Pub Date : 2019-07-01DOI: 10.1109/ICCICC46617.2019.9146039
Yuqing Gao, Wing W. Y. Ng, Ting Wang, S. Kwong
Microarray data analysis has emerged as a strong tool for cancer diagnosis. Nevertheless, researches on it are significantly challenging as the microarray datasets are imbalanced and high-dimensional with relatively small sample size. In this paper, we utilized Dual Denoising Autoencoder Features (DDAF), which integrates two Denoising Auto-Encoders (DAE) with different activation function to map the features for both minority and majority classes into a better classification representation. The experimental results on four typical microarray datasets show that the DDAF outperforms the Dual Autoencoder Features (DAF) and the Cost-sensitive Oversampling Stacked Denoising Auto-Encoder (CO-SDAE), rendering the robust ability for dimensionality reduction and imbalanced classification.
{"title":"Dual Denoising Autoencoder Feature Learning for Cancer Diagnosis","authors":"Yuqing Gao, Wing W. Y. Ng, Ting Wang, S. Kwong","doi":"10.1109/ICCICC46617.2019.9146039","DOIUrl":"https://doi.org/10.1109/ICCICC46617.2019.9146039","url":null,"abstract":"Microarray data analysis has emerged as a strong tool for cancer diagnosis. Nevertheless, researches on it are significantly challenging as the microarray datasets are imbalanced and high-dimensional with relatively small sample size. In this paper, we utilized Dual Denoising Autoencoder Features (DDAF), which integrates two Denoising Auto-Encoders (DAE) with different activation function to map the features for both minority and majority classes into a better classification representation. The experimental results on four typical microarray datasets show that the DDAF outperforms the Dual Autoencoder Features (DAF) and the Cost-sensitive Oversampling Stacked Denoising Auto-Encoder (CO-SDAE), rendering the robust ability for dimensionality reduction and imbalanced classification.","PeriodicalId":294902,"journal":{"name":"2019 IEEE 18th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"35 3-4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120994260","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 : 2019-07-01DOI: 10.1109/ICCICC46617.2019.9146088
Lalin Heng, T. Weise
Network security is becoming more and more vital in our world as the internet permeates both the industry and our private life. Today, the means of production are networked and controlled by intelligent manufacturing process and the majority of the people are constantly connected to information systems by using mobile phones. Intrusion detection systems (IDS) are software components which detect attacks and malicious attempts to gain access to networks. How to design such systems efficiently is a question of both practical and research interest. We propose and approach based on cognitive computing using deep learning for this purpose. Our method has two main advantages: It is highly efficient and accurate, yet it is simple, builds on existing standard software, and can easily be implemented and enriched with domain knowledge by an expert from computer security with little background in machine learning. Furthermore, with the parallelism and big data support of the platform, our method will also scale well with the size of the dataset available for training. In deep learning, Convolutional neural network (CNNs) have successfully been applied to a variety of classification tasks in various fields. They are also available in easily accessible and scalable standard frameworks such as TensorFlow. In this paper, we present an approach to constructing an IDS based on CNN. Network traffic is presented based on features of TCP/IP connections and the approach is trained based on known attack signatures. We evaluate this approach using the widely available NSLKDD dataset. We are able to achieve the accuracy, precision, recall and $F_{1}$-score of 98.92%, 99.82%, 92.34%, and 96.34%, respectively. Based on its simplicity and these surprisingly good performance results, we can conclude that our approach is highly suitable for constructing IDS.
