2019 IEEE 10th International Conference on Awareness Science and Technology (iCAST)最新文献_第3页

A Re-Identification Strategy Using Machine Learning that Exploits Better Side Data 利用更好的侧数据的机器学习的重新识别策略

2019 IEEE 10th International Conference on Awareness Science and Technology (iCAST) Pub Date : 2019-10-01 DOI: 10.1109/ICAwST.2019.8923378

Eina Hashimoto, Masatsugu Ichino, H. Yoshiura

{"title":"A Re-Identification Strategy Using Machine Learning that Exploits Better Side Data","authors":"Eina Hashimoto, Masatsugu Ichino, H. Yoshiura","doi":"10.1109/ICAwST.2019.8923378","DOIUrl":"https://doi.org/10.1109/ICAwST.2019.8923378","url":null,"abstract":"Data on people’s daily activities are being collected as big data and then mined for corporate and public purposes. However, concern about privacy is the major obstacle to using such data. Although data anonymisation can mitigate the privacy risk, researchers have shown that people can often be re-identified by linking the anonymised data with other data (i.e. side data). Though re-identification has been improved by the use of machine learning, two problems remain: the unavailability of data and the inappropriateness of the side data. We have developed a re-identification strategy using machine learning in which anonymised data are linked to a different type of side data that are easy to obtain and for which the represented person is easy to identify. We tested our strategy on the re-identification of the owners of 78 anonymous Twitter accounts by using information on résumés as side data. We linked the Twitter posts and résumés by estimating the profiles of the account owners and matching them with those described in the résumés. We were able to link roughly 50% of the accounts to their owners when all tweets were used and roughly 20% of the accounts when only the latest 63 tweets were used. The proposed strategy would help people be better aware of the privacy risks of using personal data and hopefully lead to the implementation of improved protection measures.","PeriodicalId":156538,"journal":{"name":"2019 IEEE 10th International Conference on Awareness Science and Technology (iCAST)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131142402","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

Smart Shoe for Women Safety 女性安全智能鞋

2019 IEEE 10th International Conference on Awareness Science and Technology (iCAST) Pub Date : 2019-10-01 DOI: 10.1109/ICAwST.2019.8923204

Vishesh Sharma, Yati Tomar, V. Dharmar

引用次数: 19

Device-Free Localization via Sparse Coding with Log-Regularizer 基于日志正则化器的稀疏编码的无设备定位

2019 IEEE 10th International Conference on Awareness Science and Technology (iCAST) Pub Date : 2019-10-01 DOI: 10.1109/ICAwST.2019.8923592

Zhaoyang Han, Chunhua Su, Shuxue Ding, Huakun Huang, Lingjun Zhao

引用次数: 3

Maternal ehealth Monitoring System using LoRa Technology 基于LoRa技术的孕产妇电子健康监测系统

2019 IEEE 10th International Conference on Awareness Science and Technology (iCAST) Pub Date : 2019-10-01 DOI: 10.1109/ICAwST.2019.8923228

Alagumeenaakshi Muthiah, S. Ajitha, S. MonishaThangamK., K. VivekaVikram, K. Kavitha, R. Marimuthu

引用次数: 9

Use Product Segmentation to Enhance the Competitiveness of Enterprises in the IoT 利用产品细分提升企业在物联网领域的竞争力

2019 IEEE 10th International Conference on Awareness Science and Technology (iCAST) Pub Date : 2019-10-01 DOI: 10.1109/ICAwST.2019.8923220

Shu-Chin Wang, Hsiu-Wei Hsu, C. Dai, C. Ho, Fang-Yu Zhang

{"title":"Use Product Segmentation to Enhance the Competitiveness of Enterprises in the IoT","authors":"Shu-Chin Wang, Hsiu-Wei Hsu, C. Dai, C. Ho, Fang-Yu Zhang","doi":"10.1109/ICAwST.2019.8923220","DOIUrl":"https://doi.org/10.1109/ICAwST.2019.8923220","url":null,"abstract":"With the development of technology, the world of Internet of Things (IoT) is more and more developed, resulting in the rapid growth of diversified data and the formation of Big Data. Extract suitable data from a pile of seemingly useless materials, and apply different analysis and processing methods to form new and valuable data for the enterprise to enhance the competitiveness of the enterprise. Therefore, in this paper, the SOM (Self-Organization Map) will be used to aggregate the samples with similar characteristics from the product. In addition, RFM data analysis technology is used, we find out the more valuable customers in each cluster to solve the problem that the RFM total score has a large difference in different product attributes. After identifying the customers who are more valuable to the company, they then observe the products they purchased based on their past transaction data, perform the FP-Growth algorithm and construct the FP-tree. Finally, find out the frequent itemsets of the products through FP-tree and observe their relevance to provide companies with more accurate marketing strategies.","PeriodicalId":156538,"journal":{"name":"2019 IEEE 10th International Conference on Awareness Science and Technology (iCAST)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131673195","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: 2

