Shushma Patel, D. Patel, M. Gusev, S. Ristov, J. Tasic, D. Tasic
{"title":"Mind gymnastics for good intellectual health of elderly people - MindGym","authors":"Shushma Patel, D. Patel, M. Gusev, S. Ristov, J. Tasic, D. Tasic","doi":"10.1109/ICCI-CC.2015.7259403","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2015.7259403","url":null,"abstract":"MindGym aims at improving the quality of life of older citizens and their caregivers by applying mind gymnastics that will keep the elderly active in vital mental shape. We plan to realize multidisciplinary research and innovation actions to achieve the following objectives: understanding the mental health conditions, preventing disruptive mental disorders and their early diagnosis, and mind gymnastic treatment. The target of this research is to influence mental conditions that lead to some mental disorders, such as depression, dementia, sedentariness, cognitive decline and personality disorders, which are present in older people, but can also be experienced earlier. The initial, understanding phase includes scanning mind activities using different audio-visual stimuli, by applying the sophisticated fMRI and EEG technologies to identify the regions of the brain that demonstrate increased activation with positive stimuli. Prevention is based on analysis and correlation of the results and will enable the development of a methodology for increasing mind activities drawing on the conclusions from experts about which audio-visual stimuli support the best mind gymnastic; as well as matching the results on various socio-economic, gender, religious, environmental and physical factors. An interactive system based on recommended audio-visual content, IPTV, social networks, cloud enabled devices and applications will be developed as a prototype tool for creating everyday mind gymnastics. Early diagnosis of mental reactions will be determined by EEG or fMRI technologies for various stimuli, enabling conditions to detect abnormal changes in the brain activity. This paper gives an overview of current research and projects in the area. It defines the basic objectives of planned MindGym research activities.","PeriodicalId":328695,"journal":{"name":"2015 IEEE 14th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114120724","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 epistemic programming approach for automated theorem finding","authors":"Hongbiao Gao, Jingde Cheng","doi":"10.1109/ICCI-CC.2015.7259365","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2015.7259365","url":null,"abstract":"The problem of automated theorem finding is one of 33 basic research problems in automated reasoning which was originally proposed by Wos. The problem is still an open problem until now. Specific knowledge is the power of any scientist, therefore, if a scientist in a particular area takes part in the process of automated theorem finding, then the scientist should certainly make some contributions for automated theorem finding in the target area. Epistemic programming was proposed as a novel program paradigm to program epistemic processes of scientific discovery, which regards conditionals as the subject of computing, takes primary epistemic operations as basic operations of computing, and regards epistemic processes as the subject of programming. Epistemic programming provides not only programming means but also interactive means for scientists to control cognitive processes. This paper proposes an epistemic programming approach for automated theorem finding following the epistemic programming paradigm and shows some examples to do automated theorem finding by using the approach.","PeriodicalId":328695,"journal":{"name":"2015 IEEE 14th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115219413","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}
Sonia López, José-Antonio Cervantes, Félix F. Ramos, Yingxu Wang
{"title":"A cognitive model of motor planning for virtual creatures","authors":"Sonia López, José-Antonio Cervantes, Félix F. Ramos, Yingxu Wang","doi":"10.1109/ICCI-CC.2015.7259415","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2015.7259415","url":null,"abstract":"The planning is one of the most important cognitive functions of the human beings. It is essential for the solution of mental and physical problems. This paper shows a conceptual and computational model of motor planning. It is based on recent findings of the human brain and how the human can develop several motor plans in order to solve their daily problems. The objective of our bio-inspired model is to develop appropriate mechanisms to endow virtual creatures with them, in order to emulate both internal and external processes of the human brain.","PeriodicalId":328695,"journal":{"name":"2015 IEEE 14th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125434586","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 orthogonal subspace based signal design framework for satellite-terrestrial cognitive coexistence","authors":"Na Gu, Linling Kuang, Zuyao Ni, Jianhua Lu","doi":"10.1109/ICCI-CC.2015.7259371","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2015.7259371","url":null,"abstract":"To address the spectrum scarcity caused by the development of broadband services, cognitive radio is recognized as one of the most effective methods. Herein, in the perspective of cognitive radio, we study anti-interference techniques for the coexistence of satellite and terrestrial systems with the terrestrial downlink as primary and the satellite reverse link as secondary. First, a design framework based on the orthogonal subspace theory for anti-interference signals is proposed in this paper. With the extraction of the subspace gathering the interference characteristics, the satellite anti-interference signal is designed to be orthogonal to the terrestrial interference signal in the orthogonal complementary subspace. Then non-contiguous OFDMA (NC-OFDMA) and eigen-based CDMA (ECDMA) are unified in the proposed framework and their distinctions are analyzed. Finally, the performances of NC-OFDMA and ECDMA under different interference scenarios and the spectral efficiency are evaluated respectively by simulations, providing references for system engineering design.","PeriodicalId":328695,"journal":{"name":"2015 IEEE 14th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126106848","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":"Formal conversion between information and intelligence","authors":"Yixin Zhong","doi":"10.1109/ICCI-CC.2015.7259362","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2015.7259362","url":null,"abstract":"The significant law of information conversion and intelligence creation, which is also a unified theory