Pub Date : 1900-01-01DOI: 10.3233/978-1-61499-589-0-48
Michel Edkrantz, Alan Said
{"title":"Predicting Cyber Vulnerability Exploits with Machine Learning","authors":"Michel Edkrantz, Alan Said","doi":"10.3233/978-1-61499-589-0-48","DOIUrl":"https://doi.org/10.3233/978-1-61499-589-0-48","url":null,"abstract":"","PeriodicalId":322432,"journal":{"name":"Scandinavian Conference on AI","volume":"155-156 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":"114383992","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}
The Houria constraint solver is an efficient incremental algorithm that uses local propagation to maintain sets of required and preferential constraints. Houria represents constraints between variables by sets of short procedures (methods) and incrementally resatisftes the set of constraints when individual constraints are added and removed. The criterion of comparison used in Houria is more powerful than that of some other solvers. Houria is used to construct a graph of methods by planning and executing all these methods to found a best solution. The solution found by Houria satisfies more constraints than the one produced by some other solvers and that for the same over-constrained problems while respecting the hierarchy.
{"title":"The Houria Constraint Solver","authors":"M. Bouzoubaa","doi":"10.2495/AI950241","DOIUrl":"https://doi.org/10.2495/AI950241","url":null,"abstract":"The Houria constraint solver is an efficient incremental algorithm that uses local propagation to maintain sets of required and preferential constraints. Houria represents constraints between variables by sets of short procedures (methods) and incrementally resatisftes the set of constraints when individual constraints are added and removed. The criterion of comparison used in Houria is more powerful than that of some other solvers. Houria is used to construct a graph of methods by planning and executing all these methods to found a best solution. The solution found by Houria satisfies more constraints than the one produced by some other solvers and that for the same over-constrained problems while respecting the hierarchy.","PeriodicalId":322432,"journal":{"name":"Scandinavian Conference on AI","volume":"51 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":"129817787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.3233/978-1-61499-589-0-88
Tuwe Löfström, Jing Zhao, H. Linusson, K. Jansson
This study introduces the conformal prediction framework to the task of predicting the presence of adverse drug events in electronic health records with an associated measure of statistically valid ...
本研究引入适形预测框架，以预测电子健康档案中药物不良事件的存在，并采用统计有效的相关措施。
{"title":"Predicting Adverse Drug Events with Confidence","authors":"Tuwe Löfström, Jing Zhao, H. Linusson, K. Jansson","doi":"10.3233/978-1-61499-589-0-88","DOIUrl":"https://doi.org/10.3233/978-1-61499-589-0-88","url":null,"abstract":"This study introduces the conformal prediction framework to the task of predicting the presence of adverse drug events in electronic health records with an associated measure of statistically valid ...","PeriodicalId":322432,"journal":{"name":"Scandinavian Conference on AI","volume":"71 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":"128000797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.3233/978-1-61499-330-8-3
P. Davidsson
Experiences from different applications of agent technology aiming to make transport and energy systems more efficient are presented. The examples will cover real-time applications on the operation ...
介绍了智能体技术在提高交通和能源系统效率方面的不同应用经验。示例将涵盖操作的实时应用…
{"title":"Intelligent Transport and Energy Systems Using Agent Technology","authors":"P. Davidsson","doi":"10.3233/978-1-61499-330-8-3","DOIUrl":"https://doi.org/10.3233/978-1-61499-330-8-3","url":null,"abstract":"Experiences from different applications of agent technology aiming to make transport and energy systems more efficient are presented. The examples will cover real-time applications on the operation ...","PeriodicalId":322432,"journal":{"name":"Scandinavian Conference on AI","volume":"96 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":"125708833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.3233/978-1-61499-330-8-299
V. Valaitis
{"title":"Learning inverse kinematics problem in changing task environment","authors":"V. Valaitis","doi":"10.3233/978-1-61499-330-8-299","DOIUrl":"https://doi.org/10.3233/978-1-61499-330-8-299","url":null,"abstract":"","PeriodicalId":322432,"journal":{"name":"Scandinavian Conference on AI","volume":"13 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":"132882315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.3233/978-1-61499-589-0-58
Yuantao Fan, Sławomir Nowaczyk, Thorsteinn S. Rögnvaldsson
In the automotive industry, cost effective methods for predictive maintenance are increasingly in demand. The traditional approach for developing diagnostic methods on commercial vehicles is heavily based on knowledge of human experts, and thus it does not scale well to modern vehicles with many components and subsystems. In previous work we have presented a generic self-organising approach called COSMO that can detect, in an unsupervised manner, many different faults. In a study based on a commercial fleet of 19 buses operating in Kungsbacka, we have been able to predict, for example, fifty percent of the compressors that break down on the road, in many cases weeks before the failure.In this paper we compare those results with a state of the art approach currently used in the industry, and we investigate how features suggested by experts for detecting compressor failures can be incorporated into the COSMO method. We perform several experiments, using both real and synthetic data, to identify issues that need to be considered to improve the accuracy. The final results show that the COSMO method outperforms the expert method.
