• Science of Emotion and Sensibility
• /
• v.21 no.3
• /
• pp.151-164
• /
• 2018

The appropriate interpretation of social cues is a crucial ability for everyday life. While processing socially relevant information, beyond the low-level physical features of the stimuli to emotional information is known to influence human cognition in various stages, from early perception to later high-level cognition, such as working memory (WM). However, it remains unclear how the influence of each type of emotional information on cognitive processes changes in response to what has occurred in the processing stage. Past studies have largely adopted face stimuli to address this type of research question, but we used a unique class of socially relevant motion stimuli, called biological motion (BM), which depicts various human actions and emotions with moving dots to exhibit the effects of anger, happiness, and neutral emotion on task performance in perceptual and working memory. In this study, participants determined whether two BM stimuli, sequentially presented with a delay between them (WM task) or one immediately after the other (perceptual task), were identical. The perceptual task showed that discrimination accuracies for emotional stimuli (i.e., angry and happy) were lower than those for neutral stimuli, implying that emotional information has a negative impact on early perceptual processes. Alternatively, the results of the WM task showed that the accuracy drop as the interstimulus interval increased was actually lower in emotional BM conditions than in the neutral condition, which suggests that emotional information benefited maintenance. Moreover, anger and happiness had distinct impacts on the performance of perception and WM. Our findings have significance as we provide evidence for the interaction of type of emotion and information-processing stage.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.7
• /
• pp.685-691
• /
• 2020

In this study, an algorithm that recognizes numbers from 0 to 9 was developed using the data obtained after tracking hand movements using the echo signal of a millimeter-wave radar sensor at 77 GHz. The echo signals obtained from the radar sensor by detecting the motion of a hand gesture revealed a cluster of irregular dots due to the difference in scattering cross-sectional area. A valid center point was obtained from them by applying a K-Means algorithm using 3D coordinate values. In addition, the obtained center points were connected to produce a numeric image. The recognition rate was compared by inputting the obtained image and an image similar to human handwriting by applying the smoothing technique to a CNN (Convolutional Neural Network) model trained with MNIST (Modified National Institute of Standards and Technology database). The experiment was conducted in two ways. First, in the recognition experiments using images with and without smoothing, average recognition rates of 77.0% and 81.0% were obtained, respectively. In the experiment of the CNN model with augmentation of learning data, a recognition rate of 97.5% and 99.0% on average was obtained in the recognition experiment using the image with and without smoothing technique, respectively. This study can be applied to various non-contact recognition technologies using radar sensors.

• Journal of the Korean Crystal Growth and Crystal Technology
• /
• v.6 no.3
• /
• pp.351-359
• /
• 1996

We have investigated the effect of hydrogen plasma on the formation of InAs QDs (quantum dots) structure by using a CBE (chemical beam epitaxy)system equipped with ECR (electron cyclotron resonance) plasma source. It is confirmed that the formation of self-organized InAs-QDs on GaAs is started after the growth of InAs layer up to 2.6 ML (monolayer) with the irradiation of hydrogen plasma while it is started after 1.9 ML without hydrogen gas and hydrogen plasma through the observation of RHEED patterns. Density and size of the QDs formed at $T_{sub}=370^{\circ}C$ are $1.9{\times}10^{11}cm^{-2}$ and 17.7 nm without hydrogen plasma, and $1.3{\times}10^{11}cm^{-2}$ and 19.4 nm with hydrogen plasma, respectively. It is also observed from the PL(photoluminescence) measurement on InAs-QDs that red shift in PL peak energy and broadening in FWHM (full width at half maximum)of PL peak caused by the effects of hydrogen plasma on the increment of size and its distribution. These effects of hydrogen plasma are considered as a act of atomic hydrogen which enhances the layer-growth of InAs on GaAs resulted from the relief of misfit strain between GaAs substrate and InAs.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.43 no.1 s.307
• /
• pp.9-16
• /
• 2006

