Pub Date : 2016-08-01DOI: 10.1109/ICCI-CC.2016.7862077
Niken Prasasti, Takehiko Yamaguchi, H. Ohwada
Difficulty in performing the activities of daily living is a key clinical feature of early cognitive decline in older adults and has also been associated with the early stage of dementia in mild cognitive impairment (MCI). As the number of individuals with dementia and the development of technology rise, an immersive virtual environment or virtual reality has been used in therapy for memory problems in the area of MCI. This study evaluated the use of finger movement data obtained from the virtual-reality-based application and its ability to cluster patients with everyday action impairment. Here, as a pilot study, nine healthy adults completed lunch box packing as an everyday action task in the designated virtual reality called the Virtual Kitchen (VK), equipped with a leap motion controller to record their finger movement. We converted the finger movements to acceleration data and then employed a time series clustering algorithm to create several clusters based on the data set. In addition, to comprehensively review the clustering result, we assessed performance-based measures for the experiment using the Naturalistic Action Test (NAT). The final results indicate that the clusters formed by using the acceleration data seem reasonably analogous to the performance measures (i.e., the type and number of errors that occurred).
{"title":"Utilizing finger movement data to cluster patients with everyday action impairment","authors":"Niken Prasasti, Takehiko Yamaguchi, H. Ohwada","doi":"10.1109/ICCI-CC.2016.7862077","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2016.7862077","url":null,"abstract":"Difficulty in performing the activities of daily living is a key clinical feature of early cognitive decline in older adults and has also been associated with the early stage of dementia in mild cognitive impairment (MCI). As the number of individuals with dementia and the development of technology rise, an immersive virtual environment or virtual reality has been used in therapy for memory problems in the area of MCI. This study evaluated the use of finger movement data obtained from the virtual-reality-based application and its ability to cluster patients with everyday action impairment. Here, as a pilot study, nine healthy adults completed lunch box packing as an everyday action task in the designated virtual reality called the Virtual Kitchen (VK), equipped with a leap motion controller to record their finger movement. We converted the finger movements to acceleration data and then employed a time series clustering algorithm to create several clusters based on the data set. In addition, to comprehensively review the clustering result, we assessed performance-based measures for the experiment using the Naturalistic Action Test (NAT). The final results indicate that the clusters formed by using the acceleration data seem reasonably analogous to the performance measures (i.e., the type and number of errors that occurred).","PeriodicalId":135701,"journal":{"name":"2016 IEEE 15th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124240248","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 : 2016-08-01DOI: 10.1109/ICCI-CC.2016.7862089
Samiul Azam, M. Gavrilova
Gender estimation for security and forensic purposes is not a trivial task. Recently, researchers provided methods for predicting gender based on face-images, fingerprint ridge density, body shape, voice and gait. No research to date have been concerned with using one's image aesthetic preferences for predicting gender. Cognitively and psychologically, males and females have different visual aesthetic preferences. This paper is a proof of concept that it is possible to use image's perceptual aesthetic features to identify the gender of a person. This article identifies a bag of image aesthetic features and selects a number of most differentiating features using filter and wrapping selection methods. To improve the classification accuracy, weighted combination of decisions obtained by the conventional binary classifiers is used. The final decision is made based on the fusion of probabilities generated by the mixture of classifiers. The prediction model is trained and tested on a database consisting of 24000 images from 120 Flickr users. Experiment shows that a proper weight assignments allows to obtain 77% accuracy in gender prediction based on aesthetics alone.
