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检索条件"任意字段=International Conference on Measurement and Modeling of Computer Systems"

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3D inversion and 3D visualization of 2D survey data based on high density electrical method: take Guilester BarQin mining area as an example 5

3D inversion and 3D visualization of 2D survey data based on...

引用

5th international conference on Geoscience and Remote Sensing Mapping, ICGRSM 2023

作者： Ma, Dexi Zhang, Wei Zhang, Zhiyong Peng, Wuxu Center for Geophysical Survey China Geological Survey Langfang China School of Geophysics and Measurement-Control Technology East China University of Technology Nanchang China

ISBN: (纸本)9781510672789

The development of electrical detection technology and quantitative interpretation of results, 3D geological modeling, and the search for hidden mines have made conducting electrical 3D inversion and 3D visualization expression an important research topic. The three-dimensional nature of underground space determines the limitations of using two- dimensional profile measurement results to interpret three-dimensional underground geological bodies. 3Dinversionand3D visual expression are carried out based on the high-density electrical method 2D profile survey data in GuiLest BarQin mining area, Inner Mongolia. The continuous distribution of near east-west low resistivity anomaly zone reflects that there is a low resistivity structural zone in the contact zone of Jurassic and Devonian strata, and the structural attitude is nearly vertical;the polarizability anomaly body is distributed on both sides of the corresponding low resistivity structural belt. The strength and scale of the anomaly indicate that the mineralization is mainly distributed in the Jurassic strata close to the structural belt, followed by continuous mineralization in the deep Devonian strata far away from the structural belt. The mineralization projection on the surface corresponds to the IP anomaly, and has certain specificity with the Jurassic Tuff. The three-dimensional inversion and visualization results of high-density electrical method 2D profile measurement data in the mining area directly reflect the spatial occurrence of the structure and the spatial position relationship with mineralization, the exclusive relationship between mineralization and rock strata, and the corresponding relationship between mineralization and IP anomalies, indicating the direction for further exploration work. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Three dimensional computer graphics

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Research on Dual Station Target Detection and Tracking Algorithm Based on Weighted Centroid Compensation 3

Research on Dual Station Target Detection and Tracking Algor...

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3rd international conference on Electronic Information Engineering and computer Science, EIECS 2023

作者： Chen, Peng Shi, Yuejun Zheng, Qian Liu, Zhijun Li, Qinghang Yuan, Kaixuan Unit 32382 Beijing China

ISBN: (纸本)9798350316674

In response to the problems of slow detection speed and low tracking accuracy of conventional low altitude unmanned aerial vehicle (UAV) target detection and tracking systems, this paper studies the dual station target intersection tracking algorithm. By using sub weighted pixel processing method and estimating and compensating tracking errors, By conducting experimental tests at different time periods and comparing traditional methods, the method proposed in this article the detection and tracking accuracy of low altitude UAV targets are greatly improved. © 2023 IEEE.

关键词： cancellation optical measurement servo trajectory tracking

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A Deep Learning Approach for Automated Skin Disease Classification and Diagnosis 2

A Deep Learning Approach for Automated Skin Disease Classifi...

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2nd IEEE international conference on Integrated Circuits and Communication systems, ICICACS 2024

作者： Suresh, Helina Rajini Amutha, M. Tamizharasi, A. Jaya Krishna, A.P. Lalitha, S. Nithya, P. Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India Sona College of Technology Department of ECE Tamil Nadu Salem India R.M.D. Engineering College Department of Computer Science and Engineering Kavarapettai Tamil Nadu Chennai India Sona College of Technology Department of Electronics and Communication Engineering Tamilnadu Salem India Arunai Engineering College Department of Computer Science and Engineering Tamil Nadu Tiruvannamalai India

