2019 International Conference on Intelligent Computing, Automation and Systems (ICICAS)最新文献_第10页

Detection of Threat Situation for UAV Collision Avoidance Based on Sliding Window Polynomial Fitting Prediction Method 基于滑动窗口多项式拟合预测方法的无人机避碰威胁态势检测

2019 International Conference on Intelligent Computing, Automation and Systems (ICICAS) Pub Date : 2019-12-01 DOI: 10.1109/ICICAS48597.2019.00056

Xusheng Gan, Hong Qu, Pingni Liu, Qian Wang

引用次数: 1

A Physical Layer Authentication Method Based on Exponential Average Data Enhancement 一种基于指数平均数据增强的物理层认证方法

2019 International Conference on Intelligent Computing, Automation and Systems (ICICAS) Pub Date : 2019-12-01 DOI: 10.1109/ICICAS48597.2019.00184

Baifeng Ning, Xinchen Xu, Wei Wang, Zhonghang Li, Zhihan Zhang, Feiyi Xie, H. Wen

引用次数: 0

The Uncertainty Property on Intelligent Resource Provision in Complex Cloud Environment 复杂云环境下智能资源配置的不确定性

2019 International Conference on Intelligent Computing, Automation and Systems (ICICAS) Pub Date : 2019-12-01 DOI: 10.1109/ICICAS48597.2019.00043

Hang Zhou, Xinying Zhu, Jian Wang

引用次数: 0

A Duplication Reduction Approach for Unstructured Data Using Machine Learning Method 基于机器学习方法的非结构化数据重复减少方法

2019 International Conference on Intelligent Computing, Automation and Systems (ICICAS) Pub Date : 2019-12-01 DOI: 10.1109/ICICAS48597.2019.00113

Lin Qian, Jun Yu, Guangxin Zhu, Feng Mei, Wenda Lu, Bingyu Ge, Lin Wang, Zhu Mei, Hengmao Pang, Mingjie Xu, Haiyang Chen

引用次数: 1

TagNet: Tag Out the Value Sequence of SQL Statement TagNet:标记出SQL语句的值序列

2019 International Conference on Intelligent Computing, Automation and Systems (ICICAS) Pub Date : 2019-12-01 DOI: 10.1109/ICICAS48597.2019.00173

Yujie Zhong, Liutong Xu

{"title":"TagNet: Tag Out the Value Sequence of SQL Statement","authors":"Yujie Zhong, Liutong Xu","doi":"10.1109/ICICAS48597.2019.00173","DOIUrl":"https://doi.org/10.1109/ICICAS48597.2019.00173","url":null,"abstract":"In order to assist person who doesn't know how to write SQL to access the data in a relation database, using a deep neural architecture to translate the natural language to SQL has recently been extensively studied. Previous work suffers from the complexity of where clause, since the number of conditions is totally random and predicting the value of condition is a sequence-to-sequence problem. We follow the slot filling idea, and introduce a model called TagNet. First of all, we innovatively propose a task attention mechanism. It takes the relativity of tasks into consideration for attention mechanism. Secondly, we use type embedding of each token of question and each column to enhance the representation for value prediction. Thirdly, in the task of predicting WHERE VALUE, we propose a tag decoder. It output a sequence of equal length compared with input. It consists of two tokens:, , indicating the corresponding token of input is whether or not a value token. We evaluate out model on WikiSQL, and compared to our baseline-SQLNet, we gain an absolute 7.6% increase on logic form accuracy and 6.3% increase on execution accuracy.","PeriodicalId":409693,"journal":{"name":"2019 International Conference on Intelligent Computing, Automation and Systems (ICICAS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132476160","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

A Novel Spatial-Temporal Fusion Framework Based on Object Trajectories 一种基于目标轨迹的时空融合框架

2019 International Conference on Intelligent Computing, Automation and Systems (ICICAS) Pub Date : 2019-12-01 DOI: 10.1109/ICICAS48597.2019.00139

Canghong Jin, Ting Tao, Tao Ruan, Lei Xu, Xianzhe Luo, Rui Li

{"title":"A Novel Spatial-Temporal Fusion Framework Based on Object Trajectories","authors":"Canghong Jin, Ting Tao, Tao Ruan, Lei Xu, Xianzhe Luo, Rui Li","doi":"10.1109/ICICAS48597.2019.00139","DOIUrl":"https://doi.org/10.1109/ICICAS48597.2019.00139","url":null,"abstract":"With the development of information technology, the traces of residents could be caught by sensors all over the city, from which to identify specific people such as suspects, has become the focus of public security departments in recent years. Although there are some advantages of the mass of Spatio-temporal records, the activity records contain both temporal and spatial context is high-order and sparse. Therefore, it is difficult to identify users, especially for those small groups of individuals. In this paper, we propose a framework to identify users by fuzzed Spatio-temporal traces, in which we first extract the features from several perspectives and generate the TSGH (Time-slice Geohash) model and STPS (Spatio-temporal Proportion and Similarity) model. All these features are combined with classical classification models to distinguish users. We set up a real-life dataset and evaluate performance effectiveness with precision and recall measures. The final results show that the fuzzy operations could describe the characteristic of traces better and improve the prediction performance","PeriodicalId":409693,"journal":{"name":"2019 International Conference on Intelligent Computing, Automation and Systems (ICICAS)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132553056","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

