Searching for reliable information in textual data with highly heterogeneous vocabulary yields major difficulties. The task at hand was to study an amalgam of transcripts of think-aloud experiments conducted with entrepreneurs with different backgrounds. The many different backgrounds of the entrepreneurs are translated into the high variability of the vocabulary found in the transcripts. In an effort to reduce this variability while using the method for investigating textual databases in the form of association rules presented by Agrawal et al. [1], is exposed a novel approach based on the use of synonyms to standardize the data prior to applying association rules. Moreover, as association rules retrieval techniques produce large datasets and because those statistical objects express relationships between items, a method to analyze those discovered associations in the form of a network is further presented. This enables the use of Graph Theory/Network Science, two mature related fields whose methods can lead to interesting and nontrivial discoveries.
{"title":"Mining and visualizing robust maximal association rules on highly variable textual data in entrepreneurship","authors":"Frédéric Simard, J. St-Pierre, Ismaïl Biskri","doi":"10.1145/3012071.3012097","DOIUrl":"https://doi.org/10.1145/3012071.3012097","url":null,"abstract":"Searching for reliable information in textual data with highly heterogeneous vocabulary yields major difficulties. The task at hand was to study an amalgam of transcripts of think-aloud experiments conducted with entrepreneurs with different backgrounds. The many different backgrounds of the entrepreneurs are translated into the high variability of the vocabulary found in the transcripts. In an effort to reduce this variability while using the method for investigating textual databases in the form of association rules presented by Agrawal et al. [1], is exposed a novel approach based on the use of synonyms to standardize the data prior to applying association rules. Moreover, as association rules retrieval techniques produce large datasets and because those statistical objects express relationships between items, a method to analyze those discovered associations in the form of a network is further presented. This enables the use of Graph Theory/Network Science, two mature related fields whose methods can lead to interesting and nontrivial discoveries.","PeriodicalId":294250,"journal":{"name":"Proceedings of the 8th International Conference on Management of Digital EcoSystems","volume":"127 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128613115","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}
Mobile cloud computing (MCC) has attracted more and more attention from both Small and Medium Enterprises (SMEs). MCC provides access to cloud services for mobile devices. With the growing popularity of smart mobile devices, customers need efficient and new high quality services. In this context, mobile ERP services management and adaptation at real time are becoming a challenging task. However, it is necessary to handle in a dynamic intelligent and transparent platform various mobile cloud services provided by multiple cloud providers with several qualities. This paper presents CloudCxQERP platform, which is a cloud-based semantic platform for dynamic management of context-aware mobile ERP applications. It is based on semantic web technologies and cloud computing and provides fast ERP development process and "an ecosystem" of enterprises that ensures quality customer service. Moreover, our platform provides a middleware that offers to users more efficient services corresponding to current situations and adapts its ERP applications more quickly and cost effectively. Experiments are based on online packaging boxes services.
{"title":"Cloud-based semantic platform for dynamic management of context-aware mobile ERP applications","authors":"Hamza Reffad, A. Alti, P. Roose","doi":"10.1145/3012071.3012076","DOIUrl":"https://doi.org/10.1145/3012071.3012076","url":null,"abstract":"Mobile cloud computing (MCC) has attracted more and more attention from both Small and Medium Enterprises (SMEs). MCC provides access to cloud services for mobile devices. With the growing popularity of smart mobile devices, customers need efficient and new high quality services. In this context, mobile ERP services management and adaptation at real time are becoming a challenging task. However, it is necessary to handle in a dynamic intelligent and transparent platform various mobile cloud services provided by multiple cloud providers with several qualities. This paper presents CloudCxQERP platform, which is a cloud-based semantic platform for dynamic management of context-aware mobile ERP applications. It is based on semantic web technologies and cloud computing and provides fast ERP development process and \"an ecosystem\" of enterprises that ensures quality customer service. Moreover, our platform provides a middleware that offers to users more efficient services corresponding to current situations and adapts its ERP applications more quickly and cost effectively. Experiments are based on online packaging boxes services.","PeriodicalId":294250,"journal":{"name":"Proceedings of the 8th International Conference on Management of Digital EcoSystems","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124872781","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, the principle of image mining plays a vital role in various areas of our life, where numerous frameworks based on image mining are proposed for object recognition, object tracking, sensing images and medical image diagnosis. Nevertheless, the research in the image authentication based on image mining is still confined. Therefore, this paper comes to present an efficient engagement between the frequent pattern mining and digital watermarking to contribute significantly in the authentication of images transmitted via public networks. The proposed framework exploits some robust features of image to extract the frequent patterns in the image data. The maximal relevant patterns are used to discriminate between the textured and smooth blocks within the image, where the texture blocks are more appropriate to embed the secret data than smooth blocks. The experiment's result proves the efficiency of the proposed framework in terms of stabilization and robustness against different kind of attacks. The results are interesting and remarkable to preserve the image authentication.
