Pub Date : 2018-10-01DOI: 10.23919/icmu.2018.8653579
{"title":"ICMU 2018 Committees","authors":"","doi":"10.23919/icmu.2018.8653579","DOIUrl":"https://doi.org/10.23919/icmu.2018.8653579","url":null,"abstract":"","PeriodicalId":398108,"journal":{"name":"2018 Eleventh International Conference on Mobile Computing and Ubiquitous Network (ICMU)","volume":"1 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":"115593380","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}
Pub Date : 2018-10-01DOI: 10.23919/icmu.2018.8653254
{"title":"[Copyright notice]","authors":"","doi":"10.23919/icmu.2018.8653254","DOIUrl":"https://doi.org/10.23919/icmu.2018.8653254","url":null,"abstract":"","PeriodicalId":398108,"journal":{"name":"2018 Eleventh International Conference on Mobile Computing and Ubiquitous Network (ICMU)","volume":"17 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":"115061924","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}
Pub Date : 2018-10-01DOI: 10.23919/ICMU.2018.8653597
Masaki Nishizaka, Kenta Okina, H. Morino
Localization of persons in the building after a disaster occurs is one of prominent issues for rescuing them and also it is technically challenging, considering that communication infrastructures such as cellular or WiFi would be often unavailable due to the severe damage or heavy traffic concentration. This paper focuses on estimating person’s moving distance in the stairs and presents a scheme to estimate only with rotation vector sensor, being typically installed in the recent smartphone. Performance evaluation by experiments shows that the proposed scheme can estimate the number of floors by which the person moved with error of almost zero.
{"title":"Estimating Distance of Going Up and down Stairs in a Building Using the Smartphone’s Rotation Vector Sensor","authors":"Masaki Nishizaka, Kenta Okina, H. Morino","doi":"10.23919/ICMU.2018.8653597","DOIUrl":"https://doi.org/10.23919/ICMU.2018.8653597","url":null,"abstract":"Localization of persons in the building after a disaster occurs is one of prominent issues for rescuing them and also it is technically challenging, considering that communication infrastructures such as cellular or WiFi would be often unavailable due to the severe damage or heavy traffic concentration. This paper focuses on estimating person’s moving distance in the stairs and presents a scheme to estimate only with rotation vector sensor, being typically installed in the recent smartphone. Performance evaluation by experiments shows that the proposed scheme can estimate the number of floors by which the person moved with error of almost zero.","PeriodicalId":398108,"journal":{"name":"2018 Eleventh International Conference on Mobile Computing and Ubiquitous Network (ICMU)","volume":"14 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":"116016439","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}
Pub Date : 2018-10-01DOI: 10.23919/ICMU.2018.8653257
Masanari Hatano, Y. Taniguchi, H. Yajima
In this paper, we tried to apply the framework of PDE(Personal Data Eco-system), in which data subjects (patients etc.) manage and operate their own data, to the medical field. Specifically, we proposed an agent function that made it possible for patients who were data subjects to easily find desired information from information of other patients.
在本文中，我们尝试将数据主体(患者等)管理和操作自己数据的PDE(Personal Data Eco-system)框架应用到医疗领域。具体来说，我们提出了一个代理函数，使得作为数据主体的患者可以很容易地从其他患者的信息中找到想要的信息。
{"title":"Applying PDE in the Medical Field and Basic Concept of PDS Agent","authors":"Masanari Hatano, Y. Taniguchi, H. Yajima","doi":"10.23919/ICMU.2018.8653257","DOIUrl":"https://doi.org/10.23919/ICMU.2018.8653257","url":null,"abstract":"In this paper, we tried to apply the framework of PDE(Personal Data Eco-system), in which data subjects (patients etc.) manage and operate their own data, to the medical field. Specifically, we proposed an agent function that made it possible for patients who were data subjects to easily find desired information from information of other patients.","PeriodicalId":398108,"journal":{"name":"2018 Eleventh International Conference on Mobile Computing and Ubiquitous Network (ICMU)","volume":"1 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":"128658159","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}
Pub Date : 2018-10-01DOI: 10.23919/ICMU.2018.8653261
Hiten Karamchandani, M. Naeem, Farhaan Mirza, M. Baig
Patients often rely on a printed discharge summary for clinical information, post-discharge treatment, medications and other health activities, non-adherence to which may lead to readmission. With the active involvement of clinicians, medical informatics professionals and technical advisors a mobile prototype application has been designed and developed to provide a user-friendly presentation of clinical information aiming to increase the adherence of medical advice. We conducted a task-based usability and accuracy test and found that the average accuracy was 97%, time taken for each task to complete was 7.5s (average) and the overall navigation was termed as ‘easy to understand’ by the users.
