{"title":"Business process mining algorithms","authors":"Diana Chinces, I. Salomie","doi":"10.1109/ICCP.2013.6646120","DOIUrl":"https://doi.org/10.1109/ICCP.2013.6646120","url":null,"abstract":"This paper presents our work in developing three business process mining algorithms, followed by a comparison between GLS Miner, ILS Miner and ACO Miner. All of these algorithms have been proved as generating better solutions compared to the state of the art and can discover process models that correctly map to the event log. The algorithms and a comparison between them is presented in the current paper, as well as the mapping of each algorithm to the common business process structures.","PeriodicalId":380109,"journal":{"name":"2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122454904","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":"A generic statistical approach for emission computed tomography reconstruction","authors":"A. Ciurte, S. Nedevschi, I. Raşa","doi":"10.1109/ICCP.2013.6646085","DOIUrl":"https://doi.org/10.1109/ICCP.2013.6646085","url":null,"abstract":"Nowadays nuclear imaging is increasingly used for non-invasive diagnosis. The image modalities in nuclear imaging suffer of worse statistics, in comparison with computed tomography, since they are based on emission transition tomography. Thus, precise reconstruction methods that can deal with incomplete or missing measurements are needed in order to improve the quality of nuclear images. In this paper we present a generalization of the state of the art EMML and ISRA algorithms for emission computed tomography reconstruction. The proposed method was tested and validated in comparison with the mentioned state of the art methods on a set of synthetic data. Better results (in terms of speed of convergence) were obtained for certain parameter settings.","PeriodicalId":380109,"journal":{"name":"2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122150238","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":"An approach to mining financial markets through market state classification","authors":"V. Ionescu, M. Dînsoreanu","doi":"10.1109/ICCP.2013.6646078","DOIUrl":"https://doi.org/10.1109/ICCP.2013.6646078","url":null,"abstract":"Financial markets have always been one of the most common application areas for a multitude of data mining techniques. Over the years a large number of autonomous prediction systems have been designed. In this paper an approach is proposed that offers a higher degree of control over the prediction process and over the exact market aspects that are being analyzed by the system. The concept can be applied to any trading strategy with the aim of enhancing forecasting accuracy. The paper also demonstrates how the theoretical concept can be applied in practice and concludes by illustrating the gains obtained by using the proposed approach.","PeriodicalId":380109,"journal":{"name":"2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125757734","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}
Nenad Tomašev, Doni Pracner, R. Brehar, Miloš Radovanović, D. Mladenić, M. Ivanović, S. Nedevschi
{"title":"Object recognition in wikimage data based on local invariant image features","authors":"Nenad Tomašev, Doni Pracner, R. Brehar, Miloš Radovanović, D. Mladenić, M. Ivanović, S. Nedevschi","doi":"10.1109/ICCP.2013.6646097","DOIUrl":"https://doi.org/10.1109/ICCP.2013.6646097","url":null,"abstract":"Object recognition is an essential task in content-based image retrieval and classification. This paper deals with object recognition in WIKImage data, a collection of publicly available annotated Wikipedia images. WIKImage comprises a set of 14 binary classification problems with significant class imbalance. Our approach is based on using the local invariant image features and we have compared 3 standard and widely used feature types: SIFT, SURF and ORB. We have examined how the choice of representation affects the k-nearest neighbor data topology and have shown that some feature types might be more appropriate than others for this particular problem. In order to assess the difficulty of the data, we have evaluated 7 different k-nearest neighbor classification methods and shown that the recently proposed hubness-aware classifiers might be used to either increase the accuracy of prediction, or the macro-averaged F-score. However, our results indicate that further improvements are possible and that including the textual feature information might prove beneficial for system performance.","PeriodicalId":380109,"journal":{"name":"2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115010843","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":"AgentSlang: A fast and reliable platform for Distributed Interactive Systems","authors":"O. Șerban, A. Pauchet","doi":"10.1109/ICCP.2013.6646077","DOIUrl":"https://doi.org/10.1109/ICCP.2013.6646077","url":null,"abstract":"This paper proposes a generic platform for developing fast and reliable Distributed Interactive Systems. The modelling is based on a component design approach, with element structure simple and versatile enough to allow the integration of existing algorithm. Moreover, we propose Syn!bad as a unified knowledge extraction language, focused around the usage of synonyms, useful for dialogue management. The AgentSlang platform consists in a series of original components integrated with several existing algorithms, to provide a development environment for Interactive Systems. There are several original parts in our approach. First, the platform is based on a data and component oriented design, which integrates into a unified system the concept of Feedback Management, Dialogue Management and a flexible component architecture. Second, the Syn!bad language, is integrated as a component of AgentSlang. Third, the message exchange speed is superior of any existing platforms, even in the context of providing extra features, such as action execution feedback and data type consistency check.","PeriodicalId":380109,"journal":{"name":"2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116854526","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":"Energy-aware