{"title":"Soft biometric: Give me your favorite images and i will tell your gender","authors":"Samiul Azam, M. Gavrilova","doi":"10.1109/ICCI-CC.2016.7862089","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2016.7862089","url":null,"abstract":"Gender estimation for security and forensic purposes is not a trivial task. Recently, researchers provided methods for predicting gender based on face-images, fingerprint ridge density, body shape, voice and gait. No research to date have been concerned with using one's image aesthetic preferences for predicting gender. Cognitively and psychologically, males and females have different visual aesthetic preferences. This paper is a proof of concept that it is possible to use image's perceptual aesthetic features to identify the gender of a person. This article identifies a bag of image aesthetic features and selects a number of most differentiating features using filter and wrapping selection methods. To improve the classification accuracy, weighted combination of decisions obtained by the conventional binary classifiers is used. The final decision is made based on the fusion of probabilities generated by the mixture of classifiers. The prediction model is trained and tested on a database consisting of 24000 images from 120 Flickr users. Experiment shows that a proper weight assignments allows to obtain 77% accuracy in gender prediction based on aesthetics alone.","PeriodicalId":135701,"journal":{"name":"2016 IEEE 15th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122607548","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 : 2016-08-01DOI: 10.1109/ICCI-CC.2016.7862055
Etienne Dumesnil, Philippe-Olivier Beaulieu, M. Boukadoum
This work presents the implementation of operant conditioning (OC) and classical conditioning (CC) with a single spiking neural network (SNN) architecture, thus suggesting that the two types of leaning may relate to the same cognitive process. Both are achieved by using a modified version of spike-timing-dependent plasticity (STDP), where the connection weight between a cue neuron and an action neuron depends on the temporal relation between their spikes and those of a reward neuron. This reward driven STDP (RD-STDP) was implemented with simple computational resources to form an electronic robot's brain, using an adaptation of the synapto-dendritic kernel adapting neuron (SKAN) model. Then, a robot driven by the new neuronal architecture was tested in a maze with changing features, successfully exhibiting CC and OC. These results and the simple computational resources used make the proposed architecture promising for very large scale time-dependent parallel data analysis, with high capacity of adaptation in a dynamic environment. Moreover, it proposes a theoretic framework to model learning by conditioning.
{"title":"Robotic implementation of classical and operant conditioning within a single SNN architecture","authors":"Etienne Dumesnil, Philippe-Olivier Beaulieu, M. Boukadoum","doi":"10.1109/ICCI-CC.2016.7862055","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2016.7862055","url":null,"abstract":"This work presents the implementation of operant conditioning (OC) and classical conditioning (CC) with a single spiking neural network (SNN) architecture, thus suggesting that the two types of leaning may relate to the same cognitive process. Both are achieved by using a modified version of spike-timing-dependent plasticity (STDP), where the connection weight between a cue neuron and an action neuron depends on the temporal relation between their spikes and those of a reward neuron. This reward driven STDP (RD-STDP) was implemented with simple computational resources to form an electronic robot's brain, using an adaptation of the synapto-dendritic kernel adapting neuron (SKAN) model. Then, a robot driven by the new neuronal architecture was tested in a maze with changing features, successfully exhibiting CC and OC. These results and the simple computational resources used make the proposed architecture promising for very large scale time-dependent parallel data analysis, with high capacity of adaptation in a dynamic environment. Moreover, it proposes a theoretic framework to model learning by conditioning.","PeriodicalId":135701,"journal":{"name":"2016 IEEE 15th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123663386","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 : 2016-08-01DOI: 10.1109/ICCI-CC.2016.7862056
N. Melton, D. Wunsch
A method for hybridizing supervised learning with adaptive dynamic programming was developed to increase the speed, quality, and robustness of on-line neural network learning from an imperfect teacher. Reinforcement learning is used to modify and enhance the original supervisory signal before learning occurs. This paper describes the method of hybridization and presents a model problem in which a human supervisor teaches a simulated car to drive around a race track. Simulation results show successful learning and improvements in convergence time, error rate, and stability over either component method alone.
{"title":"Enhancing supervisory training signals with environmental reinforcement learning using adaptive dynamic programming and artificial neural networks","authors":"N. Melton, D. Wunsch","doi":"10.1109/ICCI-CC.2016.7862056","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2016.7862056","url":null,"abstract":"A method for hybridizing supervised learning with adaptive dynamic programming was developed to increase the speed, quality, and robustness of on-line neural network learning from an imperfect teacher. Reinforcement learning is used to modify and enhance the original supervisory signal before learning occurs. This paper describes the method of hybridization and presents a model problem in which a human supervisor teaches a simulated car to drive around a race track. Simulation results show successful learning and improvements in convergence time, error rate, and stability over either component method alone.","PeriodicalId":135701,"journal":{"name":"2016 IEEE 15th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130058863","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 : 2016-08-01DOI: 10.1109/ICCI-CC.2016.7862027
J. D. T. Gonzalez, W. Kinsner
This paper compares the probability similarities between a cyberattack, the distributed denial-of-service, and the mathematical model of probability, Lévy walks. This comparison aims to explore the validity of Lévy walks as a model resembling the DDoS probability features. This research also presents a method, based on the Smirnov transform, for generating synthetic data with the statistical properties of Lévy-walks. This method for synthetic data generation can be utilized for generating arbitrary prescribed probability density functions (pdf). The Smirnov transform is used to solve a cybersecurity engineering problem associated with Internet traffic. The synthetic Lévy-walk process is intertwined with sections of other distinct characteristics (uniform noise, Gaussian noise, and an ordinary sinusoid) to create a composite signal, which is then analyzed with zero-crossing rate (ZCR) within a varying-size window. This paper shows that it is possible to identify the distinct sections present in the composite signal through ZCR. The differentiation of these sections shows an increasing ZCR value as the section under analysis exhibits a higher activity or complexity (from the sinusoid, to a synthetic Lévy-walk process, and uniform and Gaussian noise, respectively). The advantages of the ZCR computation directly in the time-domain are appealing for real-time implementations. The varying window in the ZCR produces more defined values as the window size increases. The changing world of security systems is deeply considered, in an approach for its improvement. This as our society is highly dependent on electronically interconnected systems-of-systems demanding operational robustness and security. The approach proposed for providing a higher degree of security aiming to the development of cognitive security systems.
