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2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)最新文献

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Deep Neural Network for Melanoma Classification in Dermoscopic Images 皮肤镜图像中黑色素瘤分类的深度神经网络
2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2021-01-15 DOI: 10.1109/ICCECE51280.2021.9342158
W. Jiahao, Jin Xingguang, Wenjie Yuan, Zhenyi Luo, Zhengyang Yu
{"title":"Deep Neural Network for Melanoma Classification in Dermoscopic Images","authors":"W. Jiahao, Jin Xingguang, Wenjie Yuan, Zhenyi Luo, Zhengyang Yu","doi":"10.1109/ICCECE51280.2021.9342158","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342158","url":null,"abstract":"Melanoma classification in dermoscopic images is a very challenging task on account of the low contrast of skin lesions, the various forms of melanomas, the high degree of visual similarity between melanoma and non-melanoma lesions and artifacts of dermoscopic images such as dark lighting. In this paper, we investigate pathological course of outlier lesions developing to be melanoma and try to meet the above challenges by proposing a novel neural network based on Efficient-B5. Compared with existing approaches, our deeper, wider and higher resolution network can capture far more complex and more fine-grained feature representations for melanoma classification. In order to evaluate model performance, we conduct a variety of experiments. The experimental results on a large publicly available dataset ISIC 2020 Challenge Dataset, which is generated by the International Skin Imaging Collaboration and images of it are from several primary medical sources, have demonstrated the significant performance gains of our proposed network compared with prior popular melanoma classifiers, ranking the first in melanoma classification.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116433366","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: 10
Machine Learning Model for Sales Forecasting by Using XGBoost 基于XGBoost的销售预测机器学习模型
2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2021-01-15 DOI: 10.1109/ICCECE51280.2021.9342304
Xie dairu, Zhang Shilong
{"title":"Machine Learning Model for Sales Forecasting by Using XGBoost","authors":"Xie dairu, Zhang Shilong","doi":"10.1109/ICCECE51280.2021.9342304","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342304","url":null,"abstract":"For modern retail corporations operating a huge chain of businesses, exact sales predication is the key in driving corporations development, even success or failure. Sales forecasting allows corporations to efficiently allocate resources including cash flow, production, and make better informed business plan. In this paper, we propose an efficient and accurate sales forecasting model using machine learning. Initially, feature engineering is conducted for extracting features from historical sales data. Furthermore, we used eXtreme Gradient Boosting (XGBoost) to utilize these features for forecasting the future sales amount. The experiment results on a publicly Walmart retail goods dataset provide by Kaggle competition demonstrate our proposed model performs extremely well for sales prediction with less computing time and memory resources.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"464 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131080855","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: 23
Design of basic process of information security risk assessment in cloud computing environment 云计算环境下信息安全风险评估基本流程设计
2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2021-01-15 DOI: 10.1109/ICCECE51280.2021.9342156
Min Huang
{"title":"Design of basic process of information security risk assessment in cloud computing environment","authors":"Min Huang","doi":"10.1109/ICCECE51280.2021.9342156","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342156","url":null,"abstract":"in the risk assessment of cloud computing, how to quantify the risk probability is one of the most important problems. Generally speaking, people can only make use of conjecture, quantitative information and so on. But the risk probability obtained by this way is often different from the actual probability. In this paper, by constructing the attack and defense game model of malicious attacker and defender in cloud computing, the interactive game process of attack and defense is analyzed. Cloud computing system can predict the behavior of attack, get scientific quantitative risk probability, and then realize the risk assessment process of cloud computing system.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130021304","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
Local Communication Data Protection Scheme of Measurement Automation System Based on CAN Bus 基于CAN总线的测量自动化系统本地通信数据保护方案
2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2021-01-15 DOI: 10.1109/ICCECE51280.2021.9342197
