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Innovation in Technology (ASIANCON), Asian Conference on

作者： Manjunatha Sathish A S Jayanthy Judeson Antony Kovilpillai J Viyaskrishna S Senthamil Arasi T Sudharsan S Department of Electronics and Communications Engineering Sri Ramakrishna Engineering College Coimbatore India Department of Computer Science Engineering Alliance University Bangalore India

ISBN: (数字)9798350354218

ISBN: (纸本)9798350354225

Arrhythmogenic Right Ventricular Dysplasia is a heart disorder in which the heart muscle is replaced by fatty fibrous tissue. This causes sudden deaths in young men. The proposed novel AC-GAN and machine learning based ARVD detection system focuses mainly on detection of ARVD using ECG signals. This is the first machine learning based approach of detection of ARVD. This system involves creating synthetic ECG data of ARVD using AC-GAN. Since there is no available dataset in the internet, this approach results in large amount of synthetical ECG dataset. The primary characteristics of ARVD include inverted T waves and Epsilon waves at the end of the QRS complex. Various machine learning algorithm, such as the Decision Tree algorithm, Linear discriminant algorithm, Logistic regression algorithm, Naïve Bayes algorithm, RNN LSTM were trained and tested. The RNN LSTM has the highest tested accuracy of 89.2%. And was concluded to be the best fit for the ARVD detection system. The users can upload their ECG data to the web dashboard for real-time prediction.

关键词： Heart Training Technological innovation Machine learning algorithms Accuracy Machine learning Electrocardiography Prediction algorithms Real-time systems Long short term memory

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Enhancing the Sense of Unity with Performers in VR Space by Mutual Presentation of Electroencephalogram Information 11

Enhancing the Sense of Unity with Performers in VR Space by ...

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11th IEEE Global Conference on Consumer Electronics, GCCE 2022

作者： Ide, Kota Horie, Ryota Shibaura Institute of Technology Graduate School of Engineering and Science Department of Electrical Engineering and Computer Science Tokyo Japan Shibaura Institute of Technology Department of Information and Communications Engineering Tokyo Japan

ISBN: (纸本)9781665492324

Performances in VR space, such as VR music concerts, are less likely to convey audience's reactions than in real space, making it difficult to feel the sense of unity. In this paper, we introduce a system that enhances the sense of unity among performers and audience in VR space by generating visual effects based on the beta-alpha ratio signals obtained from a single-channel electroencephalograph and sharing them with the others. We evaluated the significance of the system by conducting juggling-shows in VR space using the system. The results showed the potential to enhance the sense of unity among the performers and the audience. © 2022 IEEE.

关键词： Electroencephalography

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Comparative Performance Exploration of Different Machine Learning and Deep Learning Algorithms for Classification of Hand Wrist Gestures 2

Comparative Performance Exploration of Different Machine Lea...

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2nd International Conference on Disruptive Technologies, ICDT 2024

作者： Tiwari, Bhawna Gupta, Sindhu Hak Balyan, Vipin Amity University Noida India Gl Bajaj Institute of Technology & Management Greater Noida India Amity University Department of Electronics and Communications Noida India Cape Peninsula University of Technology Department of Electrical Electronics and Computer Engineering Cape Town South Africa

ISBN: (纸本)9798350371055

In the current scenario, reliable recognition and classification of hand wrist gestures are gaining high demand for numerous applications including health care application, for Sign language recognition, and in robotics for managing mobile robots etc. This paper highlights the comparative evaluation of various machine learning and deep learning algorithms for classification of hand wrist gestures in terms of classification accuracies, confusion matrix, recall, and precision. This research presents the experiment conducted on ten different subjects demonstrates six different hand wrist gestures for creation of dataset based on variation in scattering parameters of designed wearable Antennas. © 2024 IEEE.

关键词： Body worn antenna classification algorithm deep learning hand wrist gestures Machine learning

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A System Level Study on LDM for Mixed Broadcast-Broadband Service Delivery in 5G

A System Level Study on LDM for Mixed Broadcast-Broadband Se...