{"title":"Intrusion Detection System Using Convolutional Neuronal Networks: A Cognitive Computing Approach for Anomaly Detection based on Deep Learning","authors":"Lalin Heng, T. Weise","doi":"10.1109/ICCICC46617.2019.9146088","DOIUrl":"https://doi.org/10.1109/ICCICC46617.2019.9146088","url":null,"abstract":"Network security is becoming more and more vital in our world as the internet permeates both the industry and our private life. Today, the means of production are networked and controlled by intelligent manufacturing process and the majority of the people are constantly connected to information systems by using mobile phones. Intrusion detection systems (IDS) are software components which detect attacks and malicious attempts to gain access to networks. How to design such systems efficiently is a question of both practical and research interest. We propose and approach based on cognitive computing using deep learning for this purpose. Our method has two main advantages: It is highly efficient and accurate, yet it is simple, builds on existing standard software, and can easily be implemented and enriched with domain knowledge by an expert from computer security with little background in machine learning. Furthermore, with the parallelism and big data support of the platform, our method will also scale well with the size of the dataset available for training. In deep learning, Convolutional neural network (CNNs) have successfully been applied to a variety of classification tasks in various fields. They are also available in easily accessible and scalable standard frameworks such as TensorFlow. In this paper, we present an approach to constructing an IDS based on CNN. Network traffic is presented based on features of TCP/IP connections and the approach is trained based on known attack signatures. We evaluate this approach using the widely available NSLKDD dataset. We are able to achieve the accuracy, precision, recall and $F_{1}$-score of 98.92%, 99.82%, 92.34%, and 96.34%, respectively. Based on its simplicity and these surprisingly good performance results, we can conclude that our approach is highly suitable for constructing IDS.","PeriodicalId":294902,"journal":{"name":"2019 IEEE 18th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121124091","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 : 2019-07-01DOI: 10.1109/ICCICC46617.2019.9146072
R. Zou, Yu Zou, Bihai Zou, Xin Liu
Primary and secondary schools is a centralized area of population, and the teaching buildings are the main places where the campus stampede accidents occurred. In order to reduce the occurrence of stampede accidents in primary and secondary school teaching buildings and improve the pertinence of risk prevention and control, a risk assessment and analysis model based on Bayesian network (BN) was worked out. Firstly, the risk factors of the stampede accidents in teaching buildings were summarized, and the causal relationship of each factor was analyzed, thus the BN structure was built. Then, the network parameters are determined by the data collected in the reference and the expert assignment. Finally, diagnostic reasoning was used to test and debug the model. When the model was built, the risk of stampede accidents in primary and secondary school teaching buildings was assessed by causal reasoning, and the sensitive risk factors were found with sensitivity analysis based on GenIe 2.0. The results show that the occurrence probability of stampede accidents in a teaching building is 0.87%, and strengthening safety management, especially preparation of a comprehensive and effective emergency plan, can significantly reduce the occurrence probability of stampede accidents in teaching buildings.
{"title":"A Risk Assessment Model of Stampede Accidents in Primary and Secondary School Teaching Buildings Based on Bayesian Network","authors":"R. Zou, Yu Zou, Bihai Zou, Xin Liu","doi":"10.1109/ICCICC46617.2019.9146072","DOIUrl":"https://doi.org/10.1109/ICCICC46617.2019.9146072","url":null,"abstract":"Primary and secondary schools is a centralized area of population, and the teaching buildings are the main places where the campus stampede accidents occurred. In order to reduce the occurrence of stampede accidents in primary and secondary school teaching buildings and improve the pertinence of risk prevention and control, a risk assessment and analysis model based on Bayesian network (BN) was worked out. Firstly, the risk factors of the stampede accidents in teaching buildings were summarized, and the causal relationship of each factor was analyzed, thus the BN structure was built. Then, the network parameters are determined by the data collected in the reference and the expert assignment. Finally, diagnostic reasoning was used to test and debug the model. When the model was built, the risk of stampede accidents in primary and secondary school teaching buildings was assessed by causal reasoning, and the sensitive risk factors were found with sensitivity analysis based on GenIe 2.0. The results show that the occurrence probability of stampede accidents in a teaching building is 0.87%, and strengthening safety management, especially preparation of a comprehensive and effective emergency plan, can significantly reduce the occurrence probability of stampede accidents in teaching buildings.","PeriodicalId":294902,"journal":{"name":"2019 IEEE 18th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116535117","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 : 2019-07-01DOI: 10.1109/ICCICC46617.2019.9146085