This Paper proposes an adaptive error diffusioThis paper proposes an adaptive error diffusion algorithm for text enhancement followed by an efficient text segmentation that uses the maximum gradient difference (MGD). The gradients are calculated along with scan lines, and the MGD values are filled within a local window to merge the potential text segments. Isolated segments are then eliminated in the non-text region filtering process. After the left segmentation, a conventional error diffusion method is applied to the background, while the edge enhancement error diffusion is used for the text. Since it is inevitable that visually objectionable artifacts are generated when using two different halftoning algorithms, the gradual dilation is proposed to minimize the boundary artifacts in the segmented text blocks before halftoning. Sharpening based on the gradually dilated text region (GDTR) prevents the printing of successive dots around the text region boundaries. The error diffusion algorithm with edge enhancement is extended to halftone color images to sharpen the tort regions. The proposed adaptive error diffusion algorithm involves color halftoning that controls the amount of edge enhancement using a general error filter. The multiplicative edge enhancement parameters are selected based on the amount of edge sharpening and color difference. Plus, the additional error factor is introduced to reduce the dot elimination artifact generated by the edge enhancement error diffusion. By using the proposed algorithm, the text of a scanned image is sharper than that with a conventional error diffusion without changing background.

• The Journal of the Korea Contents Association
• /
• v.12 no.5
• /
• pp.52-61
• /
• 2012

Text visualization is one of sectors in data visualization. This study is on methods to visually represent text's contents, structure, and form aspects based on various analytic techniques about wide range of text data. In this study -as a text visualization study-, 1) a method to find out the characteristics of a book's genre using words in the text of the book was looked into, 2) elements of visualization of a book's genre based on verification through an experiment were drew, and 3) the ways to intuitionally and efficiently visualize this were explained. According to visualization suggested by this study, first, actual genre of a book can be understood based on words used in the book. Second, with which genre is closed to the book can be found out with one glance through images of visualization. Moreover, the characteristics of complicated genres included in a book can be understood. Furthermore, the level of closeness (similarity) of a genre -which is found to be a representative genre using the number of dots, curvature of a curve, and brightness in the image- can be assumed. Finally, the outcome of this study can be used for a variety of fields including book customizing service such as a book recommendation system that provides images of personal preference books or genres through application of books favored by individual customers.

• Applied Chemistry for Engineering
• /
• v.28 no.6
• /
• pp.705-713
• /
• 2017

A novel material, $Bi_2WO_6-GO-TiO_2$ composite, was successfully synthesized using a facile hydrothermal method. During the hydrothermal reaction, the loading of $Bi_2WO_6$ and $TiO_2$ nanoparticles onto graphene sheets was achieved. The obtained $Bi_2WO_{6-GO-TiO2}$ composite photo-catalysts were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray (EDX) analysis, transmission electron microscopy (TEM), Raman spectroscopy, ultraviolet-visible diffuse reflectance spectroscopy (UV-vis-DRS), and X-ray photoelectron spectroscopy (XPS). The $Bi_2WO_6$ nanoparticle showed an irregular dark-square block nanoplate shape, while $TiO_2$ nanoparticles covered the surface of the graphene sheets with a quantum dot size. The degradation of rhodamine B (RhB), methylene blue trihydrate (MB), and reactive black B (RBB) dyes in an aqueous solution with different initial amount of catalysts was observed by UV spectrophotometry after measuring the decrease in the concentration. As a result, the $Bi_2WO_6-GO-TiO_2$ composite showed good decolorization activity with MB solution under visible light. The $Bi_2WO_6-GO-TiO_2$ composite is expected to become a new potential material for decolorization activity. Photocatalytic reactions with different photocatalysts were explained by the Langmuir-Hinshelwood model and a band theory.

