• Title/Summary/Keyword: Quantitative visualization

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Analyses of Steady State Mixing Process of Two-Liquids Using Artificial Intelligence (인공지능을 이용한 이종액체 정상 상태 혼합의 혼합과정 해석)

  • KONG, DAEKYEONG;YUM, JUHO;CHO, GYEONGRAE;DOH, DEOGHEE
    • Transactions of the Korean hydrogen and new energy society
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    • v.29 no.5
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    • pp.523-529
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    • 2018
  • Two liquids which are generally used as fuels of rockets are mixed and their mixing process is quantitatively investigated by the use of particle image velocimetry (PIV). As working fluids for the liquid mixing, Dimethylfuran (DMF) and JetA1 oils have been used. Since the specific gravity of DMF is larger than that of JetA1 oil, the DMF oil has been set at the lower part of the JetA1 oil. For better visualization of the mixing process, Rhodamin B powder has been blended into the DMF oil. An agitator having 3 blades has been used for mixing the two liquids. For quantitative visualization, a LCD monitor has been used as a light source. A color camera, camcoder, has been used for recording the mixing process. The images captured by the camcoder have been digitized into three color components, R, G, and B. The color intensities of R, G, and B have been used as the inputs of the neural network of which hidden layer has 20 neurons. Color-to-concentration calibration has been performed before commencing the main experiments. Once this calibration is completed, the temporal changes of the concentration of the DMF has been quantitatively analyzed by using the constructed measurement system.

A Study on Information Visualization using Building Information Modeling (BIM을 이용한 정보 시각화에 관한 연구)

  • Cha, Gi-Chun;Park, Seunghee
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.6
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    • pp.4170-4175
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    • 2015
  • The global warming has been recognized as a serious problem. To solve this problem, the country of all the world have conducted techniques such as energy saving and reduction of greenhouse gas. The 30% of total energy is being consumed by buildings domestically and BAS/BEMS are being operated for the management of building energy. But, BEMS is unsatisfactory condition to manage the energy efficiently. In this study, We investigate real application on Chamsaem elementary school as a target buildings and develop 3D Web Browser platform. The spatial information of target buildings is described with used BIM and the energy information is presented for facilities operation and electricity consumption in floor and facility. We perform the quantitative evaluation based on ISO/IEC 9126 and operate this system for two months. in result, energy decreased by about 16%. We expect that the proposed 3D Web Browser system will bring operating efficiency improvement of the current BEMS.

Improment of Diesel Combustion using multiple injection under Cold Start Condition (냉시동 조건에서 디젤 연소 특성 및 연소 개선에 대한 연구)

  • Lee, Haeng-Soo;Lee, Jin-Woo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.4
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    • pp.711-717
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    • 2017
  • Startability and harmful emissions are the main issues in diesel engine development under cold conditions. The characteristics of combustion with multiple injection were investigated under cold start conditions. For quantitative analysis, the in-chamber pressure profile was measured and combustion visualization using direct imaging was accomplished. With multiple injection, the peak in-chamber pressure and heat release rate were increased compared to single injection. In addition, the period of flame luminosity detection was shortened using multiple injection. Combustion by main injection was improved with an increase in heat released by pilot combustion when the pilot injection quantity was increased. Finally, an increase in injection pressure also showed the possibility of combustion improvement. On the other hand, an increase of in the pilot injection quantity and injection pressure can cause an increase in harmful emissions, such as HC and CO due to wall wetting. Therefore, more sensitive calibration will be needed when applying a multiple injection strategy under cold start conditions.

Advanced Information Data-interactive Learning System Effect for Creative Design Project

  • Park, Sangwoo;Lee, Inseop;Lee, Junseok;Sul, Sanghun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.8
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    • pp.2831-2845
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    • 2022
  • Compared to the significant approach of project-based learning research, a data-driven design project-based learning has not reached a meaningful consensus regarding the most valid and reliable method for assessing design creativity. This article proposes an advanced information data-interactive learning system for creative design using a service design process that combines a design thinking. We propose a service framework to improve the convergence design process between students and advanced information data analysis, allowing students to participate actively in the data visualization and research using patent data. Solving a design problem by discovery and interpretation process, the Advanced information-interactive learning framework allows the students to verify the creative idea values or to ideate new factors and the associated various feasible solutions. The student can perform the patent data according to a business intelligence platform. Most of the new ideas for solving design projects are evaluated through complete patent data analysis and visualization in the beginning of the service design process. In this article, we propose to adapt advanced information data to educate the service design process, allowing the students to evaluate their own idea and define the problems iteratively until satisfaction. Quantitative evaluation results have shown that the advanced information data-driven learning system approach can improve the design project - based learning results in terms of design creativity. Our findings can contribute to data-driven project-based learning for advanced information data that play a crucial role in convergence design in related standards and other smart educational fields that are linked.

