Earticle

The growing global demand for Agaricus bisporus has focused on automated harvesting systems, prompting the adoption of artificial intelligence to enhance precision and efficiency. This study aimed to prove the possibility of automated analysis for mushroom phenotypic traits including pileus diameter and color parameters (L*, a*, b*) by using AI model, YOLOv11-seg. Mushroom images were obtained in custom-designed imaging chamber and image training was processed using YOLOv11-seg. By achieving an mAP50 of 0.96, model demonstrated high detection and segmentation performance with stable predictive behavior. To evaluate biological validity, predicted phenotypic traits were compared with mechanically measured values. Pearson correlation coefficient analysis showed that the correlation coefficient for chromaticity was above 0.69, while the correlation coefficient for shoulder diameter was very low at 0.03. Linear regression analysis showed correlations above 0.69 for all phenotypic traits, indicating that the model analysis reflected the actual measurement variation well. Mean absolute error (MAE) analysis showed less than 10% error of 1.32, 2.43, 0.55, and 0.90 in pileus diameter, L*, a*, and b*, respectively, resulting in significant model accuracy. Based on these results, YOLO-based estimation of pileus area was processed to prove the model’s capacity to extract phenotypic traits beyond the limits of traditional analysis. These results indicate that AI models including YOLOv11 show the possibility of the automated growth monitoring for the next-generation smart cultivation systems.

In the present study, a new microbial TTI system was developed based on encapsulation techniques. TTI response (color change) was evaluated by using primarily the CIELab coordinates which were further used for the conversion into the secondary and tertiary variables and finally compared all the variables to choose the best ones for calculation of activation energy (Ea) quickly and accurately. In order to select the best variables for calculating the Ea, 95% confidence interval was also used. Primary variable $a^*$ exhibited the best linearity, narrowest 95% confidence interval and simplicity in interpretation of the color-developing reaction. Ea of the developed microbial TTIs ranged from 57.28 to 110.23 kJ/mol and maintains a consistent performance similar to that of other microbial and nonmicrobial TTIs which are commercially available. Therefore, it can be concluded that this new microbial TTI system can be used effectively in the food industry for monitoring food quality.

최근 10년 동안의 측광 및 분광관측을 통하여 우리은하 내 구상성단들 중 대부분이 적어도 2개 이상의 항성종족을 갖는다고 밝혀졌다. 현재까지 이루어진 대부분의 구상성단의 항성종족 연구에서는 관측된 색등급도와 항성종족 합성모델 사이에 eye-fitting을 함으로써 항성종족 파라미터, 즉 중원소함량, 나이, 헬륨함량 등을 추정해왔다. 우리는 구상성단의 항성종족을 분석하기 위해 ${\chi}^2$-Minimization에 의거하여 구상성단과 항성종족 합성모델의 Hess Diagram을 비교하고, 수치계산 기법을 도입하여 최적의 파라미터를 추정하는 알고리즘을 개발하였다. 이 연구에서는 가상으로 만든 성단에 대하여 Recovery Test를 수행함으로써 이 알고리즘의 Self-Consistency를 검증하였고, 실제 관측결과를 사용하여 이 연구의 적용 가능성을 조사하였다.

최근 10년 동안의 측광 및 분광관측을 통하여 우리은하 내 구상성단들 중 대부분이 적어도 2개 이상의 항성종족을 갖는다고 밝혀졌다. 현재까지 이루어진 대부분의 구상성단의 항성종족 연구에서는 관측된 색등급도와 항성종족 합성모델 사이에 eye-fitting을 함으로써 항성종족 파라미터, 즉 중원소함량, 나이, 헬륨함량 등을 추정해왔다. 우리는 구상성단의 항성종족을 분석하기 위해 ${\chi}^2$-Minimization에 의거하여 구상성단과 항성종족 합성모델의 Hess Diagram을 비교하고, 수치계산 기법을 도입하여 최적의 파라미터를 추정하는 알고리즘을 개발하였다. 이 연구에서는 가상으로 만든 성단에 대하여 Recovery Test를 수행함으로써 이 알고리즘의 Self-Consistency를 검증하였고, 실제 관측결과를 사용하여 이 연구의 적용 가능성을 조사하였다.

