Proceedings of the 5th International Conference on Computer Science and Application Engineering最新文献_第4页

A Method of Federated Learning Based on Blockchain 一种基于区块链的联邦学习方法

Proceedings of the 5th International Conference on Computer Science and Application Engineering Pub Date : 2021-10-19 DOI: 10.1145/3487075.3487143

Shi Xu, Sihan Liu, Guangyu He

{"title":"A Method of Federated Learning Based on Blockchain","authors":"Shi Xu, Sihan Liu, Guangyu He","doi":"10.1145/3487075.3487143","DOIUrl":"https://doi.org/10.1145/3487075.3487143","url":null,"abstract":"Currently many enterprises face issues regarding insufficient data collection samples and data recording dimensions, thus it's hard to make efficient predictions. Since it is limited by the requirement of protecting privacy and trade secrets, data can't be effectively shared among enterprises. Federated learning is an effective method to solve this problem, but there are some performance bottlenecks, information security issues and data trust issues still existed, which need to be improved in combination with other advanced technologies to meet the practical requirements. This paper combines the blockchain technology with federated learning technology, and uses decentralized blockchain system to replace the traditional centralized federated learning architecture. We adopt training method of updating models to achieve machine learning. In this way, we can avoid transmission of intermediate computing data and achieve mechanism of node access, model evaluation, motivation and audit with combination of block chain. In terms of the algorithm, the horizontal federated learning adopts the integrated learning algorithm, and the vertical federated learning adopts the deep learning algorithm. It will be described in detail below.","PeriodicalId":354966,"journal":{"name":"Proceedings of the 5th International Conference on Computer Science and Application Engineering","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127302314","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: 1

The Novel Risk Analysis of Emergency Food Supply under Post-earthquake Conditions 地震后应急食品供应风险分析

Proceedings of the 5th International Conference on Computer Science and Application Engineering Pub Date : 2021-10-19 DOI: 10.1145/3487075.3487095

Xu Sun, Y. Liu, Hong Zhang

引用次数: 0

The Control System Design for 600kV High Voltage Platform of HIAF Electron Cooler HIAF电子冷却器600kV高压平台控制系统设计

Proceedings of the 5th International Conference on Computer Science and Application Engineering Pub Date : 2021-10-19 DOI: 10.1145/3487075.3487085

Yunbin Zhou, L. Mao, Wei Zhang, K. Yan, Xiaoming Ma, Mingrui Li

{"title":"The Control System Design for 600kV High Voltage Platform of HIAF Electron Cooler","authors":"Yunbin Zhou, L. Mao, Wei Zhang, K. Yan, Xiaoming Ma, Mingrui Li","doi":"10.1145/3487075.3487085","DOIUrl":"https://doi.org/10.1145/3487075.3487085","url":null,"abstract":"HIAF is the next generation heavy ion accelerator in China, it contains lots of sub facilities. The electron cooler is one of the most significant facilities in HIAF of Spectrometer Ring (SRing). With the electron cooler, SRing could generate high quality and high intensity ion beam for the experiments. The electron cooler in HIAF was designed to produce 600KeV electron beam. To achieve this design target, high voltage needs to reach 600kV maximum and ripple wave less than 1*10-4. A new control system was designed for the high voltage platform which uses cascaded transformer construction. The system makes use of XGS-PON network as the main means of communication. Zynq 7015 as the CPU of the embedded controller. The controller integrated 2 DAC ports with 100KS/S and 4 ADC ports with 200KS/S for high voltage modules setting and high voltage divider monitor, 8 low-speed ADC ports for auxiliary power supplies, and the environment sensors. The embedded Ubuntu Linux and the EPICS frameworks were programmed in the controller, all of the control parameters were sent through channel access protocol. No need for host computer to participate in control logic, only used for display. The hardware mentioned above interacts with the operating system through the FPGA part of Zynq. The FPGA is programed as a coprocessor for communicating, data processing and interlock control. Corresponding drivers are integrated in the Linux system at the same time.","PeriodicalId":354966,"journal":{"name":"Proceedings of the 5th International Conference on Computer Science and Application Engineering","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125560610","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: 1

