Pub Date : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622286
Xue Wang, Jing Liu
Aiming at image mosaic for high-resolution and high-amplification image of porous media, it proposed a compound method process based on Scale Invariance Feature Transform (SIFT) and Second Generation Wavelets (SGWs). The process is divided into two steps, one is quick match with SIFT, the other is precise image fused by SGWs. It takes full advantage of image's texture to make image matching fast, and then the image fused strategy and method based on SGWs are developed. A series of experiments show that according to high-resolution and high-amplification image, such algorithm could achieve well mosaic result, moreover, obviously it could be applied other likely case.
{"title":"A mosaic algorithm for high-resolution s-μCT image of porous media based on SIFT & SGWs","authors":"Xue Wang, Jing Liu","doi":"10.1109/ICCI-CC.2013.6622286","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622286","url":null,"abstract":"Aiming at image mosaic for high-resolution and high-amplification image of porous media, it proposed a compound method process based on Scale Invariance Feature Transform (SIFT) and Second Generation Wavelets (SGWs). The process is divided into two steps, one is quick match with SIFT, the other is precise image fused by SGWs. It takes full advantage of image's texture to make image matching fast, and then the image fused strategy and method based on SGWs are developed. A series of experiments show that according to high-resolution and high-amplification image, such algorithm could achieve well mosaic result, moreover, obviously it could be applied other likely case.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121962157","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 : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622256
S. Tsumoto, S. Hirano, H. Iwata
Schedule management of hospitalization is important to maintain or improve the quality of medical care and application of a clinical pathway is one of the important solutions for the management. This research proposed an data-oriented maintenance of existing clinical pathways by using data on histories of nursing orders. If there is no clinical pathway for a given disease, the method will induce a new clinical care plan from the data. The method was evaluated on 10 diseases. The results show that the reuse of stored data will give a powerful tool for management of nursing schedule and lead to improvement of hospital services.
{"title":"Granularity-based mining for construction of nursing care plan","authors":"S. Tsumoto, S. Hirano, H. Iwata","doi":"10.1109/ICCI-CC.2013.6622256","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622256","url":null,"abstract":"Schedule management of hospitalization is important to maintain or improve the quality of medical care and application of a clinical pathway is one of the important solutions for the management. This research proposed an data-oriented maintenance of existing clinical pathways by using data on histories of nursing orders. If there is no clinical pathway for a given disease, the method will induce a new clinical care plan from the data. The method was evaluated on 10 diseases. The results show that the reuse of stored data will give a powerful tool for management of nursing schedule and lead to improvement of hospital services.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127514067","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 : 2013-07-16DOI: 10.4018/ijcini.2013100101
Vlad Chiriacescu, Leen-Kiat Soh, D. Shell
Within cognitive science, computational modeling based on cognitive architectures has been an important approach to addressing questions of human cognition and learning. This paper reports on a multi-agent computational model based on the principles of the Unified Learning Model (ULM). Derived from a synthesis of neuroscience, cognitive science, psychology, and education, the ULM merges a statistical learning mechanism with a general learning architecture. Description of the single agent model and the multi-agent environment which translate the principles of the ULM into an integrated computational model is provided. Validation results from simulations with respect to human learning are presented. Simulation suitability for cognitive learning investigations is discussed. Multi-agent system performance results are presented. Findings support the ULM theory by documenting a viable computational simulation of the core ULM components of long-term memory, motivation, and working memory and the processes taking place among them. Implications for research into human learning and intelligent agents are presented.
{"title":"Understanding human learning using a multi-agent simulation of the unified learning model","authors":"Vlad Chiriacescu, Leen-Kiat Soh, D. Shell","doi":"10.4018/ijcini.2013100101","DOIUrl":"https://doi.org/10.4018/ijcini.2013100101","url":null,"abstract":"Within cognitive science, computational modeling based on cognitive architectures has been an important approach to addressing questions of human cognition and learning. This paper reports on a multi-agent computational model based on the principles of the Unified Learning Model (ULM). Derived from a synthesis of neuroscience, cognitive science, psychology, and education, the ULM merges a statistical learning mechanism with a general learning architecture. Description of the single agent model and the multi-agent environment which translate the principles of the ULM into an integrated computational model is provided. Validation results from simulations with respect to human learning are presented. Simulation suitability for cognitive learning investigations is discussed. Multi-agent system performance results are presented. Findings support the ULM theory by documenting a viable computational simulation of the core ULM components of long-term memory, motivation, and working memory and the processes taking place among them. Implications for research into human learning and intelligent agents are presented.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130420578","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 : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622246
Chen Sun, Yang Wang, Jun Zheng, D. Hsu
The aim of this paper is to investigate feature fusion problem for mobile usage prediction using combinatorial fusion analysis (CFA). CFA uses the rank-score characteristics (RSC) function to guide the process of selecting score-based fusion (SF) or rank-based fusion (RF). We study the feature fusion of two mobile adaptive user interface applications: dynamic shortcuts for application launching and dynamic contact list, which improve the usability of mobile devices through usage predication. Our results confirm that for mobile usage prediction RSC function is useful for feature fusion decision. It also proves that RF outperforms SF when the features have unique scoring behavior and relatively high performance.
