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Dynamic Vehicle Graph Interaction for Trajectory Prediction Based on Video signals 48

Dynamic Vehicle Graph Interaction for Trajectory Prediction ...

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48th ieee international conference on Acoustics, Speech and signal processing, ICASSP 2023

作者： Chen, Jian Wang, Wei Chen, Junxin Cai, Ming Shenzhen MSU-BIT University Department of Engineering Shenzhen518172 China Sun Yat-Sen University School of Intelligent Systems Engineering Shenzhen518107 China Dalian University of Technology School of Software Dalian116621 China

ISBN: (纸本)9781728163277

The roadside video surveillance signal can help people achieve vehicle tracking and trajectory generation. Using these trajectories can learn the future motion of vehicles. Existing prediction methods can not analyze the interaction between vehicles well. To this end, we design a dynamic vehicle graph to represent the dynamic interaction between vehicles for trajectory prediction. A graph convolution module with an attention mechanism is used to extract the feature of the dynamic vehicle graph. Experiments comparing with baseline methods are conducted on a real-world dataset to demonstrate our model's improvement in forecast accuracy. © 2023 ieee.

关键词： Attention Mechanism Trajectory Prediction Vehicle Interaction Graph Video signal processing

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Prescribed Performance Control of Mobile Wheeled Inverted Pendulum systems under Arbitrary Initial Conditions 8

Prescribed Performance Control of Mobile Wheeled Inverted Pe...

引用

8th ieee international conference on Advanced robotics and Mechatronics, ICARM 2023

作者： Zhang, Mengshi Cao, Yu Yang, Bo Huang, Jian School of Artificial Intelligence and Automation Huazhong University of Science and Technology Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control Wuhan430074 China Shenzhen Huazhong University of Science and Technology Research Institute ShenZhen518060 China

ISBN: (纸本)9798350300178

Mobile wheeled inverted pendulum (MWIP) is a typical naturally unstable underactuated system and it is very necessary to constrain its transient response to improve the overall safety. Prescribed performance control (PPC) is an effective method, however the system initial conditions are usually required to be known and constraint, otherwise it can lead to singularity problems. In practical systems, it is often difficult to obtain the exact initial state leading to limitations in the application of PPC. To overcome this issue, this paper presented a composite error transformation function to address the problem of initial condition dependence. A continuous bounded function was designed to compress the arbitrary initial error into the predefined bound to avoid singularities. After a set time, it was degraded to an original system error. Based on this composite transformation, a state feedback controller was proposed for the underactuated MWIP system to achieve the constraint outputs. Then, by employing the Lyapunov theorem, it was guaranteed that the closed-loop system would remain stable. Various numerical simulations under different initial conditions were carried out to prove the validity of the proposed controller. © 2023 ieee.

关键词： Closed loop systems

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Design of a compact Microstrip Bandpass Filter for 2.4 GHz Applications

Design of a compact Microstrip Bandpass Filter for 2.4 GHz A...

引用

2024 international conference on Circuit, systems and Communication, ICCSC 2024

作者： Khardioui, Youssef El Alami, Ali El Ghzaoui, Mohammed Errachidia Moulay Ismail University Intelligent Renewable Energies Information Processing and Transmission Laboratory Faculty of Sciences and Technics Meknes Morocco Sidi Mohamed Ben Abdellah University Faculty of Sciences Fez Morocco

ISBN: (纸本)9798350365306

Microstrip bandpass filters are the core part of wireless communications. They help refine the signal and ensure that only the desired signal reaches the receiver. Microstrip bandpass filters are the core part of wireless communications. In this paper, a compact bandpass filter is designed using two rectangular open-loop resonators. The rectangular shape is used to achieve compact size and wide bandwidth performance. The substrate used is Rogers 6010 substrate with a thickness of 1.27 mm, a relative permittivity of 10.2, and an overall filter size of 11.55 × 6.62 mm. The resulting passband has a center frequency of 2.40 GHz, a bandwidth of 1.55 GHz, a fractional bandwidth (FBW) of 64.5%, a return loss of approximately -26.3 dB, and an insertion loss of -0.1 dB. The proposed filter was simulated and performance evaluated using HFSS (High Frequency Simulation Software). The resulting performance of the proposed filter makes it very desirable for Bluetooth and Wi-Fi applications (ieee 802.11n). © 2024 ieee.