placement of VMs in a datacenter","authors":"D. Diaconescu, Florin Pop, V. Cristea","doi":"10.1109/ICCP.2013.6646128","DOIUrl":"https://doi.org/10.1109/ICCP.2013.6646128","url":null,"abstract":"In the recent years many applications were moved to Cloud and the Cloud computing became more popular. For being able to satisfy all the clients resource demands, the Cloud service providers are continuously increasing their data centers. The recent studies has shown that a data center can be very costly due to the energy power consumption so the cloud service providers may have issues in cost recovering. In this paper we propose a framework that aims to reduce the energy consumption of a data center. There are many resources that are not used at their maximum capacity or even worst, there are many resources that are not used at all. This research objective is to migrate some resources between different data centers in order to turn off some hosts that are not used. The cost can be reduced significantly if some hosts are turned off.","PeriodicalId":380109,"journal":{"name":"2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127542820","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":"Stereovision on mobile devices for obstacle detection in low speed traffic scenarios","authors":"A. Trif, F. Oniga, S. Nedevschi","doi":"10.1109/ICCP.2013.6646103","DOIUrl":"https://doi.org/10.1109/ICCP.2013.6646103","url":null,"abstract":"Since smart mobile devices having capabilities of synchronous stereo image acquisition have been released on the market, the topic of real-time 3D environment reconstruction by stereovision on such mobile platforms has become of a greater interest among researchers. In this paper we continue the sparse stereovision approach proposed in [15], while focusing on improving the reconstruction results by refining the disparity computation accuracy to a sub-pixel level and by using the available sensors to gain more information about the position of the device relative to the world. After the 3D points are reconstructed by triangulation, a correction is applied on them to compensate for a possible pitch rotation of the device. Moreover, we present a fast approach for detecting the obstacle on the estimated trajectory of the vehicle. A series of experiments have been conducted which proved that although mobile development is constrained by the available features of the device and its operating system, sensor information is beneficial, and more importantly, both reconstruction accuracy and obstacle detection at short-medium distances and real-time processing can be achieved. Thus, developing driving assistance functions with such devices is possible for low vehicle speeds / short range scenarios, which often occur in urban environments.","PeriodicalId":380109,"journal":{"name":"2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131037085","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":"Urban traffic dense-stereo obstacle classification using boosting over visual codebook features","authors":"Ion Giosan, A. Costea, S. Nedevschi","doi":"10.1109/ICCP.2013.6646092","DOIUrl":"https://doi.org/10.1109/ICCP.2013.6646092","url":null,"abstract":"Every driving assistance system should have an obstacle classification module. Its main role is to accurately classify obstacles within a set of predefined classes. This paper presents a real-time dense-stereo based obstacle classification system that integrates visual codebook features like HOG, LBP and texton descriptor types in a powerful classifier. The system classifies the obstacles in four main classes: cars, pedestrians, poles/trees and other obstacles. The system acquires the image scenes using a pair of gray level stereo video-cameras. A combined approach using both 2D intensity and 3D depth information is firstly used for accurate obstacle segmentation. Then, the visual codebook features are extracted for a large set of obstacles with manually labeled classes and used for training a robust boosting classifier. The comparative classification results with an approach based on a random forest classifier trained on a relevant feature set show a considerable improvement, especially for the class of other obstacles.","PeriodicalId":380109,"journal":{"name":"2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130476489","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":"Detection of thrown objects using ToF cameras","authors":"S. Oprisescu, L. Florea, E. Ovreiu","doi":"10.1109/ICCP.2013.6646086","DOIUrl":"https://doi.org/10.1109/ICCP.2013.6646086","url":null,"abstract":"This paper deals with the issue of thrown or dropped object detection as an application of the 3D time-of-flight (ToF) camera. The use of distance information provided by the ToF camera makes the segmentation step straight forward. Then, instead of high computational motion detection and estimation algorithms, mainly a labeling and tracking procedure is used. This approach provides real time low complexity object detection and trajectory estimation. The method is validated on 50 video sequences taken with the ToF camera.","PeriodicalId":380109,"journal":{"name":"2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126463421","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":"A rule-based, domain independent approach for opinion and holder identification","authors":"Ioana Maria Sima, Mariana Vunvulea","doi":"10.1109/ICCP.2013.6646081","DOIUrl":"https://doi.org/10.1109/ICCP.2013.6646081","url":null,"abstract":"Mining sentiments from text is currently an important problem in information retrieval systems. In this paper we propose a solution for extracting opinions and opinion holders from large texts. Our goal is to achieve a high level of domain independence by implementing a rule-based approach. The results of our system have proven an accuracy which is comparable to that of systems that use a supervised learning approach, which is domain dependent.","PeriodicalId":380109,"journal":{"name":"2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114232842","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}