Summary form only given. We are living with networks surrounding us. The first such network was probably the postal services, and now the youngsters are already using 4G mobile internet. Megawatts and gigawatts are not so easy to handle than megabytes and gigabytes. Transferring huge amounts of electrical energy requires big investments. The story started at the end of the 19th century with steam engines, generating power first for the factories, later for the settlements of the workers, moving close to the big industrial centres. Connecting those resulted in national grids available at least for the urbanized areas. It may sound strange, but the consumption habits have changed very little during the last 120 years. There is a meter outside the house and anybody can draw any time as much energy as he/she pleases. All this happening with fixed prices not depending upon the actual state of the supply and the demand - which is rather strange nowadays. The events on 11th of Sept. 2001 taught us that we are vulnerable even at home. The 2003 big blackout lasting four days on the east coast of USA and causing huge damages and even losses of lives implied that something has to be done: it should not happen any more. We already know from the information technology: networks should be redundant, diverse, distributed, hierarchically built, self-diagnosing and self-healing in order to be able to provide robust and reliable service. How to achieve that? On the other hand, the unpredictable and renewable energy resources are growing very rapidly. Photovoltaic cells, wind turbines, biogas, etc. They are relatively small, but very numerous and they cannot be handled efficiently in the oldfashioned centralized way. We need local energy storage as much as possible to cover periods of time when the sun is down and the wind is not blowing. That implies that customers have to be smart, more intelligent to optimize the various possibilities in the environment of new, fast-changing flexible electricity tariffs. Different countries are in different situation, depending upon the different history and levels of development. There is no common approach to improve. There will be different ideas, different methods presented and compared in a relatively easy understandable way. This is where our knowledge and experience steps in: simulation. Experimenting with big power is expensive, but the modeling is straightforward and reliable, and different approaches can be worked out relatively easy and this should not last very long periods of time.
{"title":"Intelligent electrical energy distribution and consumption: SMARTGRID [keynote speaker 3]","authors":"J. S. Janosy","doi":"10.1109/EMS.2014.103","DOIUrl":"https://doi.org/10.1109/EMS.2014.103","url":null,"abstract":"Summary form only given. We are living with networks surrounding us. The first such network was probably the postal services, and now the youngsters are already using 4G mobile internet. Megawatts and gigawatts are not so easy to handle than megabytes and gigabytes. Transferring huge amounts of electrical energy requires big investments. The story started at the end of the 19th century with steam engines, generating power first for the factories, later for the settlements of the workers, moving close to the big industrial centres. Connecting those resulted in national grids available at least for the urbanized areas. It may sound strange, but the consumption habits have changed very little during the last 120 years. There is a meter outside the house and anybody can draw any time as much energy as he/she pleases. All this happening with fixed prices not depending upon the actual state of the supply and the demand - which is rather strange nowadays. The events on 11th of Sept. 2001 taught us that we are vulnerable even at home. The 2003 big blackout lasting four days on the east coast of USA and causing huge damages and even losses of lives implied that something has to be done: it should not happen any more. We already know from the information technology: networks should be redundant, diverse, distributed, hierarchically built, self-diagnosing and self-healing in order to be able to provide robust and reliable service. How to achieve that? On the other hand, the unpredictable and renewable energy resources are growing very rapidly. Photovoltaic cells, wind turbines, biogas, etc. They are relatively small, but very numerous and they cannot be handled efficiently in the oldfashioned centralized way. We need local energy storage as much as possible to cover periods of time when the sun is down and the wind is not blowing. That implies that customers have to be smart, more intelligent to optimize the various possibilities in the environment of new, fast-changing flexible electricity tariffs. Different countries are in different situation, depending upon the different history and levels of development. There is no common approach to improve. There will be different ideas, different methods presented and compared in a relatively easy understandable way. This is where our knowledge and experience steps in: simulation. Experimenting with big power is expensive, but the modeling is straightforward and reliable, and different approaches can be worked out relatively easy and this should not last very long periods of time.","PeriodicalId":350614,"journal":{"name":"European Symposium on Computer Modeling and Simulation","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130778768","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}
Summary form only given, as follows. Feature selection (FS) addresses the problem of selecting those system descriptors that are most predictive of a given outcome. Unlike other dimensionality reduction methods, with FS the original meaning of the features is preserved. This has found application in tasks that involve datasets containing very large numbers of features that might otherwise be impractical to model and process (e.g., large-scale image analysis, text processing and Web content classification). This talk will focus on the development and application of FS mechanisms based on rough and fuzzyrough theories. Such techniques provide a means by which data can be effectively reduced without the need for user-supplied information. In particular, fuzzy-rough feature selection (FRFS) works with discrete and real-valued noisy data (or a mixture of both). As such, it is suitable for regression as well as for classification. The only additional information required is the fuzzy partition for each feature, which can be automatically derived from the data. FRFS has been shown to be a powerful technique for data dimensionality reduction. In introducing the general background of FS, this talk will first cover the rough-set-based approach, before focusing on FRFS and its application to real-world problems. The talk will conclude with an outline of opportunities for further development.
