Extractive summarization is an important natural language processing approach used for document compression, improved reading comprehension, key phrase extraction, indexing, query set generation, and other analytics approaches. Extractive summarization has specific advantages over abstractive summarization in that it preserves style, specific text elements, and compound phrases that might be more directly associated with the text. In this article, the relative effectiveness of extractive summarization is considered on two widely different corpora: (1) a set of works of fiction (100 total, mainly novels) available from Project Gutenberg, and (2) a large set of news articles (3000) for which a ground truthed summarization (gold standard) is provided by the authors of the news articles. Both sets were evaluated using 5 different Python Sumy algorithms and compared to randomly-generated summarizations quantitatively. Two functional approaches to assessing the efficacy of summarization using a query set on both the original documents and their summaries, and using document classification on a 12-class set to compare among different summarization approaches, are introduced. The results, unsurprisingly, show considerable differences consistent with the different nature of these two data sets. The LSA and Luhn summarization approaches were most effective on the database of fiction, while all five summarization approaches were similarly effective on the database of articles. Overall, the Luhn approach was deemed the most generally relevant among those tested.
{"title":"Summarization assessment methodology for multiple corpora using queries and classification for functional evaluation","authors":"Sam Wolyn, S. Simske","doi":"10.3233/ica-220680","DOIUrl":"https://doi.org/10.3233/ica-220680","url":null,"abstract":"Extractive summarization is an important natural language processing approach used for document compression, improved reading comprehension, key phrase extraction, indexing, query set generation, and other analytics approaches. Extractive summarization has specific advantages over abstractive summarization in that it preserves style, specific text elements, and compound phrases that might be more directly associated with the text. In this article, the relative effectiveness of extractive summarization is considered on two widely different corpora: (1) a set of works of fiction (100 total, mainly novels) available from Project Gutenberg, and (2) a large set of news articles (3000) for which a ground truthed summarization (gold standard) is provided by the authors of the news articles. Both sets were evaluated using 5 different Python Sumy algorithms and compared to randomly-generated summarizations quantitatively. Two functional approaches to assessing the efficacy of summarization using a query set on both the original documents and their summaries, and using document classification on a 12-class set to compare among different summarization approaches, are introduced. The results, unsurprisingly, show considerable differences consistent with the different nature of these two data sets. The LSA and Luhn summarization approaches were most effective on the database of fiction, while all five summarization approaches were similarly effective on the database of articles. Overall, the Luhn approach was deemed the most generally relevant among those tested.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":null,"pages":null},"PeriodicalIF":6.5,"publicationDate":"2022-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88474278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Consumer-centric energy management approaches are emerging as a major solution for future power systems. In this context, intelligent home management systems should manage different kinds of devices existing in the houses assuring convenient comfort levels and understanding the users’ behaviour. At the same time, the home management systems should be able to interact with other actors such as energy communities, aggregators, and system operators. The main contribution of this work is a new methodology allowing intelligent management, in near real-time (1 minute), of different types of energy resources existing in a smart home. The energy resources include appliances and other loads, micro-generation, and electric vehicles. The proposed system includes a permanent evaluation of the operation state of each energy resource considering their functional model and the behaviour and comfort level defined by the users. Participation in demand response programs reducing the power consumption limits is also considered showing the advantage of the proposed approach. The case study contains two scenarios considering a demand response program of power limitation with 120 minutes duration. To guarantee participation in these demand response events, the system should evaluate the priority of each device according to its model. A domestic consumer with 45 energy resources (appliances, generation, and electric vehicles) is used for demonstration purposes.