{"title":"A robust associative watermarking technique based on frequent pattern mining and texture analysis","authors":"Musab Ghadi, L. Laouamer, Laurent Nana, A. Pascu","doi":"10.1145/3012071.3012101","DOIUrl":"https://doi.org/10.1145/3012071.3012101","url":null,"abstract":"Nowadays, the principle of image mining plays a vital role in various areas of our life, where numerous frameworks based on image mining are proposed for object recognition, object tracking, sensing images and medical image diagnosis. Nevertheless, the research in the image authentication based on image mining is still confined. Therefore, this paper comes to present an efficient engagement between the frequent pattern mining and digital watermarking to contribute significantly in the authentication of images transmitted via public networks. The proposed framework exploits some robust features of image to extract the frequent patterns in the image data. The maximal relevant patterns are used to discriminate between the textured and smooth blocks within the image, where the texture blocks are more appropriate to embed the secret data than smooth blocks. The experiment's result proves the efficiency of the proposed framework in terms of stabilization and robustness against different kind of attacks. The results are interesting and remarkable to preserve the image authentication.","PeriodicalId":294250,"journal":{"name":"Proceedings of the 8th International Conference on Management of Digital EcoSystems","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115049364","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}
Rafael Angarita, M. Rukoz, Maude Manouvrier, Yudith Cardinale
In the context of service-oriented applications, the self-healing property provides reliable execution in order to support failures and assist automatic recovery techniques. This paper presents a knowledge-based approach for self-healing Composite Service (CS) applications. A CS is an application composed by a set of services interacting each other and invoked on the Web. Our approach is supported by Service Agents, which are in charge of the CS fault-tolerance execution control, making decisions about the selection of recovery and proactive strategies. Service Agents decisions are based on the information they have about the whole application, about themselves, and about what it is expected and what it is really happening at run-time. Hence, application knowledge for decision making comprises off-line precomputed global and local information, user QoS preferences, and propagated actual run-time information. Our approach is evaluated experimentally using a case study.
