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检索条件"任意字段=International Conference on Data and Knowledge Systems for Manufacturing and Engineering"

共 37040 条记录，以下是4701-4710 订阅

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An Important Sampling over Graph Convolutional Network for Community Detection 8

An Important Sampling over Graph Convolutional Network for C...

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8th international conference on Advanced Computing and Communication systems, ICACCS 2022

作者： Meena, Pawan Pawar, Mahesh Pandey, Anjana University Institute of Technology Rgpv Department of Computer Science & Engineering MP Bhopal India University Institute of Technology Rgpv Department of Information Technology MP Bhopal India

ISBN: (纸本)9781665408165

According to graph theory, the complex network is transformed into graph structure data to process the convolutional neural network efficiently and conveniently. The convolution kernel is defined by extending the convolution operation on the image to the graph structure data, and the convolution layer is used for the graph. Coarse-graining and pooling operations extract features of complex networks with irregular data. When training the network with stochastic gradient descent, an important sampling method is designed to change the distribution of samples to reduce variance, thereby saving gradient calculation time. Experimental results show that this method can obtain better community discovery accuracy with lower computational complexity in social networks, citation networks, and knowledge graph datasets, reducing computational time compared with the existing graph convolutional network. In addition, the memory footprint can be extended to use in large-scale complex networks. © 2022 IEEE.

关键词： Stochastic systems

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Utilizing Transfer Learning Models to Classify Absence Defects on Aluminum Plates Using Feature-Based Approaches 2nd

Utilizing Transfer Learning Models to Classify Absence Defec...

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2nd international conference on Intelligent manufacturing and Robotics, ICIMR 2024

作者： Pandian, Kiran Zhen, Lim Weng Majeed, Anwar P. P. Abdul Teh, Sze-Hong Goon, Koon Yin Razman, Mohd Azraai Mohd Faculty of Manufacturing and Mechatronics Engineering Technology University Malaysia Pahang Al-Sultan Abdullah Pahang26600 Malaysia Department of Computing and Information Systems Sunway University Bandar Sunway Selangor Darul Ehsan47500 Malaysia Xi’an Jiaotong-Liverpool University Suzhou215123 China TT Vision Technologies Sdn. Bhd. Plot 106 Hilir Sungai Keluang 5 Bayan Lepas Phase 4 Penang11900 Malaysia

ISBN: (纸本)9789819639489

Screw – the small but important elements used in various industry. Its presence plays a significant role as it securely holds the product in place, preventing loosening or collision with the case. Such occurrences could lead to the displacement of small components or compartments, resulting in product failure. The advent of Industry 4.0 has contributed to reducing labor costs and human errors. This research aims to develop a robust classification model for machine vision detection, specifically for identifying the absence or presence of a screw. The model can be integrated into relevant robotics applications. To collect the customized dataset, a 6-degree-of-freedom (DOF) robot. The collected dataset was then categorized into two groups: absent and present. For the training process, a pretrained dataset called ImageNet was employed to facilitate the training process. Transfer learning techniques were used to extract the features required for different machine learning models. Each machine learning model underwent hyperparameter tuning to achieve the highest classification accuracy. The data was divided into training, validation, and testing sets using a sampling ratio of 60:20:20, respectively, before being fed into the various machine learning models. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Screws

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Intelligent Information System for Detection of COVID-19 Based on AI 3rd

Intelligent Information System for Detection of COVID-19 Bas...

引用

3rd international conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications, ICMISC 2022

作者： Raut, Roshani Jadhav, Anuja Jaiswal, Swati Kathole, Atul Patil, Sonali Department of Information Technology Pimpri Chinchwad College of Engineering Savitribai Phule Pune University Pune India

ISBN: (纸本)9789811960871

The pandemic is changing the clinical needs and potential for AI-driven computer-assisted diagnoses (CDS). Since the beginning, rapid identification of COVID-19 patients has been a significant difficulty, especially in areas with limited diagnostic testing capacity. Intelligent Information System (IIS) represents the knowledge progression of available data. It has been directed by recent technological integration, data processing, and distribution in multiple computational environments. Intelligent Information systems are aimed to work like an advanced human brain, where, as per the requirement of changing circumstances, the optimal decision can be evolved. IIS tools are expected to be adaptive, which may vary according to their processing data. As a result, the goal of this study was to provide a complete analysis of various technologies for combating COVID-19, with a focus on their features, problems, and domiciliation nation. Our findings demonstrate the performance of developing technologies. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： COVID-19

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Reasonable Setting Values for Anonymization Algorithms for Online Educational data Analysis Support System 26

Reasonable Setting Values for Anonymization Algorithms for O...