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IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)

作者： Yu Xue Yuxiao Zhai Elvino Sousa Wei Li Liang Zhang Zhihong Hong Yiyan Wu Department of Electrical and Computer Engineering University of Toronto Toronto Canada Communications Research Centre Ottawa Canada

ISBN: (数字)9798350364262

ISBN: (纸本)9798350364279

The vision of the future 5 G - Multicast Broadcast Services (5 G -MBS) is to achieve full convergence of broadcast and broadband services by providing these services on the same infrastructure and dynamically switching between them without impacting user experiences. Using Layered Division Multiplexing (LDM) and a novel antenna precoding system, the 5 G MIMO antenna can seamlessly combine wide coverage broadcast service and narrow-beam MIMO broadband service to improve spectrum efficiency. The LDM network can transmit a 2-layered signal where the higher power Core Layer (CL) transmits a Single Frequency Network (SFN) broadcast signal, and the lower power Enhanced Layer (EL) is used for broadband services. Full simulations of the 2-layered network using 3GPP self-evaluation Dense Urban - eMBB and Rural-eMBB reference scenarios show in both cases, the CL can provide three 4 k video streaming services while supporting full broadband services in the EL.

关键词： 5G mobile communication Precoding Switches Streaming media Broadband communication Broadband antennas 3GPP

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IoT based Coal Mining Monitoring and Control 2

IoT based Coal Mining Monitoring and Control

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2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023

作者： Esther, B Priya Chandan, Madhavarapu Dattu, Vinjamuri S. N. Ch. Sakthivel, M. Rajesh, R. Sarishma Mohanavel, V. Srm Institute of Science and Technology Department of Mechatronics Tamil Nadu 603203 India Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Andhra Pradesh 522302 India Aditya Engineering College Department of Mechanical Engineering Andhra Pradesh 533437 India Velammal College of Engineering and Technology Department of Electronics and Communications Engineering Tamil Nadu 625009 India Vellore Institute of Technology Department of Computer Science and Engineering Tamil Nadu Chennai600127 India Graphic Era Deemed to Be University Department of Computer Science and Engineering Uttarakhand Dehradun248002 India Centre for Materials Engineering and Regenerative Medicine Bharath Institute of Higher Education and Research Tamil Nadu Chennai600073 India

ISBN: (纸本)9781665456302

IoT (Internet of Things) technology is used here to monitor underground mining locations. Developing sensor based device is highly challenging and hence accelerometer is used to monitor the deep mining region. Each and every analyzed boundary/qualities/characteristics are then sent to the Micro Controller Unit (MCU). The MCU unit is utilized to perform a basic analysis. When a critical situation is detected, an alarm will be given and the corresponding details will be sent directly to the web server. The collected data are then displayed on the webserver page of the underground control centre to present the screen and take quick action to prevent serious damage. Simultaneously, the Zigbee handset module is employed in the proposed model to communicate data from the mining section to take immediate action and reach the location. Finally, the experimental results show the increase in coal mining safety with the proposed underground coal mine monitoring system. © 2023 IEEE.

关键词： Microcontrollers

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Comparative Assessment of Off-shore Wind Converters and Wave Energy Converters in the Philippines 15

Comparative Assessment of Off-shore Wind Converters and Wave...

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15th IEEE International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management, HNICEM 2023

作者： Alquiza, Laurence Keith P. Recto, King Harold A. Loresco, Pocholo James M. Villalobos, Jesus Ateneo de Manila University Department of Electronics Computer and Communications Engineering Quezon City Philippines Feu Institute of Technology Department of Electronics Engineering Manila Philippines Institut Catholique d'Arts et Métiers International Program in General Engineering Toulouse France

