Pub Date : 2019-07-01DOI: 10.1109/ICCICC46617.2019.9146068
Ismael Ali, A. Melton
In this era of data-analytics, the unstructured text remains the main data format. The vector space model is commonly used in representing and modeling text semantics; however, it has some limitations. The main alternative for the vector space model is the graph model from graph theory. Then, the question is: On what basis should text semantics be modeled using graph modeling? Using semantic-graphs, cognitive-semantics tries to answer this question, as it models underlying mechanisms of our human cognition modules in learning, representing and expanding semantics. The fact that textual data is produced in the form of human natural language by human cognition skills means that a reverse-engineering methodology could be promising to extract back semantics from text. In this paper, we present a systematic perspective of the main computational graph-based cognitive-semantic models of human memory, that have been used for the semantic processing of unstructured text. The applications, strengths, and limitations of each model are described. Finally, open problems, future work and conclusions are presented.
{"title":"Computational Cognitive-Semantic Based Semantic Learning, Representation and Growth: A Perspective","authors":"Ismael Ali, A. Melton","doi":"10.1109/ICCICC46617.2019.9146068","DOIUrl":"https://doi.org/10.1109/ICCICC46617.2019.9146068","url":null,"abstract":"In this era of data-analytics, the unstructured text remains the main data format. The vector space model is commonly used in representing and modeling text semantics; however, it has some limitations. The main alternative for the vector space model is the graph model from graph theory. Then, the question is: On what basis should text semantics be modeled using graph modeling? Using semantic-graphs, cognitive-semantics tries to answer this question, as it models underlying mechanisms of our human cognition modules in learning, representing and expanding semantics. The fact that textual data is produced in the form of human natural language by human cognition skills means that a reverse-engineering methodology could be promising to extract back semantics from text. In this paper, we present a systematic perspective of the main computational graph-based cognitive-semantic models of human memory, that have been used for the semantic processing of unstructured text. The applications, strengths, and limitations of each model are described. Finally, open problems, future work and conclusions are presented.","PeriodicalId":294902,"journal":{"name":"2019 IEEE 18th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"5 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":"114211678","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/ICCICC46617.2019.9146033
Hang Ya, G. Luo
Point cloud object detection is a key step in many 3D applications, such as autonomous driving and housekeeping robots. In this paper, we present MPNet, a Multi-Scale PointPillars Network for 3D object detection using point clouds. This paper aims at high accuracy and efficient speed. The proposed neural network is mainly composed of three part, a feature extracting part, a region proposal network, and finally a detection head. We use multi-scale encoders to concurrently extract features by PointNet, and then treat the 3D feature map as a pseudo image with many channels. Inspired by feature pyramid networks (FPN) and deformable convolution, our region proposal network achieves high accuracy while keeps high speed. MPNet combines features with different receptive field, and accelerates model by using 2D convolution, balancing the accuracy and speed well. Experiments on KITTI car detection benchmark show that our MPNet captures better location information on the bird's eye view. It ranks the third place in the Bird's Eye View Leaderboard. Meanwhile, it is the most efficient model compared within the top 10 models in the Bird's Eye View leaderboard.