PURPOSE. The purpose of this study was to derive and compare the inherent color (hue angle, chroma), translucency ($TP_{SCI}$), surface gloss (${\Delta}E^*_{SCE-SCI}$), and surface roughness ($R_a$) amongst selected shades and brands of three hybrid CAD/CAM blocks [GC Cerasmart (CS); Lava Ultimate (LU); Vita Enamic (VE)]. MATERIALS AND METHODS. The specimens (N = 225) were prepared into square-shaped ($12{\times}12mm^2$) with different thicknesses and shades. The measurements of color, translucency, and surface gloss were performed by a reflection spectrophotometer. The surface roughness and surface topography were assessed by white light interferometry. RESULTS. Results revealed that hue and chroma values were influenced by the material type, material shade, and material thickness (P < .001). The order of hue angle amongst the materials was LU > CS > VE, whereas the order of chroma was VE > CS > LU. $TP_{SCI}$ results demonstrated a significant difference in terms of material types and material thicknesses ($P{\leq}.001$). $TP_{SCI}$ values of the tested materials were ordered as LU > CS > VE. ${\Delta}E^*_{SCE-SCI}$ and $R_a$ results were significantly varied amongst the materials (P < .001) and amongst the shades (P < .05). The order of ${\Delta}E^*_{SCE-SCI}$ amongst the materials were as follows $LU>VE{\geq}CS$, whereas the order of $R_a$ was $CS{\geq}VE>LU$. CONCLUSION. Nano-ceramic and polymer-infiltrated-feldspathic ceramic-network CAD/CAM materials exhibited different optical, inherent color and surface parameters.

Viewing zone shape and size perform a key role in creating viewing comfort for the viewer. The horizontal and vertical sizes of viewing zones, formed by a full color transmission type holographic screen with a stereoscopic image projection are investigated. The screens have been recorded as holograms of a narrow stripe shaped object with different width; to extend the vertical size of the viewing zone the holograms were exposed two times with the hologram shifting between exposures. The viewing zone parameters were measured as a function of the stripe width of the object and of the exit pupil size of projection optics for several holographic screens having the size of the 30 $\times$ 40 $\textrm{cm}^2$.

PURPOSE. The purpose of this study is to mix dental ceramic powder in varying ratios and evaluate the effect of the mixing ratio on color and translucency. MATERIALS AND METHODS. The ceramic powder of shade A3 of the same product was mixed with the shade A2 of three products: IPS e.max Ceram (Ivoclar Vivadent, Schaan, Liechtenstein), Vintage Halo (SHOFU Inc., Kyoto, Japan), and Ceramco 3 (Ceramco-Dentsply, Burlington, NJ, USA) in the following fixed ratios (0 wt%, 25 wt%, 50 wt%, 75 wt%, and 100 wt%) and then fired. A total of 150 specimen of ceramic fired were manufactured in a regular size (W: 8.5 mm, L: 10.5 mm, and H: 1.5 mm). For color and translucency, $L^*$, $a^*$, and $b^*$ were measured and Two-way analysis of variance (ANOVA) and One-way analysis of variance (ANOVA) were used for data analysis (${\alpha}$=0.05). RESULTS. The higher the mixing ratio was, $L^*$, $a^*$, and $b^*$ of IPS e.max Ceram were all increased, and $L^*$ of Vintage Halo was reduced and $a^*$ and $b^*$ were increased. $L^*$ and $a^*$ of Ceramco3 were reduced and $b^*$ of Ceramco3 was increased. Color difference (${\Delta}E^*ab$) was increased in all three products as the mixing ratio got higher. Increased mixing ratios resulted in decreased translucency parameter (TP) values for IPS e.max Ceram but increased TP values for Vintage Halo and Ceramco3. CONCLUSION. In this limited study, CIE $L^*$, $a^*$, and $b^*$ were influenced by the mixing ratio of the A3 powders and porcelain powder mixtures represented a various color and translucency.

본 연구에서는 2종류의 색온도(4000 K, 2700 K)조건 하에서 작업자의 피로도를 평가하기 위하여 피험자에게 검색작업을 부가하고 주관평가 및 생리신호를 측정하였다. 주관평가는 ME(Magnitude Estimation)법의 설문지를 사용했으며, 생리신호는 ECG, 맥파, 피부전도도, 피부온도, 호흡, 뇌파를 측정하여 그중 ECG신호를 분석하였다. ECG신호 파라미터로서 IBI, BPM, 평균 BPM, LF/HF, CSI, CVI, CV-RR를 분석한 결과, 특히 CSI, CVI, CV-RR가 피로도와 상관관계가 높았다.