{"title":"Feature selection in data-driven systems modelling [keynote speaker 1]","authors":"Q. Shen","doi":"10.1109/EMS.2014.79","DOIUrl":"https://doi.org/10.1109/EMS.2014.79","url":null,"abstract":"Summary form only given, as follows. Feature selection (FS) addresses the problem of selecting those system descriptors that are most predictive of a given outcome. Unlike other dimensionality reduction methods, with FS the original meaning of the features is preserved. This has found application in tasks that involve datasets containing very large numbers of features that might otherwise be impractical to model and process (e.g., large-scale image analysis, text processing and Web content classification). This talk will focus on the development and application of FS mechanisms based on rough and fuzzyrough theories. Such techniques provide a means by which data can be effectively reduced without the need for user-supplied information. In particular, fuzzy-rough feature selection (FRFS) works with discrete and real-valued noisy data (or a mixture of both). As such, it is suitable for regression as well as for classification. The only additional information required is the fuzzy partition for each feature, which can be automatically derived from the data. FRFS has been shown to be a powerful technique for data dimensionality reduction. In introducing the general background of FS, this talk will first cover the rough-set-based approach, before focusing on FRFS and its application to real-world problems. The talk will conclude with an outline of opportunities for further development.","PeriodicalId":350614,"journal":{"name":"European Symposium on Computer Modeling and Simulation","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125087027","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}
Summary form only given, as follows. The resolution power of experiments is improving steadily and the data rate production is rapidly increasing. The success of the experiments depends critically on handling effectively and efficiently huge amounts of data. The on-detector reduction of the data rate will be a major topic as only a fraction of the data can be archived for later long-term analyses. In the project “Large Scale Data Management and Analysis” (LSDMA) several Helmholtz centres and German universities are cooperating in order to support researchers in maintaining their huge amounts of data. Besides supporting individual scientific communities, generic services are being developed, e.g. Federated identity management; Federated data access; Meta data repositories; Archive services; Monitoring, modelling, optimization; and Data intensive computing & analysis. The talk will explore the general challenges of Big Data. Several instructive examples from different scientific communities are presented. An overview of the current status of the LSDMA project is given. In addition, recent results on real-time and near-real time analysis of Big Data are presented.