ISBN: (纸本)9798350381177

The Republic of the Philippines is confronted with rebuilding its energy landscape, which now depends heavily on imported fossil fuels for a substantial supply. The department of Energy (DOE) has established lofty objectives to enhance the nation's renewable energy (RE) capability;nevertheless, these objectives are still to be achieved. This research supports DOE's goals by studying other possible renewable energy sources. In particular, the primary aim of this research is to examine the viability of Offshore Wind Converters (OWCs) and Wave Energy Converters (WECs) as viable sustainable energy options for the Philippines. Ocean wave converters (OWCs) provide inherent benefits in terms of dependability and have widespread societal acceptance. Conversely, wave energy converters (WECs) harness the vast energy potential contained within ocean waves. A comparative evaluation was undertaken to analyze the differences between these two potential renewable energy sources. The assessment concludes that OWCs possess a minor advantage over WECs regarding their economic viability and higher societal acceptability. It recommended that the government adopts a diversified energy portfolio, which may include the incorporation of WECs to effectively navigate the changing dynamics of the energy sector, enhance sustainability, and ensure the long-term security of the nation's energy supply. © 2023 IEEE.

关键词： Water waves

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Feasibility Study of Noise-Cancelling Low Noise Amplifiers for Millimeter-Wave Wi-Fi 8 Applications 7

Feasibility Study of Noise-Cancelling Low Noise Amplifiers f...

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7th International Youth Conference on Radio Electronics, Electrical and Power engineering, REEPE 2025

作者： Alhilo, Hassan Albasha, Lutfi Budimir, Djuradj American University of Sharjah Department of Electrical Engineering Sharjah United Arab Emirates School of Computer Science and Eng University of Westminster Wireless Communications Research Group London United Kingdom

ISBN: (纸本)9798331531836

A literature review on low noise amplifier (LNA) designs was conducted to validate the feasibility of an LNA design. The LNA is meant to operate in a receiver system for a Wi-Fi 8 communication system, which requires ultra-high reliability in its communication links. Additionally, due to its requirement for high data throughput, the system will operate in the millimeter wave (mm-wave) frequency range as this would allow for large bandwidths. Due to this frequency range as well as its potential operation in industrial applications, techniques to help mitigate any drawbacks were explored. The use of the noisecancelling technique was identified as a suitable one, as its improvement in the noise performance of the receiver system can ensure that a communication link can be reliably maintained. The literature review first identified designed LNAs for other related wireless communication technologies, such as previous generations of Wi-Fi and WiGig to understand the requirements needed for such a system. Next, a review of LNAs designed to operate in the mm-wave were conducted to help understand the effects encountered in this range as well as any useful techniques. Finally, a review of noise-cancelling LNAs designed in the mm wave and for wireless communication purposes was performed for similar reasons. With this review performed, a comprehensive understanding was obtained to aid in the design of an LNA for Wi-Fi 8 purposes. © 2025 IEEE.

关键词： Telecommunication links

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An intricate spectrogram processing in speech enhancement using machine learning with cloud computing 7

An intricate spectrogram processing in speech enhancement us...

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7th International Conference on Image Information Processing, ICIIP 2023

作者： Reddy, Yenna Geetha Mahendran, G. Al-Khaykan, Ameer Alkawak, Omar A. Kalaiselvan, S.A. Priya, A. Department of Computer Science And Engineering Kompally Telangana Secunderabad India R.M.K Engineering College Department of Mechancal Engineering Chennai Tamil Nadu Kavaraipettai India University of Kufa Department of Electronic And Communications Engineering Najaf Iraq Al-Mustaqbal University College Department of Air Conditioning And Refrigeration Technical Engineering Babil Hilla Iraq Department of Computer Science And Engineering Tamil Nadu Chennai India School of Architecture Koneru Lakshmaiah Educational Foundation Andhra Pradesh Guntur India

