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

共 91621 条记录，以下是1491-1500 订阅

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Predictive modeling for Mold Material Defects Using CNN-Random Forest Fusion

Predictive Modeling for Mold Material Defects Using CNN-Rand...

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2024 IEEE international conference on Information Technology, Electronics and Intelligent Communication systems, ICITEICS 2024

作者： Rajora, Ricky Banerjee, Deepak Malhotra, Sonal Devlival, Swati Kumar, Gotte Ranjith Rajora, Aarju Graphic Era Hill University Uttarakhand Dehradun India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Graphic Era Deemed to Be University Uttarakhand Dehradun India School of Computer Science & Artificial Intelligence Sr University Warangal India Chandigarh Engineering College Department of Computer Science & Engineering Mohali Jhanjeri India

ISBN: (纸本)9798350382693

In the abstract, The effective identification and categorization of mould material faults are critical for ensuring the quality and dependability of substances in a variety of industrial settings. This paper, it provides a unique approach to recognizing mould defects that utilizes a CNN (Convolutional Neural Network) and a Random Forest algorithm. Our technique is tested across an array of defect classifications, including pitting, blistering, cracking, inclusions, and flashing. The precision, recall, or FI-Score metrics demonstrate the framework's ability to reliably detect each fault type. Notably, our model has a macro-average F1 score of 82.95%, indicating strong performance throughout all classes. The weighted mean FI-Score of 83.06% corrects for class imbalances, illustrating the model's capacity to manage varied fault incidences. The previously micro-average F1 score of 83.07% measures the model's overall performance across the dataset. The Support Percentage metrics provide an understanding of the range of defect categories in the dataset, while an overall precision of 93% demonstrates the model's ability to anticipate mould material flaws. This research advances manufacturing quality assurance procedures by providing a dependable solution for the timely identification and categorization of mould flaws, assuring the quality and dependability of final goods in a variety of sectors. © 2024 IEEE.

关键词： Convolutional neural networks

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Detection of Fusarium Wilt Disease in Pomegranate Plants using Deep Learning Techniques

Detection of Fusarium Wilt Disease in Pomegranate Plants usi...

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2024 IEEE international conference on modeling, Simulation and Intelligent Computing, MoSICom 2024

作者： Pakruddin, B. Hemavathy, R. Presidency University Presidency School of Computer Science & Engineering and Information Science Bengaluru560064 India Visvesvaraya Technological University R.V College of Engineering Department of Computer Science & Engineering Belagavi590018 India

ISBN: (纸本)9798331533311

India is the world's largest producer of pomegranates, but plant diseases significantly impact crop productivity, leading to major agricultural losses annually. Fusarium wilt, caused by Fusarium oxysporum f. sp. ciceris (Foc), is one of the most common and severe diseases affecting pomegranate crops in India, reducing both the quantity and quality of production. Globally, Fusarium wilt poses a serious threat, with the potential to devastate entire fields under favorable conditions, causing up to 1 0 0% loss. Identifying this disease typically requires specialized knowledge or advanced systems. Deep learning (DL) is proposed as an effective method for disease recognition and classification due to its ability to extract features from images automatically. This study developed a deep learning model using Convolutional Neural Networks (CNNs) for feature extraction and a Softmax layer to classify pomegranate plant diseases. We collected 945 images directly from various farms in different cities, including Ballari, Bengaluru, and Bagalakote. Various image preprocessing techniques were applied, and data augmentation was used to prevent overfitting. The model was trained and evaluated on 3,000 images with data augmentation, with 8 0% of the images used for training and 20% for testing. The proposed integrated PomeNetV2 and ResNet50V2 CNN model demonstrated strong performance in identifying pomegranate plant diseases, achieving an accuracy of 9 8%. The study concludes that the proposed CNN outperforms existing methods in disease detection and classification. © 2024 IEEE.

关键词： Plant diseases

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Graph Matching Optimization Network for Point Cloud Registration

Graph Matching Optimization Network for Point Cloud Registra...