{"title":"Big data in [keynote speaker 2]","authors":"H. Hessling","doi":"10.1109/EMS.2014.80","DOIUrl":"https://doi.org/10.1109/EMS.2014.80","url":null,"abstract":"Summary form only given, as follows. The resolution power of experiments is improving steadily and the data rate production is rapidly increasing. The success of the experiments depends critically on handling effectively and efficiently huge amounts of data. The on-detector reduction of the data rate will be a major topic as only a fraction of the data can be archived for later long-term analyses. In the project “Large Scale Data Management and Analysis” (LSDMA) several Helmholtz centres and German universities are cooperating in order to support researchers in maintaining their huge amounts of data. Besides supporting individual scientific communities, generic services are being developed, e.g. Federated identity management; Federated data access; Meta data repositories; Archive services; Monitoring, modelling, optimization; and Data intensive computing & analysis. The talk will explore the general challenges of Big Data. Several instructive examples from different scientific communities are presented. An overview of the current status of the LSDMA project is given. In addition, recent results on real-time and near-real time analysis of Big Data are presented.","PeriodicalId":350614,"journal":{"name":"European Symposium on Computer Modeling and Simulation","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124563734","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}
Jakob L. Honeder, P. Goebel, T. Mandl, M. Vincze, M. Schachinger
A structure based finite element analysis (FEA) model can be a means to gain better insight on how surface electromyography (EMG) signals are affected by limb geometry and tissue structures. Beyond that, and to optimize the control of myoelectric prostheses, such models can be used to evaluate signal separation algorithms, or to test the performance of different electrode configurations without the need to have several measurement sessions with a human subject present. This work presents a novel approach to the approximate modeling of a three-dimensional, subject-specific, generic EMG model by using FEA. The problems stemming from the nonrigid and irregular geometry of human body parts, the nonlinear tissue properties over frequency and temperature, the various muscle-fiber innervation possibilities, and the overall complexity of the model, are solved by defining an adequate fiber source description, simulating the volume conductor FEA model as being quasi-stationary, normalizing the true forearm geometry to a cylinder and unrolling it to be able to apply Helmholtz's principle of superposition to combine simulation results for the solving of more complex muscle-fiber set-ups. Thus, the source description presented herein appears suitable for application to different subject-specific geometries, as shown additionally by the setting into the 'Musculus pectoralis' of a targeted muscle reinnervation subject. Hence in conclusion, the strategy applied yields an overall reduced complexity of the FEA model, and therefore, substantially simplifies the processing and the visualization of the simulation results.
{"title":"A Quasi-stationary Approach to the Approximate Solution of a FEA 3D Subject-Specific EMG Model","authors":"Jakob L. Honeder, P. Goebel, T. Mandl, M. Vincze, M. Schachinger","doi":"10.1109/EMS.2012.34","DOIUrl":"https://doi.org/10.1109/EMS.2012.34","url":null,"abstract":"A structure based finite element analysis (FEA) model can be a means to gain better insight on how surface electromyography (EMG) signals are affected by limb geometry and tissue structures. Beyond that, and to optimize the control of myoelectric prostheses, such models can be used to evaluate signal separation algorithms, or to test the performance of different electrode configurations without the need to have several measurement sessions with a human subject present. This work presents a novel approach to the approximate modeling of a three-dimensional, subject-specific, generic EMG model by using FEA. The problems stemming from the nonrigid and irregular geometry of human body parts, the nonlinear tissue properties over frequency and temperature, the various muscle-fiber innervation possibilities, and the overall complexity of the model, are solved by defining an adequate fiber source description, simulating the volume conductor FEA model as being quasi-stationary, normalizing the true forearm geometry to a cylinder and unrolling it to be able to apply Helmholtz's principle of superposition to combine simulation results for the solving of more complex muscle-fiber set-ups. Thus, the source description presented herein appears suitable for application to different subject-specific geometries, as shown additionally by the setting into the 'Musculus pectoralis' of a targeted muscle reinnervation subject. Hence in conclusion, the strategy applied yields an overall reduced complexity of the FEA model, and therefore, substantially simplifies the processing and the visualization of the simulation results.","PeriodicalId":350614,"journal":{"name":"European Symposium on Computer Modeling and Simulation","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115870059","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 paper presents an ontology for systems engineering, by means of a set of information models based on a modelling methodology derived from and a simplification of the ISO 15926 part 2 data model. The methodology matches the way people think and communicate and is designed specifically to be useful for engineers. The information models are derived from ISO 15288 System Life Cycle Processes. Based on the information models and the set of relationships defined herein one can, in combination with a reference data library, build or configure an information system or data exchange mechanism in order to support Systems Engineering processes or set up a specific product knowledge model. An implementation method based on RDF is given as example.
