Pub Date : 2012-06-18DOI: 10.1109/DEST.2012.6227928
Ali Larab, E. Conchon, R. Bastide, N. Singer
The Ageing of population is a major concern for Western societies and leads to the development of new solutions to improve home care for elders, in order to delay their admission in specialized institutions (retirement house, healthcare facility and so on). These new solutions can be hardware or software based, and most often rely on home automation (e.g. motion sensors, temperature, light...). These sensors are used to monitor elderly or disabled people in order to detect their activities and the potential accidents that may occur. In this paper, we present a software architecture based on interoperable components for home care solutions. This architecture considers two kinds of components: the data providers, for instance a motion sensor, and the data consumers that process sensor data in order to infer higher level information such as a fall detector. The overall architecture is loosely coupled by design, in order to ease the addition of new sensors and of new functionalities.
{"title":"A sustainable software architecture for home care monitoring applications","authors":"Ali Larab, E. Conchon, R. Bastide, N. Singer","doi":"10.1109/DEST.2012.6227928","DOIUrl":"https://doi.org/10.1109/DEST.2012.6227928","url":null,"abstract":"The Ageing of population is a major concern for Western societies and leads to the development of new solutions to improve home care for elders, in order to delay their admission in specialized institutions (retirement house, healthcare facility and so on). These new solutions can be hardware or software based, and most often rely on home automation (e.g. motion sensors, temperature, light...). These sensors are used to monitor elderly or disabled people in order to detect their activities and the potential accidents that may occur. In this paper, we present a software architecture based on interoperable components for home care solutions. This architecture considers two kinds of components: the data providers, for instance a motion sensor, and the data consumers that process sensor data in order to infer higher level information such as a fall detector. The overall architecture is loosely coupled by design, in order to ease the addition of new sensors and of new functionalities.","PeriodicalId":320291,"journal":{"name":"2012 6th IEEE International Conference on Digital Ecosystems and Technologies (DEST)","volume":"357 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132895565","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 : 2012-06-18DOI: 10.1109/DEST.2012.6227947
Sebastian Smolorz, Bernardo Wagner
Mobile multi-robot systems are a main focus in robotic research. An obvious advantage of operating with several robots is the fact that solving problems like exploration cooperatively is better, faster and more precise. But there is potentiality for another enhancement, namely the distribution of necessary tasks and algorithms to available computers in such a way that as much processing time as possible is left free to further intensify sophisticated approaches. This paper presents an idea for reaching an optimal task distribution pattern without human intervention based on the concept of Autonomie Computing. A genetic algorithm in combination with the max-plus algebra is proposed to generate, analyze and optimize task distribution patterns.
{"title":"Self-organized distribution of tasks inside an autonomous mobile robotic system","authors":"Sebastian Smolorz, Bernardo Wagner","doi":"10.1109/DEST.2012.6227947","DOIUrl":"https://doi.org/10.1109/DEST.2012.6227947","url":null,"abstract":"Mobile multi-robot systems are a main focus in robotic research. An obvious advantage of operating with several robots is the fact that solving problems like exploration cooperatively is better, faster and more precise. But there is potentiality for another enhancement, namely the distribution of necessary tasks and algorithms to available computers in such a way that as much processing time as possible is left free to further intensify sophisticated approaches. This paper presents an idea for reaching an optimal task distribution pattern without human intervention based on the concept of Autonomie Computing. A genetic algorithm in combination with the max-plus algebra is proposed to generate, analyze and optimize task distribution patterns.","PeriodicalId":320291,"journal":{"name":"2012 6th IEEE International Conference on Digital Ecosystems and Technologies (DEST)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123850327","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 : 2012-06-18DOI: 10.1109/DEST.2012.6227909
Matthew Smith, Christian Szongott, B. Henne, G. Voigt
Big Data is a new label given to a diverse field of data intensive informatics in which the datasets are so large that they become hard to work with effectively. The term has been mainly used in two contexts, firstly as a technological challenge when dealing with dataintensive domains such as high energy physics, astronomy or internet search, and secondly as a sociological problem when data about us is collected and mined by companies such as Facebook, Google, mobile phone companies, retail chains and governments. In this paper we look at this second issue from a new perspective, namely how can the user gain awareness of the personally relevant part Big Data that is publicly available in the social web. The amount of user-generated media uploaded to the web is expanding rapidly and it is beyond the capabilities of any human to sift through it all to see which media impacts our privacy. Based on an analysis of social media in Flickr, Locr, Facebook and Google+, we discuss privacy implications and potential of the emerging trend of geo-tagged social media. We then present a concept with which users can stay informed about which parts of the social Big Data deluge is relevant to them.