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26th international conference on knowledge-Based and Intelligent Information and engineering systems, KES 2022

作者： Takaki, Osamu Hamamoto, Nobukuni Takefusa, Atsuko Yokoyama, Shigetoshi Aida, Kento Gunma University 4-2 Aramaki-machi Maebashi371-8510 Japan National Institute of Informatics 2-1-2 Hitotsubashi Tokyo101-8430 Japan

We propose a criterion of reasonable parameters for an algorithm that aggregates target data with anonymized data for safe data analysis in online educational systems, called learning management systems (LMSs). We also statistically investigate parameters that can satisfy the proposed criteria using an anonymization algorithm and real large-scale data. We use an open dataset containing one year's worth of product review data due to the difficulty of collecting LMS data large enough for the evaluation. Furthermore, we discuss an approach to address cases where no parameter satisfies the proposed criteria. © 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the 26th international conference on knowledge-Based and Intelligent Information & engineering systems (KES 2022)

关键词： Parameter estimation

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An Analysis of Situational Intelligence for First Responders in Military

An Analysis of Situational Intelligence for First Responders...

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2023 international conference on Artificial Intelligence and Applications, ICAIA 2023 and Alliance Technology conference, ATCON-1 2023

作者： Vallikannu, R. Kanpur Rani, V. Kavitha, Bc Sankar, P. Hindustan Institute of Technology and Science Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9781665456272

Situational awareness is the sense and knowledge of one's immediate surroundings. In safety-critical sectors, maintaining situational awareness is essential for performance and error prevention. Situational awareness (SAW) is crucial for the success of activities in many different domains, such as surveillance, humanitarian aid, and search and rescue efforts. SAW is however susceptible to enemy attacks. By giving users enhanced coverage, it increases survivability and mission capability. Recently, Smart gadgets used data to address crisis scenarios and provide real-time tracking to protect law enforcement personnel out in the field. Despite these developments, it might be challenging for first responders to get a precise feel of their surroundings due to an abundance of field data. Security teams need to be able to quickly transform this data into actionable intelligence using a few instruments at their disposal, including body cameras, fingerprint scanners, and facial recognition software. Officers can cut through the noise to acquire actual real-time situational awareness by integrating heterogeneous information into a cohesive platform. Therefore, the proposed work examines potential mitigation measures while considering hostile threats and assaults against SAW systems. Additionally, information and alarms can be instantly sent between operators and field officers using vital interface features. The optimization of the AutoML system is proposed for fusion of sensor data. AutoML classification with Bayesian and ASHA (Asynchronous successive halving algorithm) is used for situational forecasting and decision-making awareness, IoT is used to monitor data gathered from Kaggle and sensor readings, while thingspeak cloud is used to monitor sensor output. © 2023 IEEE.

关键词： Decision making

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Precision 3D Motion Capture Using Pose Estimation Techniques: Application in Sports Video Analysis 20th

Precision 3D Motion Capture Using Pose Estimation Techniques...

引用

20th Principle and Practice of data and knowledge Acquisition Workshop, PKAW 2024, held in conjunction with the 21st Pacific Rim international conference on Artificial Intelligence, PRICAI 2024

作者： Kitano, Shuzo Ebihara, Akimasa Sawada, Tomohide Martono, Niken Prasasti Ohwada, Hayato Department of Industrial and Systems Engineering Tokyo University of Science Noda Japan

ISBN: (纸本)9789819600250

This paper suggests a new technique for 3D reconstruction that makes use of two cameras. The setup environment was limited by the need for many cameras in conventional 3D reconstruction techniques. Alternatively, decreased accuracy and problems with invisible areas resulted from utilizing fewer cameras. We apply domain knowledge of the human skeleton structure to our technique, using BlazePose as matching points for skeletal keypoint recognition. The suggested technique comprises of triangulation to reconstruct 3D coordinates and applying RANSAC for extrinsic parameter estimation. Despite severe parallax, this method produces 3D reconstruction with good accuracy. We employed motion capture data from athletes’ agility measurement moves for evaluation. In the studies, two cameras were recording at 960 Hz and ten cameras were recording at 250 Hz while the subjects wore markers. The average distance error of the evaluation, which was 42 mm on average, indicated accuracy appropriate for sports video analysis. Furthermore, examining the effect of frame rates revealed no appreciable variations in accuracy between 120 Hz and 960 Hz. This suggests that common electronics could be used for high-accuracy 3D reconstruction. With fewer cameras, this research achieves high-precision 3D reconstruction, indicating possible uses in sports science. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Motion capture

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data Encryption in Fog Computing using Granular Access Control Method 4

Data Encryption in Fog Computing using Granular Access Contr...

