Addressing the spiraling amount of music and video consumption via streaming services, in particular on mobile devices, we present a music player application for the Android platform, which employs a hybrid approach to generate a list of track recommendations for a user. We propose and evaluate two different algorithms, namely a content-based algorithm and an approach that exploits social similarity. While the former is based on rhythm features, the latter exploits "related videos" relations from YouTube. We show via a user questionnaire that recommendation results based on content slightly, but statistically significantly, outperform the social approach. Given that full audio content is not available immediately in a streaming environment, however, we suggest a hybrid, dynamic approach to music recommendation. Playlists are created as a linear, user-adjustable mixture of both content and social similarity. They are offered to the user via an Android application dubbed "Beat Commander". Besides displaying the results of the playlist generation approach as text, the player features a dynamic visualization of the playlist, using a version of Sammon's mapping.
{"title":"Personalized Music Recommendation in a Mobile Environment","authors":"Claus Schabetsberger, M. Schedl","doi":"10.1145/2536853.2536946","DOIUrl":"https://doi.org/10.1145/2536853.2536946","url":null,"abstract":"Addressing the spiraling amount of music and video consumption via streaming services, in particular on mobile devices, we present a music player application for the Android platform, which employs a hybrid approach to generate a list of track recommendations for a user. We propose and evaluate two different algorithms, namely a content-based algorithm and an approach that exploits social similarity. While the former is based on rhythm features, the latter exploits \"related videos\" relations from YouTube. We show via a user questionnaire that recommendation results based on content slightly, but statistically significantly, outperform the social approach. Given that full audio content is not available immediately in a streaming environment, however, we suggest a hybrid, dynamic approach to music recommendation.\u0000 Playlists are created as a linear, user-adjustable mixture of both content and social similarity. They are offered to the user via an Android application dubbed \"Beat Commander\". Besides displaying the results of the playlist generation approach as text, the player features a dynamic visualization of the playlist, using a version of Sammon's mapping.","PeriodicalId":135195,"journal":{"name":"Advances in Mobile Multimedia","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115929174","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}
In this paper, we implement a Parallel Distributed Phase Correlation algorithm for fingerprint verification through Cloud computing services. The algorithm is proposed to be hosted by Cloud Computing Services with Quality of Service (QoS) and Quality of Protection (QoP). We also propose 128-bit encryption for security and privacy of individuals' fingerprints and the Wavelet Scalar Quantization (WSQ) compression method. Fingerprint scanners from various manufactures have different specifications in image capture size, etc. Standards need to be set on the specifications, for image size, for storage, for transmission, for interoperability of various verification algorithms, and protection.
{"title":"Fingerprint Verification through Cloud Computing","authors":"F. Noor, M. Alhaisoni","doi":"10.1145/2536853.2536902","DOIUrl":"https://doi.org/10.1145/2536853.2536902","url":null,"abstract":"In this paper, we implement a Parallel Distributed Phase Correlation algorithm for fingerprint verification through Cloud computing services. The algorithm is proposed to be hosted by Cloud Computing Services with Quality of Service (QoS) and Quality of Protection (QoP). We also propose 128-bit encryption for security and privacy of individuals' fingerprints and the Wavelet Scalar Quantization (WSQ) compression method. Fingerprint scanners from various manufactures have different specifications in image capture size, etc. Standards need to be set on the specifications, for image size, for storage, for transmission, for interoperability of various verification algorithms, and protection.","PeriodicalId":135195,"journal":{"name":"Advances in Mobile Multimedia","volume":"37 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116640380","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}
Real-Time Compressive Tracking utilizes a very spare measurement matrix to extract the features for the appearance model. Such model performs well when the tracked objects are well defined. However, when the objects are low-grain, low-resolution, or small, a fixed size sparse measurement matrix is not sufficient enough to preserve the image structure of the object. In this work, we propose a Dynamic Compressive Tracking algorithm that employs adaptive random projections that preserve the image structure of the objects during tracking. The proposed tracker uses a dynamic importance ranking weight to evaluate the classification results obtained by each of the sparse measurement matrices and complete the tracking with the optimal sparse matrix. Extensive experimental results, on challenging publicly available data sets, shows that the proposed dynamic compressible tracking algorithm outperforms conventional compressive tracker.