E. Çepni
Decision makers of today routinely encounter increasingly complex and interrelated problems, preceding the necessity for a large number of significant decisions to be dynamic in nature. Frequently rather than a single decision the requirement of a number of decisions exists, conventionally being interdependent on each other in an environment of progressive change. For thousands of years people have endeavoured to document observations of the environment and surroundings, with the aspiration of comprehending situations, which in turn enable a form of anticipation or prediction of the future. Through the contributions of a range of scientists and philosophers' humanity has affected the achievement of an improved quality of life, commencement of influence on the essence of life and encouragement to attempt to gain even further knowledge through travel to other planets. Without any doubt science is exceptional and dynamic and by far the optimum means of discovering the world and all that it encompasses. What hasn't changed is the curiosity, imagination and intelligence of those doing science [1]. Despite the fact that scientific discoveries and inventions invariably enhance life to a large degree as well as being accredited with expanding the expected lifespan of humans, scientific and technological improvements may equally precipitate alienation, loss of privacy, environmental problems (chemical and electronic waste), and a greater uncertainty or a black swan event. Science is perceived to be subject about knowledge with curiosity lying at the heart of it, differing from technology in that technology is preferably explained as doing. The 19th century scientist Pierre Laplace elevated determinism to a key place in science. He linked determinism and the ability to predict to the very notion of success in science [2]. For technical decisions science is an unrivalled tool to use, however, for managerial, institutional and personal daily life decisions the same recommendation cannot be given. Numerous key systems incorporated in the life of humans exhibit diverse complexities. Markets compromised of various buyers and sellers all categorized in groups participating in mutual funds, economies with hierarchies of workers, departments, firms, and industries; multi-celled organisms consisting of proteins, membranes, organelles, cells, and organs, the internet with users, stations, servers, and websites. Each of these complex systems exhibits a distinctive property called “emergence” roughly described by a phrase “the whole is more than the sum of the actions of the parts [3]. Scientists depend on the law of rationality; however, the fact that emotion habitually dominates humans on innumerable occasions is well recognized. Perhaps a more effective method for solving the problems of humanity should include deciphering the laws of human nature. As an alternative to the law of rationality, consideration could be given to whether it is preferable for scientists u
{"title":"The Science and Art Of Decision Making","authors":"E. Çepni","doi":"10.1109/ICCICC46617.2019.9146085","DOIUrl":"https://doi.org/10.1109/ICCICC46617.2019.9146085","url":null,"abstract":"Decision makers of today routinely encounter increasingly complex and interrelated problems, preceding the necessity for a large number of significant decisions to be dynamic in nature. Frequently rather than a single decision the requirement of a number of decisions exists, conventionally being interdependent on each other in an environment of progressive change. For thousands of years people have endeavoured to document observations of the environment and surroundings, with the aspiration of comprehending situations, which in turn enable a form of anticipation or prediction of the future. Through the contributions of a range of scientists and philosophers' humanity has affected the achievement of an improved quality of life, commencement of influence on the essence of life and encouragement to attempt to gain even further knowledge through travel to other planets. Without any doubt science is exceptional and dynamic and by far the optimum means of discovering the world and all that it encompasses. What hasn't changed is the curiosity, imagination and intelligence of those doing science [1]. Despite the fact that scientific discoveries and inventions invariably enhance life to a large degree as well as being accredited with expanding the expected lifespan of humans, scientific and technological improvements may equally precipitate alienation, loss of privacy, environmental problems (chemical and electronic waste), and a greater uncertainty or a black swan event. Science is perceived to be subject about knowledge with curiosity lying at the heart of it, differing from technology in that technology is preferably explained as doing. The 19th century scientist Pierre Laplace elevated determinism to a key place in science. He linked determinism and the ability to predict to the very notion