ISBN: (纸本)9798350371406

The spectrogram is defined as the visual representation of the signal strength with a particular interval of time regarding frequencies in the appropriate waveform. It is demonstrated using the Fourier transform. It is illustrated in a three-dimensional plot of signal composed with amplitude versus frequency and time. They are classified as long signal sections and short signal sections with filters. It demonstrates the consecutive spectacle of the sound signal at a particular interval of time. The time-frequency representation of audio signals is obtained through spectrograms. This helps in the understanding of the speech data. Machine learning plays an important role in the identification of the relevant features in the spectrogram. The intricate patterns in the time and frequency domains are represented through CNN and RNN. These models are trained and tested through a large dataset which includes both clean and noisy speech samples. This helps to learn complex interrelationships and patterns associated with varied environmental conditions and interference systems. The computational demands of these systems are handled through the cloud computing techniques. They provide a platform for effective solutions for performing real-time interference. These cloud services provide various collaborations to numerous models to achieve desired outcomes. The proposed system provides higher adaptability in varied environmental and noisy profiles. Thus the integration of cloud computing with machine learning provides real-time processing with a natural seamless user experience. © 2023 IEEE.

关键词： Cloud computing

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Innovative Method of Predicting Crime Rate by CNN Model Compared with Naive Bayes Algorithm to Increase Accuracy

Innovative Method of Predicting Crime Rate by CNN Model Comp...

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2023 Intelligent Computing and Control for engineering and Business Systems, ICCEBS 2023

作者： Konduru, Yaswanth Kumar Raju Kanimozhi, K.V. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Electronics and Communications Science and Engineering Tamilnadu Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Computer Science and Engineering Tamilnadu Chennai India

ISBN: (纸本)9798350394580

The objective is precisely determine rate of crime utilizing an enhanced methodology using innovative CNN model in comparison to NB. There are two groups made up of a total of 20 samples. Ten samples each were given. Group 1 is a member of the CNN algorithm, whereas Group 2 is a member of the Naive Bayes algorithm. Naive Bayes' accuracy (84%) is less than CNN's (86%). © 2023 IEEE.

关键词： Analysis Convolutional Neural Network Crime rate Forecasts, Naive Bayes Algorithm Peace Prediction

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Spiral Fractal Compression in Transform Domains for Underwater Communication

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Annals of Data Science 2024年第3期11卷 1003-1030页

作者： Selim, A. Taha, Taha E. El-Fishawy, Adel S. Zahran, O. Hadhoud, M.M. Dessouky, M.I. El-Samie, Fathi E. Abd El-Hag, Noha ERTU Cairo Egypt Department of Information Technology Faculty of Computers and Information Menoufia University Shebeen El-Kom32511 Egypt Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt The Higher Institute of Commercial Sciences Al mahalla Al kubra Algarbia31951 Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University Riyadh11671 Saudi Arabia

This paper presents a simplified fractal image compression algorithm, which is implemented on a block-by-block basis. This algorithm achieves a Compression Ratio (CR) of up to 10 with a Peak Signal-to-Noise Ratio (PSNR) as high as 35 dB. Hence, it is very appropriate for the new applications of underwater communication. The idea of the proposed algorithm is based on the segmentation of the image, first, into blocks to setup reference blocks. The image is then decomposed again into block ranges, and a search process is carried out to find the reference blocks with the best match. The transmitted or stored values, after compression, are the reference block values and the indices of the reference block that achieves the best match. If there is no match, the average value of the block range is transmitted or stored instead. The effect of the spiral architecture instead of square block decomposition is studied. A comparison between different algorithms, including the conventional square search, the proposed simplified fractal compression algorithm and the standard JPEG compression algorithm, is introduced. We applied the types of fractal compression on a video sequence. In addition, the effect of using the fractal image compression algorithms in transform domain is investigated. The image is transferred firstly to a transform domain. The Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) are used. After transformation takes place, the fractal algorithm is applied. A comparison between three fractal algorithms, namely conventional square, spiral, and simplified fractal compression, is presented. The comparison is repeated in the two cases of transformation. The DWT is used also in this paper to increase the CR of the block domain pool. We decompose the block domain by wavelet decomposition to two levels. This process gives a CR for block domain transmission as high as 16. The advantage of the proposed implementation is the simplicity of computation. We f

关键词： Discrete wavelet transforms

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