{"title":"Big data privacy issues in public social media","authors":"Matthew Smith, Christian Szongott, B. Henne, G. Voigt","doi":"10.1109/DEST.2012.6227909","DOIUrl":"https://doi.org/10.1109/DEST.2012.6227909","url":null,"abstract":"Big Data is a new label given to a diverse field of data intensive informatics in which the datasets are so large that they become hard to work with effectively. The term has been mainly used in two contexts, firstly as a technological challenge when dealing with dataintensive domains such as high energy physics, astronomy or internet search, and secondly as a sociological problem when data about us is collected and mined by companies such as Facebook, Google, mobile phone companies, retail chains and governments. In this paper we look at this second issue from a new perspective, namely how can the user gain awareness of the personally relevant part Big Data that is publicly available in the social web. The amount of user-generated media uploaded to the web is expanding rapidly and it is beyond the capabilities of any human to sift through it all to see which media impacts our privacy. Based on an analysis of social media in Flickr, Locr, Facebook and Google+, we discuss privacy implications and potential of the emerging trend of geo-tagged social media. We then present a concept with which users can stay informed about which parts of the social Big Data deluge is relevant to them.","PeriodicalId":320291,"journal":{"name":"2012 6th IEEE International Conference on Digital Ecosystems and Technologies (DEST)","volume":"31 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129955101","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 : 2012-06-18DOI: 10.1109/DEST.2012.6227937
Andrej Eisfeld, D. McMeekin, A. Karduck
Service infrastructures are often key for the efficient operation of complex environments, such as a large Smart Home infrastructure for a mining camp. The evolution of such service infrastructures, in response to an increased workload on the system or a changing resource allocation, is often tedious and expensive, due to weak evolvability support of its service portfolio. This underpins the need for services to be designed with high evolvability characteristics. Semantic Web technologies have been anticipated as a basis for the required Web service evolution. JSON-LD is a prominent Semantic Web technology used in combination with ontologies, developed with the Web Ontology Language (OWL), to face the evolutionary challenges. Our applied research investigates common Web service tasks, automated using above technologies. It is explained, that this enables the creation of evolutionary building blocks. These building blocks are incrementally combined here for the overall service portfolio, culminating in a model of a semantic agent which excels in its capacity to evolve. Our model is then adopted and assessed for the system infrastructure of the Smart Camp project, as a use case for an agile, complex logistic environment.