• The Journal of Information Systems
• /
• v.27 no.1
• /
• pp.153-169
• /
• 2018

Purpose Since human brains catch images faster than texts or numbers, infographics has been widely used in business in the form of "information dashboard" to enhance the efficiency of decision-making. Groupware, however, has neglected the adoption and use of infographics, in particular, in the idea generation process. Given that an overall performance of groupware-based idea generation is no better than that of the (paper-and-pencil-based) Nominal Group Technique, Jung et al. (2010) adopted the notion of infographics in the form of performance feedback to solve the productivity paradox. With the consistent results, which demonstrate beneficial effects of infographics on performance enhancement, an interesting observation that groups with the bar chart treatment performed better than groups with the dot chart treatment was made. The main purpose of this study was to find if there were a performance consistency between the outcomes from the previous study and the outcomes from the current study. Design/methodology/approach In experiment 1, we employed the same system used in the previous study (i.e., Jung et al., 2010). As individuals' contributions accumulated, the mechanism visually displayed individuals' performances two-dimensionally in the form of a bar chart or a dot chart. Then, we compared the performance outcomes from this study to the outcomes from previous study (i.e., Jung et al., 2010). In experiment 2, we modified the performance graph to test the effect of "playfulness" on performance by converting dots to car images. Then, we compared the performance outcome from experiment 2 to the outcomes from experiment 1. Findings Just like our interesting (and unexpected) finding in Jung et al.'s study (2010), the outcome confirmed a consistent superior performance of a bar chart. This implies that a bar chart is a better choice when stimulating performance with a visual aid in the context of groupware-based idea generation. Although a bar chart was criticized in a way that errors of length-area judgments are 40 ~ 250% greater than those of positional judgments along a common scale, such illusion turned out to be facilitating upward performance comparison better. Regarding Experiment 2, the outcome showed that the revised-dot graph is as good as the bar graph in terms of quantity and quality score of ideas. We attribute the performance enhancement of the resized-dot to the interaction between the motivational characteristic and the situational characteristic of playfulness because individuals in the revised-dot graph treatment performed better than individuals in the dot graph treatment. Given the order of performance (Bar >= Revised Dot > Dot) that the revised-dot treatment performed the same as (or lower than) the bar treatment, an additional research is warranted to reach to a consistent outcome.

• Proceedings of the Korean Vacuum Society Conference
• /
• 2010.08a
• /
• pp.297-297
• /
• 2010

Precise control of the position and density of doping elements at the nanoscale is becoming a central issue for realizing state-of-the-art silicon-based optoelectronic devices. As dimensions are scaled down to take benefits from the quantum confinement effect, however, the presence of interfaces and the nature of materials adjacent to silicon turn out to be important and govern the physical properties. Utilization of visible light is a promising method to overcome the efficiency limit of the crystalline Si solar cells. Si quantum dots (QDs) have been proposed as an emission source of visible light, which is based on the quantum confinement effect. Light emission in the visible wavelength has been reported by controlling the size and density of Si QDs embedded within various types of insulating matrix. For the realization of all-Si QD solar cells with homojunctions, it is prerequisite not only to optimize the impurity doping for both p- and n-type Si QDs, but also to construct p-n homojunctions between them. In this study, XPS and SIMS were used for the development of p-type and n-type Si quantum dot solar cells. The stoichiometry of SiOx layers were controlled by in-situ XPS analysis and the concentration of B and P by SIMS for the activated doping in Si nano structures. Especially, it has been experimentally evidenced that boron atoms in silicon nanostructures confined in SiO2 matrix can segregate into the Si/$SiO_2$ interfaces and the Si bulk forming a distinct bimodal spatial distribution. By performing quantitative analysis and theoretical modelling, it has been found that boron incorporated into the four-fold Si crystal lattice can have electrical activity. Based on these findings, p-type Si quantum dot solar cell with the energy-conversion efficiency of 10.2% was realized from a [B-doped $SiO_{1.2}$(2 nm)/$SiO_2(2\;nm)]^{25}$ superlattice film with a B doping level of $4.0{\times}10^{20}\;atoms/cm^2$.