{"title":"Dynamic Compressive Tracking","authors":"Ting Chen, Yanning Zhang, Tao Yang, H. Sahli","doi":"10.1145/2536853.2536883","DOIUrl":"https://doi.org/10.1145/2536853.2536883","url":null,"abstract":"Real-Time Compressive Tracking utilizes a very spare measurement matrix to extract the features for the appearance model. Such model performs well when the tracked objects are well defined. However, when the objects are low-grain, low-resolution, or small, a fixed size sparse measurement matrix is not sufficient enough to preserve the image structure of the object. In this work, we propose a Dynamic Compressive Tracking algorithm that employs adaptive random projections that preserve the image structure of the objects during tracking. The proposed tracker uses a dynamic importance ranking weight to evaluate the classification results obtained by each of the sparse measurement matrices and complete the tracking with the optimal sparse matrix. Extensive experimental results, on challenging publicly available data sets, shows that the proposed dynamic compressible tracking algorithm outperforms conventional compressive tracker.","PeriodicalId":135195,"journal":{"name":"Advances in Mobile Multimedia","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117164965","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}
Asim Jalal, Nicholas Gibbins, D. Millard, B. Al-Hashimi, Naif R. Aljohani
As a result of tremendous enhancements in the capabilities of mobile devices and availability of higher data rate mobile internet, the use of online multimedia learning resources on mobile devices is increasingly becoming popular. Limited Battery Power of mobile devices, however, is still one big challenge in Mobile Learning. High Quality multimedia learning resources are power hungry and if used on mobile devices drain battery power rapidly limiting learning opportunities on the move. Lack of significant improvements in battery capacities has resulted in significant interest in battery power saving techniques. Existing power-saving streaming multimedia adaptation techniques tend to extend battery life by reducing quality of multimedia making them susceptible to information loss. This loss may affect the learning content efficacy and jeopardizes the learning process. To the best of our knowledge, no previous work has considered the learning content efficacy in multimedia streaming adaptation mechanism. In this paper, we present MoBELearn system, which is a prototype implementation of our proposed Content Aware Power Saving Educational Multimedia Adaptation (CAPS-EMA) approach. We demonstrate battery efficiency in educational multimedia streaming while keeping the adapted resource suitable for learning. We also describe our semantic metamodel for educational multimedia resource that support our energy efficient adaptation technique.
{"title":"Energy-Aware Adaptation of Educational Multimedia in Mobile Learning","authors":"Asim Jalal, Nicholas Gibbins, D. Millard, B. Al-Hashimi, Naif R. Aljohani","doi":"10.1145/2536853.2536896","DOIUrl":"https://doi.org/10.1145/2536853.2536896","url":null,"abstract":"As a result of tremendous enhancements in the capabilities of mobile devices and availability of higher data rate mobile internet, the use of online multimedia learning resources on mobile devices is increasingly becoming popular. Limited Battery Power of mobile devices, however, is still one big challenge in Mobile Learning. High Quality multimedia learning resources are power hungry and if used on mobile devices drain battery power rapidly limiting learning opportunities on the move. Lack of significant improvements in battery capacities has resulted in significant interest in battery power saving techniques. Existing power-saving streaming multimedia adaptation techniques tend to extend battery life by reducing quality of multimedia making them susceptible to information loss. This loss may affect the learning content efficacy and jeopardizes the learning process. To the best of our knowledge, no previous work has considered the learning content efficacy in multimedia streaming adaptation mechanism. In this paper, we present MoBELearn system, which is a prototype implementation of our proposed Content Aware Power Saving Educational Multimedia Adaptation (CAPS-EMA) approach. We demonstrate battery efficiency in educational multimedia streaming while keeping the adapted resource suitable for learning. We also describe our semantic metamodel for educational multimedia resource that support our energy efficient adaptation technique.","PeriodicalId":135195,"journal":{"name":"Advances in Mobile Multimedia","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114613969","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}
