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检索条件"任意字段=4th International Conference on Research in Intelligent and Computing in Engineering, RICE 2019"

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4th international conference on research in intelligent and computing in engineering, rice 2019

4th International Conference on Research in Intelligent and ...

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4th international conference on research in intelligent and computing in engineering, rice 2019

ISBN: (纸本)9789811527791

the proceedings contain 123 papers. the special focus in this conference is on research in intelligent and computing in engineering. the topics include: Concept of cancer treatment by heating methodology of microwave;dynamics of self-guided rocket control with the optimal angle coordinate system combined with measuring target parameters for frequency modulated continuous wave radar;an approach of utilizing binary bat algorithm for pattern nulling;An application of WSN in smart aquaculture farming;a newly developed approach for transmit beamforming in multicast transmission;post-quantum commutative deniable encryption algorithm;Indoor positioning using BLE iBeacon, smartphone sensors, and distance-based position correction algorithm;assessing the transient structure with respect to the voltage stability in large power system;cellular automata approach for optimizing radio coverage: A case study on archipelago surveillance;smart bicycle: IoT-based transportation service;LNA nonlinear distortion impacts in multichannel direct RF digitization receivers and linearization techniques;novel approach to detect and extract the contents in a picture or image;Modified biological model of meat in the frequency range from 50 Hz to 1 MHz;A research on clustering and identifying automated communication in the HTTP environment;Sequential all-digital background calibration for channel mismatches in time-interleaved ADC;Comparison BICM-ID to turbo code in wide band communication systems in the future;a design of a vestibular disorder evaluation system;about model separation techniques and control problems of wheeled mobile robots;Fuzzy supply chain performance measurement model based on SCOR 12.0;lightweight convolution neural network based on feature concatenate for facial expression recognition;light fidelity system.

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Status and prospects of mechanical precision machining technologies: an econometric analysis of literature based on 2019-2024 4

Status and prospects of mechanical precision machining techn...

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4th international conference on Advanced Manufacturing Technology and Electronic Information, AMTEI 2024

作者： Sun, Zhen Qin, Zechuan College of Intelligent Equipment Shandong University of Science and Technology Taian China

ISBN: (数字)9781510688247

ISBN: (纸本)9781510688230

Status and Prospects of Mechanical Precision Machining Technologies: an Econometric Analysis of Literature Based on 2019-2024" is a key research topic[1]. In this study, bibliometric methods were used to systematically analyse the research developments and trends in the field of mechanical precision machining between 2019 and 2024[2]. Relying on the Web of Science (WoS) database, this study quantitatively analyses and visually presents the relevant literature with the help of visualization tools such as CiteSpace and VOSviewer, and then deeply analyzes the current status of mechanical precision machining technology and its future development path. the study reveals the technological progress, research focuses and potential directions for future research in this field[3], and summarises the main conclusions: mechanical precision machining technology is steadily developing in the direction of intelligence, high precision and high efficiency, which provides a solid technological support for the development of related industries. © 2025 SPIE.

关键词： Micromachining

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Person Re-Identification Using Siamese Triplet Network 4

Person Re-Identification Using Siamese Triplet Network

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4th international conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Menon, Aparna Yashwanthika, R. Shreya, J.V. Somasundaram, K. thangavel, Senthil Kumar Asawa, Shreeya Amrita School of Computing Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Coimbatore India Amrita School of Physical Sciences Department of Mathematics Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (纸本)9798331523923

Due to the increasing demand for public safety and the rapid development of intelligent surveillance networks, the re-identification of individuals (Re-ID) has become one of the most important research topics in computer vision. Person re-identification (Re-ID) has a wide range of applications, which increases its popularity in recent studies. the main goal of person re-identification (Re-ID) is to retrieve people with the same identity from different cameras. In the open world, there are still some challenges. First, existing re-ID research usually assumes that only one-factor variable (view, clothing, pedestrian pose, pedestrian occlusion, image resolution, RGB/IR modality) changes, and ignores the complexity of multi-factor variables in the open world. Second, existing ID methods are overly dependent on clothing color and other obvious pedestrian features that can be easily obscured or changed. In addition, the lack of benchmark datasets that include multifactor variables hinders the practical application of ID in the open world. the proposed model uses a Deep learning model -Siamese triplet network to extract the features, and a similarity measure to re-identify the individual. the evaluation metrics used are cumulative matching features (CMC) and mean average precision (mAP). Preliminary results show that the model performs well in comparison to existing methods, and future work will focus on improving robustness under varying environmental conditions. © 2025 IEEE.