Agility Measurement of Agile Supply Chain Network Based on Complex Network Theory 基于复杂网络理论的敏捷供应链网络敏捷性度量

2019 International Conference on Intelligent Computing, Automation and Systems (ICICAS) Pub Date : 2019-12-01 DOI: 10.1109/ICICAS48597.2019.00163

Yunxia Yao, Lin Li

{"title":"Agility Measurement of Agile Supply Chain Network Based on Complex Network Theory","authors":"Yunxia Yao, Lin Li","doi":"10.1109/ICICAS48597.2019.00163","DOIUrl":"https://doi.org/10.1109/ICICAS48597.2019.00163","url":null,"abstract":"With the development of information technology, the supply chain has developed into a new stage of intelligent supply chain which is deeply integrated with the Internet and the Internet of Objects. In order to give full play to the characteristics of innovation, collaboration, win-win, openness and greenness in supply chain, and to build a smart supply chain system with big data support, network sharing and intelligent collaboration, the agility measurement of supply chain has become an urgent and important topic. This paper presents an agile metric based on complex network theory for agile supply chain network. Firstly, the mathematical expression of agile supply chain network and its agility measurement method are defined, and the constraints of complex network theory are also defined. Secondly, to facilitate the calculation of agility metrics, complex network theory is introduced into agile supply chain network. In addition, a large number of experiments have been designed and implemented to verify the accuracy of the proposed complex network theory in agile supply chain network measurement. At the same time, the agility of the supply chain network is measured, and its changing rules and optimization methods are summarized. The experimental results show that the proposed complex network theory can accurately measure the agility of agile supply chain network. The purpose of this paper is to provide a method to turn agile supply chain system into intelligent information system through mathematical modeling.","PeriodicalId":409693,"journal":{"name":"2019 International Conference on Intelligent Computing, Automation and Systems (ICICAS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114304084","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

The Search and Improvement of DES Algorithm for Data Transmission Security in SCADA SCADA数据传输安全DES算法的研究与改进

2019 International Conference on Intelligent Computing, Automation and Systems (ICICAS) Pub Date : 2019-12-01 DOI: 10.1109/ICICAS48597.2019.00066

Xudong Xu, Na Tian

引用次数: 2

A Novel Controllable Image Segmentation Method Using the Inverse GAMMA Distribution Function Based on Histogram Specification 一种基于直方图规范的GAMMA逆分布函数的可控图像分割方法

2019 International Conference on Intelligent Computing, Automation and Systems (ICICAS) Pub Date : 2019-12-01 DOI: 10.1109/ICICAS48597.2019.00147

Dhekra Saeed, Huibin Shi, Barakat Ameen

{"title":"A Novel Controllable Image Segmentation Method Using the Inverse GAMMA Distribution Function Based on Histogram Specification","authors":"Dhekra Saeed, Huibin Shi, Barakat Ameen","doi":"10.1109/ICICAS48597.2019.00147","DOIUrl":"https://doi.org/10.1109/ICICAS48597.2019.00147","url":null,"abstract":"Image segmentation(IMSEG) is defined as a top of the basic and most significant process of digital image handling which refers to the techniques that used to partitioning and dividing an image into useful and meaningful parts, called segments. It's so important for many applications which difficult and inefficient to process the entire image, such as object recognition or image compression. So, IMSEG aims to segment the image into districts for further operations and processing. There are several techniques for image segmentation which divide the image into many parts regarding to some specific image properties such as the intensity value of pixels, relation between pixels, color, texture and so on. However, most image segmentation techniques have deficient ability to plainly tune the segment sensitivity of the segmented image. In our manuscript we will propose a new technique for image segmentations using the invers GAMMA distribution function based on histogram matching, the proposed technique provides a method to manage the segment sensitivity of segmented image via setting one parameter. Experimental outcomes pretend a superior execution of this created technique","PeriodicalId":409693,"journal":{"name":"2019 International Conference on Intelligent Computing, Automation and Systems (ICICAS)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115059957","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

Image Segmentation Algorithm Based on the Background Skeleton Feature 基于背景骨架特征的图像分割算法

2019 International Conference on Intelligent Computing, Automation and Systems (ICICAS) Pub Date : 2019-12-01 DOI: 10.1109/ICICAS48597.2019.00036

Bing Li, Shuofeng Li, Jin Li

引用次数: 2