Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things最新文献_第4页

Analysis and identification of glass components based on regression models and improved K-means++ clustering algorithms 基于回归模型和改进k -means++聚类算法的玻璃组分分析与识别

Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things Pub Date : 2023-05-26 DOI: 10.1145/3603781.3603893

Rifen Lin, Xuanye Tian, Gang Chen, Xuanran Wang

{"title":"Analysis and identification of glass components based on regression models and improved K-means++ clustering algorithms","authors":"Rifen Lin, Xuanye Tian, Gang Chen, Xuanran Wang","doi":"10.1145/3603781.3603893","DOIUrl":"https://doi.org/10.1145/3603781.3603893","url":null,"abstract":"This paper proposes a machine learning-based method for identifying and analyzing ancient glass artifact types, with the aim of improving the efficiency of studying such objects. The method uses partial least squares regression models and an improved K-means++ clustering algorithm. To predict the chemical composition of weathering detection sites before weathering, the paper constructs a partial least squares regression model based on chi-square tests and analyses of variance. An Adaptive-LASSO regression model was then used to analyze the correlation between the chemical composition of different categories of glass artifacts. Additionally, a random forest classification model was established to analyze the classification patterns of high potassium glass and lead-barium glass, and feature screening of the chemical composition was carried out. A stepwise prediction model based on Bayesian parameter optimization of random forest was then used to analyze the chemical composition and identify the type of glass artifacts of unknown categories. To improve the K-means++ algorithm, the paper establishes a K-means++ clustering model based on weighted distance, which classifies the two types of glass separately. The method determines that for high-potassium glass, the fitting goodness-of-fit coefficients R for SiO2 and K2O curves are 0.92 and 0.92. For lead-barium glass, the fitting goodness-of-fit coefficients R for PbO and BaO are 0.91 and 0.82, both at a high level. The model fitting effect is good, and the optimal clustering number for both types of glass is K=3, with a reasonable model classification.","PeriodicalId":391180,"journal":{"name":"Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134357745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Secure Transaction Mechanism of Blockchain Digital Assets Based on Distributed Identity 基于分布式身份的区块链数字资产安全交易机制

Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things Pub Date : 2023-05-26 DOI: 10.1145/3603781.3604219

Naijia Liu, Yuwen Zhang, Haihua Li, Qizheng Sun

{"title":"Secure Transaction Mechanism of Blockchain Digital Assets Based on Distributed Identity","authors":"Naijia Liu, Yuwen Zhang, Haihua Li, Qizheng Sun","doi":"10.1145/3603781.3604219","DOIUrl":"https://doi.org/10.1145/3603781.3604219","url":null,"abstract":"With the development of the new industrial revolution, data has become an important factor of production. Many physical assets and value data will appear in the form of digital original ecology. Traditional digital asset trading schemes have security problems such as difficulty in confirming the ownership of assets, difficulty in tracing the transaction process, and leakage of identity information. Aiming at the problems of digital asset confirmation and identity information leakage, we propose a secure transaction mechanism of blockchain digital assets based on distributed identity. Aiming at the problems of data leakage and anti-counterfeiting traceability in the process of digital asset transaction, we propose a digital fingerprint embedding scheme based on homomorphic encryption. Finally, it is verified in the digital collection transaction scenario, and deployed on the “Spark Chain Digital Native Asset Service Network” to verify the effectiveness of this mechanism. The scheme ensures the secure and credible sharing of digital assets in the transaction process, and provides a technical path for the future transaction of digital assets in the meta universe.","PeriodicalId":391180,"journal":{"name":"Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134505204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SE-UF-PVNet: A Structure Enhanced Pixel-wise Union vector Fields Voting Network for 6DoF Pose Estimation SE-UF-PVNet:用于6DoF姿态估计的结构增强逐像素联合向量场投票网络

Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things Pub Date : 2023-05-26 DOI: 10.1145/3603781.3603859