{"title":"Complex environment evolution: Challenges with semantic service infrastructures","authors":"Andrej Eisfeld, D. McMeekin, A. Karduck","doi":"10.1109/DEST.2012.6227937","DOIUrl":"https://doi.org/10.1109/DEST.2012.6227937","url":null,"abstract":"Service infrastructures are often key for the efficient operation of complex environments, such as a large Smart Home infrastructure for a mining camp. The evolution of such service infrastructures, in response to an increased workload on the system or a changing resource allocation, is often tedious and expensive, due to weak evolvability support of its service portfolio. This underpins the need for services to be designed with high evolvability characteristics. Semantic Web technologies have been anticipated as a basis for the required Web service evolution. JSON-LD is a prominent Semantic Web technology used in combination with ontologies, developed with the Web Ontology Language (OWL), to face the evolutionary challenges. Our applied research investigates common Web service tasks, automated using above technologies. It is explained, that this enables the creation of evolutionary building blocks. These building blocks are incrementally combined here for the overall service portfolio, culminating in a model of a semantic agent which excels in its capacity to evolve. Our model is then adopted and assessed for the system infrastructure of the Smart Camp project, as a use case for an agile, complex logistic environment.","PeriodicalId":320291,"journal":{"name":"2012 6th IEEE International Conference on Digital Ecosystems and Technologies (DEST)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117108821","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 : 2012-06-18DOI: 10.1109/DEST.2012.6227927
S. Fahl, M. Harbach, Matthew Smith
This paper introduces a novel human-centric, visual, and context-aware access control (AC) system for distributed clinical data management and health information systems. Human-centricity in this context means that medical staff should be able to configure AC rules, both in a timesaving and reliable manner. Since medical data often include meta information about a patient, it is essential that an AC system only grants access requests that meet the patient's intent. Hence, it is desirable that a patient be included in the AC process. To cater for the strong security needs in the medical domain, both the AC policy creation by medical staff as well as the patient-interaction feature need to be supervised by governing policies. While traditional AC systems such as role-based access control offer sufficient security in theory, they lack in comfort and flexibility. This property does not fulfil the requirements of flexible and distributed environments. Distributed medical institutions could enormously benefit from the opportunity of dynamic AC configuration at an end-user level while adhering to legal, ethical or other privacy requirements. Hence, this paper presents a human-centric visual AC model for medical data, addressing usability, information security and patient interaction. To demonstrate our approach, an integration with the DCM4CHE open source system is presented.
{"title":"Human-centric visual access control for clinical data management","authors":"S. Fahl, M. Harbach, Matthew Smith","doi":"10.1109/DEST.2012.6227927","DOIUrl":"https://doi.org/10.1109/DEST.2012.6227927","url":null,"abstract":"This paper introduces a novel human-centric, visual, and context-aware access control (AC) system for distributed clinical data management and health information systems. Human-centricity in this context means that medical staff should be able to configure AC rules, both in a timesaving and reliable manner. Since medical data often include meta information about a patient, it is essential that an AC system only grants access requests that meet the patient's intent. Hence, it is desirable that a patient be included in the AC process. To cater for the strong security needs in the medical domain, both the AC policy creation by medical staff as well as the patient-interaction feature need to be supervised by governing policies. While traditional AC systems such as role-based access control offer sufficient security in theory, they lack in comfort and flexibility. This property does not fulfil the requirements of flexible and distributed environments. Distributed medical institutions could enormously benefit from the opportunity of dynamic AC configuration at an end-user level while adhering to legal, ethical or other privacy requirements. Hence, this paper presents a human-centric visual AC model for medical data, addressing usability, information security and patient interaction. To demonstrate our approach, an integration with the DCM4CHE open source system is presented.","PeriodicalId":320291,"journal":{"name":"2012 6th IEEE International Conference on Digital Ecosystems and Technologies (DEST)","volume":"149 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124357273","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 : 2012-06-18DOI: 10.1109/DEST.2012.6227953
Pietro Colombo, E. Ferrari
Although almost any software application processes personal data, effective development frameworks that properly handle privacy are still missing. This work makes a step to fill this void. This paper investigates requirements and development strategies of a privacy-preserving development framework that deals with privacy since the early phases of the development.