{"title":"Multi-Scale PointPillars 3D Object Detection Network","authors":"Hang Ya, G. Luo","doi":"10.1109/ICCICC46617.2019.9146033","DOIUrl":"https://doi.org/10.1109/ICCICC46617.2019.9146033","url":null,"abstract":"Point cloud object detection is a key step in many 3D applications, such as autonomous driving and housekeeping robots. In this paper, we present MPNet, a Multi-Scale PointPillars Network for 3D object detection using point clouds. This paper aims at high accuracy and efficient speed. The proposed neural network is mainly composed of three part, a feature extracting part, a region proposal network, and finally a detection head. We use multi-scale encoders to concurrently extract features by PointNet, and then treat the 3D feature map as a pseudo image with many channels. Inspired by feature pyramid networks (FPN) and deformable convolution, our region proposal network achieves high accuracy while keeps high speed. MPNet combines features with different receptive field, and accelerates model by using 2D convolution, balancing the accuracy and speed well. Experiments on KITTI car detection benchmark show that our MPNet captures better location information on the bird's eye view. It ranks the third place in the Bird's Eye View Leaderboard. Meanwhile, it is the most efficient model compared within the top 10 models in the Bird's Eye View leaderboard.","PeriodicalId":294902,"journal":{"name":"2019 IEEE 18th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"94 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":"114224003","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/ICCICC46617.2019.9146036
Yingxu Wang, James Y. Xu
AI programming toward autonomous software generation is not only a highly demanded technology by the software industry, but also a hard challenge to the theories of software engineering and computational intelligence. A methodology and tool for autonomous program generation (APG) are recently developed based on Real-Time Process Algebra (RTPA). This paper demonstrates an experimental result of autonomous code generation on a digital clock system by the APG tool. The experimental results indicate a novel approach towards AI programming for machine-enabled software generation theories and technologies.
{"title":"RTPA-based Software Generation by AI Programming","authors":"Yingxu Wang, James Y. Xu","doi":"10.1109/ICCICC46617.2019.9146036","DOIUrl":"https://doi.org/10.1109/ICCICC46617.2019.9146036","url":null,"abstract":"AI programming toward autonomous software generation is not only a highly demanded technology by the software industry, but also a hard challenge to the theories of software engineering and computational intelligence. A methodology and tool for autonomous program generation (APG) are recently developed based on Real-Time Process Algebra (RTPA). This paper demonstrates an experimental result of autonomous code generation on a digital clock system by the APG tool. The experimental results indicate a novel approach towards AI programming for machine-enabled software generation theories and technologies.","PeriodicalId":294902,"journal":{"name":"2019 IEEE 18th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"32 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":"114509141","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/ICCICC46617.2019.9146094
Z. Bochniarz
Higher education's most important role is to effectively respond to 21st century challenges by generating new knowledge and shaping human and social capital to resolve communities/stakeholder problems and secure sustainable development. The 21st century has been characterized by rapid changes that have produced numerous challenges, ranging from climate change, information overload and fake news; growing populism, nationalism and xenophobia that increase the probability of conflicts and wars; huge gaps between the rich and the poor; and emerging new technologies that could either empower people or make them more dependent on ruling, and often non-democratic, governments. All these challenges make the future much more uncertain and riskier than ever before. Academia needs to respond to these emerging conditions with an appropriate “toolkit” for students to survive and prosper.
{"title":"How Should Higher Education Respond to 21st Century Challenges? Some Practical Comments","authors":"Z. Bochniarz","doi":"10.1109/ICCICC46617.2019.9146094","DOIUrl":"https://doi.org/10.1109/ICCICC46617.2019.9146094","url":null,"abstract":"Higher education's most important role is to effectively respond to 21st century challenges by generating new knowledge and shaping human and social capital to resolve communities/stakeholder problems and secure sustainable development. The 21st century has been characterized by rapid changes that have produced numerous challenges, ranging from climate change, information overload and fake news; growing populism, nationalism and xenophobia that increase the probability of conflicts and wars; huge gaps between the rich and the poor; and emerging new technologies that could either empower people or make them more dependent on ruling, and often non-democratic, governments. All these challenges make the future much more uncertain and riskier than ever before. Academia needs to respond to these emerging conditions with an appropriate “toolkit” for students to survive and prosper.","PeriodicalId":294902,"journal":{"name":"2019 IEEE 18th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"1 6 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":"122583739","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/ICCICC46617.2019.9146096
Qimin Zhang, N. Chen
Based on the big data theory and data mining of gas pipeline failure history, the key factors determining the safety of pipeline system are found out, such as probability, function, time and prescribed conditions. Based on the reliability principle, the interference state of probability density distribution of stress and strength is analyzed, and the failure area of pipeline is obtained. Deviation coefficient and reliability coefficient are introduced to establish a reliability evaluation model for a hydrogen blistering defect in gas transmission pipelines, which is distinguished by normal distribution function. After variable replacement, the nonstandard normal distribution function can be transformed into the standard normal distribution function. Referring to the national unified standards for reliability design of building structures, and considering the failure characteristics and consequences of ductile failure of pipeline steel, the criteria for judging reliability of pipeline defects are reasonably determined. Taking the hydrogen bubbling defect of ZQ gas pipeline as an example, the reliability of single bubbling defect and adjacent bubbling defect with different sizes under yield strength and blasting pressure are calculated respectively, and the safety grade of pipeline is evaluated, which provides scientific decision-making basis for safe operation of pipeline.
