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共 1120 条记录，以下是431-440 订阅

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Convolutional Neural Network with Attention Mechanism for Image-Based Smoke Detection 4

Convolutional Neural Network with Attention Mechanism for Im...

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4th international conference on Advances in Computer Technology, Information science and Communications, CTISC 2022

作者： Chen, Hanyang Ji, Qingge Sun Yat-sen University Guangdong Key Laboratory of Big Data Analysis and Processing School of Computer Science and Engineering Guangzhou510006 China

ISBN: (数字)9781665458726

ISBN: (纸本)9781665458726

Smoke detection based on computer vision plays a key role in fire prevention. With the development of deep learning, convolutional neural network frameworks are increasingly used in this field. However, due to the large span of smoke's scale and the variety of its color as well as its texture, the features are even more complex. In addition, the sampling of features by the existing neural networks is limited to the size of the convolution kernel. It is difficult to extract the global features. So, detecting smoke from pictures is still a problem. In this work, we proposed a feature-fusion method based on local and global attention mechanisms. It is able to better fuse the low-level and high-level features. In order to solve the scale problem, we proposed a mechanism for selection and offset of the receptive field. In addition, we combine the transformer based on self-attention mechanism and convolution operation to make the model aware of global information. Finally, we optimize the sampling of feature maps by the detection head of the one-stage network based on the smoke color features. Experiments show that the proposed model outperforms state-of-the-art relevant competitors by 4.6% on AP.5:.95. © 2022 IEEE.

关键词： Smoke

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Health data Accessibility Method using Smart Card in IoT 4

Health Data Accessibility Method using Smart Card in IoT

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4th international conference on Inventive Research in computing Applications, ICIRCA 2022

作者： Pooja, S. Tamilvizhi, T. Jayarani, R. Prethy, M. Dr.Rangarajan Dr.Sakunthala Engineering College Department of Information Technology Vel Tech Multi Tech Chennai India Panimalar Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497077

Health and medical information are critical and should be diligently preserved so that an immediate access can be provided whenever it is required. Wireless health care surveillance systems are widely used in hospitals and other healthcare practicesfor witnessing the recent revolution in the medical field. the proposed research idea will assist the disabled patients to manage their health data on their own by eliminating the need to explain their health situation to a physician. As a result, the proposed project's major goal is to create a lucrative medical-care system that uses intelligent health cards to provide voice to the voiceless. People with impairments may be able to advance in their fields with the support of these smart health cards that include patient alert and data management systems. the use of such designed smart cards, which are accessible to the disabled, aids the nation's growth in both the health and technological sectors. Patients' records are well kept in this initiative thanks to ubiquitous health care data processing employing RFID. the RFID labels are carried by people who are sick. In this situation, if the impaired person has an emergency, the alert system will send a message to the care taker, who will receive updates on the impaired person's health. the proposed module also integrates a pulse rate sensor, which may be sought by an Emergency Medical Technician (EMT), who can provide appropriate therapy based on past patient recordings. © 2022 IEEE.

关键词： data handling

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Utilization of Big data Analytics for Risk Management 4

Utilization of Big Data Analytics for Risk Management

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4th international conference on Inventive Research in computing Applications, ICIRCA 2022

作者： Santhikumar, R. Kartillkayani, K. Mishra, Manoj Kumar thota, Sridhar Beschi, I.S. Mishra, B.P. Aditya Institute of Technology and Management India Srm Institute of Science and Technology Computer Science and Engineering India College of Business and Economics Salale University Fitche Ethiopia College of Engineering Design Alliance University Department of Ece Alliance India India Jss Academy of Technical Education India

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497077

Big data (BD) is a form of data, which contains a huge variety and grows exponentially with time. Additionally, risk management also becomes an important part of an organisation so that they can identify their future potential risks and develop new strategies for maximising organisational success. this paper has aimed to analyse different ways of using BD analytics regarding risk management of organisations. In order to achieve research aim, the paper has conducted literature review, where it has discussed different forms of big data and different organisations that use big data regarding risk management. It has only used topic-related existing resources to get a clear insight into this topic. Additionally, it has considered a secondary research method, where it has collected secondary data from currently available journals and articles so that it could understand perspectives of other authors on this topic. Based on collected information, it has conducted a thematic analysis. Findings of this research paper indicated that utilisation of big data could help businesses to identify fraud, financial risk and potential risk factors regarding their business operations. Moreover, several large organisations are significantly utilising BD for their business works and they are using different big data technologies including, AI, and R-programming. Hence, it has been concluded that in this digital era, when there are increased issues of fraud and cyber-threats, Big data helps in identifying risks and opportunities and making fact-based decisions. Additionally, all these technologies are offering extensive positive results to companies in terms of risk management. © 2022 IEEE.