关键词： Bandwidth

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CSA-SVM method for internal cavitation defects detection and its application of district heating pipes

CSA-SVM method for internal cavitation defects detection and...

引用

ieee/RSJ international conference on intelligent Robots and systems (IROS)

作者： Chen, Yanran Ma, Shugen Li, Longchuan Li, Zhiqing Yang, Yulin Beijing Univ Chem Technol Coll Informat Sci & Technol Beijing Peoples R China Ritsumeikan Univ Grad Sch Sci & Engn 1-1-1 Nojihigashi Shiga 5258577 Japan Beijing Univ Chem Technol Coll Informat Sci & Technol Beijing Peoples R China Ritsumeikan Univ Grad Sch Sci & Engn 1-1-1 Nojihigashi Shiga 5258577 Japan

ISBN: (数字)9781665479271

ISBN: (纸本)9781665479271

The goal of this paper is to develop an ultrasonic detection device that can be mounted on an underwater snake vehicle (USV) for underwater district heating pipe (DHP) detection in the future. Ultrasonic detection technology (UDT) is the detection means used, and the cavitation defects in polyurethane (PUR) layer of DHPs are the object being detected. Due to the large thickness of PUR layer and the complex interface information of multi-layer structure, detecting defects of DHPs quantitatively is a difficult task. To address this issue, this paper proposes an approach that combines feature extraction and crow search algorithm (CSA) optimized support vector machine (SVM). Firstly, the main parameters and detection method of UDT are designed after investigation. Secondly, defective signals are pre-processed by signal processing to extract the features form three domains. Finally, four different classifiers are used to identify cavitation defects based on the feature-set. When compared among optimized random forest (RF), k-nearest neighbor (KNN), and ordinary SVM, the experimental results show that CSA-SVM had the highest accuracy in defect size prediction, and the validation-experiment verifies the practicability and feasibility of the CSA-SVM classifier. All experiments illustrate that the issue could be well solved by our method.

关键词： Support vector machines Heating systems Resistance Sensitivity signal processing algorithms signal processing Feature extraction

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Designing of an Autonomous System for Electric Vehicle 3

Designing of an Autonomous System for Electric Vehicle

引用

3rd international conference on robotics, Electrical and signal processing Techniques, ICREST 2023

作者： Mridul, Towfiq Mahmud Sagor, Abidur Rahman Mridha, Faisal Ahmad Bhuiyan, Md. Mosaraf Hosen Hasan, Md. Jahid Rahman, Md. Abdur American International University-Bangladesh Department of Electrical and Electronics Engineering Dhaka Bangladesh Independent University Bangladesh Department of Computer Science and Engineering Dhaka Bangladesh American International University-Bangladesh Faculty of Engineering Dhaka Bangladesh

ISBN: (纸本)9798350346435

The creation of an autonomous vehicle has two major goals: to minimize the amount of labor that must be performed manually and to provide the automobile with superior intelligence. In order to turn a standard automobile into an autonomous vehicle that can drive itself around a predetermined map (in this case, a university campus), several modifications need to be made. The outcomes of this project will also contribute to the creation of a more technologically advanced campus atmosphere. Additional responsibilities include taking control of the horn system and being in charge of the headlights while also receiving the response signal from the station. In order to guarantee that everything functions correctly, we utilized components such as the Raspberry Pi, light sensors, motors, Arduino Uno, ultrasonic sensors, buzzers, and cameras. A temporary model is built to ensure that this project is successful right from the start. The training model trains the deep learning approach using images captured by a camera in manual mode, which enables the vehicle to operate in autonomous mode using the multilayered neural network that was taught. The final prototype utilizes image processing methods to track lanes. A few image processing technologies, such as intelligent edge detection, provide autonomous movement capabilities. These algorithms were built and tested on the vehicle. The system operated without a hitch, and the data gathered was within reasonable bounds of expectations. As well as demonstrating how the autonomous system of an electric car works. © 2023 ieee.