{"title":"Near real-time management of appliances, distributed generation and electric vehicles for demand response participation","authors":"F. Fernandes, H. Morais, Z. Vale","doi":"10.3233/ica-220679","DOIUrl":"https://doi.org/10.3233/ica-220679","url":null,"abstract":"Consumer-centric energy management approaches are emerging as a major solution for future power systems. In this context, intelligent home management systems should manage different kinds of devices existing in the houses assuring convenient comfort levels and understanding the users’ behaviour. At the same time, the home management systems should be able to interact with other actors such as energy communities, aggregators, and system operators. The main contribution of this work is a new methodology allowing intelligent management, in near real-time (1 minute), of different types of energy resources existing in a smart home. The energy resources include appliances and other loads, micro-generation, and electric vehicles. The proposed system includes a permanent evaluation of the operation state of each energy resource considering their functional model and the behaviour and comfort level defined by the users. Participation in demand response programs reducing the power consumption limits is also considered showing the advantage of the proposed approach. The case study contains two scenarios considering a demand response program of power limitation with 120 minutes duration. To guarantee participation in these demand response events, the system should evaluate the priority of each device according to its model. A domestic consumer with 45 energy resources (appliances, generation, and electric vehicles) is used for demonstration purposes.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":null,"pages":null},"PeriodicalIF":6.5,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89411469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Black Hole (BH) is a bioinspired metaheuristic algorithm based on the theory of relativity in which a sufficiently compact mass can deform the space-time to form a black hole, where no particles or electromagnetic radiation can escape from it. Thus, such an approach is based on the concept of a population of individuals (stars) representing solutions for a given computational problem to be optimized. In the literature, such an approach has been used to solve clustering problems, among others, since it is parameter-free and simple to implement. In this article, due to such characteristics, a hybrid solution, in software/hardware, of parallelization of the BH algorithm is proposed, aiming at accelerating its processing in hardware through a methodology that allows any user, even non-expert, implement hardware accelerators, for optimization problems, among others, through a high level tool. A System on Chip (SoC) platform was used for this implementation, containing a Zynq chip from Xilinx, which has two ARM cores and an FPGA. The BH Algorithm was implemented in software first and then in hardware for runtime comparison purposes to validate this approach. Also, in this paper, simpler and more popular optimization algorithms, such as Particle Swarm Optimization (PSO), Gravitational Search (GSA), and Big Bang – Big Crunch (BB-BC), along with simpler datasets, were used for comparison purposes, due to its ease of implementation and to keep a fairer comparison with BH as realized in other works in the literature. Therefore, the results obtained were satisfactory in terms of execution time and quality, with an average speedup of 25 times compared to the same implementation in software. In the future, it is intended to use this procedure to implement more recent clustering and optimization algorithms with larger datasets as well.
{"title":"Hybrid parallelization of the black hole algorithm for systems on chip","authors":"Saulo Akamatu, D. P. Lima, E. C. Pedrino","doi":"10.3233/ica-220678","DOIUrl":"https://doi.org/10.3233/ica-220678","url":null,"abstract":"Black Hole (BH) is a bioinspired metaheuristic algorithm based on the theory of relativity in which a sufficiently compact mass can deform the space-time to form a black hole, where no particles or electromagnetic radiation can escape from it. Thus, such an approach is based on the concept of a population of individuals (stars) representing solutions for a given computational problem to be optimized. In the literature, such an approach has been used to solve clustering problems, among others, since it is parameter-free and simple to implement. In this article, due to such characteristics, a hybrid solution, in software/hardware, of parallelization of the BH algorithm is proposed, aiming at accelerating its processing in hardware through a methodology that allows any user, even non-expert, implement hardware accelerators, for optimization problems, among others, through a high level tool. A System on Chip (SoC) platform was used for this implementation, containing a Zynq chip from Xilinx, which has two ARM cores and an FPGA. The BH Algorithm was implemented in software first and then in hardware for runtime comparison purposes to validate this approach. Also, in this paper, simpler and more popular optimization algorithms, such as Particle Swarm Optimization (PSO), Gravitational Search (GSA), and Big Bang – Big Crunch (BB-BC), along with simpler datasets, were used for comparison purposes, due to its ease of implementation and to keep a fairer comparison with BH as realized in other works in the literature. Therefore, the results obtained were satisfactory in terms of execution time and quality, with an average speedup of 25 times compared to the same implementation in software. In the future, it is intended to use this procedure to implement more recent clustering and optimization algorithms with larger datasets as well.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":null,"pages":null},"PeriodicalIF":6.5,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88166140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the increasing complexity of engineered systems, digital twins (DTs) have been widely used to support integrated modeling, simulation, and decision-making of the system of systems (SoS). However, when integrating DTs of each constituent system, it is challenging to implement complexity management, interface definition, and service integration across DTs. This study proposes a new concept called cognitive twin (CT) to support SoS development and operation. CTs have been defined as DTs with augmented semantic capabilities for promoting the understanding of interrelationships be-tween virtual models and enhancing the decision-making. First, CTs aim to integrate the information description of DTs across constituent systems using a unified ontology and semantic modeling technique. Second, CTs provide integrated simulations among DTs for decision-making of the SoS based on a high-level architecture (HLA). Finally, through reasoning ontology models, CTs provide decision-making options for the operations of real constituent systems. A case study on unmanned aerial vehicles (UAVs) landing on unmanned surface vehicles (USVs) is used to verify the flexibility of this approach. From the results, we find that the CT based on the proposed ontology provides a unified formalism of DTs across UAVs and USVs. Moreover, the reasoning based on the CT provides decision-making capabilities for UAVs by implementing cognitive computing to select target USVs for landing.