关键词： Reamers

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Phase Retrieval System Based on Refractive Index Change 4

Phase Retrieval System Based on Refractive Index Change

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4th international Computational Imaging conference, CITA 2024

作者： Cheng, Hong Zhang, Hongyi Wang, Li Fenzhang Li, Shuhan Key Laboratory of Intelligent Computing & Signal Processing Anhui University Anhui Province Hefei230601 China

ISBN: (纸本)9781510688834

the phase recovery method based on the Transport of Intensity Equation is widely used in the field of microscopic imaging of biological cells. When using this method for phase recovery, the CCD is always moved to acquire intensity images at different out-of-focus positions, which introduces mechanical errors, it also causes errors when using the traditional FFT method. Based on this, this paper proposes a phase recovery system based on refractive index change: firstly, an image acquisition system with a refractive index medium is built, and two intensity images with different refractive index are acquired;the intensity-phase equation based on refractive index change is established, and the "maximum intensity" assumption method is introduced to solve this equation. then, we can obtain high-precision phase results without moving the CCD. In this paper, the feasibility and accuracy of this technique are confirmed by numerical simulation and optical experiment respectively. © 2025 SPIE.

关键词： Refractive index

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IPDD: intelligent Parkinson Disease Detection System 4th

IPDD: Intelligent Parkinson Disease Detection System

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4th international conference on Smart IoT Systems: Innovations and computing, SSIC 2023

作者： Singhal, Manish Tiwari, Vinita Sharma, Ashish Electronic and Communication Indian Institute of Information Technology Rajasthan Kota325003 India Computer Science and Engineering Manipal University Rajasthan Jaipur303007 India

ISBN: (纸本)9789819751990

Worldwide, millions of peoples are affected by complex neuro degenerative disorder, that is known as PD (Parkinson Disease). In recent years, it is very critical for accurate diagnosis of PD at early stage for implementing timely interventions and improving patient life. there have been growing interest in developing intelligent systems for Parkinson’s disease detection, harnessing the potential of cutting-edge technologies such as artificial intelligence, machine l earning, and sensor-based data analysis. this research paper presents an in-depth exploration of an intelligent Parkinson Disease Detection System (IPDDS) designed for early diagnosis and quality level monitoring of PD using two most accurate machine learning techniques—SVM and Random Forest. the presented work relates the use of various performance metrices like Accuracy, Confusion Matrix, Precision, etc. Standard Dataset having voice samples of human’s having Parkinson Disease and not having PD is used to validate the various performance parameters and predict the PD or non-PD. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Neurodegenerative diseases

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Diverse human motion prediction based on orthogonal basis vectors 4

Diverse human motion prediction based on orthogonal basis ve...

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4th international conference on Computer Vision, Application, and Algorithm, CVAA 2024

作者： Tong, Hanqing Ding, Wenwen Li, Qing Wang, Xin Anhui Province Key Laboratory of Intelligent Computing and Applications Huaibei Normal University Huaibei235000 China School of Mathematics and Statistics Huaibei Normal University Huaibei235000 China

ISBN: (数字)9781510687622

ISBN: (纸本)9781510687615

the diversity human motion prediction task predicts multiple future motion sequences from historical data. Existing research uses likelihood-based sampling, but human motion's inhomogeneity often causes modal collapse and complex training. Our paper proposes a method using a linear dynamical system to model spatiotemporal dependence, obtaining orthogonal basis vectors via Tucker decomposition. By connecting these with encoded motion residuals and sampling the Grassmann manifold with a relaxed Bernoulli distribution, we predict future motions. Compared to existing methods on Human3.6M and HumanEva-I datasets, our approach mitigates pattern collapse, improves diversity by 3%, and reduces average error by 0.07. © 2025 SPIE.

关键词： Prediction models

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research on dynamic network security detection technology based on SDN 4

Research on dynamic network security detection technology ba...

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4th international conference on Network Communication and Information Security, ICNCIS 2024

作者： Zhao, Kai Beijing Polytechnic Beijing100176 China

ISBN: (数字)9781510688261

ISBN: (纸本)9781510688254

Traditional network architecture can no longer meet the development needs of technologies such as cloud computing and big data. SDN network architecture has the characteristics of high openness and programmability, which can quickly respond to changes in business requirements. SDN decouples the control management function of the network from the data forwarding function, simplifies network configuration work based on logic centralized controllers and open programming interfaces, thereby achieving a flat management mode and flexible data forwarding function. the centralized control and programmability of SDN networks also pose significant security threats to SDN. Based on the CSE-CIC-IDS2018 dataset, this article tests the performance of various intelligent learning algorithms, analyzes data flows, distinguishes normal data from abnormal data, improves detection accuracy, and has practical significance for the security defense of SDN networks. © 2025 SPIE.

关键词： Network security Computer security Network architectures Control systems Machine learning Data transmission Defense and security Detection and tracking algorithms Information security Security technologies

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Comparison of Segmentation Algorithms for Extraction of Stone from Kidney X-ray Image 4th

Comparison of Segmentation Algorithms for Extraction of Ston...