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IEEE/RSJ international conference on Intelligent Robots and systems (IROS)

作者： Wu, Qianliang Shen, Yaqi Jiang, Haobo Mei, Guofeng Ding, Yaqing Luo, Lei Xie, Jin Yang, Jian Nanjing Univ Sci & Technol Sch Comp Sci & Engn Jiangsu Key Lab Image & Video Understanding Socia Nanjing Peoples R China Nanjing Univ Sci & Technol PCA Lab Key Lab Intelligent Percept & Syst HighDi Minist Educ Nanjing Peoples R China Univ Technol Sydney Fac Engn & Informat Technol Sydney NSW 2007 Australia

ISBN: (纸本)9781665491907

Point Cloud Registration is a fundamental and challenging problem in 3D computer vision. Recent works often utilize geometric structure features in downsampled points (patches) to seek correspondences, then propagate these sparse patch correspondences to the dense level in the corresponding patches' neighborhood. However, they neglect the explicit global scale rigid constraint at the dense level point matching. We claim that the explicit isometry-preserving constraint in the dense level on a global scale is also important for improving feature representation in the training stage. To this end, we propose a Graph Matching Optimization based Network (GMONet for short), which utilizes the graph-matching optimizer to explicitly exert the isometry preserving constraints in the point feature training to improve the point feature representation. Specifically, we exploit a partial graph-matching optimizer to enhance the super point (i.e., down-sampled key points) features and a full graph-matching optimizer to improve the dense level point features in the overlap region. Meanwhile, we leverage the inexact proximal point method and the mini-batch sampling technique to accelerate these two graph-matching optimizers. Given high discriminative point features in the evaluation stage, we utilize the RANSAC approach to estimate the transformation between the scanned pairs. The proposed method has been evaluated on the 3DMatch/3DLoMatch and the KITTI datasets. The experimental results show that our method performs competitively compared to state-of-the-art baselines.

关键词： Surface measurement

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2023 IEEE 17th international conference on the Experience of Designing and Application of CAD systems, CADSM 2023 - Proceedings

2023 IEEE 17th International Conference on the Experience of...

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17th IEEE international conference on the Experience of Designing and Application of CAD systems, CADSM 2023

ISBN: (纸本)9798350310856

The proceedings contain 45 papers. The topics discussed include: designing the topology of microelectromechanical systems by machine learning methods;development of a remote-control system for a mobile vibration-driven robot;models of recurrent distributions statistical averaging for electronic components with fluctuations;inverse-dynamic neural controller simulation;a method of creating virtual pixels in matrix;the computer modeling of the thermal agent hydrodynamics through the alcohol distillery stillage stationary layer;method for estimating the topological structure of self-organized networks;a new hybrid method for predicting recommendations for collaborative recommender systems;software-defined transmitter to support automatic dependent surveillance-broadcast;deductive matrix synthesis for fault simulation;investigation of response from the micro objects of complex shape irradiated by acoustic wave;outdoor positioning for industrial workplace;a software complex for researching algorithms for working with graphs;and hydrogen adsorption in porous silicon: simulation and control method.

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Attack research of multilayer network vulnerability in the urban transport system

Attack research of multilayer network vulnerability in the u...

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2022 international conference on Signal Processing and Communication Security, ICSPCS 2022

作者： Cao, Jie Li, Jinyu Hou, Liang College of Computer and Communication Lanzhou University of Technology Gansu Lanzhou China

ISBN: (纸本)9781510660151

The urban public transport system comprises various networks representing different transportation modes with complex internal connections. The common single-layer complex network cannot fully describe the interior characteristics of the system. Therefore, this paper proposes a multi-layer network modeling method for the urban public transport system, which couples different traffic networks into multi-layer networks. We also proposed a centrality measurement of node transfer and designed an attack strategy called the multi-metric joint. The simulation experiment using the geographic information data of Chengdu urban public transport shows that the modeling method can completely and accurately describe the natural urban public transport system. And the multi-metric joint attack strategy is more effective than the traditional attack strategy, which will cause more severe damage to the network. This paper provides a new perspective and method for multilayer network modeling and vulnerability analysis of urban public transport systems. © 2022 SPIE.