{"title":"A knowledge-based approach for self-healing service-oriented applications","authors":"Rafael Angarita, M. Rukoz, Maude Manouvrier, Yudith Cardinale","doi":"10.1145/3012071.3012100","DOIUrl":"https://doi.org/10.1145/3012071.3012100","url":null,"abstract":"In the context of service-oriented applications, the self-healing property provides reliable execution in order to support failures and assist automatic recovery techniques. This paper presents a knowledge-based approach for self-healing Composite Service (CS) applications. A CS is an application composed by a set of services interacting each other and invoked on the Web. Our approach is supported by Service Agents, which are in charge of the CS fault-tolerance execution control, making decisions about the selection of recovery and proactive strategies. Service Agents decisions are based on the information they have about the whole application, about themselves, and about what it is expected and what it is really happening at run-time. Hence, application knowledge for decision making comprises off-line precomputed global and local information, user QoS preferences, and propagated actual run-time information. Our approach is evaluated experimentally using a case study.","PeriodicalId":294250,"journal":{"name":"Proceedings of the 8th International Conference on Management of Digital EcoSystems","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123354579","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}
Unstructured data refers to information that either does not have a pre-defined data model or is not organized in a pre-defined manner. Many studies confirm that around 80--90% of all produced information is in unstructured form. So this kind of content, rich and most importantly too precious, must be integrated and taken into consideration for processing and exploitation: extraction of relevant information from heterogeneous textual data. The goal of the research described here is to present an approach for automating the detection and the extraction of meaning from unstructured Web using its normalized part: Web of data & Linked Open data (LOD) such as RDF WordNet, DBpedia, etc. The process follows a "cyclical process" that consists of two phases (a) creating & generating normalized smart data by the experts or automatically, (b) exploiting the created data in (a), as "validated expert data", to analyze the Big Data and generate automatically new ones by learning from Linked Open Data (LOD). The approach is based on a range of linguistic and ontological techniques, in the context of Big Data. A software, EC3, is being implemented and at LIP6. EC3 is actually tested on very large corpuses on electronic supports, provided by the labex OBVIL (http://obvil.paris-sorbonne.fr) and the BNF (National Library of France).
非结构化数据是指没有预定义的数据模型或没有以预定义的方式组织的信息。许多研究证实，大约80% -90%的信息都是非结构化的。因此，这种内容丰富，最重要的是过于宝贵，必须整合和考虑处理和开发:从异构文本数据中提取相关信息。本文所描述的研究目标是提出一种方法，利用非结构化Web的规范化部分(Web of data & Linked Open data, LOD)，如RDF WordNet、DBpedia等，从非结构化Web中自动检测和提取意义。该过程遵循一个“循环过程”，包括两个阶段(a)由专家或自动创建和生成规范化的智能数据，(b)利用(a)中创建的数据作为“经过验证的专家数据”，分析大数据并通过学习关联开放数据(LOD)自动生成新数据。该方法基于大数据背景下的一系列语言学和本体论技术。一个名为EC3的软件正在LIP6上实现。EC3实际上是在非常大的语料库上测试的，由labex OBVIL (http://obvil.paris-sorbonne.fr)和BNF(法国国家图书馆)提供电子支持。
{"title":"Towards an automatic analyze and standardization of unstructured data in the context of big and linked data","authors":"Hammou Fadili, C. Jouis","doi":"10.1145/3012071.3012103","DOIUrl":"https://doi.org/10.1145/3012071.3012103","url":null,"abstract":"Unstructured data refers to information that either does not have a pre-defined data model or is not organized in a pre-defined manner. Many studies confirm that around 80--90% of all produced information is in unstructured form. So this kind of content, rich and most importantly too precious, must be integrated and taken into consideration for processing and exploitation: extraction of relevant information from heterogeneous textual data. The goal of the research described here is to present an approach for automating the detection and the extraction of meaning from unstructured Web using its normalized part: Web of data & Linked Open data (LOD) such as RDF WordNet, DBpedia, etc. The process follows a \"cyclical process\" that consists of two phases (a) creating & generating normalized smart data by the experts or automatically, (b) exploiting the created data in (a), as \"validated expert data\", to analyze the Big Data and generate automatically new ones by learning from Linked Open Data (LOD). The approach is based on a range of linguistic and ontological techniques, in the context of Big Data. A software, EC3, is being implemented and at LIP6. EC3 is actually tested on very large corpuses on electronic supports, provided by the labex OBVIL (http://obvil.paris-sorbonne.fr) and the BNF (National Library of France).","PeriodicalId":294250,"journal":{"name":"Proceedings of the 8th International Conference on Management of Digital EcoSystems","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126451316","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}
This research aims to collect the extracted HerbalMedicinalProperty relations from downloaded herbal-plant documents for creating the herbal-medicinal-property-network based representation. An HerbalMedicinalProperty relation is a semantic relation between one herbal-plant-component concept and several herbal-medicinal-property-concept expressions on texts and vice versa. An herbal-plant-component occurrence is a noun-phrase expression and each herbal-medicinal-property- concept occurrence is an event expression by a verb-phrase of EDU (an Elementary Discourse Unit or a simple sentence). The herbal-medicinal-property-network based representation benefits a recommendation system of solving health-problems on web-boards. The research has two main problems: 1) how to extract HerbalMedicinalProperty relations from the documents, and 2) how to collect the HerbalMedicinalProperty relations for creating the herbal-medicinal-property-network based representation. Therefore, we propose applying a co-occurrence of N-Words (or N-Word-Co) including N-Word-Co size learning on the verb phrase to identify several medicinal-property-concept EDU occurrences over the documents after the linguistic phenomena has been applied to solve the herbal-plant-component concepts. The extracted HerbalMedicinalProperty relations are then collected as a matrix of herbal-plant names, herbal-plant components, and herbal-medicinal properties for creating the herbal-medicinal-property-network based representation. The research results provide the high precision of the HerbalMedicinalProperty-relation extraction from the documents.