{"title":"Feature fusion for mobile usage prediction using rank-score characteristics","authors":"Chen Sun, Yang Wang, Jun Zheng, D. Hsu","doi":"10.1109/ICCI-CC.2013.6622246","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622246","url":null,"abstract":"The aim of this paper is to investigate feature fusion problem for mobile usage prediction using combinatorial fusion analysis (CFA). CFA uses the rank-score characteristics (RSC) function to guide the process of selecting score-based fusion (SF) or rank-based fusion (RF). We study the feature fusion of two mobile adaptive user interface applications: dynamic shortcuts for application launching and dynamic contact list, which improve the usability of mobile devices through usage predication. Our results confirm that for mobile usage prediction RSC function is useful for feature fusion decision. It also proves that RF outperforms SF when the features have unique scoring behavior and relatively high performance.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134237956","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 : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622277
H. Ohwada, Masato Okada, K. Kanamori
This paper describes flexible route planning for amusement parks (e.g. Disneyland) navigation. Unlike conventional shortest path finding, we provide several types of algorithms that consider waiting time estimation in real time, exploit the reservation facility of an attraction such as Fast Pass in Disneyland, and balance a series of enjoyment types such as excitement or relaxation. These features extend Dikstra's shortest path algorithm to be more flexible and dynamical. We have developed a navigation tool as a Web application in which users select their interesting attractions and then the application suggests reasonable and enjoyable routes. The experiment was conducted to show the performance of this application focusing on well-known attractions in Tokyo Disneyland.
{"title":"Flexible route planning for amusement parks navigation","authors":"H. Ohwada, Masato Okada, K. Kanamori","doi":"10.1109/ICCI-CC.2013.6622277","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622277","url":null,"abstract":"This paper describes flexible route planning for amusement parks (e.g. Disneyland) navigation. Unlike conventional shortest path finding, we provide several types of algorithms that consider waiting time estimation in real time, exploit the reservation facility of an attraction such as Fast Pass in Disneyland, and balance a series of enjoyment types such as excitement or relaxation. These features extend Dikstra's shortest path algorithm to be more flexible and dynamical. We have developed a navigation tool as a Web application in which users select their interesting attractions and then the application suggests reasonable and enjoyable routes. The experiment was conducted to show the performance of this application focusing on well-known attractions in Tokyo Disneyland.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127073777","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 : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622258
J. O. Wallgrün, Jinlong Yang, A. Klippel
We present four human behavioral experiments to address the question of intuitive granularities in fundamental spatial relations as they can be found in formal spatial calculi that focus on invariant characteristics under certain (especially topological) transformations. Of particular interest to this article is the concept of two spatially extended entities overlapping each other. The overlap concept has been extensively treated in Galton's mode of overlap calculus [1]. In the first two experiments, we used a category construction task to calibrate this calculus against behavioral data and found that participants adopted a very coarse view on the concept of overlap, only distinguishing between three general relations: proper part, overlap, and non-overlap. In the following two experiments, we changed the instructions to explicitly address the possibility that humans could be swayed to adopt a more detailed level of granularity, that is, we encouraged them to create as many meaningful groups as possible. The results show that the three relations identified earlier (overlap, non-overlap, and proper part) are very robust and a natural level of granularity across all four experiments but that contextual factors gain more influence at finer levels of granularity.
{"title":"Investigating intuitive granularities of overlap relations","authors":"J. O. Wallgrün, Jinlong Yang, A. Klippel","doi":"10.1109/ICCI-CC.2013.6622258","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622258","url":null,"abstract":"We present four human behavioral experiments to address the question of intuitive granularities in fundamental spatial relations as they can be found in formal spatial calculi that focus on invariant characteristics under certain (especially topological) transformations. Of particular interest to this article is the concept of two spatially extended entities overlapping each other. The overlap concept has been extensively treated in Galton's mode of overlap calculus [1]. In the first two experiments, we used a category construction task to calibrate this calculus against behavioral data and found that participants adopted a very coarse view on the concept of overlap, only distinguishing between three general relations: proper part, overlap, and non-overlap. In the following two experiments, we changed the instructions to explicitly address the possibility that humans could be swayed to adopt a more detailed level of granularity, that is, we encouraged them to create as many meaningful groups as possible. The results show that the three relations identified earlier (overlap, non-overlap, and proper part) are very robust and a natural level of granularity across all four experiments but that contextual factors gain more influence at finer levels of granularity.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124122320","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 : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622280
Youqing Ding, Yumei Fu, Fang Zhu, Xinwu Zan
In terms of the data characteristics of small sample, nonlinearity and seasonal regression in bridge health monitoring system, this paper analyses the applied results with different data filling methods such as linear regression, seasonal autoregressive integrated moving average (SARIMA), neural network BP approach and support vector machine (SVM). The comparison results show that support vector machines (SVM) and BP neural network have higher precision in the case of the same sample. The filling results show that support vector machines (SVM) has a higher accuracy than neural network BP with the small samples.