of information, knowledge and intelligence, is discovered recently and is presented in the paper for the first time. It is the author's belief that the law reported is of great significance to the understanding of the essence of Information Science, and of the information age as well.","PeriodicalId":328695,"journal":{"name":"2015 IEEE 14th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120883845","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 cognitive multifractal approach to characterize complexity of non-stationary and malicious DNS data traffic using adaptive sliding window","authors":"Muhammad Salman Khan, K. Ferens, W. Kinsner","doi":"10.1109/ICCI-CC.2015.7259368","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2015.7259368","url":null,"abstract":"This paper presents a cognitive feature extraction model based on scaling and multifractal dimension trajectory to analyze internet traffic time series. DNS (Domain Naming System) traffic time series is considered that contains tagged DNS Denial of Service attacks. The first step of the analysis involves transforming the DNS time series into a multifractal variance dimension trajectory keeping statistical stationarity of data intact. Then features of the trajectory are extracted to remove high variability noise. The extracted set of features indicates the presence of an attack when the denoised trajectory shows increasing variance fractal dimension. This technique is superior in finding changing patterns of a data series due to the presence of noise and denial of service attack because it is not dependent on integer dimensions and mono-scale measurement of variations in data series. Moreover, this technique provides adaptive and locally stationary windows in a highly non stationary data series.","PeriodicalId":328695,"journal":{"name":"2015 IEEE 14th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130638578","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":"The study of fear-induced power modulations for Cognitive Man-Machine Communication","authors":"Naveen Irtiza, Humera Farooq","doi":"10.1109/ICCI-CC.2015.7259409","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2015.7259409","url":null,"abstract":"The efficient development of a Brain Computer Interface is based on rapid and effective discrimination of brain signals based on Electroencephalography (EEG) patterns. Any specific mental state or thinking activity results in specific pattern of brain signals. In this paper, a method has been proposed that combines recent advances in brain imaging and machine learning techniques to predict the cognitive state of the subjects whether they are feeling themselves in a safe or dangerous environment. This method is based on the mechanism of neuroception. The changes in this state are correlated with power modulations of oscillatory rhythms in the human EEG called ERD / ERS (Event-related De-synchronization / Synchronization). In order to predict these changes, it is of high significance to find the spatio-temporal distribution of EEG band-power modulations induced by the feeling of fear or danger.","PeriodicalId":328695,"journal":{"name":"2015 IEEE 14th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131144286","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":"Correlation-based pruning of dependent binary relevance models for Multi-label classification","authors":"Yahong Zhang, Yujian Li, Zhi Cai","doi":"10.1109/ICCI-CC.2015.7259416","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2015.7259416","url":null,"abstract":"Binary relevance (BR), a basic Multi-label classification (MLC) method, learns a single binary model for each different label without considering the dependences among rest of labels. Many chaining and stacking techniques exploit the dependences among labels to improve the predictive accuracy for MLC. Using these two techniques, BR has been promoted as dependent binary relevance (DBR). In this paper we propose a pruning method for DBR, in which the Phi coefficient function has been employed to estimate correlation degrees among labels for removing irrelevant labels. We conducted our pruning algorithm on benchmark multi-label datasets, and the experimental results show that our pruning approach can reduce the computational cost of DBR and improve the predictive performance generally.","PeriodicalId":328695,"journal":{"name":"2015 IEEE 14th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133115417","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":"Cooperative spectrum sensing based on the compressed sensing","authors":"Yongkui Ma, Jiaxin Liu, Yulong Gao","doi":"10.1109/ICCI-CC.2015.7259373","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2015.7259373","url":null,"abstract":"In this paper, compressed sensing is applied to cooperative spectrum sensing to reduce the number of fused data. As the modification of OR fusion, DOR fusion is proposed as merger method to deal with information from different cognitive users. And then we analyze the relationship of detection performance and the number of users. Finally, some simulations are implemented, Simulation result and theoretical analysis illustrated that DOR fusion method improves not only probability of detection but also reduce the probability of false alarm significantly compared to the commonly used OR fusion.","PeriodicalId":328695,"journal":{"name":"2015 IEEE 14th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126100048","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":"Mining probabilistic rules using nonmonotonic rule layers","authors":"S. Tsumoto, S. Hirano","doi":"10.1109/ICCI-CC.2015.7259384","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2015.7259384","url":null,"abstract":"This paper proposes a new framework for rule induction methods based on rule layers constrained by inequalities of accuracy and coverage. When the changes of accuracy and coverage are considered with an additional example, four patterns of updates of accuracy and coverage are observed and give two important inequalities of accuracy and coverage for induction of probabilistic rules. By using these two inequalities, the proposed method classifies a set of formulae into four layers: the rule layer, subrule layer (in and out) and the non-rule layer. Using these layers, updates of probabilistic rules are equivalent to their movement between layers. The proposed method was evaluated on datasets regarding headaches and meningitis, and the results show that the proposed method outperforms the conventional methods.","PeriodicalId":328695,"journal":{"name":"2015 IEEE 14th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126100502","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}