{"title":"Zero-crossing analysis of Lévy walks for real-time feature extraction: Composite signal analysis for strengthening the IoT against DDoS attacks","authors":"J. D. T. Gonzalez, W. Kinsner","doi":"10.1109/ICCI-CC.2016.7862027","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2016.7862027","url":null,"abstract":"This paper compares the probability similarities between a cyberattack, the distributed denial-of-service, and the mathematical model of probability, Lévy walks. This comparison aims to explore the validity of Lévy walks as a model resembling the DDoS probability features. This research also presents a method, based on the Smirnov transform, for generating synthetic data with the statistical properties of Lévy-walks. This method for synthetic data generation can be utilized for generating arbitrary prescribed probability density functions (pdf). The Smirnov transform is used to solve a cybersecurity engineering problem associated with Internet traffic. The synthetic Lévy-walk process is intertwined with sections of other distinct characteristics (uniform noise, Gaussian noise, and an ordinary sinusoid) to create a composite signal, which is then analyzed with zero-crossing rate (ZCR) within a varying-size window. This paper shows that it is possible to identify the distinct sections present in the composite signal through ZCR. The differentiation of these sections shows an increasing ZCR value as the section under analysis exhibits a higher activity or complexity (from the sinusoid, to a synthetic Lévy-walk process, and uniform and Gaussian noise, respectively). The advantages of the ZCR computation directly in the time-domain are appealing for real-time implementations. The varying window in the ZCR produces more defined values as the window size increases. The changing world of security systems is deeply considered, in an approach for its improvement. This as our society is highly dependent on electronically interconnected systems-of-systems demanding operational robustness and security. The approach proposed for providing a higher degree of security aiming to the development of cognitive security systems.","PeriodicalId":135701,"journal":{"name":"2016 IEEE 15th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130070864","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 : 2016-08-01DOI: 10.1109/ICCI-CC.2016.7862057
Christina Schweikert, S. Shimojo, D. F. Hsu
When tasked with comparing two images on a screen, a subject's eye movement can be captured and analyzed in order to understand the process of preference formation. The process of comparing two images and developing a preference is analyzed based on a sample dataset. Although it is known in general that our preferences are shaped by our past experiences, a systemic understanding of the factors which lead to preference decision making remains a challenging problem. In this paper, we propose a set of five attributes which are extracted from the temporal eye movement sequence: last duration, total duration, gaze count, interest sustainability, and region change. Each of these five attributes is a scoring system (ranking system). We then use the combinatorial fusion algorithm (CFA) framework to combine pairs of attributes using the rank-score characteristic (RSC) function and cognitive diversity (CD). Our results demonstrate that combination of two attributes can improve individual attributes if the attribute pair has a higher cognitive diversity. Our work represents a new paradigm to use combinatorial fusion for preference detection based on eye movement.