关键词： Cameras

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signal processing in the Problem of Breast Tumors Detection by Impedansometry Method Based on Havriliak-Negami Model 26

Signal Processing in the Problem of Breast Tumors Detection ...

引用

26th international conference on Digital signal processing and its Applications, DSPA 2024

作者： Kuzmin, Andrey Baranov, Viktor Pushkareva, Anastasia Information and Computing Systems Penza State University Penza Russia Information-measurement Systems and Metrology Penza State University Penza Russia Biomedical Engineering Penza State Technological University Penza Russia

ISBN: (纸本)9798350361728

This article is devoted to the processing of impedance data for breast examination. Breast tumors are a serious medical problem. Their timely detection requires periodic examinations over a long period of time. For monitoring, it is advisable to use methods that are not associated with radiation exposure and other harmful factors. These include impedance measurements, since the dielectric properties of tumors differ from the properties of healthy tissues. The authors propose the use of the Havriliak-Negami model for processing primary measurement data. As a result of solving the inverse problem, informative parameters of the model are calculated that describe the dielectric properties of the object of study. To implement laboratory experiments, an original multielectrode design of a dielectric sensor has been proposed, which can be used both for detection and localization of tumors. The data received from the sensor includes about a thousand parameters. It is proposed to process such a data set using machine learning methods. A dataset is created to train and test the intelligent classifier. It is formed based on data from laboratory experiments using a phantom. Assessing the sensitivity and localization capabilities of the proposed method is the immediate task of further research. © 2024 ieee.

关键词： Tumors

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Hybrid Classifier for signal Aspect Detection in Railway Infrastructure 14

Hybrid Classifier for Signal Aspect Detection in Railway Inf...

引用

14th ieee conference on Evolving and Adaptive intelligent systems (ieee EAIS)

作者： Friedenberger, Dirk Grzelka, Felix Polze, Andreas Univ Potsdam DB Systel GmbH Hasso Plattner Inst Frankfurt Germany Univ Potsdam Hasso Plattner Inst Potsdam Germany

ISBN: (纸本)9781665437066

In this paper, we present a hybrid classifier built by combining object detection (YOLOvS) and signal aspect detection through traditional image processing routines. The hybrid classifier is part of our test automation toolchain. It is intended to be used for monitoring railway signals in end-to-end integration test scenarios when bringing interlockings into service. In our field tests, we have successfully demonstrated recognition and classification of signal aspects for German KS signals and UK running signals. The aspect detection provides distance metrics for the position, radius, and color of the lights in the signal. We trained a logistic regression classifier with these metrics to classify detected signal light candidates. The set of detected lights is then matched against all predefined signal aspects to determine the signal aspect. We tested our algorithm in our lab and a test field. The F1 score of the presented algorithm is 0.74 for the KS signal and 1 for the UK running signal.

关键词： signal aspect detection hybrid classifier computer vision object detection railway infrastructure railway digitalization

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Simulink Implementation of MFCC for Audio signal processing Applications 1

Simulink Implementation of MFCC for Audio Signal Processing ...