引用

4th international conference on Distributed Sensing and Intelligent systems, ICDSIS 2023

作者： Taher, Fatma AlHamadi, Hussam AlShamsi, Alyazia Bugawa, Afaf College of Technological Innovation Zayed University United Arab Emirates College of Engineering and IT University of Dubai United Arab Emirates College of Engineering and IT American University of Sharjah United Arab Emirates Information and communication Technology Arabian Gulf University Bahrain

ISBN: (纸本)9781839539954

It is possible to protect the privacy of data stored in the cloud and to have more control over who has access to what by using attribute-based encryption. In attribute-based encryption, the key is derived from the data itself, which explains why this is the case. When visible qualities are included in encrypted communication to help users identify important data on vast networks, attribute security has been violated. These obvious qualities are presented to aid users in recognizing important information. This work proposes anonymous key-policy attribute-based encryption, which enables fine-grained data retrieval while maintaining attribute privacy. The goal of this plugin is to provide effective attribute-based access control along with an authorized search approach. By using the secret key that the owners of the data have provided to the users, they can build the trapdoor using the EACAS data. After that, they can carry out searches based on the access constraints to obtain the required information. The design of trapdoors and the deployment of cryptographic protocols both make advantage of a synthetic characteristic that has no syntactic meaning in order to offer attribute-based searching on exported encoded data. This is done to make the information accessible. Upon knowledge which has been outsourced, granular access control can be applied in a variety of ways. Establishing the search criteria that data consumers will use to find relevant details based on protected attributes is one strategy that data owners can utilize. This makes it easier for data consumers to find content that is pertinent to their requirements. This paper demonstrate that compared to the most advanced methods now available, EACAS uses significantly less time and storage space for data processing and storage. © The Institution of engineering & Technology 2023.

关键词： anonymous key-policy attribute-based encryption cloud storage data sharing Granular access control key-policy attribute-based encryption

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A Comprehensive Study on Satellite-based data Communication for Big Earth Observation systems

A Comprehensive Study on Satellite-based Data Communication ...

引用

knowledge engineering and Communication systems (ICKECS), international conference on

作者： N Supritha M S Narasimha Murthy BMSIT&M Viswesvaraya Technological University Bangalore Karnataka India

ISBN: (数字)9798350359688

ISBN: (纸本)9798350359695

For global telecommunications systems to operate effectively, it is crucial that the communication among different satellites be monitored closely. Nearly 2,000 artificial satellites keep orbiting the Earth and they all continuously transmit both analog and digital signals that carry different types of voice, video, and other data to and from one or many locations worldwide. In areas where broadcasting is crucial and where the terrain is challenging along with very few people, satellite communications are renowned to offer the greatest service. In Big Earth Observation systems, disaster management and weather forecasting sectors, quick deployment is crucial. In the global network infrastructure, satellites are regarded as a crucial component of the communications infrastructure. Considering factors like explicit load balancing, interplanetary internet, quality of service, mobility management and packet reordering difficulties, this article reviews and evaluates suggested methods for satellite- based data transmission.

关键词： Technological innovation Satellites Protocols Reviews Satellite broadcasting Earth Observing System Weather forecasting

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Ensemble Model Based on an Improved Convolutional Neural Network with a Domain-agnostic data Augmentation Technique 13

Ensemble Model Based on an Improved Convolutional Neural Net...

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13th international conference on Information and knowledge Technology, IKT 2022

作者： Fatahnaie, Faraz Asghari, Seyyed Amir Azhdehnia, Armin Marvasti, Mohammadreza Binesh Kharazmi University Electrical and Computer Engineering Department Tehran Iran Guilan University Electrical and Computer Engineering Department Rasht Iran

ISBN: (纸本)9798350320626

With the increase of online activities and the growing number of online services, various cyber threats pose a significant challenge to Network Intrusion Detection systems (NIDS). To face these threats, available imbalance sources made researchers develop resampling techniques to have a balance training process. In this paper, a domain-agnostic data augmentation approach followed by random under sampling is used to achieve credible generalized and robust IDS. Moreover, the framework benefits from the potentiality of deep learning models to extract more meaningful features. The final model of the paper was obtained after the ensemble of three improved convolutional neural networks. Each model is trained on a specific subset of the NSL-KDD dataset which is generated by the resampling method. The simulation results illustrate that the model achieves an accuracy of 83.3% which is 6.5% higher, when the original dataset is used. The codes are available at https://***/armin-azh/ensemble. © 2022 IEEE.

关键词： Online systems

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Perception of Age and Gender Detection by using Hierarchical Deep Learning Architecture through Vision

Perception of Age and Gender Detection by using Hierarchical...

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2022 international conference on Sustainable Computing and data Communication systems, ICSCDS 2022

作者： Praveena, M. Srinija, K. Geetha Meghana, A. Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering AP Guntur India

ISBN: (纸本)9781665478847

When it comes to software systems that analyze face photos, gender detection is a crucial feature. This research provides a quantum machine learning-based approach for automated gender categorization from face photos utilizing a hybrid classical-quantum neural network, which is based on quantum machine learning. Using the knowledge of a pre-trained off-the-shelf Deep Neural Network (DNN)in conjunction with the transfer learning of a quantum variational circuit, an accurate binary classifier has been produced in this paper. An example of a hybrid network is the binary classifier, which is composed of a convolutional base of the Deep Neural Network (DNN) that has been compressed with a dressed quantum circuit and a dressed quantum circuit. In the classification of a publicly accessible collection of face photographs, better results than that have been previously reported have been obtained. © 2022 IEEE.

关键词： Deep neural networks

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