Research on Multiscale Information Storage of MEG of Depression Based on ARFI Model 基于ARFI模型的抑郁症脑电信号多尺度信息存储研究

Proceedings of the 5th International Conference on Computer Science and Application Engineering Pub Date : 2021-10-19 DOI: 10.1145/3487075.3487118

Dayou Luo, Wei Yan, Jin Li, F. Hou, Jun Wang

{"title":"Research on Multiscale Information Storage of MEG of Depression Based on ARFI Model","authors":"Dayou Luo, Wei Yan, Jin Li, F. Hou, Jun Wang","doi":"10.1145/3487075.3487118","DOIUrl":"https://doi.org/10.1145/3487075.3487118","url":null,"abstract":"As a noninvasive brain function detection technique, Magnetoencephalography (MEG) has been widely used in the research of depression. By analyzing the amount of information storage, the difference of MEG information storage between patients with depression and healthy people was studied. Our analysis was carried out in the popular multiscale entropy framework, in which the time series were first \"coarse-grained\" on the selected time scale by low-pass filtering and down-sampling, and then its complexity was evaluated ac-cording to conditional entropy. Within this framework, we used the linear fractional integral autoregressive (ARFI) model to derive the analytical expression of information storage calculated at multiple time scales. We used the information storage expression derived from the ARFI model and then collected the information storage of MEG through positive, negative and neutral stimuli and finally calculate it. The experimental results showed that it was best to distinguish between patients with depression and healthy people through the information storage of MEG through positive stimuli, and it was best to distinguish healthy people from patients with depression at a higher frequency if it was negative or neutral stimuli.","PeriodicalId":354966,"journal":{"name":"Proceedings of the 5th International Conference on Computer Science and Application Engineering","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116626169","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

Automatic Surgery Duration Prediction Using Artificial Neural Networks 基于人工神经网络的手术时间自动预测

Proceedings of the 5th International Conference on Computer Science and Application Engineering Pub Date : 2021-10-19 DOI: 10.1145/3487075.3487128

Xiaomin Chen, Li Huang, Wenzhi Liu, Po-Chou Shih, Jiaxin Bao

引用次数: 3

Infrared Air Combat Simulation Model for Deep Reinforcement Learning 基于深度强化学习的红外空战仿真模型

Proceedings of the 5th International Conference on Computer Science and Application Engineering Pub Date : 2021-10-19 DOI: 10.1145/3487075.3487094

Cong Huang, Chaozhe Wang, Qiqi Tong

引用次数: 1

Online Adversarial Knowledge Distillation for Image Synthesis of Bridge Defect 基于在线对抗知识精馏的桥梁缺陷图像合成

Proceedings of the 5th International Conference on Computer Science and Application Engineering Pub Date : 2021-10-19 DOI: 10.1145/3487075.3487171

