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international conference on Acoustics, Speech, and signal Processing (ICASSP)

作者： Mushaffa Rasyid Ridha Shinobu Hasegawa Sakriani Sakti Grad. School of Adv. Science & Tech. Japan Adv. Inst. of Science & Tech. Nomi Japan Center of IDER Japan Adv. Inst. of Science & Tech. Nomi Japan Grad. School of Science & Tech. Nara Inst. of Science & Tech. Ikoma Japan

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Most computer-assisted pronunciation training (CAPT) systems for second language (L2) learners focus on detecting mispronunciation based on predefined phonemes and assigning pronunciation scores. However, these systems often lack visual feedback or detailed corrective guidance, limiting learners’ opportunities for significant improvement. This paper presents a key advance toward developing a CAPT system that offers detailed visual feedback on articulatory movements using real-time magnetic resonance imaging (rtMRI) articulatory landmarks. The limited availability of paired speech and articulatory landmark data, typically involving only a few speakers, poses a challenge for generalizing across diverse speech patterns. To address this, we propose leveraging pretrained wav2vec 2.0 embeddings, fine-tuned to generate articulatory contours mapped to xy coordinates based on rtMRI landmark data. As evaluated with the rtMRI USC-TIMIT dataset, our system effectively reconstructs visual articulatory movements from speech, marking a significant step toward enhanced visual pronunciation learning.

关键词： Training Visualization Limiting Magnetic resonance imaging Pipelines Neural networks Speech enhancement Feature extraction Real-time systems image reconstruction

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Indoor Visible Light Positioning based on image Denoising and Phase Difference Vector Fingerprint

Indoor Visible Light Positioning Based on Image Denoising an...

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international conference on Information, Communication and Networks (ICICN)

作者： Quanyi Cheng Dingyu Ge Kai Lei Xuanbang Chen Zhenghai Wang Xiaodong Liu Yuhao Wang Nanchang University China Institut supérieur d’électronique de Paris France Digital Technology Application Industry College of Shangrao Normal University China

Visible light positioning (VLP) technology has become a promising technology in the field of indoor positioning benefits from its greenness and low cost. However, the traditional fingerprint construction scheme in radio frequency cannot be effectively applied in the VLP system and the positioning accuracy of the fingerprint-based VLP system suffers from its specific propagation channel noise. Therefore, a novel fingerprint construction method based on phase difference vector (PDV) and fingerprint denoising network (FDNet) is proposed to improve the stability and positioning accuracy of the VLP system. Specifically, the arrival phase difference information is considered to construct a fingerprint image, and the improved denoising network is designed to obtain relatively high signal-to-noise ratio fingerprint information. Moreover, the positioning is achieved by mapping the constructed fingerprint database to location information through a back propagation (BP) network. The simulation results show that the proposed PDV-based FDNet positioning method achieves an average positioning accuracy of 1. 43cm, which outperforms the existing benchmark methods.

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Color Guided Depth Map Super-Resolution with Nonlocla Autoregres-Sive Modeling

Color Guided Depth Map Super-Resolution with Nonlocla Autore...

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international conference on Acoustics, Speech, and signal Processing (ICASSP)

作者： Wei Xu Na Qi Qing Zhu Jingzhong Qi Longlu Huang Kun Cao Yuxin Bao Qianwen Wang Faculty of Information Technology Beijing University of Technology Beijing China Beijing Institute of Artificial Intelligence Beijing University of Technology Beijing China The Fifth Military Delegate Office in Beijing Beijing China

Depth map captured by 3D cameras usually suffers from low resolution and insufficient quality, which limits its applications in real world. Thus, it is an essential task to develop efficient and effective techniques to handle various depth degradations. In this paper, we propose a color guided depth map super-resolution method with nonlocal autoregressive modeling. Considering that textures in depth map demonstrate distinct geometry direction, we exploit the multi-directional dictionary which is effective in recovering subtle structures of depth patches. We further introduce two regularization terms into the sparse representation framework. Firstly, a patch based autoregressive model is introduced to represent the local patterns in a small area. Secondly, inspired by the structure consistence between depth map and color image, we propose a color guided nonlocal similarity to provide nonlocal constraint to the local structures, which is very helpful in preserving local structures and suppressing noise. Experimental results demonstrate the superior of our method compared with state-of-the-art methods.