of success in science [2]. For technical decisions science is an unrivalled tool to use, however, for managerial, institutional and personal daily life decisions the same recommendation cannot be given. Numerous key systems incorporated in the life of humans exhibit diverse complexities. Markets compromised of various buyers and sellers all categorized in groups participating in mutual funds, economies with hierarchies of workers, departments, firms, and industries; multi-celled organisms consisting of proteins, membranes, organelles, cells, and organs, the internet with users, stations, servers, and websites. Each of these complex systems exhibits a distinctive property called “emergence” roughly described by a phrase “the whole is more than the sum of the actions of the parts [3]. Scientists depend on the law of rationality; however, the fact that emotion habitually dominates humans on innumerable occasions is well recognized. Perhaps a more effective method for solving the problems of humanity should include deciphering the laws of human nature. As an alternative to the law of rationality, consideration could be given to whether it is preferable for scientists u","PeriodicalId":294902,"journal":{"name":"2019 IEEE 18th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127222366","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 : 2019-07-01DOI: 10.1109/ICCICC46617.2019.9146087
Sanjay Kumar, Rohit Beniwal, S. Singh, Vipul Gupta
Online social networks provide a great platform for internet users to share their views and ideas. Social media provides a dynamic platform that includes the formation and deformation of connections. Two types of connections, i.e., Positive and Negative, can exist in a social network. Positive connections are a sign of friendship or trust, while negative connections show enmity or distrust. Various applications in several fields have networks containing both positive and negative edges. Reliable prediction of edge sign can greatly influence in recommending friendly relationships while preventing enemy relationships across the network. Prediction of edge signs has been explored previously also. However, we intend to predict the sign of edges based on extracted features of nodes constructed upon theories of social psychology that includes classical balance theory and the status theory. Moreover, we employ emotional information theory and use the combined extracted features from all the theories to analyze networks for better prediction. Our results show that the proposed methodology has obtained significant accuracy when implemented on two real-life datasets, namely Slashdot and Epinions.
{"title":"Predicting Link Sign in Online Social Networks based on Social Psychology Theory and Machine Learning Techniques","authors":"Sanjay Kumar, Rohit Beniwal, S. Singh, Vipul Gupta","doi":"10.1109/ICCICC46617.2019.9146087","DOIUrl":"https://doi.org/10.1109/ICCICC46617.2019.9146087","url":null,"abstract":"Online social networks provide a great platform for internet users to share their views and ideas. Social media provides a dynamic platform that includes the formation and deformation of connections. Two types of connections, i.e., Positive and Negative, can exist in a social network. Positive connections are a sign of friendship or trust, while negative connections show enmity or distrust. Various applications in several fields have networks containing both positive and negative edges. Reliable prediction of edge sign can greatly influence in recommending friendly relationships while preventing enemy relationships across the network. Prediction of edge signs has been explored previously also. However, we intend to predict the sign of edges based on extracted features of nodes constructed upon theories of social psychology that includes classical balance theory and the status theory. Moreover, we employ emotional information theory and use the combined extracted features from all the theories to analyze networks for better prediction. Our results show that the proposed methodology has obtained significant accuracy when implemented on two real-life datasets, namely Slashdot and Epinions.","PeriodicalId":294902,"journal":{"name":"2019 IEEE 18th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"PP 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126403694","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 : 2019-07-01DOI: 10.1109/ICCICC46617.2019.9146057
Shuxin Yang, Kaili Zhu, Wenbing Liang
How to prevent the individual privacy from being disclosed and incorporate contextual information into recommendations process is an urgent problem that needs to be solved in recommendation systems. Challenged by the above, a context-aware recommendation method that integrates Differential Privacy and Bayesian Network technologies is proposed. Firstly, in order to alleviate sparsity of the rating matrix, the paper adopts k-means algorithm to cluster items. And then add noises to ratings to protect users' privacy. Finally, the probability that a user likes a certain type of project in contextual information is calculated by Bayesian formula. Experimental evaluations show that the proposed algorithm can provide a stronger privacy protection while improving the accuracy of recommendations.
