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김기일(K. I. Kim),권기억(K. E. Kwon),박지형(J. H. Park),최영(Y. Choi),조성욱(S. W. Cho) 한국정밀공학회 2006 한국정밀공학회 학술발표대회 논문집 Vol.2006 No.5월
In this paper, the CAE Service System for Collaborative Engineering Environment with web services and Multi-frontal Method has been investigated and developed. The enabling technologies such as SOAP and .NET Framework play great roles in the development of integrated distributed application software. In addition to the distribution of analysis modules, numerical solution process itself is again divided into parallel processes using Multi-frontal Method for computational efficiency. We believe that the proposed approach for the analysis can be extended to the entire product development process for sharing and utilizing common product data in the distributed engineering environment.
Classification of directional cognition EEG using deep learning
심희동,박현준,안장원,현예나,양석조 대한기계학회 2021 대한기계학회 춘추학술대회 Vol.2021 No.4
Brain-Computer Interface(BCI) decodes human`s thoughts into machine commands using biological signals such as Electroencephalography(EEG). However, most high-performance BCI applications are based on reactive methods like SSVEP(Steady-State Visual Evoked Potential). These methods are not only counter-intuitive, but also requiring external stimulus. Since these problems are due to low-level of understanding on human cognitive processes, to solve these, biosignal-based understanding is essential. One of the most non-intuitively used in BCI system is directional information. Even though directional information is frequently used in BCI systems, it is still used in an indirect way. In this study, we designed cognitive tasks to elicit directional cognition from subjects while measuring EEG. To elicit directional cognition, subjects were stimulated in visual and auditory sounds such as directional arrows, words and sounds. These datasets were labeled with the stimulated directions. Deep learning based neural networks were trained to classify and compared the classification results with conventional methods. We believe that the results of this study will improve the understanding in directional cognition processes through electroencephalography.