{"title":"Reliability Analysis of Hydrogen Bubble Defects in Gas Pipeline Based on Big Data","authors":"Qimin Zhang, N. Chen","doi":"10.1109/ICCICC46617.2019.9146096","DOIUrl":"https://doi.org/10.1109/ICCICC46617.2019.9146096","url":null,"abstract":"Based on the big data theory and data mining of gas pipeline failure history, the key factors determining the safety of pipeline system are found out, such as probability, function, time and prescribed conditions. Based on the reliability principle, the interference state of probability density distribution of stress and strength is analyzed, and the failure area of pipeline is obtained. Deviation coefficient and reliability coefficient are introduced to establish a reliability evaluation model for a hydrogen blistering defect in gas transmission pipelines, which is distinguished by normal distribution function. After variable replacement, the nonstandard normal distribution function can be transformed into the standard normal distribution function. Referring to the national unified standards for reliability design of building structures, and considering the failure characteristics and consequences of ductile failure of pipeline steel, the criteria for judging reliability of pipeline defects are reasonably determined. Taking the hydrogen bubbling defect of ZQ gas pipeline as an example, the reliability of single bubbling defect and adjacent bubbling defect with different sizes under yield strength and blasting pressure are calculated respectively, and the safety grade of pipeline is evaluated, which provides scientific decision-making basis for safe operation of pipeline.","PeriodicalId":294902,"journal":{"name":"2019 IEEE 18th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"22 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":"115334848","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/ICCICC46617.2019.9146102
Sutasinee Thovuttikul, Y. Ohmoto, T. Nishida
Learning about cultural differences between individuals is a challenging topic because people from many different countries have to work, live, and communicate together, but everyone's background affects their perception. Herein, we create a virtual cultural learning assistance system that can help people learn and interact with cultural agents and learn conversational skills. Learning from simulated first- and third-person camera points of view (POVs) is a method through which participants obtain different perspectives and understandings of a situation. This experiment was conducted with Japanese participants, who were asked to learn from and interact with a digital avatar acting as a customer agent and shopkeeper at the Thai night market. The behavior of the customer agent and the shopkeeper avatar were designed based on the Hofstede cultural dimension with Thai cultural values (Individualism:20, Masculinity:34, Uncertainty avoidance:64). A significant difference between first- and third-person POV groups was found on the individualism dimension (IDV). Results showed that most Japanese participants in the third-person POV group understood the Thai culture IDV better from our simulation than those in the first-person POV group. Furthermore, participants from both first- and third-person POV groups gave a similar score for Thai culture in the masculinity and uncertainty avoidance dimensions. Thus, this scenario and setting were suitable for learning and understanding Thai cultural communication at the night flea-market in both first- and third-person POVs.