关键词： Complex networks

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Radar and Fuzzy systems Technologies for Monitoring and Management of Vehicle Traffic and Pedestrian Flow 24

Radar and Fuzzy Systems Technologies for Monitoring and Mana...

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24th international conference on Control systems and computer Science, CSCS 2023

作者： Pruteanu, Eusebiu Nitu, Costica Puiu, Petru University Vasile Alecsandri of Bacau Department of Energy and Computer Science Calea Marasesti 157 Bacǎu Romania Polytechnic University Department of Intelligent Robotics Splaiul Independenei 313 Bucharest Romania

ISBN: (纸本)9798350313390

Smart traffic lights can be adaptive, with neural networks and associated with smart cameras and microwave sensors. Real-time determinations offer the possibility for specialists to intervene in real-time and collect traffic data for modeling, planning and other training studies of the expert system for traffic light management of large star intersections. When the usual approach is employed during peak hours, traffic congestion arises, hence it is suggested to enhance high-level management of intersections and fuzzy control of traffic signals. The membership functions (μR(u,v)) of both input and output fuzzy variables used to control the traffic lights in the intersection are defined, as well as the main fuzzy rules for the operation of each car and pedestrian traffic light in the intersection. In situations of heavy car and pedestrian traffic, a fuzzy logic-based operation model and routing algorithm for pedestrian traffic signals are suggested. Fuzzy set theory is used for modelling, allowing decisions to be made regarding the modification of the waiting time of the pedestrian phase. The advantages of the proposed method are obvious compared to the conventional regulation. © 2023 IEEE.

关键词： Traffic signals

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computer modeling of the Electric Vehicle Traction System Based on a Boost DC/DC-converter 17

Computer Modeling of the Electric Vehicle Traction System Ba...

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17th international Scientific and Technical conference on Dynamics of systems, Mechanisms and Machines, Dynamics 2023

作者： Ivanov, Maksim Khazieva, Regina Ufa State Petroleum Technological University Department of Electrical Engineering and Electrical Facilities of Enterprises Ufa Russia

ISBN: (纸本)9798350358315

The scope of DC / DC converters is quite wide, ranging from automated low-current control systems to powerful power plants. One such application is the use of a DC/DC converter to increase the voltage supplied to an electric vehicle motor inverter. At the moment, electric vehicles are going through a fairly active period of development. The most commonly used motor in electric vehicles is permanent magnet synchronous motors. For example, such electric motors are installed in modern Tesla models. A distinctive feature of permanent magnet synchronous motors is the non-linear dependence of the electromagnetic torque of the motor on the input DC voltage. Therefore, an increase in the input voltage has a positive effect on the maximum electromagnetic torque of the motor. In addition, as the voltage increases, the losses in the motor windings decrease. In this article, a computer simulation of the movement of an electric vehicle in an urban environment is carried out with 3 different ways of powering the electric motor: directly from a 400 V battery, from a battery with an increased voltage of 650 V, and from a DC/DC converter with an output voltage of 650 V. The residual battery charge is compared. computer simulations have shown that increasing the voltage applied to the motor inverter has a positive effect on the energy efficiency of an electric vehicle. © 2023 IEEE.

关键词： Electric vehicles

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Comparison of Machine Learning and Rule-based Approaches for an Optical Fall Detection System 10

Comparison of Machine Learning and Rule-based Approaches for...

