2018 Eleventh International Conference on Mobile Computing and Ubiquitous Network (ICMU)最新文献

ICMU 2018 Committees ICMU 2018委员会

2018 Eleventh International Conference on Mobile Computing and Ubiquitous Network (ICMU) Pub Date : 2018-10-01 DOI: 10.23919/icmu.2018.8653579

引用次数: 0

[Copyright notice] (版权)

2018 Eleventh International Conference on Mobile Computing and Ubiquitous Network (ICMU) Pub Date : 2018-10-01 DOI: 10.23919/icmu.2018.8653254

引用次数: 0

Estimating Distance of Going Up and down Stairs in a Building Using the Smartphone’s Rotation Vector Sensor 使用智能手机的旋转矢量传感器估算建筑物上下楼梯的距离

2018 Eleventh International Conference on Mobile Computing and Ubiquitous Network (ICMU) Pub Date : 2018-10-01 DOI: 10.23919/ICMU.2018.8653597

Masaki Nishizaka, Kenta Okina, H. Morino

引用次数: 0

Applying PDE in the Medical Field and Basic Concept of PDS Agent PDE在医学领域的应用及PDS Agent的基本概念

2018 Eleventh International Conference on Mobile Computing and Ubiquitous Network (ICMU) Pub Date : 2018-10-01 DOI: 10.23919/ICMU.2018.8653257

Masanari Hatano, Y. Taniguchi, H. Yajima

引用次数: 0

Improving Post-Hospital Discharge Management by Implementing the Discharge Summary on a Mobile Application 通过在移动应用程序上实现出院汇总，改善出院后管理

2018 Eleventh International Conference on Mobile Computing and Ubiquitous Network (ICMU) Pub Date : 2018-10-01 DOI: 10.23919/ICMU.2018.8653261

Hiten Karamchandani, M. Naeem, Farhaan Mirza, M. Baig

引用次数: 0

Ground Object Recognition from Aerial Image-based 3D Point Cloud 基于航拍图像的三维点云地物识别

2018 Eleventh International Conference on Mobile Computing and Ubiquitous Network (ICMU) Pub Date : 2018-10-01 DOI: 10.23919/ICMU.2018.8653608

Katsuya Ogura, Yuma Yamada, Shugo Kajita, H. Yamaguchi, T. Higashino, M. Takai

{"title":"Ground Object Recognition from Aerial Image-based 3D Point Cloud","authors":"Katsuya Ogura, Yuma Yamada, Shugo Kajita, H. Yamaguchi, T. Higashino, M. Takai","doi":"10.23919/ICMU.2018.8653608","DOIUrl":"https://doi.org/10.23919/ICMU.2018.8653608","url":null,"abstract":"Recently, several attempts have been made to grasp 3D ground shape from a 3D point cloud generated by aerial vehicles, which help to fast situation recognition. For example, in case of earthquake disasters, we may detect building collapse and inclination by comparing the height of buildings in 3D models before/after the disasters. However, identifying such objects on the ground like buildings, vehicles and trees from a 3D point cloud, which consists of 3D coordinates and color information, is not straightforward due to the gap between the low-level point information (coordinates) and high level context information (objects). In this paper, we propose a ground object recognition method from a 3D point cloud that captures the heights of ground surface. Basically, we rely on some existing tools to generate such a 3D point cloud from aerial images, and our method tries to give semantics to each set of clustered points. In the proposed method, firstly, such points that correspond to the ground surface are eliminated using the elevation data from Geographical Survey Institute. Next, we apply an inter-point distance-based clustering and noise filtering method according to the point density of each cluster. Then such clusters that share some regions are merged to correctly identify a point cluster that corresponds to a single object. Finally, a filtering method is applied based on the knowledge on the sizes of objects. We have evaluated our method in several experiments conducted in real fields. We have confirmed that our method can remove the ground surface within 5% error, and can recognize most of the objects.","PeriodicalId":398108,"journal":{"name":"2018 Eleventh International Conference on Mobile Computing and Ubiquitous Network (ICMU)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123461492","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

A Cross-Platform Study on IoT Malware 物联网恶意软件跨平台研究

2018 Eleventh International Conference on Mobile Computing and Ubiquitous Network (ICMU) Pub Date : 2018-10-01 DOI: 10.23919/ICMU.2018.8653580