ISBN: (纸本)9798350317558

Everyone is ware that a wide range of problems affect skin structure, function, and appearance. Dermatological issues or dermatoses are common names used to represent the skin related illness. Early detection of skill llness is possible by employing Artificial Intellengence. A wide range of artificial intelligence techniques have been devised to promptly detect and diagnose skin problems. In this article we are proposing Mobilenetv2 and LSTM algorithms to identify skin disorders at an early stage. The combination of MobileNetV2 and LSTM (Long Short-Term Memory) for skin disease detection involves leveraging a convolutional neural network (CNN) for image feature extraction and a recurrent neural network (RNN) with LSTM units for sequence modeling, this architecture aims to capture both spatial and temporal dependencies in skin image data, making it well-suited for skin disease detection tasks. The method shown in this study can identify five distinct diseases with ease, and with accuracy rates of 99.2%. © 2024 IEEE.

关键词： Image segmentation

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High-precision Position Control of Ultrasonic Motor Based on Transient Response

High-precision Position Control of Ultrasonic Motor Based on...

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2024 IEEE international conference on Electrical Energy Conversion systems and Control, IEECSC 2024

作者： Qu, Huajie Wen, Zhongpu Shi, Mengdi Qu, Jianjun School of Mechatronics Engineering Beijing Polytechnic Department of Mechanical and Electrical Technology Beijing100176 China Beijing Engineering Research Center of Precision Measurement Technology and Instruments Beijing University of Technology Beijing100124 China School of Mechatronics Engineering Harbin Institute of Technology Harbin150001 China

ISBN: (纸本)9798350389357

In order to improve the accuracy of the position control of the ultrasonic motor and give full play to its characteristics such as low speed, fast response and self-locking in case of power failure, this paper proposes a stepping control method of the ultrasonic motor based on the transient response. A digital ultrasonic motor controller based on DSP is designed. A high-precision angular displacement test-bed is built by combining the above controller, a high-precision absolute rotary encoder and the LabVIEW upper computer program. Taking traveling wave ultrasonic motor with 60mm in diameter as the control object, the influence of ultrasonic motor's driving parameters on the step angle under transient response is studied. The experimental results show that the minimum open-loop step angle of ultrasonic motor is less than 1' with good stability. In addition, in order to achieve fast and high-precision positioning control combined with the transient response characteristics of ultrasonic motor, a composite control algorithm of step control and traditional PID control is proposed. This control algorithm realizes the high-precision closed-loop position control of ultrasonic motor and the information exchange between the upper computer and the lower computer with fast response. The experimental results show that the maximum adj ustment time is 0.8s and the maximum positioning difference is less than or equal to 2.9' within 3600. © 2024 IEEE.

关键词： Transient analysis

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Event-based Sensor Fusion and Application on Odometry: A Survey 6

Event-based Sensor Fusion and Application on Odometry: A Sur...

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6th IEEE international conference on Image Processing, Applications and systems, IPAS 2025

作者： Zhang, Jiaqiang Yu, Xianjia Sier, Ha Zhang, Haizhou Westerlund, Tomi University of Turku TIERS Lab Turku Finland

ISBN: (纸本)9798331506520

Event cameras, inspired by biological vision, are asynchronous sensors that detect changes in brightness. They offer notable advantages in environments characterized by high-speed motion, low lighting, or wide dynamic range. These distinctive properties render event cameras particularly effective for sensor fusion in robotics and computer vision, especially in enhancing traditional visual or LiDAR-inertial odometry. Conventional frame-based cameras suffer from limitations such as motion blur and drift, which can be mitigated by the continuous, low-latency data provided by event cameras. Similarly, LiDAR-based odometry encounters challenges related to the loss of geometric information in environments such as corridors. To address these limitations, unlike the existing event camera-related surveys, this survey presents a comprehensive overview of recent advancements in event-based sensor fusion for odometry applications particularly investigating fusion strategies that incorporate frame-based cameras, inertial measurement units, and LiDAR. The survey critically assesses the contributions of these fusion methods to improving odometry performance in complex environments, while highlighting key applications, and discussing the strengths, limitations, and unresolved challenges. Additionally, it offers insights into potential future research directions to advance event-based sensor fusion for next-generation odometry applications. © 2025 IEEE.