{"title":"Using First-and Third-person POV to Bridge Cultural Misunderstandings in Cognitive Learning System of Different Cultural Communication in Simulated Crowd","authors":"Sutasinee Thovuttikul, Y. Ohmoto, T. Nishida","doi":"10.1109/ICCICC46617.2019.9146102","DOIUrl":"https://doi.org/10.1109/ICCICC46617.2019.9146102","url":null,"abstract":"Learning about cultural differences between individuals is a challenging topic because people from many different countries have to work, live, and communicate together, but everyone's background affects their perception. Herein, we create a virtual cultural learning assistance system that can help people learn and interact with cultural agents and learn conversational skills. Learning from simulated first- and third-person camera points of view (POVs) is a method through which participants obtain different perspectives and understandings of a situation. This experiment was conducted with Japanese participants, who were asked to learn from and interact with a digital avatar acting as a customer agent and shopkeeper at the Thai night market. The behavior of the customer agent and the shopkeeper avatar were designed based on the Hofstede cultural dimension with Thai cultural values (Individualism:20, Masculinity:34, Uncertainty avoidance:64). A significant difference between first- and third-person POV groups was found on the individualism dimension (IDV). Results showed that most Japanese participants in the third-person POV group understood the Thai culture IDV better from our simulation than those in the first-person POV group. Furthermore, participants from both first- and third-person POV groups gave a similar score for Thai culture in the masculinity and uncertainty avoidance dimensions. Thus, this scenario and setting were suitable for learning and understanding Thai cultural communication at the night flea-market in both first- and third-person POVs.","PeriodicalId":294902,"journal":{"name":"2019 IEEE 18th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"17 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":"115563187","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/ICCICC46617.2019.9146081
Ljiljana Šerić, D. Krstinić, Pero Bogunovic
Cognitive process of selecting appropriate information plays important role in perception of hazardous phenomenon. Monitoring and early detection of phenomenon are popular measures used for preventing natural and man-induced hazards. Forest fires management can especially benefit from early fire detection. Forest fire video surveillance improves effectiveness of monitoring, especially if automatic fire detection and alarming is a part of a video surveillance system. However, real benefits of monitoring, early detection and fire prevention can only be achieved with human engagement in decision making about the fire hazard. In this paper we report research and preliminary results on the subject of measuring and controlling visual attention in forest fire video monitoring and surveillance system. The research is designed to discover if an operator's attention can be controlled in a working environment of monitoring operative center (MOC). Control of the visual attention would enable more rapid detection of fire. With this in mind, we designed and executed two experiments. In first experiment we measured the time taken for fire detection by subjects in several different scenarios. In other experiment we performed measurement of EEG signal of subjects with single electrode instrument during monitoring period and fire detection. Analysis of the results shows that time taken to detect phenomenon depends on scenario of the video stream and that subject's recognition of fire can be detected with non invasive EEG measurement.
{"title":"Measuring and Controlling Cognitive Process of Visual Attention in Forest Fire Monitoring System","authors":"Ljiljana Šerić, D. Krstinić, Pero Bogunovic","doi":"10.1109/ICCICC46617.2019.9146081","DOIUrl":"https://doi.org/10.1109/ICCICC46617.2019.9146081","url":null,"abstract":"Cognitive process of selecting appropriate information plays important role in perception of hazardous phenomenon. Monitoring and early detection of phenomenon are popular measures used for preventing natural and man-induced hazards. Forest fires management can especially benefit from early fire detection. Forest fire video surveillance improves effectiveness of monitoring, especially if automatic fire detection and alarming is a part of a video surveillance system. However, real benefits of monitoring, early detection and fire prevention can only be achieved with human engagement in decision making about the fire hazard. In this paper we report research and preliminary results on the subject of measuring and controlling visual attention in forest fire video monitoring and surveillance system. The research is designed to discover if an operator's attention can be controlled in