{"title":"Ontology for Systems Engineering: Model-Based Systems Engineering","authors":"L. V. Ruijven","doi":"10.1109/EMS.2012.53","DOIUrl":"https://doi.org/10.1109/EMS.2012.53","url":null,"abstract":"This paper presents an ontology for systems engineering, by means of a set of information models based on a modelling methodology derived from and a simplification of the ISO 15926 part 2 data model. The methodology matches the way people think and communicate and is designed specifically to be useful for engineers. The information models are derived from ISO 15288 System Life Cycle Processes. Based on the information models and the set of relationships defined herein one can, in combination with a reference data library, build or configure an information system or data exchange mechanism in order to support Systems Engineering processes or set up a specific product knowledge model. An implementation method based on RDF is given as example.","PeriodicalId":350614,"journal":{"name":"European Symposium on Computer Modeling and Simulation","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127381134","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}
W. Ojenge, T. Afullo, P. Ogao, William OkelloOdongo
Kenya has identified radio spectrum as a keydriver in its development. Yet, globally, radio spectrum is inefficiently utilized due to ITU's static spectrum allocation.In Kenya, mobile operators are running short of bandwidth due to deployment of 4G services, which enable super fast mobile broadband/internet. In the USA and UK, FCC and Ofcom, respectively, have made effort to allow opportunistic 'poaching' of licensed spectrum as long as communication of licensed user is not interfered with. This has focused research on use of cognitive radio, which would use its sensor networks to establish which TV channels are idle in order to allocate them temporarily to cellular networks.Enabling the cognitive radio to predict which channels shall lie idle at what times introduces better planning and more temporally-efficient allocation. This study explores the viability of predicting the times of mobile telephony traffic jam for a mobile service operator with poor QoS rating within a cell of perennial mobile traffic jam in order to explore whether those times can map well with the TV spectrum holes. The times of the TV spectrum holes shall be determined in a later study.
{"title":"PSO of Neural Networks to Predict Busy Times of Cellular Traffic for Assignment to TV Idle Channels by Cognitive Radio","authors":"W. Ojenge, T. Afullo, P. Ogao, William OkelloOdongo","doi":"10.1109/EMS.2013.8","DOIUrl":"https://doi.org/10.1109/EMS.2013.8","url":null,"abstract":"Kenya has identified radio spectrum as a keydriver in its development. Yet, globally, radio spectrum is inefficiently utilized due to ITU's static spectrum allocation.In Kenya, mobile operators are running short of bandwidth due to deployment of 4G services, which enable super fast mobile broadband/internet. In the USA and UK, FCC and Ofcom, respectively, have made effort to allow opportunistic 'poaching' of licensed spectrum as long as communication of licensed user is not interfered with. This has focused research on use of cognitive radio, which would use its sensor networks to establish which TV channels are idle in order to allocate them temporarily to cellular networks.Enabling the cognitive radio to predict which channels shall lie idle at what times introduces better planning and more temporally-efficient allocation. This study explores the viability of predicting the times of mobile telephony traffic jam for a mobile service operator with poor QoS rating within a cell of perennial mobile traffic jam in order to explore whether those times can map well with the TV spectrum holes. The times of the TV spectrum holes shall be determined in a later study.","PeriodicalId":350614,"journal":{"name":"European Symposium on Computer Modeling and Simulation","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121059015","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 wireless networks environment, nodes are powered by exhaustible energy provided by batteries with limited duration. When the energy budget of a node comes to exhaustion, many undesirable situations may occur, ranking from minor alternative route discovery to unbearable network partition. Another situation which has not yet paid attention is one reached when a distributed application requires more running time than that will be provided by nodes capability. Up to now, lots of research has been devoted to this problem but all proposals addressed this issue attempt to alleviate this inconvenience through energy consuming optimization way. However, the problem remains as a hole when running long lived ubiquitous distributed applications. So, the expected results could not be provided if provisions to overcome battery depletion are not ensured. In this paper, we propose several strategies which may overcome node energy lack and may be used in any battery–based system. So, when a battery of a node suffers from depletion, either a new battery has to replace the former one, enabling the running processes to terminate execution, or uncompleted processes have to migrate to another node with large energy budget. The strategies have been compared according some convenient metrics.