Tao Ban, Ryoichi Isawa, K. Yoshioka, D. Inoue

{"title":"A Cross-Platform Study on IoT Malware","authors":"Tao Ban, Ryoichi Isawa, K. Yoshioka, D. Inoue","doi":"10.23919/ICMU.2018.8653580","DOIUrl":"https://doi.org/10.23919/ICMU.2018.8653580","url":null,"abstract":"Attacks towards the Internet of Things (IoT) devices are on the rise. For the lack of basic security monitoring and protection mechanisms, many of these devices are infected with malware and forced to join the attack campaigns on the Internet. Efficient precaution and mitigation of emerging IoT malware could only be pursued after in-depth analysis of captured malware samples. To enable efficient countermeasure against IoT malware, in this paper, we present a multi-level analysis of IoT malware programs based on static/dynamic analysis. To do so, we first use an entropy-based method to differentiate packed malware samples from non-packed ones. Then, characterizing information from static and dynamic analysis are vectorized and examined by t-SNE, which provides a visual hint on the interpretability of different features. Finally, an efficient classifier, namely support vector machine (SVM), is applied to the vector presentations of the malware for quantitative evaluation. Experiment show that opcode sequences obtained from static analysis provide sufficient discriminant information such that IoT malware can be classified with near optimal accuracy.","PeriodicalId":398108,"journal":{"name":"2018 Eleventh International Conference on Mobile Computing and Ubiquitous Network (ICMU)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121404836","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: 5

Compression Method of Position Information for IoT-based Bus Location System Using LoRaWAN 基于LoRaWAN的物联网公交车定位系统位置信息压缩方法

2018 Eleventh International Conference on Mobile Computing and Ubiquitous Network (ICMU) Pub Date : 2018-10-01 DOI: 10.23919/ICMU.2018.8653620

Takuya Boshita, Hidekazu Suzuki, Yukimasa Matsumoto

引用次数: 3

A Motivation-based Partnership Decision Model on Event-Stream Knowledge in Real-time Business 基于动机的实时业务事件流知识伙伴关系决策模型

2018 Eleventh International Conference on Mobile Computing and Ubiquitous Network (ICMU) Pub Date : 2018-10-01 DOI: 10.23919/ICMU.2018.8653626

Sunyanan Choochotkaew, H. Yamaguchi, T. Higashino

引用次数: 0

The Proposal and It’s Evalution of Biometric Authentication Method by EEG Analysis Using Image Stimulation 基于图像刺激的脑电分析生物特征认证方法的提出与评价

2018 Eleventh International Conference on Mobile Computing and Ubiquitous Network (ICMU) Pub Date : 2018-10-01 DOI: 10.23919/ICMU.2018.8653605

Masato Yamashita, M. Nakazawa, Yukinobu Nishikawa

{"title":"The Proposal and It’s Evalution of Biometric Authentication Method by EEG Analysis Using Image Stimulation","authors":"Masato Yamashita, M. Nakazawa, Yukinobu Nishikawa","doi":"10.23919/ICMU.2018.8653605","DOIUrl":"https://doi.org/10.23919/ICMU.2018.8653605","url":null,"abstract":"In recent years, techniques of Brain Machine Interface (BMI) which conducts human communication and robot manipulation using human brain activity are widely researched. This is the result of a noninvasive electroencephalograph device that can measure Electroencephalogram (EEG) in real time. However, there is a present condition that the authentication method when BMI is not much researched. In our research, we propose a biometric authentication method of electroencephalogram using image stimulation. In this research, we propose a biometric authentication method of electroencephalogram using image stimulation. In this paper, we construct and then evaluate a system that performs biometric authentication using EEG at image stimulus. We perform feature extraction using cross-correlation coefficient, and SVM for classification / authentication. Moreover We considered the method for preprocessing (digital filter, artifact countermeasure, epoch), we verify more appropriate preprocessing method. We verified the proposed method. In our proposed system, EER: 2.0% was obtained when artifact countermeasure, digital filter (IIR filter), and epoch method were used. From the result of FAR and FRR, our system was suggested that accuracy is improved by taking artifact countermeasure.","PeriodicalId":398108,"journal":{"name":"2018 Eleventh International Conference on Mobile Computing and Ubiquitous Network (ICMU)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127427369","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