive-Learning-Based Generative Adversarial Network for One-to-One Voice Conversion

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第1期4卷 92-106页

作者： Dhar, Sandipan Jana, Nanda Dulal Das, Swagatam Department of Computer Science and Engineering National Institute of Technology Durgapur Durgapur713209 India Electronics and Communication Sciences Unit Indian Statistical Institute Kolkata700108 India

Voice conversion (VC) emerged as a significant domain of research in the field of speech synthesis in recent years due to its emerging application in voice-assistive technologies, such as automated movie dubbing speech-to-singing conversion, to name a few. VC deals with the conversion of the vocal style of one speaker to another speaker while keeping the linguistic contents unchanged. Nowadays, generative adversarial network (GAN) models are widely used for speech feature mapping from the source speaker to the target speaker. In this article, we propose an adaptive-learning-based GAN model, called ALGAN-VC, to improve the one-to-one VC of speakers. Our ALGAN-VC framework consists of some approaches to improve the speech quality and voice similarity between the source and target speakers. We incorporate a dense residual network architecture into the generator network for efficient speech feature learning between source and target speakers. Our framework also includes an adaptive learning mechanism to compute the loss function for the proposed model. Moreover, a boosted learning rate approach is incorporated to enhance the learning capability of the proposed model. The proposed model is tested on Voice Conversion Challenge 2016, 2018, and 2020 datasets along with our self-prepared Indian regional-language-based speech dataset. In addition, an emotional speech dataset is also considered for evaluating the model's performance. The objective and subjective evaluations of the generated speech samples indicated that the proposed model elegantly performed the voice conversion task by achieving high speaker similarity and good speech quality. © 2022 IEEE.

关键词： Quality control

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Simultaneous Wireless Information and Power Transfer for STAR-RIS Assisted UAV Networks

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IEEE Internet of Things Journal 2025年第12期12卷 19915-19928页

作者： Xie, Wenwu Qin, Lijuan Wang, Ji Wu, Weimin Li, Xingwang Xu, Hongbo Yang, Liang Hunan Institute of Science and Technology School of Information Science and Engineering Yueyang414006 China Central China Normal University Department of Electronics and Information Engineering Wuhan430079 China Huazhong University of Science and Technology School of Electronic Information and Communications Wuhan430074 China Henan Polytechnic University School of Physics and Electronic Information Engineering Jiaozuo454003 China Hunan University College of Computer Science and Electronic Engineering Changsha410082 China

This paper explores the benefits of deploying simultaneously transmitting and reflecting reconfigurable intelligence surfaces (STAR-RIS) in unmanned aerial vehicle (UAV) networks with simultaneous wireless information and power transfer. In the proposed system, the UAV utilizes STAR-RIS to radiate energy-carrying information signals (ECISs) to multiple outdoor energy receivers and multiple indoor information receivers without flying over indoor no-fly zone. Based on the UAV propulsion power formula, we successively introduce fly-hover-broadcast (FHB) and path discretization (PD) protocols to minimize the total UAV energy consumption by jointly using the extended penalty function and optimization algorithm based on the expected value of channel status information, where the UAV flight constraints, no-fly constraint, minimized energy or information threshold constraints, and STAR-RIS phase-shift constraints are met. The FHB protocol, which requires the UAV to radiate the ECISs to the users at only a few hovering positions, provides a lower-bound performance of UAV energy consumption, while the PD protocol is used to discuss the general situation of the ECISs during UAV flight. Simulation results demonstrate that the utilization of the STAR-RIS in UAV networks outperforms the traditional RIS in improving energy efficiency and extending UAV flight time. © 2014 IEEE.

关键词： Energy utilization

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