Jiongyu Guo, Can Wang, Yan Feng

{"title":"Online Adversarial Knowledge Distillation for Image Synthesis of Bridge Defect","authors":"Jiongyu Guo, Can Wang, Yan Feng","doi":"10.1145/3487075.3487171","DOIUrl":"https://doi.org/10.1145/3487075.3487171","url":null,"abstract":"Bridge defect detection is an essential task of its daily maintenance, which aims to protect people's life and property safety. However, for a variety of reasons, research institutions have been faced with the scarcity of anomaly samples. One solution is using generative adversarial network (GAN) to generate extra samples for data augmentation. In this paper, we draw on the idea from online knowledge distillation to improve the self-attention GAN, and propose a new framework called Online Knowledge Distillation -Self Attention Generative Adversarial Network (OKD-SAGAN). We introduce a new module called connector which has the same structure with discriminator to train multiple groups of SAGAN together. The role of the connector is to control the output distribution of the corresponding generator to be consistent with the surrounding generators in order to achieve the purpose of mutual learning. We have conducted experiments on the CODEBRIM dataset and in order to further illustrate the effectiveness of OKD structure, we also applied OKD on ACGAN for experiments. The results show that the performance of some generators has exceeded a single set of SAGAN and ACGAN. Compared with SAGAN, OKD-SAGAN ’s FID score decreases by 15.4% and the average FID score decreases by 5.5%. As for ACGAN, OKD-ACGAN ’s FID score decreases by 7.6% and the average FID score decreases by 3.8%, which proves the validity of OKD structure.","PeriodicalId":354966,"journal":{"name":"Proceedings of the 5th International Conference on Computer Science and Application Engineering","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114314301","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: 1

Super Visual Semantic Embedding for Cross-Modal Image-Text Retrieval 跨模态图像-文本检索的超视觉语义嵌入

Proceedings of the 5th International Conference on Computer Science and Application Engineering Pub Date : 2021-10-19 DOI: 10.1145/3487075.3487167

Zhixian Zeng, Jianjun Cao, Guoquan Jiang, Nianfeng Weng, Yuxin Xu, Zibo Nie

{"title":"Super Visual Semantic Embedding for Cross-Modal Image-Text Retrieval","authors":"Zhixian Zeng, Jianjun Cao, Guoquan Jiang, Nianfeng Weng, Yuxin Xu, Zibo Nie","doi":"10.1145/3487075.3487167","DOIUrl":"https://doi.org/10.1145/3487075.3487167","url":null,"abstract":"Visual semantic embedding network or cross-modal cross-attention network are usually adopted for image-text retrieval. Existing works have confirmed that both visual semantic embedding network and cross-modal cross-attention network can achieve similar performance, but the former has lower computational complexity so that its retrieval speed is faster and its engineering application value is higher than the latter. In this paper, we propose a Super Visual Semantic Embedding Network (SVSEN) for cross-modal image-text retrieval, which contains two independent branch substructures including the image embedding network and the text embedding network. In the design of the image embedding network, firstly, a feature extraction network is employed to extract the fine-grained features of the image. Then, we design a graph attention mechanism module with residual link for image semantic enhancement. Finally, the Softmax pooling strategy is used to map the image fine-grained features to a common embedding space. In the design of the text embedding network, we use the pre-trained BERT-base-uncased to extract context-related word vectors, which will be fine-tuned in training. Finally, the fine-grained word vectors are mapped to a common embedding space by a maximum pooling. In the common embedding space, a soft label-based triplet loss function is adopted for cross-modal semantic alignment learning. Through experimental verification on two widely used datasets, namely MS-COCO and Flickr-30K, our proposed SVSEN achieves the best performance. For instance, on Flickr-30K, our SVSEN outperforms image retrieval by 3.91% relatively and text retrieval by 1.96% relatively (R@1).","PeriodicalId":354966,"journal":{"name":"Proceedings of the 5th International Conference on Computer Science and Application Engineering","volume":"50 17","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132974051","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: 1

An Improved Hyperspectral Image Anomaly Detection Algorithm using Low-Rank Representation 一种改进的低秩表示高光谱图像异常检测算法

Proceedings of the 5th International Conference on Computer Science and Application Engineering Pub Date : 2021-10-19 DOI: 10.1145/3487075.3487170

Dongying Bai, Dongli Tang, Hailin Tian, Zhaozhan Li

引用次数: 0

Investigation of Octane Number Loss Based on Particle Swarm Optimization 基于粒子群优化的辛烷值损失研究

Proceedings of the 5th International Conference on Computer Science and Application Engineering Pub Date : 2021-10-19 DOI: 10.1145/3487075.3487086

Huawen Yang, Zihao Wang, Liang Chen

引用次数: 0