Andrew Ennis, Liming Luke Chen, C. Nugent, G. Ioannidis, Alexandru Stan
Improvements and portability of technologies and smart devices has enabled rapid growth in the amount of user generated media such as photographs and videos. Whilst various media generation and management systems exist it still remains a challenge to discover the "right" metadata information for the right purpose. This paper describes an approach to extract relevant geospatial information through reverse geocoding in addition to cross-referencing several public geospatial data sources. The extracted geospatial information can be used to enable enrichment of media with rich semantic geo-metadata and therefore enable improved organisation and searching of the media. Central to the system is the cross-referencing and data fusion of several public geospatial datasets to determine the most relevant Points of Interest and extract their relevant features. These relevant Points of Interest and features are subsequently used to annotate media with human readable information, leading to enriched media repositories. The system has been implemented as a client/server architecture, with a web interface for the client front end and Java for the backend server side processing. Details of the implementation are discussed. Testing in a scenario has been undertaken and a discussion of the testing technique and results is presented. The initial results show the system to be effective at fusing several public geospatial datasets and extracting relevant geo-metadata.
{"title":"A System for Real-Time High-Level Geo-Information Extraction and Fusion for Geocoded Photos","authors":"Andrew Ennis, Liming Luke Chen, C. Nugent, G. Ioannidis, Alexandru Stan","doi":"10.1145/2536853.2536888","DOIUrl":"https://doi.org/10.1145/2536853.2536888","url":null,"abstract":"Improvements and portability of technologies and smart devices has enabled rapid growth in the amount of user generated media such as photographs and videos. Whilst various media generation and management systems exist it still remains a challenge to discover the \"right\" metadata information for the right purpose. This paper describes an approach to extract relevant geospatial information through reverse geocoding in addition to cross-referencing several public geospatial data sources. The extracted geospatial information can be used to enable enrichment of media with rich semantic geo-metadata and therefore enable improved organisation and searching of the media. Central to the system is the cross-referencing and data fusion of several public geospatial datasets to determine the most relevant Points of Interest and extract their relevant features. These relevant Points of Interest and features are subsequently used to annotate media with human readable information, leading to enriched media repositories. The system has been implemented as a client/server architecture, with a web interface for the client front end and Java for the backend server side processing. Details of the implementation are discussed. Testing in a scenario has been undertaken and a discussion of the testing technique and results is presented. The initial results show the system to be effective at fusing several public geospatial datasets and extracting relevant geo-metadata.","PeriodicalId":135195,"journal":{"name":"Advances in Mobile Multimedia","volume":"191 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114859618","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}
R. Findling, Fabian Wenny, Clemens Holzmann, R. Mayrhofer
Face detection (finding faces of different perspectives in images) is an important task as prerequisite to face recognition. This is especially difficult in the mobile domain, as bad image quality and illumination conditions lead to overall reduced face detection rates. Background information still present in segmented faces and unequally normalized faces further decrease face recognition rates. We present a novel approach to robust single upright face detection and segmentation from different perspectives based on range information (pixel values corresponding to the camera-object distance). We use range template matching for finding the face's coarse position and gradient vector flow (GVF) snakes for precisely segmenting faces. We further evaluate our approach on range faces from the u'smile face database, then perform face recognition using the segmented faces to evaluate and compare our approach with previous research. Results indicate that range template matching might be a good approach to finding a single face; in our tests we achieved an error free detection rate and average recognition rates above 98%/96% for color/range images.