{"title":"Differential Privacy for Context-Aware Recommender Systems","authors":"Shuxin Yang, Kaili Zhu, Wenbing Liang","doi":"10.1109/ICCICC46617.2019.9146057","DOIUrl":"https://doi.org/10.1109/ICCICC46617.2019.9146057","url":null,"abstract":"How to prevent the individual privacy from being disclosed and incorporate contextual information into recommendations process is an urgent problem that needs to be solved in recommendation systems. Challenged by the above, a context-aware recommendation method that integrates Differential Privacy and Bayesian Network technologies is proposed. Firstly, in order to alleviate sparsity of the rating matrix, the paper adopts k-means algorithm to cluster items. And then add noises to ratings to protect users' privacy. Finally, the probability that a user likes a certain type of project in contextual information is calculated by Bayesian formula. Experimental evaluations show that the proposed algorithm can provide a stronger privacy protection while improving the accuracy of recommendations.","PeriodicalId":294902,"journal":{"name":"2019 IEEE 18th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126424995","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 : 2019-07-01DOI: 10.1109/ICCICC46617.2019.9146097
Chaoqun Chu, G. Luo, Mingyang Zhang
With the continuous advancement of the information society, the dependence of hardware and software systems in almost all fields is increasing. Model checking is a method of automatically verifying hardware and software systems in a finite state space. If system does not satisfy the formal formula description, then the system's counterexamples are given and the system's error will be corrected. However, the typical state explosion problem increases its complexity in time and space, which severely limits its applicability. In this paper, an optimized parallel algorithm for searching strongly connected components based on CUDA(FW-BW-CUDA) is proposed, which can effectively accelerate the speed of LTL model checking algorithm. More over, experimental results based on benchmark datasets show that compared with some state-of-the-art model checking algorithms, FW-BW-CUDA performs better in terms of speed in most cases.
{"title":"An Optimized Model Checking Parallel Algorithm Based on CUDA","authors":"Chaoqun Chu, G. Luo, Mingyang Zhang","doi":"10.1109/ICCICC46617.2019.9146097","DOIUrl":"https://doi.org/10.1109/ICCICC46617.2019.9146097","url":null,"abstract":"With the continuous advancement of the information society, the dependence of hardware and software systems in almost all fields is increasing. Model checking is a method of automatically verifying hardware and software systems in a finite state space. If system does not satisfy the formal formula description, then the system's counterexamples are given and the system's error will be corrected. However, the typical state explosion problem increases its complexity in time and space, which severely limits its applicability. In this paper, an optimized parallel algorithm for searching strongly connected components based on CUDA(FW-BW-CUDA) is proposed, which can effectively accelerate the speed of LTL model checking algorithm. More over, experimental results based on benchmark datasets show that compared with some state-of-the-art model checking algorithms, FW-BW-CUDA performs better in terms of speed in most cases.","PeriodicalId":294902,"journal":{"name":"2019 IEEE 18th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"17 10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127647567","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 : 2019-07-01DOI: 10.1109/ICCICC46617.2019.9146086
S. Vidhusha, B. Divya, K. Anandan, R. Narayanan, D. Yaamini
Individuals with autism spectrum disorder demonstrate impairments in social functions including difficulties in social interactions, social communication and emotion recognition. They struggle in making eye contact and this hampers their learning due to lack of listening. Virtual reality provides a supportive environment for individuals with autism disorders to learn and practice things safely. In this work, a Virtual reality (VR) platform has been developed which acts as a simulative learning tool to teach and train kids affected with autism spectral disorder. EEG signals of participants during flashcard teaching and VR teaching sessions were acquired and functional connectivity parameters were estimated from the acquired signals. This VR experiment with autistic children indicate that their cognitive ability can be enhanced through constructive teaching by using suitable VR environments. Thus it can be extended for different learning disorders in assisting children to practice things safely without any social fear and in enhancing their interpersonal skills.