{"title":"Incorporating Expert Knowledge into a Self-Organized Approach for Predicting Compressor Faults in a City Bus Fleet","authors":"Yuantao Fan, Sławomir Nowaczyk, Thorsteinn S. Rögnvaldsson","doi":"10.3233/978-1-61499-589-0-58","DOIUrl":"https://doi.org/10.3233/978-1-61499-589-0-58","url":null,"abstract":"In the automotive industry, cost effective methods for predictive maintenance are increasingly in demand. The traditional approach for developing diagnostic methods on commercial vehicles is heavily based on knowledge of human experts, and thus it does not scale well to modern vehicles with many components and subsystems. In previous work we have presented a generic self-organising approach called COSMO that can detect, in an unsupervised manner, many different faults. In a study based on a commercial fleet of 19 buses operating in Kungsbacka, we have been able to predict, for example, fifty percent of the compressors that break down on the road, in many cases weeks before the failure.In this paper we compare those results with a state of the art approach currently used in the industry, and we investigate how features suggested by experts for detecting compressor failures can be incorporated into the COSMO method. We perform several experiments, using both real and synthetic data, to identify issues that need to be considered to improve the accuracy. The final results show that the COSMO method outperforms the expert method.","PeriodicalId":322432,"journal":{"name":"Scandinavian Conference on AI","volume":"28 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":"124353630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.3233/978-1-61499-330-8-235
F. Schadd, N. Roos
Ontology mapping is a crucial step for the facilitation of information exchange between knowledge sources. In the industry this process is often performed semi-automatically, with a domain expert supervising the process. Such an expert can supply a partial alignment, known as anchors, which can be exploited with more elaborate mapping techniques in order to identify the remaining correspondences. To do this we propose a novel approach, referred to as anchor-profiles. For each concept its degree of similarity to each anchor is gathered into a profile for comparison. We evaluated our approach on the Ontology Alignment Evaluation Initiative (OAEI) benchmark dataset using partial alignments that are randomly generated from the reference alignments. The evaluation reveals an overall high performance when compared with mapping systems that participated in the OAEI2012 campaign, where larger partial alignments lead to a higher f-measure.
{"title":"Anchor-Profiles for Ontology Mapping with Partial Alignments","authors":"F. Schadd, N. Roos","doi":"10.3233/978-1-61499-330-8-235","DOIUrl":"https://doi.org/10.3233/978-1-61499-330-8-235","url":null,"abstract":"Ontology mapping is a crucial step for the facilitation of information exchange between knowledge sources. In the industry this process is often performed semi-automatically, with a domain expert supervising the process. Such an expert can supply a partial alignment, known as anchors, which can be exploited with more elaborate mapping techniques in order to identify the remaining correspondences. To do this we propose a novel approach, referred to as anchor-profiles. For each concept its degree of similarity to each anchor is gathered into a profile for comparison. We evaluated our approach on the Ontology Alignment Evaluation Initiative (OAEI) benchmark dataset using partial alignments that are randomly generated from the reference alignments. The evaluation reveals an overall high performance when compared with mapping systems that participated in the OAEI2012 campaign, where larger partial alignments lead to a higher f-measure.","PeriodicalId":322432,"journal":{"name":"Scandinavian Conference on AI","volume":"11 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":"128431843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.3233/978-1-61499-589-0-108
Hamidur Rahman, S. Begum, Mobyen Uddin Ahmed
Today research is going on within different essential functions need to bring automatic vehicles to the roads. However, there will be manual driven vehicles for many years before it is fully automated vehicles on roads. In complex situations, automated vehicles will need human assistance for long time. So, for road safety driver monitoring is even more important in the context of autonomous vehicle to keep the driver alert and awake. But, limited effort has been done in total integration between automatic vehicle and human driver. Therefore, human drivers need to be monitored and able to take over control within short notice. This papers provides an overview on autonomous vehicles and un-obstructive driver monitoring approaches that can be implemented in future autonomous vehicles to monitor driver e.g., to diagnose and predict stress, fatigue etc. in semi-automated vehicles.
{"title":"Driver Monitoring in the Context of Autonomous Vehicle","authors":"Hamidur Rahman, S. Begum, Mobyen Uddin Ahmed","doi":"10.3233/978-1-61499-589-0-108","DOIUrl":"https://doi.org/10.3233/978-1-61499-589-0-108","url":null,"abstract":"Today research is going on within different essential functions need to bring automatic vehicles to the roads. However, there will be manual driven vehicles for many years before it is fully automated vehicles on roads. In complex situations, automated vehicles will need human assistance for long time. So, for road safety driver monitoring is even more important in the context of autonomous vehicle to keep the driver alert and awake. But, limited effort has been done in total integration between automatic vehicle and human driver. Therefore, human drivers need to be monitored and able to take over control within short notice. This papers provides an overview on autonomous vehicles and un-obstructive driver monitoring approaches that can be implemented in future autonomous vehicles to monitor driver e.g., to diagnose and predict stress, fatigue etc. in semi-automated vehicles.","PeriodicalId":322432,"journal":{"name":"Scandinavian Conference on AI","volume":"1 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":"120955758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.3233/978-1-61499-330-8-195
J. Nieves, Esteban Guerrero, H. Lindgren
Recognizing and supporting human activities is an important challenge for ambient assisted living. In this paper we introduce a novel argumentation-based approach for dealing with human activity re ...
{"title":"Reasoning about Human Activities: an Argumentative Approach","authors":"J. Nieves, Esteban Guerrero, H. Lindgren","doi":"10.3233/978-1-61499-330-8-195","DOIUrl":"https://doi.org/10.3233/978-1-61499-330-8-195","url":null,"abstract":"Recognizing and supporting human activities is an important challenge for ambient assisted living. In this paper we introduce a novel argumentation-based approach for dealing with human activity re ...","PeriodicalId":322432,"journal":{"name":"Scandinavian Conference on AI","volume":"48 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":"116714129","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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