a working environment of monitoring operative center (MOC). Control of the visual attention would enable more rapid detection of fire. With this in mind, we designed and executed two experiments. In first experiment we measured the time taken for fire detection by subjects in several different scenarios. In other experiment we performed measurement of EEG signal of subjects with single electrode instrument during monitoring period and fire detection. Analysis of the results shows that time taken to detect phenomenon depends on scenario of the video stream and that subject's recognition of fire can be detected with non invasive EEG measurement.","PeriodicalId":294902,"journal":{"name":"2019 IEEE 18th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"183 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":"127027161","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/ICCICC46617.2019.9146055
Yushi Li, G. Baciu
The 3D scanning and reconstruction technologies for augmented reality, autonomous vehicles, remote sensing, GIS, object recognition and localization, are often impaired by a critical fundamental problem: noise. Noise is even more problematic in 3D models generated by SfM, or Structure from Motion. Here, the outlier points have an adverse effect on the processing and application of the generated point clouds that are often the basis for 3D feature detection, localization and navigation algorithms. In general, visualization of 3D environments, navigation, and volumetric medical image segmentation present numerous challenges when noisy outliers interfere with the surface delimiters of the scanned objects. In this paper, we propose an effective strategy to filter noisy points generated in the process of SfM reconstruction. We formulate a novel approach based on an adaptive moving least squares (MLS) to optimize the geometric structure of a typical 3D indoor scene model. Different from other existing adaptive MLS, our method considers the adverse interactions between the neighboring non-continuous model components. The effectiveness and the performance of our approach is demonstrated on extended indoor scene models generated from 3D point clouds based on SfM.
{"title":"Multiscale Point Cloud Optimization for SfM Reconstruction","authors":"Yushi Li, G. Baciu","doi":"10.1109/ICCICC46617.2019.9146055","DOIUrl":"https://doi.org/10.1109/ICCICC46617.2019.9146055","url":null,"abstract":"The 3D scanning and reconstruction technologies for augmented reality, autonomous vehicles, remote sensing, GIS, object recognition and localization, are often impaired by a critical fundamental problem: noise. Noise is even more problematic in 3D models generated by SfM, or Structure from Motion. Here, the outlier points have an adverse effect on the processing and application of the generated point clouds that are often the basis for 3D feature detection, localization and navigation algorithms. In general, visualization of 3D environments, navigation, and volumetric medical image segmentation present numerous challenges when noisy outliers interfere with the surface delimiters of the scanned objects. In this paper, we propose an effective strategy to filter noisy points generated in the process of SfM reconstruction. We formulate a novel approach based on an adaptive moving least squares (MLS) to optimize the geometric structure of a typical 3D indoor scene model. Different from other existing adaptive MLS, our method considers the adverse interactions between the neighboring non-continuous model components. The effectiveness and the performance of our approach is demonstrated on extended indoor scene models generated from 3D point clouds based on SfM.","PeriodicalId":294902,"journal":{"name":"2019 IEEE 18th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"22 4 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":"128636794","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/ICCICC46617.2019.9146093
Yuya Hatakeyama, Runhe Huang, Bowen Du, N. Yen, Haiquan Wang
Studies concerning sentiment analysis haven drawn attentions from a wide spectrum of researchers in the past few years. One of the most eye-catching topics within this emerging field is how emotion can be dectected and extracted properly from the given contexts. This study chooses content from novel to stimulate above mentioned long contexts, and expects analysis results can be projected to a three-dimensions space model. Two major tasks are conducted. First, specific content selected from novel is proceeded through morpheme analysis to estimate emotion status. Second, obtained emotion status is calculated through existing emotion dictionary which was built based on data from the novel. Results are then demonstrated on the three-dimensions space model. At last, two experiments, a systematic way to compare emotion status and an empirical questionnaire, are conducted to verify the performance of proposed method.
