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Underwater Image Enhancement Using Gaussian Smoothing and Edge Detection

Underwater Image Enhancement Using Gaussian Smoothing and Ed...

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International conference on Inventive Computation Technologies (ICICT)

作者： V. Lambodara Aravind C. Bagyalakshmi Department of Computer Applications Hindustan Institute of Technology and Science

ISBN: (数字)9798331512248

ISBN: (纸本)9798331512255

Underwater acoustic communication is used for oceanographic data collection, environmental monitoring, disaster alarm systems, and navy applications. Underwater has its peculiarities such strong signal attenuation and limited bandwidths, multipath nature of signals, and ambient noises. All these characteristics bring a great deal of interference probably in transmission with certainty and effectiveness. This work propounded an optimized hybrid model that works concurrently with advanced signal processing and noise-reducing techniques for communication enhancement. The purpose of the proposed model is to develop high signal-to-noise ratio (SNR) received signals with lesser transmission error using time-frequency domain analysis and filtering techniques, which are specifically designed for underwater applications. Thus, the main aim of this work, in fact, is towards the development of a robust underwater communication platform, which ensures a very reliable transfer of data under conditions of excessive noise even in the rapidly changing aquatic environments. Comparison of the proposed model with traditional techniques shows that this model stands much higher than the earlier techniques regarding transmission accuracy, noise resilience, and overall efficiency, thus extending the development of more reliable underwater communication systems toward future marine and defense applications.

关键词： Adaptation models Underwater communication Smoothing methods Image edge detection Computational modeling signal processing algorithms Reliability Underwater acoustics Image enhancement signal to noise ratio

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Edge-IoT Architecture-Based Visualization Service Platform for RTO Real-Time Monitoring

Edge-IoT Architecture-Based Visualization Service Platform f...

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International conference on advanced Communication Technology (ICACT)

作者： Hoon-Min Park Dal-Hwan Yoon Hyun-Min Jung Dae-Hee Lee Tae-Yeung Lim Hyun Kim Myung-Ki Jang Emsolution Co. Ltd Suwon Korea Department of Electronic Engineering Semyung University Korea Devicenet Co. Ltd Korea

ISBN: (数字)9791188428137

ISBN: (纸本)9798331507602

In this study, we present the Edge IoT Architecture (Architecture) for analyzing the real-time state information of the regenerative thermal oxidizer (RTO) and implement a visualization method. The Edge-IoT architecture system interfaces with the programmable logic control (PLC) that controls the monitoring of RTO operations and transmits real-time data to a remote server, analyzes the channel data received through the IoT to build a database, and visualizes the characteristics of database (DB) analysis. IoT architecture implementation for fault diagnosis and maintenance of RTO designs IoT circuits on PLC control panels that control monitoring. Compatibility and information security are considered to facilitate remote maintenance. The received data is segmented by each channel and analyzed by a visualization algorithm to detect anomalies in the segmented data. At this time, the visualized data is judged to be normal, insufficient, or warning, depending on the threshold.

关键词： Image edge detection Data visualization signal processing algorithms signal processing Real-time systems Maintenance Thermal analysis Visual databases Servers Monitoring

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11th WSEAS International conference on Robotics, Control and Manufacturing Technology, ROCOM'11, 11th WSEAS International conference on Multimedia Systems and signal processing, MUSP'11

11th WSEAS International Conference on Robotics, Control and...

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11th WSEAS International conference on Robotics, Control and Manufacturing Technology, ROCOM'11, 11th WSEAS International conference on Multimedia Systems and signal processing, MUSP'11

ISBN: (纸本)9789604742837

The proceedings contain 26 papers. The topics discussed include: path following and obstacle avoidance fuzzy controller for mobile indoor robots;vision based defect detection on 3D objects and path planning for processing;a neural based position controller for an electrohydraulic servo system;evaluation of noise characteristics for a cooling system using neural network;design of a fuzzy logic controller for a plant of n-order based on genetic algorithms;advanced control methodology for intelligent universal transformers based on fuzzy logic controllers;object-oriented execution and monitoring of industrial control logic for automated manufacturing system;introduction of a hybrid control approach for automotive logistics;tone quality improvement of bone conduction voice by cepstrum-based local conversion models;and digital watermarking scheme using direct-sequence spread spectrum with adaptive voltage control for spread watermark signals.

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SIGMAP 2012 WINSYS 2012 - Proceedings of the International conference on signal processing and Multimedia Applications and Wireless Information Networks and Systems

SIGMAP 2012 WINSYS 2012 - Proceedings of the International C...

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International conference on signal processing and Multimedia Applications, SIGMAP 2012 and International conference on Wireless Information Networks and Systems, WINSYS 2012

ISBN: (纸本)9789898565259

The proceedings contain 60 papers. The topics discussed include: adaptive rate control scheme for improving quality of multimedia in broadband wireless networks;time-frequency filtering of Gaussian and impulse noise for spread spectrum power line communication;design of short irregular LDPC codes for a Markov-modulated Gaussian channel;enhancing photoware in the social networks environment;diffusion tracking algorithm for image segmentation;optimization of smoothing parameter of diffeomorphism kernel estimate for bounded random data;development of computer algorithms to control a weelchair through the movement of the head by artificial vision;fast algorithm of short-time DCT for low resolution signal processing;finding a tradeoff between compression and loss in motion compensated video coding;and new two-step motion estimation using adjustable partial distortion search - advanced selected search point and early termination for two step motion search.