{"title":"Range Face Segmentation: Face Detection and Segmentation for Authentication in Mobile Device Range Images","authors":"R. Findling, Fabian Wenny, Clemens Holzmann, R. Mayrhofer","doi":"10.1145/2536853.2536880","DOIUrl":"https://doi.org/10.1145/2536853.2536880","url":null,"abstract":"Face detection (finding faces of different perspectives in images) is an important task as prerequisite to face recognition. This is especially difficult in the mobile domain, as bad image quality and illumination conditions lead to overall reduced face detection rates. Background information still present in segmented faces and unequally normalized faces further decrease face recognition rates. We present a novel approach to robust single upright face detection and segmentation from different perspectives based on range information (pixel values corresponding to the camera-object distance). We use range template matching for finding the face's coarse position and gradient vector flow (GVF) snakes for precisely segmenting faces. We further evaluate our approach on range faces from the u'smile face database, then perform face recognition using the segmented faces to evaluate and compare our approach with previous research. Results indicate that range template matching might be a good approach to finding a single face; in our tests we achieved an error free detection rate and average recognition rates above 98%/96% for color/range images.","PeriodicalId":135195,"journal":{"name":"Advances in Mobile Multimedia","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125465705","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}
Yongchun Xu, N. Stojanović, Ljiljana Stojanović, Dusan Kostic
In this paper we present a novel approach for dynamic remote activity monitoring based on mobile complex event processing that has been used in a use case in the eHealth domain. Using complex event processing (CEP) in mobile environment enables a more flexible and efficient processing of personal sensor data and environment data, which are detected by sensors embedded in a mobile device. The main advantages of our approach are: an efficient combination of the mobile and server-side event processing through the semantic event model, optimal usage of mobile resources through dynamic management of mobile event processing and modelling of complex situations by using more expressive knowledge representation formalism. We present the settings for the use case and the results from the preliminary evaluation.
{"title":"An Approach for Dynamic Personal Monitoring based on Mobile Complex Event Processing","authors":"Yongchun Xu, N. Stojanović, Ljiljana Stojanović, Dusan Kostic","doi":"10.1145/2536853.2536866","DOIUrl":"https://doi.org/10.1145/2536853.2536866","url":null,"abstract":"In this paper we present a novel approach for dynamic remote activity monitoring based on mobile complex event processing that has been used in a use case in the eHealth domain. Using complex event processing (CEP) in mobile environment enables a more flexible and efficient processing of personal sensor data and environment data, which are detected by sensors embedded in a mobile device. The main advantages of our approach are: an efficient combination of the mobile and server-side event processing through the semantic event model, optimal usage of mobile resources through dynamic management of mobile event processing and modelling of complex situations by using more expressive knowledge representation formalism. We present the settings for the use case and the results from the preliminary evaluation.","PeriodicalId":135195,"journal":{"name":"Advances in Mobile Multimedia","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126087343","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}
Tracking services play a fundamental role in the smartphone ecosystem. While their primary purpose is to provide a smartphone user with the ability to regulate the extent of sharing private information with external parties, these services can also be misused by advertisers in order to boost revenues. In this paper, we investigate tracking services on the Android and iOS smartphone platforms. We present a simple and effective way to monitor traffic generated by tracking services to and from the smartphone and external servers. To evaluate our work, we dynamically execute a set of Android and iOS applications, collected from their respective official markets. Our empirical results indicate that even if the user disables or limits tracking services on the smartphone, applications can by-pass those settings and, consequently, leak private information to external parties. On the other hand, when testing the location 'on' setting, we notice that generally location is not tracked.