이미지 정보 수집을 위해 스마트폰과 비전 카메라를 활용한 템플릿을 설계하고, 색상 정보를 기반으로 상태 판별에 적합한 주요 파라미터를 도출하였다. 이를 위해 RGB 채널 중 G값, HSL 모델의 L값, 그리고 Brightness의 평균 및 표준편차를 핵심 분석 요소로 선정하였다. 또한, 색상 정보와 상태 판별 간의 관계를 정량적으로 분석하기 위해 Pearson 상관 계수를 적용하여 신뢰성 있는 판별 기준을 마련하였다. 본 이미지 상태 판별 방법론은 픽셀 단위에서 최대한의 색상 민감성을 활용하는 접근 방식에 기반하며, 스마트폰과 청색 필터를 적용한 비전 카메라를 이용한 이미지 처리 과정을 통해 그 유효성을 검증하였다. 이러한 연구를 바탕으로 효과적인 상태 판별이 가능한 구조적 프로그램을 개발하였으며, 이를 비전 카메라 시스템에 적용하여 실용성을 확보하였다.

We designed a template utilizing smartphones and vision cameras for image data collection and derived key parameters suitable for state classification based on color information. To achieve this, we selected the mean and standard deviation of the G value in the RGB channel, the L value in the HSL model, and Brightness as the core analytical elements. Additionally, to quantitatively analyze the relationship between color information and state classification, we applied the Pearson correlation coefficient, establishing a reliable classification criterion. This image state classification methodology is based on an approach that maximizes color sensitivity at the pixel level. Its validity was verified through an image processing procedure using smartphones and vision cameras with a blue filter. Based on this research, we developed a structured program capable of effective state classification and integrated it into a vision camera system, ensuring its practical applicability.

시각 정보 중 색채는 인간의 감성을 일으키는 중요한 요소이다. 그러므로 감성을 유발하거나 예측하기 위해서 색의 효과를 확인하는 것은 중요하다. 본 연구는 색채에 따른 감성의 차이를 확인하고자 색채 자극에 따른 심혈관 반응을 측정하였다. 색채 자극은 Red, Green, Blue, Cyan, Mangenta, Yellow의 6가지 색상으로 구성된 이미지들을 사용하였다. 실험에 참여한 대학생 26명(남자 13명)은 Electrocardiogram (ECG) 센서를 착용하고 모니터에 제시된 각 자극을 본 후 주관감성을 평가하였다. 색채 자극에 따른 심혈관 반응 데이터는 Kruskal-wallis 검정과 Mann-Whitney 검정을 수행하여 분석하였다. 그 결과 Coherence ratio가 Green과 Magenta (p=.004), Red (p=.006), Yellow (p=.004) 색상에서 유의한 차이가 있었다. 본 연구는 색상에 따른 유효한 심혈관 반응 변수와 감성의 차이를 확인하였으며 이러한 차이는 쾌-불쾌의 감성과 관련이 있었다. 본 연구는 녹색이 쾌의 감성을 유발하고 적색이 불쾌의 감성을 유발할 수 있음을 보인 실증적인 연구로써 의의가 있다.

Color is a significant factor for evoking human emotion. Therefore, the effects of color have been analyzed to predict and evaluate human emotion. The purpose of this study was to measure the cardiovascular responses depending on color stimuli in order to observe differences in color-emotions. Images consisting of six colors (red, green, blue, cyan, magenta, yellow) were used as visual stimuli. 26 college or graduate students (13 males) watched the color stimuli on the monitor and scored their subjective emotion while electrocardiogram (ECG) was meausred. The effects of the color on emotion were tested using Kruskal-Wallis test and Mann-Whitney U test. The coherence ratio showed significant differences between green and magenta (p = .004), green and red (p = .006), and green and yellow (p = .004). The significant differences of cardiovascular and emotions were relevant to emotional valence. This study shows significance as an empirical study by indicating that green induces pleasant and red induces unpleasant.