{"title":"Cognitive Attention in Autism using Virtual Reality Learning Tool","authors":"S. Vidhusha, B. Divya, K. Anandan, R. Narayanan, D. Yaamini","doi":"10.1109/ICCICC46617.2019.9146086","DOIUrl":"https://doi.org/10.1109/ICCICC46617.2019.9146086","url":null,"abstract":"Individuals with autism spectrum disorder demonstrate impairments in social functions including difficulties in social interactions, social communication and emotion recognition. They struggle in making eye contact and this hampers their learning due to lack of listening. Virtual reality provides a supportive environment for individuals with autism disorders to learn and practice things safely. In this work, a Virtual reality (VR) platform has been developed which acts as a simulative learning tool to teach and train kids affected with autism spectral disorder. EEG signals of participants during flashcard teaching and VR teaching sessions were acquired and functional connectivity parameters were estimated from the acquired signals. This VR experiment with autistic children indicate that their cognitive ability can be enhanced through constructive teaching by using suitable VR environments. Thus it can be extended for different learning disorders in assisting children to practice things safely without any social fear and in enhancing their interpersonal skills.","PeriodicalId":294902,"journal":{"name":"2019 IEEE 18th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132933333","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 : 2019-07-01DOI: 10.1109/ICCICC46617.2019.9146090
Pedro Cárdenas, Georgios Theodoropoulos, B. Obara
Social Media has become the primary communication channel to share feelings and opinions to big audiences. This characteristic is especially important when dealing with a crisis because people use it to send a variety of messages; however, to emphasise or complement what they post, individuals include links to web pages or other web services. Contributing a component to a novel framework for National Security crises analysis and management, this paper focuses on Web Insights as a mechanism that can help to comprehend the nature and state of a crisis. The mechanism analyses web resources and provides insights along three different dimensions: Firstly, the escalation of the crisis over time. Secondly, the interpretation of the information that the main actors have published (Social Networking Services, Information Outlets, Non-Governmental Organisations and Independent Websites). Thirdly, an estimate whether the crisis has turned violent.
{"title":"Web Insights for National Security: Analysing Participative Online Activity to Interpret Crises","authors":"Pedro Cárdenas, Georgios Theodoropoulos, B. Obara","doi":"10.1109/ICCICC46617.2019.9146090","DOIUrl":"https://doi.org/10.1109/ICCICC46617.2019.9146090","url":null,"abstract":"Social Media has become the primary communication channel to share feelings and opinions to big audiences. This characteristic is especially important when dealing with a crisis because people use it to send a variety of messages; however, to emphasise or complement what they post, individuals include links to web pages or other web services. Contributing a component to a novel framework for National Security crises analysis and management, this paper focuses on Web Insights as a mechanism that can help to comprehend the nature and state of a crisis. The mechanism analyses web resources and provides insights along three different dimensions: Firstly, the escalation of the crisis over time. Secondly, the interpretation of the information that the main actors have published (Social Networking Services, Information Outlets, Non-Governmental Organisations and Independent Websites). Thirdly, an estimate whether the crisis has turned violent.","PeriodicalId":294902,"journal":{"name":"2019 IEEE 18th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122348725","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 : 2019-07-01DOI: 10.1109/ICCICC46617.2019.9146083
M. V. D. Voorde, M. Fitzpatrick
The modern approach to research cuts across traditional boundaries. In order to obtain maximum benefit from research effort globally, Universities need to adapt their approaches to the management and organization of research and teaching, to foster cross-discipline working and promote global mobility for the next generation of students.
{"title":"Discovery and Innovation in Science and Technology: Inter- and trans-disciplinary in cognitive learning","authors":"M. V. D. Voorde, M. Fitzpatrick","doi":"10.1109/ICCICC46617.2019.9146083","DOIUrl":"https://doi.org/10.1109/ICCICC46617.2019.9146083","url":null,"abstract":"The modern approach to research cuts across traditional boundaries. In order to obtain maximum benefit from research effort globally, Universities need to adapt their approaches to the management and organization of research and teaching, to foster cross-discipline working and promote global mobility for the next generation of students.","PeriodicalId":294902,"journal":{"name":"2019 IEEE 18th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125728949","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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