{"title":"Improving Post-Hospital Discharge Management by Implementing the Discharge Summary on a Mobile Application","authors":"Hiten Karamchandani, M. Naeem, Farhaan Mirza, M. Baig","doi":"10.23919/ICMU.2018.8653261","DOIUrl":"https://doi.org/10.23919/ICMU.2018.8653261","url":null,"abstract":"Patients often rely on a printed discharge summary for clinical information, post-discharge treatment, medications and other health activities, non-adherence to which may lead to readmission. With the active involvement of clinicians, medical informatics professionals and technical advisors a mobile prototype application has been designed and developed to provide a user-friendly presentation of clinical information aiming to increase the adherence of medical advice. We conducted a task-based usability and accuracy test and found that the average accuracy was 97%, time taken for each task to complete was 7.5s (average) and the overall navigation was termed as ‘easy to understand’ by the users.","PeriodicalId":398108,"journal":{"name":"2018 Eleventh International Conference on Mobile Computing and Ubiquitous Network (ICMU)","volume":"48 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":"126761268","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}
Pub Date : 2018-10-01DOI: 10.23919/ICMU.2018.8653608
Katsuya Ogura, Yuma Yamada, Shugo Kajita, H. Yamaguchi, T. Higashino, M. Takai
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.
{"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}
Pub Date : 2018-10-01DOI: 10.23919/ICMU.2018.8653580
Tao Ban, Ryoichi Isawa, K. Yoshioka, D. Inoue
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.
{"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}
The authors aim to realize an Internet of Things-based bus location system that can be achieved with low operation cost using Long Range Wide Area Network (LoRaWAN). However, in Japan, when LoRaWAN is operated in the mode where the communication distance is the longest, the data size that can be transmitted at once is limited to 11 bytes. This paper proposes a location information compression method to transmit the time information and the traveling position of the bus under this constraint. When transmitting time and location information acquired from GPS, 280 bits are required in the general method, whereas in the proposed method it can be compressed to 49 bits.
{"title":"Compression Method of Position Information for IoT-based Bus Location System Using LoRaWAN","authors":"Takuya Boshita, Hidekazu Suzuki, Yukimasa Matsumoto","doi":"10.23919/ICMU.2018.8653620","DOIUrl":"https://doi.org/10.23919/ICMU.2018.8653620","url":null,"abstract":"The authors aim to realize an Internet of Things-based bus location system that can be achieved with low operation cost using Long Range Wide Area Network (LoRaWAN). However, in Japan, when LoRaWAN is operated in the mode where the communication distance is the longest, the data size that can be transmitted at once is limited to 11 bytes. This paper proposes a location information compression method to transmit the time information and the traveling position of the bus under this constraint. When transmitting time and location information acquired from GPS, 280 bits are required in the general method, whereas in the proposed method it can be compressed to 49 bits.","PeriodicalId":398108,"journal":{"name":"2018 Eleventh International Conference on Mobile Computing and Ubiquitous Network (ICMU)","volume":"15 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":"126533835","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}
Pub Date : 2018-10-01DOI: 10.23919/ICMU.2018.8653626
Sunyanan Choochotkaew, H. Yamaguchi, T. Higashino
Toward a brand-new multi-dimensional knowledge-sharing framework for the future Internet of Business Intelligence (BI), we tackle the challenges of sharing decisions at knowledge owners. In this paper, we provide an automatic decision-maker model responding to requesting offers from knowledge investors. To achieve that, we refer the theory about motivational factors behind sharing behavior in the context of event-stream processing for decision criteria in owner aspect. Then, we exploit the multi-criteria decision technique named AHP to provide numerical score ranking. To gain the flexibility of offering, we allow investors to offer both direct incentive (money) and indirect incentive (computation power) and propose a method to assess the value of resource for event-stream processing tasks considering both energy and time of computation and communication. To illustrate the proposed decision model, we raise example case studies on social/interest-leading disaster knowledge and attitude-leading market-trend knowledge.
{"title":"A Motivation-based Partnership Decision Model on Event-Stream Knowledge in Real-time Business","authors":"Sunyanan Choochotkaew, H. Yamaguchi, T. Higashino","doi":"10.23919/ICMU.2018.8653626","DOIUrl":"https://doi.org/10.23919/ICMU.2018.8653626","url":null,"abstract":"Toward a brand-new multi-dimensional knowledge-sharing framework for the future Internet of Business Intelligence (BI), we tackle the challenges of sharing decisions at knowledge owners. In this paper, we provide an automatic decision-maker model responding to requesting offers from knowledge investors. To achieve that, we refer the theory about motivational factors behind sharing behavior in the context of event-stream processing for decision criteria in owner aspect. Then, we exploit the multi-criteria decision technique named AHP to provide numerical score ranking. To gain the flexibility of offering, we allow investors to offer both direct incentive (money) and indirect incentive (computation power) and propose a method to assess the value of resource for event-stream processing tasks considering both energy and time of computation and communication. To illustrate the proposed decision model, we raise example case studies on social/interest-leading disaster knowledge and attitude-leading market-trend knowledge.","PeriodicalId":398108,"journal":{"name":"2018 Eleventh International Conference on Mobile Computing and Ubiquitous Network (ICMU)","volume":"50 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":"132601599","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}
Pub Date : 2018-10-01DOI: 10.23919/ICMU.2018.8653605
Masato Yamashita, M. Nakazawa, Yukinobu Nishikawa
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.
{"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}
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