{"title":"Collection of HerbalMedicinalProperty relation extracted from texts","authors":"C. Pechsiri, Onuma Moolwat","doi":"10.1145/3012071.3012075","DOIUrl":"https://doi.org/10.1145/3012071.3012075","url":null,"abstract":"This research aims to collect the extracted HerbalMedicinalProperty relations from downloaded herbal-plant documents for creating the herbal-medicinal-property-network based representation. An HerbalMedicinalProperty relation is a semantic relation between one herbal-plant-component concept and several herbal-medicinal-property-concept expressions on texts and vice versa. An herbal-plant-component occurrence is a noun-phrase expression and each herbal-medicinal-property- concept occurrence is an event expression by a verb-phrase of EDU (an Elementary Discourse Unit or a simple sentence). The herbal-medicinal-property-network based representation benefits a recommendation system of solving health-problems on web-boards. The research has two main problems: 1) how to extract HerbalMedicinalProperty relations from the documents, and 2) how to collect the HerbalMedicinalProperty relations for creating the herbal-medicinal-property-network based representation. Therefore, we propose applying a co-occurrence of N-Words (or N-Word-Co) including N-Word-Co size learning on the verb phrase to identify several medicinal-property-concept EDU occurrences over the documents after the linguistic phenomena has been applied to solve the herbal-plant-component concepts. The extracted HerbalMedicinalProperty relations are then collected as a matrix of herbal-plant names, herbal-plant components, and herbal-medicinal properties for creating the herbal-medicinal-property-network based representation. The research results provide the high precision of the HerbalMedicinalProperty-relation extraction from the documents.","PeriodicalId":294250,"journal":{"name":"Proceedings of the 8th International Conference on Management of Digital EcoSystems","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126977812","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 digital service ecosystems (DSEs), business stakeholders provide the most important driving factors and managing them is a challenge. It requires systems and services to handle uncertainty. Uncertainty in DSEs can be attributed to several factors; for example, dynamic nature and the unknown deployment environment, and change and evolution of requirements. Therefore, there is a need for novel software engineering methods and tools to handle these uncertainties in DSEs. In this regard, valuable lessons can be learnt from the autonomic computing (AC) paradigm and systems that are characterized by self-* properties. This paper proposes a novel, systematic service engineering methodology called ADSEng for ecosystem-based engineering of autonomous digital services. In the current research, the means of handling uncertainty from requirements to architecture and running systems are investigated. To do this, two interrelated research problems are studied: reflexivity that is realized using AC techniques, and evolvability of the ecosystem, supported by automated transformations. Our main contributions are: (i) a modeling methodology from uncertainty specification to runtime models and (ii) quality-driven adaptation patterns embodied by digital services. The paper also presents key lessons learnt from the research experience thus far.