{"title":"Cognitive twin construction for system of systems operation based on semantic integration and high-level architecture","authors":"Han Li, Guoxin Wang, Jinzhi Lu, D. Kiritsis","doi":"10.3233/ica-220677","DOIUrl":"https://doi.org/10.3233/ica-220677","url":null,"abstract":"With the increasing complexity of engineered systems, digital twins (DTs) have been widely used to support integrated modeling, simulation, and decision-making of the system of systems (SoS). However, when integrating DTs of each constituent system, it is challenging to implement complexity management, interface definition, and service integration across DTs. This study proposes a new concept called cognitive twin (CT) to support SoS development and operation. CTs have been defined as DTs with augmented semantic capabilities for promoting the understanding of interrelationships be-tween virtual models and enhancing the decision-making. First, CTs aim to integrate the information description of DTs across constituent systems using a unified ontology and semantic modeling technique. Second, CTs provide integrated simulations among DTs for decision-making of the SoS based on a high-level architecture (HLA). Finally, through reasoning ontology models, CTs provide decision-making options for the operations of real constituent systems. A case study on unmanned aerial vehicles (UAVs) landing on unmanned surface vehicles (USVs) is used to verify the flexibility of this approach. From the results, we find that the CT based on the proposed ontology provides a unified formalism of DTs across UAVs and USVs. Moreover, the reasoning based on the CT provides decision-making capabilities for UAVs by implementing cognitive computing to select target USVs for landing.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":null,"pages":null},"PeriodicalIF":6.5,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75201723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Image binarization is one of the fundamental methods in image processing and it is mainly used as a preprocessing for other methods in image processing. We present an image binarization method with the primary purpose to find markers such as those used in mobile 3D scanning systems. Handling a mobile 3D scanning system often includes bad conditions such as light reflection and non-uniform illumination. As the basic part of the scanning process, the proposed binarization method successfully overcomes the above problems and does it successfully. Due to the trend of increasing image size and real-time image processing we were able to achieve the required small algorithmic complexity. The paper outlines a comparison with several other methods with a focus on objects with markers including the calibration system plane of the 3D scanning system. Although it is obvious that no binarization algorithm is best for all types of images, we also give the results of the proposed method applied to historical documents.
{"title":"Image binarization method for markers tracking in extreme light conditions","authors":"M. Ćurković, A. Curkovic, D. Vucina","doi":"10.3233/ica-210674","DOIUrl":"https://doi.org/10.3233/ica-210674","url":null,"abstract":"Image binarization is one of the fundamental methods in image processing and it is mainly used as a preprocessing for other methods in image processing. We present an image binarization method with the primary purpose to find markers such as those used in mobile 3D scanning systems. Handling a mobile 3D scanning system often includes bad conditions such as light reflection and non-uniform illumination. As the basic part of the scanning process, the proposed binarization method successfully overcomes the above problems and does it successfully. Due to the trend of increasing image size and real-time image processing we were able to achieve the required small algorithmic complexity. The paper outlines a comparison with several other methods with a focus on objects with markers including the calibration system plane of the 3D scanning system. Although it is obvious that no binarization algorithm is best for all types of images, we also give the results of the proposed method applied to historical documents.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":null,"pages":null},"PeriodicalIF":6.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77456342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An integrated low-cost system for object detection in underwater environments","authors":"G. Foresti, Ivan Scagnetto","doi":"10.3233/ICA-220675","DOIUrl":"https://doi.org/10.3233/ICA-220675","url":null,"abstract":"","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":null,"pages":null},"PeriodicalIF":6.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83575771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Mukhin, Ihar A. Kilbas, R. Paringer, N. Ilyasova, A. Kupriyanov
{"title":"A method for balancing a multi-labeled biomedical dataset","authors":"A. Mukhin, Ihar A. Kilbas, R. Paringer, N. Ilyasova, A. Kupriyanov","doi":"10.3233/ICA-220676","DOIUrl":"https://doi.org/10.3233/ICA-220676","url":null,"abstract":"","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":null,"pages":null},"PeriodicalIF":6.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80631993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cristóvão Sousa, Daniel Teixeira, Davide Carneiro, Diogo Nunes, Paulo Novais
As the availability of computational power and communication technologies increases, Humans and systems are able to tackle increasingly challenging decision problems. Taking decisions over incomplete visions of a situation is particularly challenging and calls for a set of intertwined skills that must be put into place under a clear rationale. This work addresses how to deliver autonomous decisions for the management of a public street lighting network, to optimize energy consumption without compromising light quality patterns. Our approach is grounded in an holistic methodology, combining semantic and Artificial Intelligence principles to define methods and artefacts for supporting decisions to be taken in the context of an incomplete domain. That is, a domain with absence of data and of explicit domain assertions.