{"title":"Comparison of missing data filling methods in bridge health monitoring system","authors":"Youqing Ding, Yumei Fu, Fang Zhu, Xinwu Zan","doi":"10.1109/ICCI-CC.2013.6622280","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622280","url":null,"abstract":"In terms of the data characteristics of small sample, nonlinearity and seasonal regression in bridge health monitoring system, this paper analyses the applied results with different data filling methods such as linear regression, seasonal autoregressive integrated moving average (SARIMA), neural network BP approach and support vector machine (SVM). The comparison results show that support vector machines (SVM) and BP neural network have higher precision in the case of the same sample. The filling results show that support vector machines (SVM) has a higher accuracy than neural network BP with the small samples.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122652072","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 : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622265
Yi Xiang, Ying Wu, Jun Peng
Weighting parameters are introduced to ensure the weak classifier that comes with the False Rejection Rate (FRR) to significantly reduce the False Acceptance Rate (FAR). Knowing that the Haar-Like features redundancy, the most effective combination of features is chosen from all the features upon the completion of the classifier training, aiming to improve the speed and rate of face recognition. The results show that the improved AdaBoost algorithm saw an improved recognition rate of 15% compared to the traditional algorithm, where the video image sequence presented an average face recognition rate of 21.5ms/frame, being able to meet the requirements of real-time face detection.
{"title":"An Improved AdaBoost face detection algorithm based on the weighting parameters of weak classifier","authors":"Yi Xiang, Ying Wu, Jun Peng","doi":"10.1109/ICCI-CC.2013.6622265","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622265","url":null,"abstract":"Weighting parameters are introduced to ensure the weak classifier that comes with the False Rejection Rate (FRR) to significantly reduce the False Acceptance Rate (FAR). Knowing that the Haar-Like features redundancy, the most effective combination of features is chosen from all the features upon the completion of the classifier training, aiming to improve the speed and rate of face recognition. The results show that the improved AdaBoost algorithm saw an improved recognition rate of 15% compared to the traditional algorithm, where the video image sequence presented an average face recognition rate of 21.5ms/frame, being able to meet the requirements of real-time face detection.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122038389","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 : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622281
Zhihao Huang, Dan-lu Jiang, Yin Huang
The effectiveness of applying saving energy saving measures has been affected by various attributes. As choosing different energy saving measures will result in different energy saving performance, it is important to understand what and how these attributes affect the choice of specific energy saving method. There are many types of attributes affecting the way of choosing energy saving methods. This paper presents these majors attributes that determine the way how to choose energy saving methods. The data used for analysis are collected from a questionnaire survey to Chongqing practice in China. The results provide valuable references to decision-making on adopting adequate methods for improving energy saving in urban residential buildings.
{"title":"Attributes affecting the application of energy saving measures — A Chongqing study","authors":"Zhihao Huang, Dan-lu Jiang, Yin Huang","doi":"10.1109/ICCI-CC.2013.6622281","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622281","url":null,"abstract":"The effectiveness of applying saving energy saving measures has been affected by various attributes. As choosing different energy saving measures will result in different energy saving performance, it is important to understand what and how these attributes affect the choice of specific energy saving method. There are many types of attributes affecting the way of choosing energy saving methods. This paper presents these majors attributes that determine the way how to choose energy saving methods. The data used for analysis are collected from a questionnaire survey to Chongqing practice in China. The results provide valuable references to decision-making on adopting adequate methods for improving energy saving in urban residential buildings.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130480529","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 : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622253
Jonathan-Hernando Rosales, Karina Jaime, Félix F. Ramos, M. Ramos
Emotional regulation is a mechanism to adjust our behavior to the current environment. We use this mechanism to achieve goals and objectives. This paper proposes a model for emotional regulation in virtual agents based on biological evidence of human brain function. The evidence shows different brain activation during emotional regulation. The model defines the techniques that are implemented, the data flow, and the data processing in each brain area during the emotional regulation. In the case study, a virtual agent shows behavior changes when it takes into account the emotional regulation mechanism and when it does not. The agent has emotional memories; they are from previous experiences and help to provide the desired behavior.
{"title":"An emotional regulation model with memories for virtual agents","authors":"Jonathan-Hernando Rosales, Karina Jaime, Félix F. Ramos, M. Ramos","doi":"10.1109/ICCI-CC.2013.6622253","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622253","url":null,"abstract":"Emotional regulation is a mechanism to adjust our behavior to the current environment. We use this mechanism to achieve goals and objectives. This paper proposes a model for emotional regulation in virtual agents based on biological evidence of human brain function. The evidence shows different brain activation during emotional regulation. The model defines the techniques that are implemented, the data flow, and the data processing in each brain area during the emotional regulation. In the case study, a virtual agent shows behavior changes when it takes into account the emotional regulation mechanism and when it does not. The agent has emotional memories; they are from previous experiences and help to provide the desired behavior.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114999423","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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