Yuqing Huang, Kefeng Wu, Fujun Sun, ChaoQuan Cai

{"title":"SE-UF-PVNet: A Structure Enhanced Pixel-wise Union vector Fields Voting Network for 6DoF Pose Estimation","authors":"Yuqing Huang, Kefeng Wu, Fujun Sun, ChaoQuan Cai","doi":"10.1145/3603781.3603859","DOIUrl":"https://doi.org/10.1145/3603781.3603859","url":null,"abstract":"This paper focuses on addressing the problem of 6DoF object pose estimation with a known 3D model from a single RGB image. Some recent works have shown that structure information is effective for 6DoF pose estimation but they do not make full use. We propose SE-UF-PVNet, a more explicit, flexible, and powerful framework to introduce structure information. We construct a keypoint graph in the object coordinate system, introduce a Graph Convolution Network module to extract structure features from the keypoint graph, and concatenate them with features extracted from RGB images by the keypoints regressing network at pixel-wise. To make the estimation more robust, we predict direction vector fields and distance vector fields concurrently, propose a modified pixel-wise voting based keypoint localization algorithm on distance vector fields and further propose an algorithm based on union vector fields. Additionally, we add an Atrous Spatial Pyramid Pooling module to enhance the multi-scale feature sensing capability. Experiment results show that our method achieves 91.88 average ADD (-S) accuracy on Linemod dataset, which is the best among existing pixel-wise voting based methods. Similarly, our method achieves 49.01 average ADD (-S) accuracy on Occlusion Linemod dataset, which is the state-of-the-art among all compared methods without pose refinement.","PeriodicalId":391180,"journal":{"name":"Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things","volume":"72 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114391107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Attention-Based BiLSTM For Malware Family Classification 基于注意力的BiLSTM恶意软件族分类

Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things Pub Date : 2023-05-26 DOI: 10.1145/3603781.3603838

Yonglin Liao, Nurbol Luktarhan, Yue Wang, Qinlin Chen

引用次数: 0

A Point Cloud Optimization Algorithm Based on Spatial Geometry Relationship and Siamese Network 基于空间几何关系和Siamese网络的点云优化算法

Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things Pub Date : 2023-05-26 DOI: 10.1145/3603781.3603872

N. Yang, Yaping Zhang

引用次数: 0

Energy-Saving Small-Cell Wake Up Strategy for Ultra-Dense Networks Based on User Behavior Prediction 基于用户行为预测的超密集网络节能小小区唤醒策略

Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things Pub Date : 2023-05-26 DOI: 10.1145/3603781.3603824

Peng Long, Jin Li, Nan Liu, Zhiwen Pan, Xiaohu You

{"title":"Energy-Saving Small-Cell Wake Up Strategy for Ultra-Dense Networks Based on User Behavior Prediction","authors":"Peng Long, Jin Li, Nan Liu, Zhiwen Pan, Xiaohu You","doi":"10.1145/3603781.3603824","DOIUrl":"https://doi.org/10.1145/3603781.3603824","url":null,"abstract":"Ultra-dense networks (UDNs) is one of the key technologies that can offer large capacities with numerous small base stations (BSs) deployed. However, the BSs consume a lot of energy when they are all turned on. To save energy, small cells with zero or low load should be in sleep mode. In this paper, we propose a small cell wake-up strategy based on the mobile application usage prediction of the users. First, LSTM neural network model is used to predict the users’ application usage in the next interval and the training data is from a real-world anonymous datasets. The small BS will be woken up when it is predicted that one or more users in its coverage area will use high data-rate applications in the next time period. Numerical results show that the LSTM method achieves higher prediction precision and recall compared with the other prediction algorithms. Employing our scheme, we can get about 14% gain in energy consumption compared to the energy efficient system where the small cell is woken up based on the predicted number of users in its coverage area.","PeriodicalId":391180,"journal":{"name":"Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things","volume":"210 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124722977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on Ship Target Recognition based on Infrared Image Method 基于红外图像方法的舰船目标识别研究

Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things Pub Date : 2023-05-26 DOI: 10.1145/3603781.3603814

Yibo Cao, Wei Cheng, Xuming Wang, Yuxin Huang

{"title":"Research on Ship Target Recognition based on Infrared Image Method","authors":"Yibo Cao, Wei Cheng, Xuming Wang, Yuxin Huang","doi":"10.1145/3603781.3603814","DOIUrl":"https://doi.org/10.1145/3603781.3603814","url":null,"abstract":"Infrared thermal imaging technology has been widely applied in the field of target detection at present, which lays the foundation of research on situational awareness for the Maritime Autonomous Surface Ship. Compared with the traditional image recognition technology with defects such as low recognition accuracy, strong light dependence and poor anti-interference ability, infrared thermal imaging technology is not only adaptive to different light intensity environments, but also has the advantages of high concealment, strong detection capability, long detection distance and high detection sensitivity. In this paper, it proposes an improved method of Canny segmentation algorithm based on maximum inter-class variance method on the basis of infrared imaging, where the image is preprocessed by wavelet transform, it is achieved the moving target detection, to restrain noise interference. And then, the edge blurring is effectively processed by using the mask image of Canny edge detection as inputs of pattern recognition. The optimal threshold is determined by the improved Otus algorithm, which can stabilize the optical flow field of the background, to realize effective segmentation of ship images to obtain the high definition moving target. Finally, the availability of the algorithm has been verified by taking the tourist ferry under the Yangtze River as the object. The results showed that the improved algorithm can stabilize the optical flow field of the background, and the application effect is improved, which can provide technical support for the research and application of intelligent ship target perception.","PeriodicalId":391180,"journal":{"name":"Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123292720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dynamic Topology Identification of Wireless Communication Networks Based on Hawkes Process 基于Hawkes过程的无线通信网络动态拓扑识别

Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things Pub Date : 2023-05-26 DOI: 10.1145/3603781.3603903

Liang Chang, Y. Zhang, Qi Zhang

{"title":"Dynamic Topology Identification of Wireless Communication Networks Based on Hawkes Process","authors":"Liang Chang, Y. Zhang, Qi Zhang","doi":"10.1145/3603781.3603903","DOIUrl":"https://doi.org/10.1145/3603781.3603903","url":null,"abstract":"ABSTRACT: In the non-cooperative communication network environment, dynamic topology identification of the wireless communication network is a crucial task, because the non-cooperative and dynamic nature of the network poses challenges to topology identification. Information interaction modeling based on the Hawkes process is an emerging direction for non-cooperative network topology identification. The majority of prior topology identification methods based on the Hawkes process only considered static time-invariant topology identification problems, without considering the dynamic nature of the network topology. To tackle this issue, we propose a dynamic topology identification algorithm based on the dynamic window mechanism that is effective in inferencing dynamic network topology. The main contribution of this paper is to model communication events in dynamic networks as multidimensional Hawkes process models. On this basis, combined with the dynamic window mechanism, the Expectation-Maximum method iteratively optimizes the proxy function to identify the topology of the dynamic network. Finally, the identification accuracy performance of link (98.75% accuracy) and non-link (80.11% accuracy) is verified by experiments.","PeriodicalId":391180,"journal":{"name":"Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things","volume":"172 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126285360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

YOLOv4-based semantic information extraction for indoor scene targets fetching algorithm research 基于yolov4语义信息提取的室内场景目标提取算法研究

Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things Pub Date : 2023-05-26 DOI: 10.1145/3603781.3603864

Jin Wang, Xiaobo Sun, Mingze Wang, Changwu Li, Xiaoman Tang

引用次数: 0

Interpretable Image/Video Compression by Extracting the Least Context Map 通过提取最小上下文映射的可解释图像/视频压缩

Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things Pub Date : 2023-05-26 DOI: 10.1145/3603781.3603841

Huan Huang, Wei Yang

{"title":"Interpretable Image/Video Compression by Extracting the Least Context Map","authors":"Huan Huang, Wei Yang","doi":"10.1145/3603781.3603841","DOIUrl":"https://doi.org/10.1145/3603781.3603841","url":null,"abstract":"Current deep neural networks based image compression methods lack interpretability. Most of them follow a standard encoder-decoder framework and cannot be directly applied to video compression. We present a novel and interpretable finder-generator framework for image/video compression. The finder analyses the input image and selects important points on a one-channel binary map of the original width and height rather than compresses images into a multi-channel bitstream in a downsampled bottleneck layer. The binary one-channel map output by the finder retains the original width and height to keep the spatial information. We name it the least context map (LCM). The generator analyses the LCM to restore the original image based on its trained parameters. We put forward two different selection strategies for guiding the finder to extract the LCM. By extracting LCMs from images, our framework can reduce the size of real-world traffic surveillance videos by 96% compared to most common video codecs and by 85% compared to the next generation video compression codec VP9. This size reduction results from that adjacent frames always share similar LCMs and thus LCMs can be significantly compressed along the time axis. In addition, extensive experiments on Kodak dataset demonstrate our model surpasses the state-of-the-art image compression methods at low bit-rates. We only require an average compressed size of 2.01 kilobytes to achieve a high average MS-SSIM score of 0.9. This size is 50% smaller than JPEG, 43% smaller than FRRNN, and 11% smaller than WebP. Further comparative experiments on image generation demonstrate the LCM is superior to the semantic map and the edge map in higher information capacity and less required storage.","PeriodicalId":391180,"journal":{"name":"Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121224558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0