{"title":"ADSEng: a model-based methodology for autonomous digital service engineering","authors":"Dhaminda B. Abeywickrama, E. Ovaska","doi":"10.1145/3012071.3012072","DOIUrl":"https://doi.org/10.1145/3012071.3012072","url":null,"abstract":"In digital service ecosystems (DSEs), business stakeholders provide the most important driving factors and managing them is a challenge. It requires systems and services to handle uncertainty. Uncertainty in DSEs can be attributed to several factors; for example, dynamic nature and the unknown deployment environment, and change and evolution of requirements. Therefore, there is a need for novel software engineering methods and tools to handle these uncertainties in DSEs. In this regard, valuable lessons can be learnt from the autonomic computing (AC) paradigm and systems that are characterized by self-* properties. This paper proposes a novel, systematic service engineering methodology called ADSEng for ecosystem-based engineering of autonomous digital services. In the current research, the means of handling uncertainty from requirements to architecture and running systems are investigated. To do this, two interrelated research problems are studied: reflexivity that is realized using AC techniques, and evolvability of the ecosystem, supported by automated transformations. Our main contributions are: (i) a modeling methodology from uncertainty specification to runtime models and (ii) quality-driven adaptation patterns embodied by digital services. The paper also presents key lessons learnt from the research experience thus far.","PeriodicalId":294250,"journal":{"name":"Proceedings of the 8th International Conference on Management of Digital EcoSystems","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127072511","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}
Sarah Zenasni, E. Kergosien, M. Roche, M. Teisseire
In the past few years, texts have become an important spatial data resource, in addition to maps, satellite images and GPS. Electronic written texts used in mediated interactions, especially short messages (SMS, tweets, etc.), have triggered the emergence of new ways of writing. Extracting information from such short messages, which represent a rich source of information and opinion, is highly important due to the new and challenging text style. Short messages are, however, difficult to analyze because of their brief, unstructured and informal nature. The work presented in this paper is aimed at extracting spatial information from two authentic corpora of SMS and tweets in French in order to take advantage of the vast amount of geographical knowledge expressed in diverse natural language texts. We propose a process in which, firstly, we extract new spatial entities (e.g. Monpelier, Montpel are associated with the place name Montpellier). Secondly, we identify new spatial relations that precede these spatial entities (e.g. sur, par, etc.). Finally, we propose a general pattern for discovering spatial relations (e.g. SR+ Preposition). The task is very challenging and complex due to the specificity of short messages language, which is based on weakly standardized modes of writing (lexical creation, massive use of abbreviations, textual variants, etc.). The experiments that were carried out on the two corpora 88milSMS and Tweets highlight the efficiency of our proposed strategy for identifying new kinds of spatial entities and relations.
{"title":"Extracting new spatial entities and relations from short messages","authors":"Sarah Zenasni, E. Kergosien, M. Roche, M. Teisseire","doi":"10.1145/3012071.3012079","DOIUrl":"https://doi.org/10.1145/3012071.3012079","url":null,"abstract":"In the past few years, texts have become an important spatial data resource, in addition to maps, satellite images and GPS. Electronic written texts used in mediated interactions, especially short messages (SMS, tweets, etc.), have triggered the emergence of new ways of writing. Extracting information from such short messages, which represent a rich source of information and opinion, is highly important due to the new and challenging text style. Short messages are, however, difficult to analyze because of their brief, unstructured and informal nature. The work presented in this paper is aimed at extracting spatial information from two authentic corpora of SMS and tweets in French in order to take advantage of the vast amount of geographical knowledge expressed in diverse natural language texts. We propose a process in which, firstly, we extract new spatial entities (e.g. Monpelier, Montpel are associated with the place name Montpellier). Secondly, we identify new spatial relations that precede these spatial entities (e.g. sur, par, etc.). Finally, we propose a general pattern for discovering spatial relations (e.g. SR+ Preposition). The task is very challenging and complex due to the specificity of short messages language, which is based on weakly standardized modes of writing (lexical creation, massive use of abbreviations, textual variants, etc.). The experiments that were carried out on the two corpora 88milSMS and Tweets highlight the efficiency of our proposed strategy for identifying new kinds of spatial entities and relations.","PeriodicalId":294250,"journal":{"name":"Proceedings of the 8th International Conference on Management of Digital EcoSystems","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134326070","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}
Kirsi Kotilainen, Matti Sommarberg, P. Järventausta, Pami Aalto
Climate change is putting pressure on governments, policy makers and international organizations to increase energy efficiency and move towards using renewable energy sources. To meet growing need for energy and at the same time comply with ecologic and economic demands, the energy market structure is slowly transitioning from a centralized system to more interactive and decentralized model based on Smart Grid technology in which also end users may play a role as prosumers i.e. as producers and consumers of energy. Different scenarios exist for the level of prosumer participation in the future flexible energy ecosystem. In this paper, we propose a framework for Prosumer centric Digital Energy Ecosystem based on Smart Grid technologies, decentralized energy production using renewable energy sources and complex network of new and incumbent actors, business models and processes.
