• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.1-7
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• 2022

With the development of artificial intelligence, efforts to incorporate neuroscience mining with AI have increased. Neuroscience mining, also known as NSM, expands on this concept by combining computational neuroscience and business analytics. Using fNIRS (functional near-infrared spectroscopy)-based experiment dataset, we have investigated the potential of NSM in the context of the BPSC (business problem-solving creativity) prediction. Although BPSC is regarded as an essential business differentiator and a difficult cognitive resource to imitate, measuring it is a challenging task. In the context of NSM, appropriate methods for assessing and predicting BPSC are still in their infancy. In this sense, we propose a novel NSM method that systematically combines CNN, BiLSTM, and attention network for the sake of enhancing the BPSC prediction performance significantly. We utilized a dataset containing over 150 thousand fNIRS-measured data points to evaluate the validity of our proposed NSM method. Empirical evidence demonstrates that the proposed NSM method reveals the most robust performance when compared to benchmarking methods.

• Proceedings of the Korea Contents Association Conference
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• 2018.05a
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• pp.167-168
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• 2018

The importance of business problem-solving creativity (BPSC) becomes crucial much more as competitive situations go on in the market. However, how to assess the BPSC remains an unsolved research issue yet in the literature. In this sense, this study proposes an exploratory analysis of the BPSC from the view of neuro-science experiments called fNIRS. The fNIRS represents a functional near-infrared spectroscopy, a new type of neuro-science research paradigm. This study proposes an exploratory level of how to conduct the fNIRS-based experiments to analyze the BPSC.

• Journal of the Microelectronics and Packaging Society
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• v.26 no.2
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• pp.55-58
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• 2019

Surface plasmon effect was considered importantly because of the enhancement of optical signals. It is important to detect weak optical signal in neuroscience and bio technology due to detect weaker image or signal. The height of silver can change the optical characteristic of plasmonic nano structure including transmittance and reflectance. In this paper, the optical characteristic of plasmonic nano structure were confirmed by the FDTD analysis method depending on the silver height and it was confirmed that energy was concentrated at the center of nano structure, and high far-field gain and current density in particular wavelength coule be obtained.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.19-22
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• 2022

In this work, we studied consumers' attractiveness/usefulness perceptions (CAUP) of online commerce product photos when exposed to alternative dark/light user interface (UI) modes. We analyzed time-series EEG data from 31 individuals and performed neuroscience mining (NSM) to ascertain (a) how the CAUP of products differs among UI modes; and (b) which deep learning model provides the most accurate assessment of such neuroscience mining (NSM) business difficulties. The dark UI style increased the CAUP of the products displayed and was predicted with the greatest accuracy using a unique EEG power spectra separated wave brainwave 2D-ConvLSTM model. Then, using relative importance analysis, we used this model to determine the most relevant power spectra. Our findings are considered to contribute to the discovery of objective truths about online customers' reactions to various user interface modes used by various online marketplaces that cannot be uncovered through more traditional research approaches like as surveys.