关键词： Geometry Degradation Three-dimensional displays Dictionaries image color analysis Superresolution signal processing

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Optimizing Hybrid Sparse and Block-based Compressed Sensing: A Performance Study for Biomedical Imaging and Video Surveillance Applications

Optimizing Hybrid Sparse and Block-Based Compressed Sensing:...

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Innovations in High Speed Communication and signal Processing (IHCSP), international conference on

作者： Nitish Vashisht M. Sudhakara Reddy Gajanan H Chavhan P. K. Miniappan Praney Madan Venkatasubramanian D Chitkara Centre for Research and Development Chitkara University Himachal Pradesh India School of Sciences Physics & Electronics JAIN (Deemed to be University) Bangalore Karnataka E&TC Vishwakarma Institute of Technology Pune India Department of Mechanical Engineering Karpagam Academy of Higher Education Coimbatore India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of IT Prince Shri Venkateshwara Padmavathy Engineering College Chennai

ISBN: (数字)9798350368949

ISBN: (纸本)9798350368956

One of the most promising fields, compressed sensing has found a home in video streaming applications, where it seeks to compress or sparsely represent signals by reducing their dimensions. The sparse representation is a good approximation to the signal since the amplitude of the coefficient’s decays according to the power law. signals are projected into low-dimensional space to generate measurement vectors. A sparse signal may be accurately rebuilt using the measurement vector. signals or noise that are not sparse but can be compressed and might result in an approximation. images in the frequency or wavelet domain are ideal for Compressed Sensing because they are compressible by nature. A more precise reconstruction of the original picture is possible due to an improvement in reconstructed image quality and a reduction in the compression ratio, which is the ratio of the dimensions of the number of pixels to the measurement *** Sparse and Block-based Compressed Sensing Algorithm (HSBCA) is the name of the approach that merged sparse-based and block-based compressed sensing algorithms. Block Compressed Sensing, the first module of HSSBCA, processes each message by dividing it into numerous picture regions, which results in decreased run time. In contrast, performance drops while picture reconstruction is underway; to remedy this, the research employs the second module, the sparse compressed sensing method, to boost reconstruction efficiency.

关键词： image coding Wavelet domain Sparse approximation Magnetic resonance imaging signal processing algorithms Biomedical measurement Streaming media Vectors image reconstruction Compressed sensing

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Synthetic image Detection: Highlights from the ieee Video and image Processing Cup 2022 Student Competition

arXiv

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arXiv 2023年

作者： Cozzolino, Davide Nagano, K. Thomaz, L. Majumdar, A. Verdoliva, L.

The Video and image Processing (VIP) Cup is a student competition that takesplace each year at the ieee international conference on image Processing. The2022 ieee VIP Cup asked undergraduate students to develop a system capable ofdistinguishing pristine images from generated ones. The interest in this topicstems from the incredible advances in the AI-based generation of visual data,with tools that allows the synthesis of highly realistic images and *** this opens up a large number of new opportunities, it also undermines thetrustworthiness of media content and fosters the spread of disinformation onthe internet. Recently there was strong concern about the generation ofextremely realistic images by means of editing software that includes therecent technology on diffusion models. In this context, there is a need todevelop robust and automatic tools for synthetic image detection. Copyright © 2023, The Authors. All rights reserved.