The Effect of Stress on Optimal Bathing Time 压力对最佳沐浴时间的影响

2019 IEEE 10th International Conference on Awareness Science and Technology (iCAST) Pub Date : 2019-10-01 DOI: 10.1109/ICAwST.2019.8923254

Tianhui Li, Jianbo Xu, Peng Cui, Wenxi Chen

引用次数: 0

Bridge Sub Structure Defect Inspection Assistance by using Deep Learning 基于深度学习的桥梁子结构缺陷检测辅助研究

2019 IEEE 10th International Conference on Awareness Science and Technology (iCAST) Pub Date : 2019-10-01 DOI: 10.1109/ICAwST.2019.8923507

Pravee Kruachottikul, N. Cooharojananone, G. Phanomchoeng, Thira Chavarnakul, Kittikul Kovitanggoon, Donnaphat Trakulwaranont, K. Atchariyachanvanich

{"title":"Bridge Sub Structure Defect Inspection Assistance by using Deep Learning","authors":"Pravee Kruachottikul, N. Cooharojananone, G. Phanomchoeng, Thira Chavarnakul, Kittikul Kovitanggoon, Donnaphat Trakulwaranont, K. Atchariyachanvanich","doi":"10.1109/ICAwST.2019.8923507","DOIUrl":"https://doi.org/10.1109/ICAwST.2019.8923507","url":null,"abstract":"Road transportation is the most popular transportation in Thailand, which the top two highest traffic are the region-to-region highways; and then inter-city highways. Therefore, the regular maintenance is required to maintain the good condition due to road safety. The most significant process of bridge inspection procedures is sub structure inspection, which requires visual inspection as an initial step. This process is used to quick determine the damage severity i.e. appearance and crack that may cause damage to the structure strength. The current process requires that the experienced maintenance engineer to be on the field in order to visual inspect and estimate whether the maintenance is required. Yet, due to the limitation of number of expert engineers to be on the field, the photo verification is introduced to assist them so that they are no need on every inspection site. However, using human to verify has no standard and uncontrollable. They need to have experience and good knowledge. As well as it is highly depended on individual decision-making skill. Thus, in this paper, the deep learning technique will be presented to assist the expert for quality inspection process of bridge sub structure images. That is using image enhancement and then image splitting and overlapping for image pre-processing. After that applying CNNs for object classification. As a result, the total accuracy is 89% based on 3926 dataset.","PeriodicalId":156538,"journal":{"name":"2019 IEEE 10th International Conference on Awareness Science and Technology (iCAST)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131852856","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: 11

A Novel Maximum-Likelihood Detection for the Binary MIMO System Using DC Programming 一种基于直流编程的二进制MIMO系统最大似然检测方法

2019 IEEE 10th International Conference on Awareness Science and Technology (iCAST) Pub Date : 2019-10-01 DOI: 10.1109/ICAwST.2019.8923139

Benying Tan, Xiang Li, Shuxue Ding, Yujie Li, S. Akaho, H. Asoh

引用次数: 2

Pattern Classification of Disasters Impact on Companies Stock Prices 灾害对公司股价影响的模式分类

2019 IEEE 10th International Conference on Awareness Science and Technology (iCAST) Pub Date : 2019-10-01 DOI: 10.1109/ICAwST.2019.8923362

K. Yamaguchi, Y. Shirota

引用次数: 2

A Proposal for Shape Aware Feature Extraction for Time Series Classification 一种用于时间序列分类的形状感知特征提取方法

2019 IEEE 10th International Conference on Awareness Science and Technology (iCAST) Pub Date : 2019-10-01 DOI: 10.1109/ICAwST.2019.8923166

Hidetoshi Ito, B. Chakraborty

引用次数: 2