{"title":"Towards a framework to handle privacy since the early phases of the development: Strategies and open challenges","authors":"Pietro Colombo, E. Ferrari","doi":"10.1109/DEST.2012.6227953","DOIUrl":"https://doi.org/10.1109/DEST.2012.6227953","url":null,"abstract":"Although almost any software application processes personal data, effective development frameworks that properly handle privacy are still missing. This work makes a step to fill this void. This paper investigates requirements and development strategies of a privacy-preserving development framework that deals with privacy since the early phases of the development.","PeriodicalId":320291,"journal":{"name":"2012 6th IEEE International Conference on Digital Ecosystems and Technologies (DEST)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123232973","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 : 2012-06-18DOI: 10.1109/DEST.2012.6227910
Christian Fabbricatore, H. Boley, A. Karduck
Efficient resource and energy management is a key research and business area in todays IT markets. Cyber-physical ecosystems, like smart homes (SHs) and smart Environments (SEs) get interconnected, the efficient allocation of resources will become essential. Machine Learning and Semantic Web techniques for improving resource allocation and management are the focus of our research. They allow machines to process information on all levels, inferring expressive knowledge from raw data, in particular resource predictions from usage patterns. Our aim is to devise a novel approach for a machine learning (ML) and resource Management (RM) framework in SEs. It combines ML and Semantic Web techniques and integrates user interaction The main objective is to enable the creation of platforms that decrease the overall resource consumption by learning and predicting various usage patterns, and furthermore making decisions based on user-feedback. For this purpose, we evaluate recent research and applications, elicit framework requirements, and present a framework architecture. The approach and components are assessed and a prototype implementation is described.
{"title":"Machine learning for resource management in smart environments","authors":"Christian Fabbricatore, H. Boley, A. Karduck","doi":"10.1109/DEST.2012.6227910","DOIUrl":"https://doi.org/10.1109/DEST.2012.6227910","url":null,"abstract":"Efficient resource and energy management is a key research and business area in todays IT markets. Cyber-physical ecosystems, like smart homes (SHs) and smart Environments (SEs) get interconnected, the efficient allocation of resources will become essential. Machine Learning and Semantic Web techniques for improving resource allocation and management are the focus of our research. They allow machines to process information on all levels, inferring expressive knowledge from raw data, in particular resource predictions from usage patterns. Our aim is to devise a novel approach for a machine learning (ML) and resource Management (RM) framework in SEs. It combines ML and Semantic Web techniques and integrates user interaction The main objective is to enable the creation of platforms that decrease the overall resource consumption by learning and predicting various usage patterns, and furthermore making decisions based on user-feedback. For this purpose, we evaluate recent research and applications, elicit framework requirements, and present a framework architecture. The approach and components are assessed and a prototype implementation is described.","PeriodicalId":320291,"journal":{"name":"2012 6th IEEE International Conference on Digital Ecosystems and Technologies (DEST)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123241249","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 : 2012-06-18DOI: 10.1109/DEST.2012.6227912
Jingwei Miao, Omar Hasan, Sonia Ben Mokhtar, L. Brunie
In this paper, we present a novel routing protocol for mobile delay tolerant networks, called Community-based Adaptive Spray (CAS). How to maximize routing performance (delivery ratio) and minimize resource consumption (number of message copies) is a common goal in these networks. Our protocol considers the following two aspects toward this goal: 1) selecting the intermediate nodes that are closest to the destination, based on their mobility patterns; 2) dynamically controlling the number of message copies according to the time-to-live of a message. Experiment results demonstrate that our protocol can improve routing performance and resource consumption compared to the state-of-the-art Spray-and-Wait and BUBBLE protocols.
{"title":"A self-regulating protocol for efficient routing in mobile delay tolerant networks","authors":"Jingwei Miao, Omar Hasan, Sonia Ben Mokhtar, L. Brunie","doi":"10.1109/DEST.2012.6227912","DOIUrl":"https://doi.org/10.1109/DEST.2012.6227912","url":null,"abstract":"In this paper, we present a novel routing protocol for mobile delay tolerant networks, called Community-based Adaptive Spray (CAS). How to maximize routing performance (delivery ratio) and minimize resource consumption (number of message copies) is a common goal in these networks. Our protocol considers the following two aspects toward this goal: 1) selecting the intermediate nodes that are closest to the destination, based on their mobility patterns; 2) dynamically controlling the number of message copies according to the time-to-live of a message. Experiment results demonstrate that our protocol can improve routing performance and resource consumption compared to the state-of-the-art Spray-and-Wait and BUBBLE protocols.","PeriodicalId":320291,"journal":{"name":"2012 6th IEEE International Conference on Digital Ecosystems and Technologies (DEST)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123733703","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 : 2012-06-18DOI: 10.1109/DEST.2012.6227920
N. Brown, R. Greenough, K. Vikhorev, S. Khattak
Energy efficiency can often learn much from manufacturing in terms of available analysis techniques, from basic time series analysis through to fuzzy and knowledge based systems and artificial intelligence. On the other hand, manufacturing in many sectors has yet to make use of energy data much beyond finance. Techniques such as complex event processing and data stream analysis can be applied in near real time to determine process health. Conventional energy data, with a half-hourly time interval through fiscal metering, has been sufficient for off-line process control in the past, but to increase the utility of manufacturing energy data, a step change is needed in data frequency, accuracy, precision, portability, and documentation. This paper brings together co-dependent issues of data structure, data quality, and front-end instrumentation which advanced processing techniques must build on, discussing what must be done to use gather and use energy data more effectively, to reduce energy use and emissions, improve quality, and save costs.