关键词： Students

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IoT-based Synergistic Approach for Poultry Management System

IoT-Based Synergistic Approach for Poultry Management System

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ieee international IOT, Electronics and Mechatronics conference (IEMTRONICS)

作者： Onibonoje, Moses Oluwafemi Afe Babalola Univ Dept Elect Elect & Comp Engn Ado Ekiti Nigeria

ISBN: (纸本)9781665440677

Poultry farming has contributed immensely to global food security and the economy. Its produces are favourites and hugely subscribed, due to the uniqueness of their nutrients to all categories of people and the alternatives they provide to other high-cholesterol proteins. The increase in the world's population will continuously stretch for an increase in demands for poultry products. A smart way to ensure continuous production and increased yields in various farms is to adopt automated and remote management of poultries. This paper modelled and developed a collaborative system using the synergistic wireless sensor network technology and the internet of things. The system integrated resourcefully selected wireless sensors, mobile phone, other autonomous devices and the internet to remotely monitor and control environmental parameters and activities within the farm. Parameters such as temperature, humidity, water level, food valve level, ammonia gas, illumination are sensed, benchmarked against selected thresholds, and communicated wirelessly to the sink node and the internet cloud. The required control actions can also be initiated remotely by the administrator through messages or command signal. Also, the various parameters and actions can be read or documented in real-time over the web. The system was tested and evaluated to give an average of about 93.7% accuracy in parameters detection and 2s delay in real-time response. Therefore, a modelled system has been developed to provide robust and more intuitive solutions in poultry farming.

关键词： internet of things early chicken monitoring system poultry wireless sensors

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Implementing Cryptographic Mechanisms with IRS for Enhancing an internet of Vehicles

Implementing Cryptographic Mechanisms with IRS for Enhancing...

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ieee international conference on Computer and Communication Engineering technology (CCET)

作者： Ahmed Aljumaili Hafedh Trabelsi Wassim Jerbi Rafal Hazim dept. College of Engineering Technology Al-Kitab University - Iraq Kirkuk Iraq dept. CES LAB ENIS University of Sfax - Tunisia Sfax Tunisia

ISBN: (数字)9798350355673

ISBN: (纸本)9798350355680

The internet of Vehicles (IoV) is transforming transportation systems by allowing for seamless communication and collaboration between vehicles, roadside units (RSUs), and cloud servers. However, the dynamic and varied character of IoV settings raises serious security and efficiency concerns. This work suggests a novel strategy to address these issues by combining col-laborative cryptographic processes and intelligent reflecting surfaces (IRS). Our method employs modern encryption techniques, such as the Advanced Encryption Standard (AES), to ensure safe data delivery, while IRS dynamically adjusts their reflection properties to enhance signal propagation and reception. We provide a detailed network model and an algorithmic framework for implementing the proposed strategy, focusing on cryptographic techniques and the role of IRS in improving communication security and efficiency. The implementation of our algorith-mic framework shows significant results. Initialization includes generating public/private key pairs and securely exchanging public keys, followed by a secure key exchange mechanism to generate a shared secret key. In the session establishment phase, nonces are exchanged and session keys computed using AES-Key-Derivation. The nominal scenario involves AES-GCM encryption, message signing, and transmission of encrypted, authenticated messages, which are verified and decrypted by the receiver. Key updates and error scenarios are also addressed. Implementation results demonstrate enhanced network coverage by 30%, reduced communication costs by 25%, and increased energy efficiency by 20% due to IRS integration. Error scenarios, including signature verification failure, decryption failure, and invalid nonce handling, are effectively managed, ensuring robust security. IRS integration significantly improves communication reliability and efficiency. Theoretical analysis and discussion highlight the potential benefits of incorporating IRS in IoV networks, such as im

关键词： Costs Heuristic algorithms Collaboration Energy efficiency Encryption Security Cryptography Servers Vehicle dynamics internet of Vehicles

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Markov Chain based Predictive Model for Efficient handover Management in Vehicle-to-Infrastructure Communications 17

Markov Chain based Predictive Model for Efficient handover M...