Yong Xiao, Weibin Lin, Chao Cui, Yun Zhao, Ziwen Cai
{"title":"Local Communication Data Protection Scheme of Measurement Automation System Based on CAN Bus","authors":"Yong Xiao, Weibin Lin, Chao Cui, Yun Zhao, Ziwen Cai","doi":"10.1109/ICCECE51280.2021.9342197","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342197","url":null,"abstract":"The local communication system of the metering automation system is mainly composed of concentrators, collectors, and smart meters. In addition to power metering, it also has functions such as power consumption information storage, user-side control, and power theft prevention. Attacks on smart meters and data concentrators may cause major power outages and losses. Taking CAN bus as an example, this paper proposes a communication protection scheme based on the national secret SM4-SM3 algorithm joint mechanism, which is applied to the local communication of the metering automation system. The software and hardware design of the scheme is carried out using the ZYNQ-7020 platform, and finally analyze and evaluate the results of experimental to verify the correctness of its function.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116183348","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
Self-supervised hamiltonian mechanics neural networks 自监督哈密顿力学神经网络
2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2021-01-15 DOI: 10.1109/ICCECE51280.2021.9342165
Youqiu Zhan
{"title":"Self-supervised hamiltonian mechanics neural networks","authors":"Youqiu Zhan","doi":"10.1109/ICCECE51280.2021.9342165","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342165","url":null,"abstract":"We developed a method to derive the hamiltonian of an unknown system by machine learning the motions of the system. We modified the training process of Greydanus et al.’s hamiltonian neural network to make it be capable of learning from a dataset without the change-of-state ground truth. In other word, the learning process is self-supervised. This improvement can extend the application of the hamiltonian neural network because it is sometimes difficult to accurately measure the change of state of the system. Our model can now be able to learn the free particle system and the harmonic oscillator system.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125827279","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
A LoRa-based Low-power Smart Water Metering System 基于lora的低功耗智能水表系统
2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2021-01-15 DOI: 10.1109/ICCECE51280.2021.9342327
Yulu Ye, Yuhui Yang, Lei Zhu, Jerry Wang, D. Rao
{"title":"A LoRa-based Low-power Smart Water Metering System","authors":"Yulu Ye, Yuhui Yang, Lei Zhu, Jerry Wang, D. Rao","doi":"10.1109/ICCECE51280.2021.9342327","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342327","url":null,"abstract":"Smart cities need smart water metering. However, mechanical water meters cannot automatically read remote water consumption. While replacing all existing meters with fully electronic water meters is challenging. Therefore, in this paper, we proposed SWATS, a LoRa-based low-power Smart WAter meTering System. SWATS first reads mechanical water meters through an digitizer reader, and then facilitates a low-power detection algorithm on STM32 for computation. Moreover, an optional intelligent error correcting component of SWATS can lead to better accuracy. At last, with LoRa, collected data are transmitted back to server in semi-real time. Experiments on different water quality, water pressure and temperature showed the feasibility of SWATS.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"52 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126056766","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: 3
ResNet-Based Model for Autonomous Vehicles Trajectory Prediction 基于resnet的自动驾驶汽车轨迹预测模型
2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2021-01-15 DOI: 10.1109/ICCECE51280.2021.9342418
Zhuo Zhang
{"title":"ResNet-Based Model for Autonomous Vehicles Trajectory Prediction","authors":"Zhuo Zhang","doi":"10.1109/ICCECE51280.2021.9342418","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342418","url":null,"abstract":"Autonomous vehicles (AVs) are expected to dramatically redefine the future of traffic. However, there are still plenty of challenges need to be figured out before L5 self-driving era coming. One of them is to precisely predict the moving trajectory of traffic agents which near the AV, such as cars, pedestrians, and motorcycles. In this paper, we use ResNet to forecast AVs’ trajectories, which is able to capture the features of different dimensions to achieve better predictions. By feeding the raw input picture, the model output s three trajectories and their confidence levels respectively, which means each trajectory has its own confidence level. Experimental results show that our method performs better than other deep learning methods. The loss function value of ResNet-34 model is lower than that of VGG-16 model and VGG-19 model.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123603464","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: 12