关键词： computer vision

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Rapid-Prototyping and Early Validation of Software Models through Uniform Integration of Hardware 26

Rapid-Prototyping and Early Validation of Software Models th...

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26th ACM/IEEE international conference on Model Driven Engineering Languages and systems, MODELS 2023

作者： Uelschen, Michael Schaarschmidt, Marco Budde, Jannis Osnabrück University of Applied Sciences Engineering and Computer Science Osnabrück Germany Jüke Systemtechnik GmbH Altenberge Germany

ISBN: (纸本)9798350324808

Model-driven software engineering (MDSE) uses software models to make the complexity of cyber-physical and mechatronic systems (CPMS) manageable. For the validation of CPMS software models, closed-loop simulations are typically used. Since the system's environment is part of the simulation, the software model is directly affected by the surroundings, which enables a more realistic evaluation. In early development phases, the expected target hardware platform for these software models is usually not considered, although such CPMS have a strong hardware dependency. This paper outlines a novel approach to couple these software models with hardware systems to improve the quality of these models and shorten the development cycle. The presented method allows the evaluation of functional and non-functional requirements. For this, a new in-The-loop concept is introduced where the hardware access is transparently performed using a remote procedure call mechanism. Moreover, the achieved modeling language and tool independence makes the novel approach suitable for various applications. The provided evaluation is based on two distinct modeling languages and tools to demonstrate the feasibility and performance of the new concept. © 2023 IEEE.

关键词： Cyber Physical System

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ASPECT-ORIENTED MODELS-BASED FRAMEWORK TO SECURE INTELLIGENT systems 22

ASPECT-ORIENTED MODELS-BASED FRAMEWORK TO SECURE INTELLIGENT...

引用

8th international conference on computer Technology Applications, ICCTA 2022

作者： Alhamad, Hessa Ali Hassan, Mohammad Mahdi Department of Computer Sciences College of Computer Qassim University Saudi Arabia

ISBN: (纸本)9781450396226

Security is a high-priority issue for any software system. Emerging intelligent systems have unique security challenges that need to be addressed. In this paper, we propose a novel aspect-oriented models-based security framework to address security concerns in intelligent systems. The aspects of this framework derive from identified threats to intelligent systems. We use Unified modeling Language (UML) diagrams to present each aspect. © 2022 ACM.

关键词： Intelligent systems

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Seed Kernel Counting using Deep Learning for High-Throughput Phenotyping

Seed Kernel Counting using Deep Learning for High-Throughput...

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2024 IEEE international conference on Internet of Things and Intelligence systems, IoTaIS 2024

作者： Margapuri, Venkat Thapaliya, Prapti Neilsen, Mitchell Department of Computer Science Villanova University VillanovaPA United States Department of Computer Science Kansas State University ManhattanKS United States

ISBN: (纸本)9798331521219

High-throughput phenotyping (HTP) of seeds, also known as seed phenotyping, is the comprehensive assessment of complex seed traits such as growth, development, tolerance, resistance, ecology, yield, and the measurement of parameters that form more complex traits [1]. One of the key aspects of seed phenotyping is cereal yield estimation that the seed packaging industry relies upon to conduct their business. While mechanized seed kernel counters are available in the market, they are often priced high and outside the affordability realm of small-scale seed packaging firms. The development of object tracking neural network models such as You Only Look Once (YOLO) enables computer scientists to design algorithms that can estimate cereal yield inexpensively. The key bottleneck of neural network models is that they require a plethora of labeled training data before they can be put to task. We demonstrate that the use of synthetic imagery serves as a feasible substitute to train neural networks for object tracking that includes the tasks of object classification and detection. Furthermore, we propose a seed kernel counter that uses a low-cost mechanical hopper, trained YOLOv8 neural network model, and object tracking algorithms of StrongSORT and ByteTrack to estimate cereal yield from videos captured using a mobile phone. The experiment yields a seed kernel count with an accuracy of 95.2% and 93.2% for Soy and Wheat respectively using the StrongSORT algorithm, and an accuracy of 96.8% and 92.4% for Soy and Wheat respectively using the ByteTrack algorithm. ©2024 IEEE.