Hexagonal Grid Shadow Generation using Bézier Curves (베지어 곡선을 활용한 육각 그리드의 그림자 생성 방법)

  • Minseok Kim;Taekgwan Nam;Youngjin Park
    • Smart Media Journal
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    • v.12 no.4
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    • pp.47-57
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    • 2023
  • The hexagonal grid structure has been studied for processing and representing spatial information data in Geographic Information Systems. Visualization using a hexagonal grid has high visibility compared to other grid representation methods. However, it is difficult to effectively convey quantitative data and differences between grids depending on the geospatial data represented. In this paper, we propose a method to visually emphasize the hexagonal grid by generating shadow on the outside of the hexagonal grid. To do so, we offset the outer line segments of the hexagonal grid to be emphasized and generate a Bézier curve based on that information to determine the final shadow shape. We also apply variable transparency toward the edges of the shadow because the shadow gradually fades away from the hexagonal grid. We have shown that the proposed method can effectively generate shadow areas given not only a single hexagonal grid but also multiple hexagonal grids and can generate various shadow shapes based on user interface inputs. We apply the proposed method to Yongsan-gu, one of the districts of Seoul, and show the results of visually emphasizing it after generating shadow using the proposed method.

Chlorophyll contents and expression profiles of photosynthesis-related genes in water-stressed banana plantlets

  • Sri Nanan Widiyanto;Syahril Sulaiman;Simon Duve;Erly Marwani;Husna Nugrahapraja;Diky Setya Diningrat
    • Journal of Plant Biotechnology
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    • v.50
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    • pp.127-136
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    • 2023
  • Water scarcity decreases the rate of photosynthesis and, consequently, the yield of banana plants (Musa spp). In this study, transcriptome analysis was performed to identify photosynthesis-related genes in banana plants and determine their expression profiles under water stress conditions. Banana plantlets were in vitro cultured on Murashige and Skoog agar medium with and without 10% polyethylene glycol and marked as BP10 and BK. Chlorophyll contents in the plant shoots were determined spectrophotometrically. Two cDNA libraries generated from BK and BP10 plantlets, respectively, were used as the reference for transcriptome data. Gene ontology (GO) enrichment analysis was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) and visualized using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway prediction. Morphological observations indicated that water deficiency caused chlorosis and reduced the shoot chlorophyll content of banana plantlets. GO enrichment identified 52 photosynthesis-related genes that were affected by water stress. KEGG visualization revealed the pathways related to the 52 photosynthesisr-elated genes and their allocations in four GO terms. Four, 12, 15, and 21 genes were related to chlorophyll biosynthesis, the Calvin cycle, the photosynthetic electron transfer chain, and the light-harvesting complex, respectively. Differentially expressed gene (DEG) analysis using DESeq revealed that 45 genes were down-regulated, whereas seven genes were up-regulated. Four of the down-regulated genes were responsible for chlorophyll biosynthesis and appeared to cause the decrease in the banana leaf chlorophyll content. Among the annotated DEGs, MaPNDO, MaPSAL, and MaFEDA were selected and validated using quantitative real-time PCR.

Dark-Blood Computed Tomography Angiography Combined With Deep Learning Reconstruction for Cervical Artery Wall Imaging in Takayasu Arteritis

  • Tong Su;Zhe Zhang;Yu Chen;Yun Wang;Yumei Li;Min Xu;Jian Wang;Jing Li;Xinping Tian;Zhengyu Jin
    • Korean Journal of Radiology
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    • v.25 no.4
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    • pp.384-394
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    • 2024
  • Objective: To evaluate the image quality of novel dark-blood computed tomography angiography (CTA) imaging combined with deep learning reconstruction (DLR) compared to delayed-phase CTA images with hybrid iterative reconstruction (HIR), to visualize the cervical artery wall in patients with Takayasu arteritis (TAK). Materials and Methods: This prospective study continuously recruited 53 patients with TAK (mean age: 33.8 ± 10.2 years; 49 females) between January and July 2022 who underwent head-neck CTA scans. The arterial- and delayed-phase images were reconstructed using HIR and DLR. Subtracted images of the arterial-phase from the delayed-phase were then added to the original delayed-phase using a denoising filter to generate the final-dark-blood images. Qualitative image quality scores and quantitative parameters were obtained and compared among the three groups of images: Delayed-HIR, Dark-blood-HIR, and Dark-blood-DLR. Results: Compared to Delayed-HIR, Dark-blood-HIR images demonstrated higher qualitative scores in terms of vascular wall visualization and diagnostic confidence index (all P < 0.001). These qualitative scores further improved after applying DLR (Dark-blood-DLR compared to Dark-blood-HIR, all P < 0.001). Dark-blood DLR also showed higher scores for overall image noise than Dark-blood-HIR (P < 0.001). In the quantitative analysis, the contrast-to-noise ratio (CNR) values between the vessel wall and lumen for the bilateral common carotid arteries and brachiocephalic trunk were significantly higher on Dark-blood-HIR images than on Delayed-HIR images (all P < 0.05). The CNR values were significantly higher for Dark-blood-DLR than for Dark-blood-HIR in all cervical arteries (all P < 0.001). Conclusion: Compared with Delayed-HIR CTA, the dark-blood method combined with DLR improved CTA image quality and enhanced visualization of the cervical artery wall in patients with TAK.