{"title":"Precursors to using energy data as a manufacturing process variable","authors":"N. Brown, R. Greenough, K. Vikhorev, S. Khattak","doi":"10.1109/DEST.2012.6227920","DOIUrl":"https://doi.org/10.1109/DEST.2012.6227920","url":null,"abstract":"Energy efficiency can often learn much from manufacturing in terms of available analysis techniques, from basic time series analysis through to fuzzy and knowledge based systems and artificial intelligence. On the other hand, manufacturing in many sectors has yet to make use of energy data much beyond finance. Techniques such as complex event processing and data stream analysis can be applied in near real time to determine process health. Conventional energy data, with a half-hourly time interval through fiscal metering, has been sufficient for off-line process control in the past, but to increase the utility of manufacturing energy data, a step change is needed in data frequency, accuracy, precision, portability, and documentation. This paper brings together co-dependent issues of data structure, data quality, and front-end instrumentation which advanced processing techniques must build on, discussing what must be done to use gather and use energy data more effectively, to reduce energy use and emissions, improve quality, and save costs.","PeriodicalId":320291,"journal":{"name":"2012 6th IEEE International Conference on Digital Ecosystems and Technologies (DEST)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129605361","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 : 2012-06-18DOI: 10.1109/DEST.2012.6227916
N. Sabry, P. Krause
Carbon dioxide is one of the main greenhouse gases (GHS) that is widely blamed for climate change. Reducing greenhouse gas emissions is becoming one of the most challenging global issues. Increase in the concentration of carbon dioxide (CO2) in the atmosphere is primarily attributed to fossil fuel burning. There is a need for better planning of the electricity generation capacity expansion to meet the power demand, which powers the Internet's routers and data centres, as well as to achieve an overall reduction in CO2 emissions. The data centres, networking, cloud computing resources should reduce their carbon footprint in order to have a positive impact for the cloud computing service providers and the customers. We try to develop a linear programming model to evaluate the effectiveness of possible CO2 mitigation for the brown energy (non-renewable energy) in the Internet.
{"title":"Potential CO2 mitigation in digital ecosystems","authors":"N. Sabry, P. Krause","doi":"10.1109/DEST.2012.6227916","DOIUrl":"https://doi.org/10.1109/DEST.2012.6227916","url":null,"abstract":"Carbon dioxide is one of the main greenhouse gases (GHS) that is widely blamed for climate change. Reducing greenhouse gas emissions is becoming one of the most challenging global issues. Increase in the concentration of carbon dioxide (CO2) in the atmosphere is primarily attributed to fossil fuel burning. There is a need for better planning of the electricity generation capacity expansion to meet the power demand, which powers the Internet's routers and data centres, as well as to achieve an overall reduction in CO2 emissions. The data centres, networking, cloud computing resources should reduce their carbon footprint in order to have a positive impact for the cloud computing service providers and the customers. We try to develop a linear programming model to evaluate the effectiveness of possible CO2 mitigation for the brown energy (non-renewable energy) in the Internet.","PeriodicalId":320291,"journal":{"name":"2012 6th IEEE International Conference on Digital Ecosystems and Technologies (DEST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127104063","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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