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4th international conference on Smart IoT Systems: Innovations and computing, SSIC 2023

作者： Nisha, N. Dhaka, Vijaypal Singh Sinwar, Deepak Department of Computer and Communication Engineering Manipal University Jaipur Jaipur India Director of School of Computing and Intelligent Systems Department of Computer and Communication Engineering Manipal University Jaipur Jaipur India Department of IoT and Intelligent Systems Manipal University Jaipur Jaipur India

ISBN: (纸本)9789819751990

Healthcare systems are gaining popularity because of the advancement of new technology aiding healthcare professional for diagnosis of disease from medical modalities. the detection and classification of disease using AI and its technologies are active research areas in the last decade. Radiologist usually detects stone from the kidney using different imaging like CT scan, MRI scan, and X-ray. For the detection of stone in kidney X-ray images, various segmentation and classification methods are used. these different classification and segmentation methods are used to reduce errors and time of healthcare professional in diagnosis of stone in X-ray image. In this paper, comparison of different algorithms like thresholding algorithm, contour-based algorithm, deep learning algorithms like U-Net, U-Net++, V-Net, V-Net++, and Transformer Net are used for segmentation of stone from kidney X-ray images. the thorough comparison of different deep learning architectures in diagnosing stone from kidney X-ray images is also made in this paper. Most of the papers work on classification of stone from different medical modalities before segmentation which cause data leakage problem. In this research paper, comparisons of different segmentation algorithms help in achieving higher accuracy and reduce the data leakage problem. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Deep learning

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Lightweight design and deployment of object detection model for low-light scenes 4

Lightweight design and deployment of object detection model ...

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4th international conference on Computer Vision, Application, and Algorithm, CVAA 2024

作者： Sun, Kangjian Huo, Ju Jiang, Xiaona Gao, Yichao Cai, Chen School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China National Key Laboratory of Modeling and Simulation for Complex Systems Harbin China China FAW Corporation Limited Changchun China College of Design and Engineering National University of Singapore Singapore Signal and Communication Research Institute China Academy of Railway Sciences Beijing China

ISBN: (数字)9781510687622

ISBN: (纸本)9781510687615

Low-light scenes are common in fields such as autonomous driving, which tests the robustness of intelligent systems. this paper tests the performance of object detection in low-light scenes based on the YOLOv8n model. In order to solve the constraint of limited computing power of embedded devices, the YOLOv8n model is adjusted through model pruning and knowledge distillation. the complexity of the model is reduced through these lightweight operations. While ensuring the detection performance as much as possible, the multiply-accumulate operations (MACs) and parameters of the model decreased by about 40% and 27% respectively. the proposed model is evaluated on the Exclusively Dark (ExDARK) dataset and achieves a mean average precision (mAP) value of 0.672. In addition, the proposed model is migrated to the embedded platform NVIDIA Jetson Xavier NX. the deployment process is optimized by multi-process scheduling and multi-thread scheduling. Experiments are also conducted on real data, and the results show that the proposed model can provide a feasible solution for vision-based nighttime autonomous driving. © 2025 SPIE.

关键词： Object detection Deep learning Image processing

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Optimization of UWB-Based Indoor Positioning Algorithm and Design of Positioning System 24

Optimization of UWB-Based Indoor Positioning Algorithm and D...

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4th international conference on Signal Processing and Communication Technology, SPCT 2024

作者： Hu, Yingkun Zhuang, Yihui Zhang, Yingbin Zhang, Dongbo School of Computer and Information Engineering Guangdong Polytechnic of Industry & Commerce Guangdong Guangzhou China

ISBN: (纸本)9798400710636

Considering the varying advantages, disadvantages, and implementation difficulties of current indoor positioning algorithms, this paper conducts a comparative analysis of common UWB ranging methods. the Two-Way Ranging (TWR) algorithm significantly improves ranging accuracy compared to the One-Way Ranging (OWR) approach. An optimized bi-directional TWR algorithm is proposed, in which the tag only needs to send a single Poll message, reducing ranging time and tag power consumption. To address measurement errors, where the trilateration circles may not intersect at a single point, the least squares method is employed to linearize and optimize the equations. A real-time indoor positioning system is designed, incorporating the optimized bi-directional TWR algorithm and trilateration algorithm. the software workflows for the tags and base stations are developed, and the system visualizes the distances from the tag to four base stations in the upper computer software, along with the derived position coordinates (X, Y, Z). the system achieves static errors within 0.05–0.06 meters, demonstrating its high accuracy for indoor real-time positioning. © 2024 Copyright held by the owner/author(s).

关键词： Least squares approximations

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