{"title":"Detecting preferences based on eye movement using combinatorial fusion","authors":"Christina Schweikert, S. Shimojo, D. F. Hsu","doi":"10.1109/ICCI-CC.2016.7862057","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2016.7862057","url":null,"abstract":"When tasked with comparing two images on a screen, a subject's eye movement can be captured and analyzed in order to understand the process of preference formation. The process of comparing two images and developing a preference is analyzed based on a sample dataset. Although it is known in general that our preferences are shaped by our past experiences, a systemic understanding of the factors which lead to preference decision making remains a challenging problem. In this paper, we propose a set of five attributes which are extracted from the temporal eye movement sequence: last duration, total duration, gaze count, interest sustainability, and region change. Each of these five attributes is a scoring system (ranking system). We then use the combinatorial fusion algorithm (CFA) framework to combine pairs of attributes using the rank-score characteristic (RSC) function and cognitive diversity (CD). Our results demonstrate that combination of two attributes can improve individual attributes if the attribute pair has a higher cognitive diversity. Our work represents a new paradigm to use combinatorial fusion for preference detection based on eye movement.","PeriodicalId":135701,"journal":{"name":"2016 IEEE 15th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130115868","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 : 2016-08-01DOI: 10.1109/ICCI-CC.2016.7862038
Boxu Zhao, G. Luo, Jihong Zhu
Based on experimental data from the large amplitude oscillation experiment conducted with two degrees of freedom, this work studies and compares the ability of Polynomial Regression, LS-SVM and RBF network to describe the characteristics of unsteady nonlinear aerodynamics. This work also develops a hybrid model for use in unsteady nonlinear aerodynamics based on the standard boosting method. The results indicate that the forecast results and actual data are in good agreement using the method, thus demonstrating that these methods can effectively model highly nonlinear aerodynamics. The results also indicate that the hybrid model has a better effect compared to other methods.
{"title":"A weighted hybrid model for unsteady nonlinear aerodynamics","authors":"Boxu Zhao, G. Luo, Jihong Zhu","doi":"10.1109/ICCI-CC.2016.7862038","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2016.7862038","url":null,"abstract":"Based on experimental data from the large amplitude oscillation experiment conducted with two degrees of freedom, this work studies and compares the ability of Polynomial Regression, LS-SVM and RBF network to describe the characteristics of unsteady nonlinear aerodynamics. This work also develops a hybrid model for use in unsteady nonlinear aerodynamics based on the standard boosting method. The results indicate that the forecast results and actual data are in good agreement using the method, thus demonstrating that these methods can effectively model highly nonlinear aerodynamics. The results also indicate that the hybrid model has a better effect compared to other methods.","PeriodicalId":135701,"journal":{"name":"2016 IEEE 15th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116134282","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 : 2016-08-01DOI: 10.1109/ICCI-CC.2016.7862068
Shangzhu Jin, Jike Ge, Jun Peng
Terrorist attacks launched by extremist groups or individuals have caused catastrophic consequences worldwide. Terrorism risk assessment therefore plays a crucial role in national and international security. Fuzzy reasoning-based terrorism risk assessment systems offer a significant potential of providing decision support in combating terrorism, where highly complex situations may be involved. However, missing expertise often presents challenges for configuring systems that can otherwise assess the likelihood and risk of possible attacks due to the availability of only sparse rule bases. Hierarchical fuzzy rule interpolation systems may be adopted in order to overcome such problems. Unfortunately, situations can become more sophisticated because certain important antecedent values may be missing, which need to be inferred from the known (or hypothesised) consequences. Initial theoretical work on backward fuzzy rule interpolation has been proposed to cope with certain underlying problems. Nevertheless, little has been done in developing and applying an integrated hierarchical bidirectional (forward/backward) fuzzy rule interpolation mechanism that is tailored to suit decision support for terrorism risk assessment. This paper presents such an integrated approach that is capable of dealing with dynamic and insufficient information in the risk assessing process. In particular, the hierarchical system implementing the proposed techniques can predict the likelihood of terrorism attacks on different segments of focused attention. It also helps identify hidden variables that may be useful during the decision support process via performing reverse inference. The results of an experimental investigation of this implemented system are represented, demonstrating the potential and efficacy of the proposed approach.