关键词： Deep learning

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A Novel Architecture for a Medical Image Recognition System Using Deep Learning-Based Multiple Regression Evaluation 4th

A Novel Architecture for a Medical Image Recognition System ...

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4th international conference on Smart IoT systems: Innovations and Computing, SSIC 2023

作者： Parashar, Jyoti Upreti, Kamal Fatima, Iram Gangwar, Divya Saini, Ashok Kumar Vats, Prashant Department of Computer Science & Engineering Dr. Akhilesh Das Gupta Institute of Technology & Management New Delhi India Department of Computer Science Christ University Delhi NCR Campus Ghaziabad India Department of AI & ML Dr. Akhilesh Das Gupta Institute of Technology & Management New Delhi India Department of Management Babu Banarasi Das Institute of Technology & Management New Delhi India Department of Computer Science & Engineering School of Computer Science & Engineering Manipal University Jaipur Rajasthan Jaipur India

ISBN: (纸本)9789819751990

Models based on machine learning are optimization models that collect data, assess it, and deliver the reports required by specialists and management to make the best decisions. The application of contemporary machine learning allows the organization to quickly analyze photographs, differentiate voices assist in providing customer service, assess the information that is at hand, and uncover connections to aid in decision-making processes. The results of this investigation use quantitative methodologies to collect data and analyze it using mathematical procedures such as regression modeling as well as analysis of variance. Deep learning techniques applied to digital imaging, particularly in medical treatment, can increase picture quality, aid in modeling, aid in making the best possible diagnosis, and successfully address demands from patients. To analyze the hypothesis, investigators intend to utilize statistical approaches such as descriptive data analysis, regression evaluation, and analysis of variance (ANOVA). The authors employ the purposive sample approach to choose respondents from the healthcare industry. Purpose sampling is a non-probability sampling approach. Researchers collected data from 193 respondents working at hospitals that are privately owned in Southern Asia. As stated by the study, all factors, including efficiently meeting patient needs, have a probability value of under 0.05, indicating that they are statistically noteworthy. Following the study, the coefficient of variance (R squared) is 0.744, or 74.4%. According to the study, there is a high association between better image quality and ML-based digital picture identification systems. The recognition of patterns and the application of artificial intelligence to computerized recognition of pictures also have a close link. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Medical imaging

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5th international conference on Reliability, Safety and Security of Railway systems: Modelling, Analysis, Verification and Certification, RSSRail 2023

5th International conference on Reliability, Safety and Secu...

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5th international conference on Reliability, Safety and Security of Railway systems: Modelling, Analysis, Verification and Certification, RSSRail 2023

ISBN: (纸本)9783031433658

The proceedings contain 13 papers. The special focus in this conference is on international conference on Reliability, Safety and Security of Railway systems: Modelling, Analysis, Verification and Certification. The topics include: Halfway Generic Verification of Railway Control systems;Safety Analysis of Automatic Train Operation Based on ETCS;a Tool-Chain for the Verification of Geographic Scheme Data;towards Scenario-Based Certification of Highly Automated Railway systems;preface;remaining Useful Life Estimation for Railway Gearbox Bearings Using Machine Learning;TrainSec: A Simulation Framework for Security modeling and Evaluation in CBTC Networks;A Formal Model of Train Control with AI-Based Obstacle Detection;Modelling, Visualisation and Proof of an ETCS Level 3 Moving Block System;automating an Analysis of Safety-Security Interactions for Railway systems;Dependability Analysis of UPS Architectures for the Italian Railway Signaling System.

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