• Proceedings of the Korean Vacuum Society Conference
• /
• 2014.02a
• /
• pp.305-305
• /
• 2014

양자점(Quantum dots)은 3차원적 운반자 구속과 낮은 전류와 높은 온도에서 작동하는 나노 크기의 전기적, 광학적 소자로 응용이 적합하기 때문에 그 특성을 이용한 단전자 트랜지스터, 적외선 검출기, 레이저, LED, 태양전지 등 반도체 소자로의 응용연구가 활발히 진행되고 있다. 특히 양자점의 낮은 임계전류밀도와 높은 차동 이득(differential gain), 그리고 고온에서 작동이 용이하여 양자점 레이저로 활용되고 있다. 이러한 분야에 양자점을 응용하기 위해서는 양자점의 운반자 동역학을 이해하고 양자점의 모양, 크기, 크기 분포와 같은 특성 조절이 필요하다. 또한 기존의 연구들은 III-V족 화합물 반도체 양자점에 대한 연구가 대부분이며, II-VI족으로 구성된 연구가 미흡한 상황이기 때문에 II-VI족 화합물 반도체 양자점에 대한 많은 연구가 필요한 상황이다. II-VI 족 화합물 반도체 양자점은 기존의 III-V 족 양자점보다 더 큰 엑시톤 결합에너지(exciton binding energy)를 가지고 있으며, 이러한 특성을 가지는 II-VI 족 화합물 반도체 양자점 중에서도 CdTe 양자점은 높은 엑시톤 결합에너지와 녹색 스펙트럼 영역을 필요로 하는 광학적 장치들에 응용 가능성이 높기 때문에 더욱 주목받고 있다. 본 연구에서는 분자 선속 에피 성장법(Molecular Beam Epitaxy; MBE)과 원자 층 교대 성장법(Atomic Layer Epitaxy; ALE)으로 CdTe/ZnTe 나노구조에서 ZnTe 완충층의 두께에 따른 운반자 동역학 및 광학적 특성을 연구 하였다. 저온 광루미네센스 측정(Photoluminescence; PL) 을 통하여 ZnTe 완충층 두께가 증가할수록 양자점의 광루미네센스 피크가 낮은 에너지로 이동함을 알 수 있었는데, 이는 ZnTe 완충층의 두께가 증가할수록 ZnTe 완충층과 CdTe 양자점의 격자 불일치(lattice mismatch)로 인한 구조 변형력이 감소하고 이에 따라 CdTe 양자점으로 가해지는 변형(Strain)이 감소하여 CdTe 양자점의 크기가 증가했기 때문이다. 그리고 ZnTe 완충층의 두께가 증가할수록 PL 세기가 증가함을 알 수 있었는데, 이는 ZnTe 완충층의 두께가 증가할수록 양자 구속 효과로부터 electronic state와 conduction band edge 사이의 에너지 차이의 증가 때문이다. 또한 시분해 광루미네센스 측정 결과 ZnTe의 두께가 증가할수록 양자점의 소멸 시간이 더 길게 측정되었는데, 이는 더 큰 양자점 일수록 엑시톤 오실레이터 강도가 감소하기 때문에 더 긴 소멸 시간을 나타내는 것을 확인할 수 있었다. 결과적으로 본 연구는 ZnTe 두께 변화를 통해 양자점의 에너지 밴드를 제어할 수 있으며, 양자점의 효율 향상을 할 수 있는 좋은 방법임을 제시하고 있다.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.29 no.3C
• /
• pp.374-386
• /
• 2004

The mammogram provides the way to observe detailed internal organization of breasts to radiologists for the early detection. This paper is mainly focused on efficiently detecting the Microcalcification's Region Of Interest(ROI)s. Breast cancers can be caused from either microcalcifications or masses. Microcalcifications are appeared in a digital mammogram as tiny dots that have a little higher gray levels than their surrounding pixels. We can roughly determine the area which possibly contain microcalifications. In general, it is very challenging to find all the microcalcifications in a digital mammogram, because they are similar to some tissue parts of a breast. To efficiently detect microcalcifications ROI, we used four sequential processes; preprocessing for breast area detection, modified multilevel thresholding, ROI selection using simple thresholding filters and final ROI selection with two stages of neural networks. The filtering process with boundary conditions removes easily-distinguishable tissues while keeping all microcalcifications so that it cleans the thresholded mammogram images and speeds up the later processing by the average of 86％. The first neural network shows the average of 96.66％ recognition rate. The second neural network performs better by showing the average recognition rate 98.26％. By removing all tissues while keeping microcalcifications as much as possible, the next parts of a CAD system for detecting breast cancers can become much simpler.