{"title":"Personalized group of readers' emotion traits modeling based on sentimental analysis of novels","authors":"Yuya Hatakeyama, Runhe Huang, Bowen Du, N. Yen, Haiquan Wang","doi":"10.1109/ICCICC46617.2019.9146093","DOIUrl":"https://doi.org/10.1109/ICCICC46617.2019.9146093","url":null,"abstract":"Studies concerning sentiment analysis haven drawn attentions from a wide spectrum of researchers in the past few years. One of the most eye-catching topics within this emerging field is how emotion can be dectected and extracted properly from the given contexts. This study chooses content from novel to stimulate above mentioned long contexts, and expects analysis results can be projected to a three-dimensions space model. Two major tasks are conducted. First, specific content selected from novel is proceeded through morpheme analysis to estimate emotion status. Second, obtained emotion status is calculated through existing emotion dictionary which was built based on data from the novel. Results are then demonstrated on the three-dimensions space model. At last, two experiments, a systematic way to compare emotion status and an empirical questionnaire, are conducted to verify the performance of proposed method.","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":"133113455","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/ICCICC46617.2019.9146030
Piero Dominici
We are dealing with a new hypertechnological era, a phase of radical global mutation that forces us to reformulate our thoughts on categories, codes, languages, instruments, identity, subjectivity, cultural norms and models, (open) communities, relational and communicative areas, environment and ecosystems. Our extraordinary scientific discoveries and technological innovations not only open dizzily onto as yet unimaginable horizons and scenarios, but show, ever more clearly, the urgency of radically rethinking education, teaching and training, underlining the substantial inadequacy of our schools and universities in dealing with this hypercomplexity, in dealing with the indeterminateness and ambivalence of the ongoing metamorphosis, in dealing with the radical interdependence and interconnection of all processes and dynamics; in dealing with the global extension of all political, social and cultural processes. In the Hyperconnected Society, rethinking education is not linked only to technological innovation and to its disruptive velocity; it is not simply a matter of extending or adjusting the traditional educational methods and processes to deal with the digital revolution and with the paradigm shift it has determined. It is not simply a matter of updating contents. The idea that education and educational processes are questions of a purely technical and/or technological nature, solely a problem of skills and know-how and nothing more, is the “great mistake” we are making. It is necessary to rethink education radically because the extraordinary scientific discoveries and the dynamics of the new technologies have completely overturned the complex interaction between biological and cultural evolution, doing away with the borders between the natural and the artificial, leading us not towards simplification, but in quite the opposite direction.
{"title":"Educating for the Future in the Age of Obsolescence","authors":"Piero Dominici","doi":"10.1109/ICCICC46617.2019.9146030","DOIUrl":"https://doi.org/10.1109/ICCICC46617.2019.9146030","url":null,"abstract":"We are dealing with a new hypertechnological era, a phase of radical global mutation that forces us to reformulate our thoughts on categories, codes, languages, instruments, identity, subjectivity, cultural norms and models, (open) communities, relational and communicative areas, environment and ecosystems. Our extraordinary scientific discoveries and technological innovations not only open dizzily onto as yet unimaginable horizons and scenarios, but show, ever more clearly, the urgency of radically rethinking education, teaching and training, underlining the substantial inadequacy of our schools and universities in dealing with this hypercomplexity, in dealing with the indeterminateness and ambivalence of the ongoing metamorphosis, in dealing with the radical interdependence and interconnection of all processes and dynamics; in dealing with the global extension of all political, social and cultural processes. In the Hyperconnected Society, rethinking education is not linked only to technological innovation and to its disruptive velocity; it is not simply a matter of extending or adjusting the traditional educational methods and processes to deal with the digital revolution and with the paradigm shift it has determined. It is not simply a matter of updating contents. The idea that education and educational processes are questions of a purely technical and/or technological nature, solely a problem of skills and know-how and nothing more, is the “great mistake” we are making. It is necessary to rethink education radically because the extraordinary scientific discoveries and the dynamics of the new technologies have completely overturned the complex interaction between biological and cultural evolution, doing away with the borders between the natural and the artificial, leading us not towards simplification, but in quite the opposite direction.","PeriodicalId":294902,"journal":{"name":"2019 IEEE 18th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"19 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":"134434331","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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