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17th ieee international Wireless Communications and Mobile Computing conference (ieee IWCMC)

作者： Aboud, Ahmed Touati, Haifa Hnich, Brahim Univ Gabes Natl Engn Sch Sfax IResCoMath Lab Zrig Eddakhlania Tunisia Univ Gabes Fac Sci Gabes IResCoMath Lab Zrig Eddakhlania Tunisia Univ Sfax Fac Sci Monastir CES Lab Sfax Tunisia

ISBN: (纸本)9781728186160

The vehicular ad-hoc networks (VANET) has attracted the attention of both the industry and the academia researcher over the last decade. The concept of connecting vehicles to the internet using the already deployed cellular network architecture has opened many avenues for research and development that are contributing significantly towards the Intelligent Transportation systems (ITS). Almost every vehicle requires a seamless connectivity to the internet without interruption. However, with the emergence of the 5G network and the Vehicle-to-infrastructure(V2I) concept, the design of efficient mobility management techniques that can handle the real-world mobility constraints in VANET becomes a critical task. In this paper, we propose a new handover algorithm that uses a Markov chain predictor to determine when and where a handover will be needed. The aim of the proposed solution is to reduce the number of unnecessary handover by maintaining the vehicle connectivity to the 5G base station as long as possible without degrading the network performance. Simulation studies were conducted to evaluate the performance of the proposed scheme. Our results show that the proposed handover algorithm greatly outperforms the conventional 3GPP handover algorithms.

关键词： Mobility management 5G Vehicle-to-Infrastructure handover signal prediction Performance evaluation

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Deep Joint Source-Channel Coding for Person Re-Identification With Related image Sources

Deep Joint Source-Channel Coding for Person Re-Identificatio...

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international conference on Communication technology (ICCT)

作者： Zhihang Chu Wei Chen Ning Wang Bo Ai State Key Laboratory of Advanced Rail Autonomous Operation Beijing Jiaotong University China School of Electronic and Information Engineering Beijing Jiaotong University Beijing China Key Laboratory of Railway Industry of Broadband Mobile Information Communications Frontiers Science Center for Smart High-speed Railway System School of Information Engineering Zhengzhou University Zhengzhou China

In this paper, we propose a deep learning based joint source-channel coding (JSCC) scheme for wireless transmission of multiple related image sources in person re-identification tasks. Our network utilizes parameter sharing for the encoder at the transmitter and adopts a joint decoding architecture for the decoder at the receiver, reducing storage space and computational resource consumption. By leveraging object-related information from multiple perspectives, the decoder fuses richer features to perform corresponding re-identification tasks. Experimental results demonstrate that the performance of our proposed method degrades gracefully as available bandwidth resources decrease, and the proposed multi-transmitter JSCC scheme achieves significant gains under low bandwidth and low signal-to-noise ratio conditions, compared with the existing approach. This work shows the potential of the JSCC-based approach for efficient and robust wireless transmission of related image sources in person re-identification scenarios.

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IoT based Smart Switch With Bluetooth Speaker Using MQTT Protocol: Node-red Framework 2

IoT Based Smart Switch With Bluetooth Speaker Using MQTT Pro...

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2nd international conference on Advances in Computing, Communication, Embedded and Secure systems, ACCESS 2021

作者： Bharath, S. Electronics and telecommunication Army Institute of technology Pune India

ISBN: (纸本)9781728171364

This paper suggests a novel idea to implement a smart switch where users can control the appliances using a mobile app that is developed using kodular tool. A series of push-button was installed in the system. Users can turn on or turn off the appliances by pressing relevant buttons, which will send a message through Message Queuing Telemetry Transport (MQTT). Users can also set timer to turn on or turn off appliances after a certain time. This scheduled time will store in the database and continuously process to turn on/off the appliances at a user-specified time using the node red framework. Also, this system has Bluetooth based receiver module and speaker to hear songs which have a good amount of range to receive signal. Also, users can operate or set time intervals using mobile phone app anywhere in the world. This system will save time and gives comfort to the user to operate from anywhere. © 2021 ieee

关键词： internet of things

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