关键词： Risk management

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data organization design of file system based on NAS secure Private Cloud Network 4

Data organization design of file system based on NAS secure ...

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4th international conference on Robotics, Intelligent Control and Artificial Intelligence, RICAI 2022

作者： Yun, Zhichao ShangDong Vocational College of Science and Technology ShanDong Province WeiFang China

ISBN: (纸本)9781450398343

this paper mainly analyzes the data organization design of the file system based on the NAS secure Private Cloud network. With the development of information technology and the improvement of network storage technology, a new storage technology-cloud storage technology has emerged. Based on this, this paper presents an adaptive trust alarm associated IDs for Peer-To-peer cloud storage networks. the core of the system is the Adaptive Trust alarm correlation mechanism. the simulation results show that the average survival rate of nodes in the network is increased by more than 34% with the support of the IDs prototype operation. the proposed IDs system is effective and well suited to the open Peer-To-peer cloud storage network environment we have studied. © 2022 ACM.

关键词： Cloud storage

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Intelligent Network Architecture for Home Automation and Efficient Solution for Appliance Control in Smart Grid 4

Intelligent Network Architecture for Home Automation and Eff...

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4th international conference on Electrical, Computer and Telecommunication Engineering, ICECTE 2022

作者： Al Mamun, Abdullah Jewel, Mehedi Hasan Paul, Parag Kumar Rahin, Saima Ahmed Bangladesh Army International University of Science and Technology Department of Electrical and Electronic Engineering Cumilla Bangladesh United International University Department of Computer Science and Engineering Dhaka Bangladesh United International University Department of Electrical and Electronic Engineering Dhaka Bangladesh

ISBN: (纸本)9798350320541

the field of 'Internet of things' (IoT) technology is exploding because of the quick advancements in automation technologies, embedded systems, and networking. It has become an integral part of Home Automation which is the combination of sensor networks, cloud computing, monitoring, and control. this paper discusses networking and provides two distinct methods for managing network-connected appliances as well as two different strategies for controlling the connected appliances and devices resulting in the enhancement of the system's robustness and overall stability. LoRa and 2.4GHz Wi-Fi technology have been used for the networking architecture of the appliances. Direct load control and phase angle-based voltage control methods are designed and developed for controlling the connected appliances. the distinct wireless technologies increase the stability of data transmission while ensuring minimum power consumption. AC voltage control methodology followed in this research also improves the robustness of the control systems. A mobile application platform is also developed and presented in this paper which is used to monitor and control the appliances, also known as sensor nodes. © 2022 IEEE.

关键词： Internet of things

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Routing network traffic predict based on firewall logs using Machine Learning 4

Routing network traffic predict based on firewall logs using...

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4th international conference on Robotics, Intelligent Control and Artificial Intelligence, RICAI 2022

作者： Li, Yafei Wang, Liejun School of Information Science and Engineering Xinjiang University China

ISBN: (纸本)9781450398343

this paper employs firewall system log data to address the internet traffic issue caused by misconfigured firewall policies. the UCI machine learning library provided the data set. data sets are processed using feature engineering to produce classifiable results. Machine learning techniques are used to predict permissible base traffic for specific network traffic based on log data. the machine learning model should be able to predict actions that should be taken quickly in order to avoid unnecessary network latency, which can be detrimental to network performance. the test time must be short, regardless of the complexity of the training. this article tested several machine learning approaches and discovered that LBGM is the most effective. © 2022 ACM.

关键词： Forecasting

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Skin cancer detection using deep learning 4

Skin cancer detection using deep learning

引用

4th international conference on Cognitive computing and Information Processing, CCIP 2022

作者： Vineeth, J. Hemanth, S. Rao, Chaya V. Pavankumar, N. Javanna, H.S. Janardhan, C.N. Siddanganga Institute of Technology Information Science and Engineering Tumkuru India Siddaganga Institute of Technology Computer Science and Engineering Tumkuru India