{"title":"Improving Wireless Ad Hoc Networks Lifetime through Energy Exhaustion Recovering","authors":"Z. Aliouat, M. Aliouat","doi":"10.1109/EMS.2010.81","DOIUrl":"https://doi.org/10.1109/EMS.2010.81","url":null,"abstract":"In wireless networks environment, nodes are powered by exhaustible energy provided by batteries with limited duration. When the energy budget of a node comes to exhaustion, many undesirable situations may occur, ranking from minor alternative route discovery to unbearable network partition. Another situation which has not yet paid attention is one reached when a distributed application requires more running time than that will be provided by nodes capability. Up to now, lots of research has been devoted to this problem but all proposals addressed this issue attempt to alleviate this inconvenience through energy consuming optimization way. However, the problem remains as a hole when running long lived ubiquitous distributed applications. So, the expected results could not be provided if provisions to overcome battery depletion are not ensured. In this paper, we propose several strategies which may overcome node energy lack and may be used in any battery–based system. So, when a battery of a node suffers from depletion, either a new battery has to replace the former one, enabling the running processes to terminate execution, or uncompleted processes have to migrate to another node with large energy budget. The strategies have been compared according some convenient metrics.","PeriodicalId":350614,"journal":{"name":"European Symposium on Computer Modeling and Simulation","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129230445","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 develop an automatic voice pathology detection (VPD) system based on voice production theory. More specifically, we extract features from vocal tract area function from the tubes, which are closely located to the glottis. Voice pathology is related to a vocal fold problem, and hence the vocal tract area connected to the vocal fold or the glottis should exhibit irregular patterns over frames in case of a sustained vowel for a pathological voice. This irregular pattern is quantified in the form of variance across the frames to distinguish between normal and pathological voices. The proposed VPD system is evaluated on the MEEI database with sustained vowel samples and achieves 99.02%±0.01 accuracy.
{"title":"Voice Pathology Detection Using Vocal Tract Area","authors":"Muhammad Ghulam","doi":"10.1109/EMS.2013.29","DOIUrl":"https://doi.org/10.1109/EMS.2013.29","url":null,"abstract":"In this paper, we develop an automatic voice pathology detection (VPD) system based on voice production theory. More specifically, we extract features from vocal tract area function from the tubes, which are closely located to the glottis. Voice pathology is related to a vocal fold problem, and hence the vocal tract area connected to the vocal fold or the glottis should exhibit irregular patterns over frames in case of a sustained vowel for a pathological voice. This irregular pattern is quantified in the form of variance across the frames to distinguish between normal and pathological voices. The proposed VPD system is evaluated on the MEEI database with sustained vowel samples and achieves 99.02%±0.01 accuracy.","PeriodicalId":350614,"journal":{"name":"European Symposium on Computer Modeling and Simulation","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128936014","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 paper focuses on system testing in designing and developing the process of safety critical systems. The proposal aims at identifying the requirements for system testing of safety critical systems and connects them with system model defined in the SysML language. The design and development process is based on analysis of standards and guidelines carried out in our previous work that focused on system testing process in terms of execution. The proposed model is captured using appropriate SysML diagrams.
{"title":"Proposal of System Testing Integration into Safety Critical System Design Process Supported by SysML","authors":"L. Spendla, Lukas Hrcka","doi":"10.1109/EMS.2014.74","DOIUrl":"https://doi.org/10.1109/EMS.2014.74","url":null,"abstract":"This paper focuses on system testing in designing and developing the process of safety critical systems. The proposal aims at identifying the requirements for system testing of safety critical systems and connects them with system model defined in the SysML language. The design and development process is based on analysis of standards and guidelines carried out in our previous work that focused on system testing process in terms of execution. The proposed model is captured using appropriate SysML diagrams.","PeriodicalId":350614,"journal":{"name":"European Symposium on Computer Modeling and Simulation","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122720787","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}
{"title":"User-Centric Energy Cost Analysis of Industrial Automation Systems","authors":"A. Beck, N. Jazdi","doi":"10.1109/EMS.2011.26","DOIUrl":"https://doi.org/10.1109/EMS.2011.26","url":null,"abstract":"","PeriodicalId":350614,"journal":{"name":"European Symposium on Computer Modeling and Simulation","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133194887","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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