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Deep Learning and IoT-Enabled Framework for Accurate Classification and Monitoring of Alzheimer's Disease Based on EEG signal Analysis

Deep Learning and IoT-Enabled Framework for Accurate Classif...

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Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT), International conference on

作者： R. Sathish R. Muthukumar K Dhivya S. Karthikkumar Department of Electrical and Electronics Engineering Builders Engineering College Tirupur Tamilnadu India Department of Electrical and Electronics Engineering Erode Sengunthar Engineering College Perundurai Tamilnadu India Department of Electrical and Electronics Engineering Jai Shriram Engineering College Tirupur Tamilnadu India

ISBN: (数字)9798350356236

ISBN: (纸本)9798350356243

Alzheimer's disease is a brain ailment that impairs thinking, memory, and behaviour. The efficacy of Brain- Computer Interface (BCI) systems must be enhanced to increase their prevalence in the biomedical sector. The biomedical sector is crucial for precise and efficient patient diagnostics using digital signal processing and wireless sensor network technologies. Alzheimer's disease (AD) is an irreversible brain disorder. Inadequate Alzheimer's disease diagnosis in the early stages, together with exact identification, may aid in halting the progression of the illness. Precise and effective detection and categorization of Alzheimer's disease enhance quality of life and increase life expectancy for patients. The advanced deep learning technology surpasses traditional machine learning methods in classifying complex configurations in high-dimensional composite data, particularly in digital signal processing. The deep learning application for the early detection and accurate classification of Alzheimer's disease might be suggested for a neuron-signal methodology in extensive data analysis. This research paper proposes an intelligent decision-making system (IDMS) for the diagnosis and categorization of Alzheimer's disease (AD) and the continuous monitoring of patients utilizing connected wearable devices. Methods for measuring neuronal synchrony are proposed to diagnose and characterize Alzheimer's disease.

关键词： Deep learning Heuristic algorithms Decision making Digital signal processing Electroencephalography Encryption Security Alzheimer's disease Monitoring S Box

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IEEE International conference on signal processing and Advance Research in Computing, SPARC 2024

IEEE International Conference on Signal Processing and Advan...

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2024 IEEE International conference on signal processing and Advance Research in Computing, SPARC 2024

ISBN: (纸本)9798350385199

The proceedings contain 118 papers. The topics discussed include: comparative analysis of neural network-based routing algorithms for wireless sensor networks;leveraging ShuffleNet and LLaVA-Phi for state-of-the-art image deblurring and description for mobile devices;spotting deep fakes: exploring detection techniques for image recognition;a transfer learning approach for enhancing road surface classification in intelligent driving systems;advanced U-Net++ architecture for precise brain tumor segmentation in MRI images: a robust solution for medical image analysis;a modeling and control of load frequency for interconnected thermal/hydro/nuclear power system using pi and fuzzy controller;systematic exploration of GAN-generated image recognition techniques;controlling mouse cursor through eye movement;improvement of power quality in distribution network at low voltage side by using DVR;facial emotion recognition using image filtering techniques;and enhancing financial trading strategies: a comprehensive sentiment analysis pipeline.

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Auris Guardian - A Smartphone Application for Hearing Loss Detection

Auris Guardian - A Smartphone Application for Hearing Loss D...

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Machine Learning and Autonomous Systems (ICMLAS), International conference on

作者： Legin M L Lohit Akshaa M Dafni Rose J Department of CSE St. Joseph's Institute of Technology Chennai

ISBN: (数字)9798331505745

ISBN: (纸本)9798331505752

Hearing loss is a common problem world over, which often resulted in reduced communication skills and quality of life. Conventionally, tests were carried out by the audiologists on the patient after equipping him with precise audiometers, and it was expensive, inaccessible, and time consuming as well, especially in less fortunate health resource regions. Therefore, for this, applications have been developed on the smartphones to diagnose hearing losses using air-conduction pure-tone audiometry techniques. This project evaluates the validity and reliability of such applications, particularly their performance in the event of using the “10 dB down and 5 dB up” method to hear threshold detection. The paper extends into the design and realization of an audiometric testing application based on advanced audio signal processing algorithms to diagnose hearing loss. Some smartphone apps have demonstrated the ability to achieve up to 90% precision in identifying mild hearing loss compared to the standard audiological tests. However, inconsistencies are possible due to varying device quality, earphone calibrations, and background noise. The new system combines data acquisition along with handling audio inputs, interaction with the user, and data analysis to ascertain hearing loss more accurately. Such applications may serve as low-cost, user-friendly alternatives to traditional audiology and facilitate hearing tests even in remote locations or among those not accessible to the audiologists.