{"title":"Terrorism risk assessment using hierarchical bidirectional fuzzy rule interpolation","authors":"Shangzhu Jin, Jike Ge, Jun Peng","doi":"10.1109/ICCI-CC.2016.7862068","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2016.7862068","url":null,"abstract":"Terrorist attacks launched by extremist groups or individuals have caused catastrophic consequences worldwide. Terrorism risk assessment therefore plays a crucial role in national and international security. Fuzzy reasoning-based terrorism risk assessment systems offer a significant potential of providing decision support in combating terrorism, where highly complex situations may be involved. However, missing expertise often presents challenges for configuring systems that can otherwise assess the likelihood and risk of possible attacks due to the availability of only sparse rule bases. Hierarchical fuzzy rule interpolation systems may be adopted in order to overcome such problems. Unfortunately, situations can become more sophisticated because certain important antecedent values may be missing, which need to be inferred from the known (or hypothesised) consequences. Initial theoretical work on backward fuzzy rule interpolation has been proposed to cope with certain underlying problems. Nevertheless, little has been done in developing and applying an integrated hierarchical bidirectional (forward/backward) fuzzy rule interpolation mechanism that is tailored to suit decision support for terrorism risk assessment. This paper presents such an integrated approach that is capable of dealing with dynamic and insufficient information in the risk assessing process. In particular, the hierarchical system implementing the proposed techniques can predict the likelihood of terrorism attacks on different segments of focused attention. It also helps identify hidden variables that may be useful during the decision support process via performing reverse inference. The results of an experimental investigation of this implemented system are represented, demonstrating the potential and efficacy of the proposed approach.","PeriodicalId":135701,"journal":{"name":"2016 IEEE 15th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127038766","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 : 2016-08-01DOI: 10.1109/ICCI-CC.2016.7862040
Azzeddine Benabbou, D. Lourdeaux, D. Lenne
Critical situations are situations where a complementarity between technical and non-technical skills is crucial. Several critical dimensions characterize them. In order to train for such situations, simulation systems have to be able to generate scenarios where these dimensions are present in order to solicit one or several non-technical skills. In this paper we focus on one particular critical dimension which is the “Dilemma”. We present our approach for dynamically generating dilemma-based situations using activity and causality models.
{"title":"Dynamic generation of dilemmas in virtual learning environments for non-technical skills training","authors":"Azzeddine Benabbou, D. Lourdeaux, D. Lenne","doi":"10.1109/ICCI-CC.2016.7862040","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2016.7862040","url":null,"abstract":"Critical situations are situations where a complementarity between technical and non-technical skills is crucial. Several critical dimensions characterize them. In order to train for such situations, simulation systems have to be able to generate scenarios where these dimensions are present in order to solicit one or several non-technical skills. In this paper we focus on one particular critical dimension which is the “Dilemma”. We present our approach for dynamically generating dilemma-based situations using activity and causality models.","PeriodicalId":135701,"journal":{"name":"2016 IEEE 15th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131074924","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 : 2016-08-01DOI: 10.1109/ICCI-CC.2016.7862028
Ding Wang
Near Earth missions ranging from low-Earth orbit (LEO) to Earth-Sun Lagrangian points will continue to be a majority of future space missions. A few works have been done with delay/disruption tolerant networking (DTN) technology for LEO-satellite communications and provided feasibility for its adoption in LEO space missions. However, no much work has been done to fully evaluate the performance of DTN in such an environment, especially in the presence of long link disruption, data corruption and loss, and link asymmetry. In this paper, we present an experimental performance evaluation of DTN architecture and protocol stack, with Licklider transmission protocol (LTP) serving as a convergence layer adapter (CLA) underneath bundle protocol (BP), in a typical LEO-satellite communication infrastructure accompanied by a very long link outage, various packet corruption and loss rates, and channel rate symmetry and asymmetry. The experiment was conducted by performing realistic file transfers over a PC-based test-bed.
{"title":"Performance of Licklider transmission protocol (LTP) in LEO-satellite communications with link disruptions","authors":"Ding Wang","doi":"10.1109/ICCI-CC.2016.7862028","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2016.7862028","url":null,"abstract":"Near Earth missions ranging from low-Earth orbit (LEO) to Earth-Sun Lagrangian points will continue to be a majority of future space missions. A few works have been done with delay/disruption tolerant networking (DTN) technology for LEO-satellite communications and provided feasibility for its adoption in LEO space missions. However, no much work has been done to fully evaluate the performance of DTN in such an environment, especially in the presence of long link disruption, data corruption and loss, and link asymmetry. In this paper, we present an experimental performance evaluation of DTN architecture and protocol stack, with Licklider transmission protocol (LTP) serving as a convergence layer adapter (CLA) underneath bundle protocol (BP), in a typical LEO-satellite communication infrastructure accompanied by a very long link outage, various packet corruption and loss rates, and channel rate symmetry and asymmetry. The experiment was conducted by performing realistic file transfers over a PC-based test-bed.","PeriodicalId":135701,"journal":{"name":"2016 IEEE 15th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122233343","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：