引用

1st international conference on intelligent Technologies for Sustainable Electric and Communications systems, iTech SECOM 2023

作者： Susithra, N. Akshara, R. Harshini, A. Aiswarya, P. Abinaya, M.R. Rajalakshmi, K. Psg Institute of Technology and Applied Research Department of Ece India Psg Institute of Technology and Applied Research Department of Ece Tamilnadu India Psg College of Technology Department of Ece India

ISBN: (纸本)9798350371185

Speech recognition is has been used in wide applications such as Voice-Activated systems, Virtual Assistants, and Interactive Voice Responses (IVR). Feature extraction is a crucial stage in speech and audio signal processing for various applications, including speech recognition, speaker identification, speaker authentication and audio categorization. The accuracy of any speech recognition technique depends on the type of feature extraction method used. The most commonly used techniques are Linear Predictive Coding (LPC), Mel Frequency Cepstral coefficients (MFCC), and Perceptual Linear Prediction. Among these, MFCC is the most effective and computationally efficient method. This paper focuses on the implementation of MFCC using Simulink for speech signal processing applications. The implementation of feature extraction using MFCC in Simulink involves several steps, including pre-emphasis, framing, windowing, Fast Fourier Transform, Mel-filter bank application, and extraction of cepstral coefficients. Finally, a recurrent neural network is used to detect the presence of the word 'yes' based on the extracted features. In summary, this paper highlights the significance of feature extraction in speech recognition. The Simulink implementation of MFCC feature extraction is explained in detail, and the use of a recurrent neural network for detecting the presence of a specific word is demonstrated. © 2023 ieee.

关键词： Simulink

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Improving Marine Radar Odometry by Modeling Radar Resolution and Exploiting Additional Temporal Information

Improving Marine Radar Odometry by Modeling Radar Resolution...

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ieee/RSJ international conference on intelligent Robots and systems (IROS)

作者： Schiller, Carl H. Arsenali, Bruno Maas, Deran Marano, Stefano ABB Corp Res Baden Switzerland

ISBN: (数字)9781665479271

ISBN: (纸本)9781665479271

Radar odometry may provide valuable input for surface vessels in several marine applications. The vulnerability of global positioning satellite systems to jamming and spoofing motivates the search for alternatives. In this work, we investigate the feasibility of W-band frequency modulated continuous wave radars in marine settings for odometry. A method to model radar resolution is presented and is further extend to include multiple radar frames. Numerical implementation relies on concepts from Lie theory. The proposed methods were evaluated on datasets collected from a ferry in a harbour area, where the average relative translation error was reduced to 3.07% compared to 14.2% of a baseline method.

关键词： Radar signal processing High frequency radar Marine navigation

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Achievable Error Rate Reduction with Hexagonal QAM Constellations Over the Shadowed Fading Channels 26

Achievable Error Rate Reduction with Hexagonal QAM Constella...

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26th international conference on Digital signal processing and its Applications, DSPA 2024

作者： Gvozdarev, Aleksey S. Artemova, Tatiana K. Ermakov, Iliya Manahov, Roman Mozzhukhin, Semen Veselkov, Andrey Institute of Information Security P.G. Demidov Yaroslavl State University Yaroslavl Russia P.G. Demidov Yaroslavl State University Dept. of Intelligent Radiophysical Information Systems Yaroslavl Russia

ISBN: (纸本)9798350361728

The proposed research performs a comparative analysis of the average error rate for a wireless communication system with a shadowed fading channel with M-QAM with various shapes of the signal constellation: square (SQAM), regular (RHQAM) and irregular hexagonal (IHQAM), carried out for a recently published model - the fluctuating Nakagami-m channel. Numerical simulation has shown that an appropriate shape of the signal constellation can reduce the error rate significantly. Under the conditions of signal propagation corresponding to this channel model, the worst form of the constellation for almost all values of the channel model parameters and the signal-to-noise ratio is RHQAM, and the greatest reduction is provided by the choice of IHQAM (upto about 20%). The influence of the model parameters on the value of the achievable gain is investigated. Scenarios in which system performance is insensitive to the channel model parameters or to the signal-to noise ratio have been found. © 2024 ieee.

关键词： Quadrature amplitude modulation

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