关键词： Data analysis Working environment noise signal processing algorithms Auditory system Transforms User interfaces Reliability Smart phones Standards Testing

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Secure encryption system based on quantum access network 4

Secure encryption system based on quantum access network

引用

4th International Computational Imaging conference, CITA 2024

作者： Liu, Yuchao Wang, Tao Xu, Yuehan Zeng, Guihua State Key Laboratory of Advanced Optical Communication Systems and Networks Center of Quantum Sensing and Information Processing Shanghai Jiao Tong University Shanghai200240 China Shanghai Research Center for Quantum Sciences Shanghai201315 China Hefei National Laboratory CAS Center for Excellence in Quantum Information and Quantum Physics Hefei230026 China

ISBN: (纸本)9781510688834

Quantum secure communication technology, grounded in the principles of quantum mechanics, has revolutionized traditional cryptographic methods, which predominantly rely on mathematical algorithms and logical transformations. Quantum key distribution (QKD) facilitates the secure sharing of symmetric keys between legitimate parties, ensuring the integrity and confidentiality of information in communication channels. Among various QKD schemes, continuous variable quantum key distribution (CV-QKD) has emerged as a viable alternative to the more established discrete variable quantum key distribution (DV-QKD). CV-QKD boasts several advantages, including straightforward deployment, reduced operational costs, and stable signal quality, positioning it as a significant component of the quantum communication *** noise stream cipher (QNSC) represents a technique that employs redundant data streams to encrypt plaintext. Notably, QNSC shares structural similarities with the optical path used in quantum key distribution, allowing for compatibility with existing QKD infrastructure. Furthermore, the keys generated through quantum key distribution ensure absolute security, enabling them to substitute the data streams produced by pseudo-random sequences traditionally used in classical encryption schemes. This substitution enhances the overall security framework of the quantum noise stream encryption *** quantum access network (QAN) extends quantum key distribution capabilities from point-to-point connections to point-to-multipoint configurations, thereby becoming an essential component of contemporary network architectures. By interlinking multiple end users with a network backbone, quantum access networks can seamlessly integrate with quantum key distribution protocols. This integration offers a cost-effective and scalable solution for user access to the *** experimental verifications have demonstrated the viability of downstream access networks,

关键词： Quantum noise

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Satellite Intermittent Connectivity and Its Impact on Age of Information for Finite Horizon Scheduling

Satellite Intermittent Connectivity and Its Impact on Age of...

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advanced Satellite Mobile Systems (ASMS)

作者： Leonardo Badia Andrea Munari Dept. of Information Engineering University of Padova Italy German Aerospace Center (DLR) Inst. of Communication and Navigation Wessling Germany

ISBN: (数字)9798331522353

ISBN: (纸本)9798331522384

Low Earth Orbit (LEO) satellite communications can provide real-time services with reduced latency, which makes them ideal for applications requiring timeliness, such as Internet connectivity, remote monitoring, and disaster response. In this paper, we study a problem of information freshness optimization for such a scenario. Usually, this is quantified through the age of information (AoI) metric, but the typical scenarios involve a homogeneous time horizon, where transmission can take place indifferently at any instant. In reality, LEO communication may be severely influenced by its intermittent connectivity, which is not present for long time windows where line of sight with the satellite system is absent. Thus, we consider a problem of AoI-minimal scheduling for a finite horizon, solved via dynamic programming, where intermittent connectivity is accounted for, and addressed through different approaches. Moreover, we quantitatively evaluate the impact of different parameters on AoI and derive practical considerations for empirical setups.

关键词： Satellites Scheduling algorithms Space communications Low earth orbit satellites Optimal scheduling signal processing Information age Dynamic programming Surges Satellite communications

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The Potential of Speech Features to Discriminate between Original and Machine-Translated Texts

The Potential of Speech Features to Discriminate between Ori...

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International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Yongjian Chen Mireia Farrús Antonio Toral Center for Language and Cognition University of Groningen Groningen Netherlands Centre de Llenguatge i Computació (CLiC) Institut de Recerca en Sistemes Complexos (UBICS) Universitat de Barcelona Barcelona Spain Dep. de Llenguatges i Sistemes Informàtics Universitat d’Alacant Sant Vicent del Raspeig Spain University of Groningen

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Discriminating between original texts and machine translations involves identifying whether a text was originally authored in the target language or generated through machine translation. To our knowledge, all methods to date depend exclusively on text-based features. In this study, we move beyond this unimodal approach by incorporating speech features. Machine-translated texts display linguistic deviations from original texts, such as those in lexicon and syntax, which can also manifest in speech characteristics. We evaluate the effectiveness of using text features, speech features, and their bimodal fusion to train classifiers capable of discerning original from machine-translated texts. Additionally, we explore various classification algorithms and fusion techniques. Our results show that speech features alone surpass chance accuracy, while combining text and speech features enhances performance beyond text-only methods. Furthermore, although no single classification or fusion method proves consistently superior, advanced fusion techniques outperform simple feature concatenation.

关键词： Translation Text categorization Speech enhancement Syntactics signal processing Acoustics Robustness Multisensory integration Complexity theory Machine translation

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