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10th IEEE international conference on Computational Intelligence and Virtual Environments for measurement systems and Applications (IEEE CIVEMSA)

作者： Rothmeier, Tobias Kunze, Stefan DEG Inst Appl Informat Deggendorf Inst Technol Freyung Germany

ISBN: (数字)9781665434454

ISBN: (纸本)9781665434454

A major challenge caused by the aging of the modern society is the home care of elderly people. Many elders prefer staying in their own home over moving into a nursing home for as long as possible. For this reason, the project DeinHaus 4.0 Lower Bavaria researches possible technical solutions which can help the elderly to live in their own homes for a longer period of time. The topic of falls is one main part of the research because the number of falls and thereby caused injuries increase with rising age. In this context, this work presents a prototype for an optical fall detection system based on pose estimation, running in real time on an embedded device connected to a USB-camera. In the process of development, different approaches including machine and deep learning, as well as a rule-based algorithm are applied to solve this task. All methods reach an accuracy higher than 94% when used on publicly available data sets, but machine learning seems to have drawbacks when applied in the real-time application due to limitations in the available training data. The rule-based approach, on the other hand, seems to be more capable of generalizing different types of fall events.

关键词： artificial intelligence machine learning computer vision smart cameras pose estimation health and safety

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Optimizing Livestock Productivity with computer Vision-Based Cow Estrus Detection in Free Stall Barns using Various YOLOv8 Models 9

Optimizing Livestock Productivity with Computer Vision-Based...

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9th IEEE international conference on Smart Instrumentation, measurement and Applications, ICSIMA 2023

作者： Gunawan, Teddy Surya Kartiwi, Mira Saifudin, Ali Nur, Levy Olivia Nugroho, Bambang Setia International Islamic University Malaysia Electrical and Computer Engineering Department Kuala Lumpur53100 Malaysia International Islamic University Malaysia Information Systems Department Kuala Lumpur53100 Malaysia Airlangga University Department of Veterinary Sciences Surabaya Indonesia Telkom University School of Electrical Engineering Bandung Indonesia

ISBN: (纸本)9798350343380

In the domain of livestock management, the precise detection of estrus in cows is crucial for reproductive efficiency and enhanced livestock production. Traditional methods, primarily based on human observation, are labor-intensive and can be error-prone. This study leverages YOLOv8, a cutting-edge computer vision technology, for cow estrus detection. Our evaluation reveals that YOLOv8 achieved a remarkable accuracy rate, outperforming conventional methods in speed and reliability. Specifically, the model demonstrated a precision of 96%, a recall of 96.1%, and a mean average precision (mAP) of 98.35% for the 50% intersection over union (IoU) threshold. By integrating YOLOv8, we highlight the potential for substantial improvements in reproductive efficiency, labor cost savings, and increased profitability in the cattle sector. This work emphasizes the transformative impact of advanced technology in agriculture and paves the way for future innovations in livestock management. © 2023 IEEE.

关键词： computer vision

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Reliability modeling of Multistate systems Based on Markov State Transition

Reliability Modeling of Multistate Systems Based on Markov S...

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international conference on Guidance, Navigation and Control, ICGNC 2022

作者： Li, Zeshun Qi, Jia Zhou, Zhen Sun, Yongquan College of Measurement Control Technology and Communications Engineering Harbin University of Science and Technology Harbin150040 China

ISBN: (纸本)9789811966125

Frequency-using systems have become a hot research topic in various countries, and marine frequency-using systems are one of the typical systems. To accurately assess the reliability of the frequency-using system, this paper will take the marine frequency-using system as the research object, the regular area patrol as the mission, and the electromagnetic environment as the research background to carry out the reliability research. Firstly, the multistate system theory was introduced into the frequency-using system in the electromagnetic environment, and the multiple states of frequency-using equipment were effectively classified. Secondly, the state transfer matrix accurately described the influence of the electromagnetic environment on the state transfer process of frequency-using equipment. Then, the frequency-using equipment and system reliability modeling was established based on the state transfer matrix in the electromagnetic environment. Finally, the reliability model is validated using engineering arithmetic examples, and multidimensional analysis and suggestions are made for the results of the system. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Markov processes

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