{"title":"Prosumer centric digital energy ecosystem framework","authors":"Kirsi Kotilainen, Matti Sommarberg, P. Järventausta, Pami Aalto","doi":"10.1145/3012071.3012080","DOIUrl":"https://doi.org/10.1145/3012071.3012080","url":null,"abstract":"Climate change is putting pressure on governments, policy makers and international organizations to increase energy efficiency and move towards using renewable energy sources. To meet growing need for energy and at the same time comply with ecologic and economic demands, the energy market structure is slowly transitioning from a centralized system to more interactive and decentralized model based on Smart Grid technology in which also end users may play a role as prosumers i.e. as producers and consumers of energy. Different scenarios exist for the level of prosumer participation in the future flexible energy ecosystem. In this paper, we propose a framework for Prosumer centric Digital Energy Ecosystem based on Smart Grid technologies, decentralized energy production using renewable energy sources and complex network of new and incumbent actors, business models and processes.","PeriodicalId":294250,"journal":{"name":"Proceedings of the 8th International Conference on Management of Digital EcoSystems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127105712","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}
Noemi Biancone, Chiara Bicchielli, F. Ferri, P. Grifoni
The paper has the objective to define a fall detection methodology using the sensors available on smartphone. Furthermore, the paper proposes a platform that support the remote fall detection methodology modeling the emergency management by using a collaborative approach. The advantage of the proposed platform is that the fall detection doesn't need of a new specific hardware as the proposed solution is based on a device such as a smartphone already widely used by senior citizens. In past studies and proposed systems the results of sensors applied on skin or on cloths showed better results than sensors equipping the smartphone. To overcome the low performances of former approaches using the accelerometer and , in some cases, the gyroscope equipping the smartphone the proposed methodology use five sensors equipping the smartphone: accelerometer, gyroscope, proximity, microphone and GPS. The results obtained using the five sensors are comparable to those obtained with skin and wearable sensors, but with the advantage to avoid the use of dedicated hardware.
{"title":"Falls detection and assessment","authors":"Noemi Biancone, Chiara Bicchielli, F. Ferri, P. Grifoni","doi":"10.1145/3012071.3012088","DOIUrl":"https://doi.org/10.1145/3012071.3012088","url":null,"abstract":"The paper has the objective to define a fall detection methodology using the sensors available on smartphone. Furthermore, the paper proposes a platform that support the remote fall detection methodology modeling the emergency management by using a collaborative approach. The advantage of the proposed platform is that the fall detection doesn't need of a new specific hardware as the proposed solution is based on a device such as a smartphone already widely used by senior citizens. In past studies and proposed systems the results of sensors applied on skin or on cloths showed better results than sensors equipping the smartphone. To overcome the low performances of former approaches using the accelerometer and , in some cases, the gyroscope equipping the smartphone the proposed methodology use five sensors equipping the smartphone: accelerometer, gyroscope, proximity, microphone and GPS. The results obtained using the five sensors are comparable to those obtained with skin and wearable sensors, but with the advantage to avoid the use of dedicated hardware.","PeriodicalId":294250,"journal":{"name":"Proceedings of the 8th International Conference on Management of Digital EcoSystems","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126400767","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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