{"title":"Knowledge-based decision intelligence in street lighting management","authors":"Cristóvão Sousa, Daniel Teixeira, Davide Carneiro, Diogo Nunes, Paulo Novais","doi":"10.3233/ica-210671","DOIUrl":"https://doi.org/10.3233/ica-210671","url":null,"abstract":"As the availability of computational power and communication technologies increases, Humans and systems are able to tackle increasingly challenging decision problems. Taking decisions over incomplete visions of a situation is particularly challenging and calls for a set of intertwined skills that must be put into place under a clear rationale. This work addresses how to deliver autonomous decisions for the management of a public street lighting network, to optimize energy consumption without compromising light quality patterns. Our approach is grounded in an holistic methodology, combining semantic and Artificial Intelligence principles to define methods and artefacts for supporting decisions to be taken in the context of an incomplete domain. That is, a domain with absence of data and of explicit domain assertions.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":null,"pages":null},"PeriodicalIF":6.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77391746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vincenzo Iannino, V. Colla, Alessandro Maddaloni, J. Brandenburger, A. Rajabi, A. Wolff, Joaquín B. Ordieres Meré, M. Gutiérrez, Erwin Sirovnik, D. Mueller, Christoph Schirm
. Nowadays the steel market is becoming ever more competitive for European steelworks, especially as far as flat steel products are concerned. As such competition determines the price products, profit can be increased only by lowering production and commercial costs. Production yield can be significantly increased through an appropriate scheduling of the semi-manufactured products among the available sub-processes, to ensure that customers’ orders are timely completed, resources are optimally exploited, and delays are minimized. Therefore, an ever-increasing attention is paid toward production optimization through efficient scheduling strategies in the scientific and industrial communities. This paper proposes a hybrid approach to improve the flexibility of production scheduling in steelworks producing flat steel products. Such approach combines three methods holding different scopes and modelling different aspects: an auction-based multi-agent system is applied to face production uncertainties, multi-objective mixed-integer linear programming is used for global optimal scheduling of resources under steady conditions, while a continuous flow model copes with long-term production scheduling. According to the obtained simulation results, the integration and combination of these three approaches allow scheduling production in a flexible way by providing the capability to adapt to different production conditions.
{"title":"A hybrid approach for improving the flexibility of production scheduling in flat steel industry","authors":"Vincenzo Iannino, V. Colla, Alessandro Maddaloni, J. Brandenburger, A. Rajabi, A. Wolff, Joaquín B. Ordieres Meré, M. Gutiérrez, Erwin Sirovnik, D. Mueller, Christoph Schirm","doi":"10.3233/ICA-220685","DOIUrl":"https://doi.org/10.3233/ICA-220685","url":null,"abstract":". Nowadays the steel market is becoming ever more competitive for European steelworks, especially as far as flat steel products are concerned. As such competition determines the price products, profit can be increased only by lowering production and commercial costs. Production yield can be significantly increased through an appropriate scheduling of the semi-manufactured products among the available sub-processes, to ensure that customers’ orders are timely completed, resources are optimally exploited, and delays are minimized. Therefore, an ever-increasing attention is paid toward production optimization through efficient scheduling strategies in the scientific and industrial communities. This paper proposes a hybrid approach to improve the flexibility of production scheduling in steelworks producing flat steel products. Such approach combines three methods holding different scopes and modelling different aspects: an auction-based multi-agent system is applied to face production uncertainties, multi-objective mixed-integer linear programming is used for global optimal scheduling of resources under steady conditions, while a continuous flow model copes with long-term production scheduling. According to the obtained simulation results, the integration and combination of these three approaches allow scheduling production in a flexible way by providing the capability to adapt to different production conditions.","PeriodicalId":50358,"journal":{"name":"Integrated Computer-Aided Engineering","volume":null,"pages":null},"PeriodicalIF":6.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79656259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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