{"title":"Can Smartphone Users Turn Off Tracking Service Settings?","authors":"Veelasha Moonsamy, L. Batten, Malcolm Shore","doi":"10.1145/2536853.2536864","DOIUrl":"https://doi.org/10.1145/2536853.2536864","url":null,"abstract":"Tracking services play a fundamental role in the smartphone ecosystem. While their primary purpose is to provide a smartphone user with the ability to regulate the extent of sharing private information with external parties, these services can also be misused by advertisers in order to boost revenues. In this paper, we investigate tracking services on the Android and iOS smartphone platforms. We present a simple and effective way to monitor traffic generated by tracking services to and from the smartphone and external servers. To evaluate our work, we dynamically execute a set of Android and iOS applications, collected from their respective official markets. Our empirical results indicate that even if the user disables or limits tracking services on the smartphone, applications can by-pass those settings and, consequently, leak private information to external parties. On the other hand, when testing the location 'on' setting, we notice that generally location is not tracked.","PeriodicalId":135195,"journal":{"name":"Advances in Mobile Multimedia","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127128496","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}
Nowadays, plenty of researches focus on story generation which is widely used in computer games, education and training applications. It is highly desirable that the generated story should afford high user agency and at same time having capabilities to address user's interventions. In this paper, we apply planning, which is derived from artificial intelligence, to achieve this objective. With the use of planning, several solutions are produced, which contains a sequence of user's and system agents' actions. In addition, we propose the concept of Action Preference, which takes into account user's feedbacks, to evaluate all of the solutions after planning. Meanwhile a variant of hyperbolic tangent is utilized to calculate Action Preference. In order to evaluate its feasibility, an educational game was implemented on the basis of story generation. That result proves that planning with Action Preference is an effective approach in story generation.
{"title":"Using Planning with Action Preference in Story Generation","authors":"Xiaobo Li, S. Paracha, Jiao Wu, O. Yoshie","doi":"10.1145/2536853.2536924","DOIUrl":"https://doi.org/10.1145/2536853.2536924","url":null,"abstract":"Nowadays, plenty of researches focus on story generation which is widely used in computer games, education and training applications. It is highly desirable that the generated story should afford high user agency and at same time having capabilities to address user's interventions. In this paper, we apply planning, which is derived from artificial intelligence, to achieve this objective. With the use of planning, several solutions are produced, which contains a sequence of user's and system agents' actions. In addition, we propose the concept of Action Preference, which takes into account user's feedbacks, to evaluate all of the solutions after planning. Meanwhile a variant of hyperbolic tangent is utilized to calculate Action Preference. In order to evaluate its feasibility, an educational game was implemented on the basis of story generation. That result proves that planning with Action Preference is an effective approach in story generation.","PeriodicalId":135195,"journal":{"name":"Advances in Mobile Multimedia","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130211253","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}
V. Osmani, Alban Maxhuni, Agnes Grünerbl, P. Lukowicz, C. Haring, O. Mayora-Ibarra
Mobile computing is changing the landscape of clinical monitoring and self-monitoring. One of the major impacts will be in healthcare, where increase in number of sensing modalities is providing more and more information on the state of overall wellbeing, behaviour and health. There are numerous applications of mobile computing that range from wellbeing applications, such as physical fitness, stress or burnout up to applications that target mental disorders including bipolar disorder. Use of information provided by mobile computing devices can track the state of the subjects and also allow for experience sampling in order to gather subjective information. This paper reports on the results obtained from a medical trial with monitoring of bipolar disorder patients and how the episodes of the diseases correlate to the analysis of the data sampled from mobile phone acting as a monitoring device.
{"title":"Monitoring activity of patients with bipolar disorder using smart phones","authors":"V. Osmani, Alban Maxhuni, Agnes Grünerbl, P. Lukowicz, C. Haring, O. Mayora-Ibarra","doi":"10.1145/2536853.2536882","DOIUrl":"https://doi.org/10.1145/2536853.2536882","url":null,"abstract":"Mobile computing is changing the landscape of clinical monitoring and self-monitoring. One of the major impacts will be in healthcare, where increase in number of sensing modalities is providing more and more information on the state of overall wellbeing, behaviour and health. There are numerous applications of mobile computing that range from wellbeing applications, such as physical fitness, stress or burnout up to applications that target mental disorders including bipolar disorder. Use of information provided by mobile computing devices can track the state of the subjects and also allow for experience sampling in order to gather subjective information. This paper reports on the results obtained from a medical trial with monitoring of bipolar disorder patients and how the episodes of the diseases correlate to the analysis of the data sampled from mobile phone acting as a monitoring device.","PeriodicalId":135195,"journal":{"name":"Advances in Mobile Multimedia","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133234006","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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