ISBN: (纸本)9781665456487

Skin cancer cases around the world have been increasing throughout the last decade. It is a major public health issue around the world. According to the World Health organization (WHo), 3 million cases of skin cancer are reported worldwide each year. the early detection of the disease is very important to increase patient prognostics. over the past ten years, there has been an increase in the usage of computer-Aided diagnosis (CAD) devices for early detection of skin cancer. over the past years, skin cancer detection has been automated with AI concepts and image processing using the infected skin images. Deep learning models have recently shown promise in a variety of medical image processing tasks. An attempt has been made in our work to build a deep learning model using Convolution Neural Network (CNN) for early detection of the skin cancer using the skin images. the model is designed using various predominant features of skin cancer images for prediction. the model implements three different hidden layers with the hybrid combination of activation functions to achieve the accuracy of 95%. the model has the ability to make accurate predictions for unseen data values. the work implemented is expected to be helpful model in the early detection of skin cancer in the field of medicine and healthcare. © 2022 IEEE.

关键词： Computer aided diagnosis

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An Object Detection Algorithm with Multi-scale Context Information Based on YOLOv4 4

An Object Detection Algorithm with Multi-scale Context Infor...

引用

4th international conference on Natural Language Processing, ICNLP 2022

作者： Ma, Sugang An, Wen Yang, Xiaobao Hou, Zhiqiang Xi'an University of Posts and Telecommunications Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi'an China Xi'an University of Posts and Telecommunications School of Computer Science and Technology Xi'an China Xi'an University of Posts and Telecommunications Xi'an Key Laboratory of Big Data and Intelligent Computing Xi'an China

ISBN: (数字)9781665495448

ISBN: (纸本)9781665495448

Most current object detection algorithms have the issue of missing objects due to occlusion. As the great difference of scale between occlusion objects and their integrity is affected, how to reduce the missing rate of occlusion objects has become a challenging problem in object detection algorithms. Aiming at the problem, this paper proposes an object detection algorithm based on multi-scale context information on the basis of the YOLOv4 algorithm framework. Firstly, the object features are extracted through the CSPDarkNet53 feature extraction network. then, the proposed attention-guided multi-scale context information module (AMCM) enhances the ability to perceive object context information and endows features with different influence factors through attention weighting to improve feature discrimination. the experimental results show that the detection accuracy and recall of the proposed algorithm reach 83.2% and 96.4% respectively on PASCAL VOC dataset, and 83.2% and 91% on KITTI dataset, which improves the detection performance of YOLOv4 algorithm. © 2022 IEEE.

关键词： Object detection

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An improved density peaks clustering based on a new local density 4

An improved density peaks clustering based on a new local de...

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4th international conference on Machine Learning, Big data and Business Intelligence, MLBDBI 2022

作者： Lu, Jing Northeastern University School of Computer Science and Engineering Shenyang China

ISBN: (纸本)9798350333947

Density Peaks(DP) clustering algorithm is shown to be a novel and effective clustering approach. It has been widely used in a range of applications. DP requires computing density ρ and distance δ of each point. the clustering result is determined by ρ and δ. the δ of each point is relative to its ρ. the local density ρ is computed by counting the number of points within a cutoff distance d c. Finally, the clustering result of DP depends on the value of d c, i.e., DP is sensitive to the cut-off distance d c. We found that a tiny change in d c always results in different clustering results, which decreases the applicability of DP. this is because simply counting the number of points within the d c range is not able to describe the local density of each point very well. To solve the above problem, in this paper, we proposed DP-NLD, an improved density peaks clustering algorithm based on a new local density measurement method. In DP-NLD, we not only count the number of points within d c, but also take the distribution of neighbors into account when computing the density of each point. Compared with the original DP, DP-NLD has better robustness. Our experimental results show that DP-NLD has better clustering results than DP and other clustering algorithms. © 2022 IEEE.

关键词： Clustering algorithms

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Enhancing data Security in Mobile Cloud using Novel key Generation 4th

Enhancing Data Security in Mobile Cloud using Novel key Gene...

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4th international conference on Innovative data Communication Technologies and Application, ICIDCA 2022

作者： Virushabadoss, S. Anithaashri, T.P. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai602105 India

Cloud computing is being utilized in an assortment of ventures, including money, business, and diversion and the client's information is stored in a remote system given by the cloud supplier. One of the essential issues in the cloud is guaranteeing safe correspondence. the proposed security framework is deals with improving the degree of safety of information traded by cloud clients. this paper utilizes fuzzy investigation to evaluate cloud clients' trust levels, as well as dissemination and renouncement in a cloud and to keep up with data security during access in mobile cloud computing. It guarantees information security in versatile cloud and gets shielded from undesirable access and change. © 2023 the Authors. Published by Elsevier B.V.

关键词： Mobile cloud computing

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