Research on Users' Trust of Chatbots Driven by AI: An Empirical Analysis Based on System Factors and User Characteristics 基于AI驱动的聊天机器人用户信任研究——基于系统因素和用户特征的实证分析
2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2021-01-15 DOI: 10.1109/ICCECE51280.2021.9342098
Fan Min, Zou Fang, Yucan He, Jiang Xuan
{"title":"Research on Users' Trust of Chatbots Driven by AI: An Empirical Analysis Based on System Factors and User Characteristics","authors":"Fan Min, Zou Fang, Yucan He, Jiang Xuan","doi":"10.1109/ICCECE51280.2021.9342098","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342098","url":null,"abstract":"AI chatbots have been widely used in e-commerce, which can improve service efficiency and reduce labor cost markedly. However, consumers' evaluation of intelligent customer service is mixed. This paper explores the impact of system factors and user characteristics on service perception and users' trust. Based on the social presence theory, this study constructs the trust research model of AI chatbots. The main results show that perceived personalization, perceived media richness and past usage experience positively influence social presence, cognitive reactance has a negative impact on social presence, social presence has a positive impact on users' trust. By investigating the features influencing trust, this study provides relevant technical improvement and marketing suggestions for managers.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126000308","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
Large Scale Firmware Analysis For Open Source Components, Hard Coding and Weak Passwords 开源组件、硬编码和弱密码的大规模固件分析
2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2021-01-15 DOI: 10.1109/ICCECE51280.2021.9342303
Shen Quanjiang, Song Yan, Yu Xiaohu, Liu Tinghui, He Daojing, Y. Guisong
{"title":"Large Scale Firmware Analysis For Open Source Components, Hard Coding and Weak Passwords","authors":"Shen Quanjiang, Song Yan, Yu Xiaohu, Liu Tinghui, He Daojing, Y. Guisong","doi":"10.1109/ICCECE51280.2021.9342303","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342303","url":null,"abstract":"In recent years, Internet of things security incidents occur frequently, which has threatened the stability of the country, society and personal privacy. As the core of Internet of things equipment system, the security of firmware is very important. In order to design a more reasonable and effective firmware security detection method, the firmware needs to be analyzed in detail. This paper describes the security objectives of firmware from three aspects of confidentiality, integrity and availability, summarizes and analyzes the firmware attack surface, and carries out relevant verification experiments for each attack surface. In order to solve the tedious steps of firmware format identification, unpacking and key information extraction in the process of large-scale firmware security analysis, a firmware security analysis tool is designed and implemented, and large-scale experimental analysis of firmware is carried out from the perspectives of open-source components, weak passwords and hard coding.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130208255","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
Study of hydraulic pressure sensing characteristics based on micro-cavity structure 基于微腔结构的液压传感特性研究
2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2021-01-15 DOI: 10.1109/ICCECE51280.2021.9342512
Wei Fengjuan, Lin Lijun, Zhang Bangtong
{"title":"Study of hydraulic pressure sensing characteristics based on micro-cavity structure","authors":"Wei Fengjuan, Lin Lijun, Zhang Bangtong","doi":"10.1109/ICCECE51280.2021.9342512","DOIUrl":"https://doi.org/10.1109/ICCECE51280.2021.9342512","url":null,"abstract":"The microcavity structure is formed by adding an air cavity at the fusion splice point of single-mode, thin-core fiber and single-mode (STS). This paper takes the microcavity optical fiber sensing structure as the research object, and first analyzes the microcavity optical fiber sensing structure and the principle of temperature sensing, and combined with experiments to study the pressure sensing characteristics of the microcavity sensing structure, the results show that: as the microcavity increases, the range of measurable hydraulic pressure increases, and the sensitivity increases. The best structure is selected for hydraulic pressure sensing detection.","PeriodicalId":229425,"journal":{"name":"2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127763712","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
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