The Near-Infrared Imaging Spectroscopy to Visualize the Distribution of Sugar Content in the Flesh of a Melon

  • Tsuta, Mizuki;Sugiyama, Junichi;Sagara, Yasuyuki
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1526-1526
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    • 2001
  • To improve the accuracy of sweetness sensor in automated sorting operations, it is necessary to clarify unevenness of the sugar content distribution within fruits. And it is expected that the technique to evaluate the content distribution in fruits contribute to the development of the near-infrared (NIR) imaging spectroscopy. Sugiyama (1999) had succeeded to visualize the distribution of the sugar content on the surface of a half-cut green fresh melon. However, this method cannot be applied to red flesh melons because it depends on information of the absorption band of chlorophyll (676 nm), which is affected by the color of the fresh. The objective of this study was to develop the universal visualization method depends on the absorption band of sugar, which can be applied to various kinds of melons and other fruits. The relationship between the sugar contents and absorption spectra of both green and red fresh melons were investigated by using a NIR spectrometer to determine the absorption band of sugar. The combination of 2$\^$nd/ derivative absorbances at 902 nm and 874 nm was highly correlated with the sugar contents. The wavelength of 902 nm is attributed to the absorption band of sugar. A cooled charge-coupled device (CCD) imaging camera which has 16 bit (65536 steps) A/D resolution was equipped with rotating band-pass filter wheel and used to capture the spectral absorption images of the flesh of a vertically half-cut red fresh melon. The advantage of the high A/D resolution in this research is that each pixel of the CCD is expected to function as a detector of the NIR spectrometer for quantitative analysis. Images at 846 nm, 874 nm, 902 nm and 930 nm were acquired using this CCD camera. Then the 2$\^$nd/ derivative absorbances at 902 nm and 874 nm at each pixel were calculated using these four images. On the other hand, parts of the same melon were extracted for capturing the images and squeezed for the measurement of sugar content. Then the calibration curve between the combination of 2$\^$nd/ derivative absorbances at 902 nm and 874 nm and sugar content was developed. The calibration method based on NIR spectroscopy techniques was applied to each pixel of the images to convert the 2$\^$nd/ derivative absorbances into the Brix sugar content. Mapping the sugar content value of each pixel with linear color scale, the distribution of the sugar content was visualized. As a result of the visualization, it was quantitatively confirmed that the Brix sugar contents are low at the near of the skin and become higher towards the seeds. This result suggests that the visualization technique by the NIR imaging spectroscopy could become a new useful method fer quality evaluation of melons.

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Visualization of Korean Speech Based on the Distance of Acoustic Features (음성특징의 거리에 기반한 한국어 발음의 시각화)

  • Pok, Gou-Chol
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.13 no.3
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    • pp.197-205
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    • 2020
  • Korean language has the characteristics that the pronunciation of phoneme units such as vowels and consonants are fixed and the pronunciation associated with a notation does not change, so that foreign learners can approach rather easily Korean language. However, when one pronounces words, phrases, or sentences, the pronunciation changes in a manner of a wide variation and complexity at the boundaries of syllables, and the association of notation and pronunciation does not hold any more. Consequently, it is very difficult for foreign learners to study Korean standard pronunciations. Despite these difficulties, it is believed that systematic analysis of pronunciation errors for Korean words is possible according to the advantageous observations that the relationship between Korean notations and pronunciations can be described as a set of firm rules without exceptions unlike other languages including English. In this paper, we propose a visualization framework which shows the differences between standard pronunciations and erratic ones as quantitative measures on the computer screen. Previous researches only show color representation and 3D graphics of speech properties, or an animated view of changing shapes of lips and mouth cavity. Moreover, the features used in the analysis are only point data such as the average of a speech range. In this study, we propose a method which can directly use the time-series data instead of using summary or distorted data. This was realized by using the deep learning-based technique which combines Self-organizing map, variational autoencoder model, and Markov model, and we achieved a superior performance enhancement compared to the method using the point-based data.

Stochastic Self-similarity Analysis and Visualization of Earthquakes on the Korean Peninsula (한반도에서 발생한 지진의 통계적 자기 유사성 분석 및 시각화)

  • JaeMin Hwang;Jiyoung Lim;Hae-Duck J. Jeong
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.11
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    • pp.493-504
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    • 2023
  • The Republic of Korea is located far from the boundary of the earthquake plate, and the intra-plate earthquake occurring in these areas is generally small in size and less frequent than the interplate earthquake. Nevertheless, as a result of investigating and analyzing earthquakes that occurred on the Korean Peninsula between the past two years and 1904 and earthquakes that occurred after observing recent earthquakes on the Korean Peninsula, it was found that of a magnitude of 9. In this paper, the Korean Peninsula Historical Earthquake Record (2 years to 1904) published by the National Meteorological Research Institute is used to analyze the relationship between earthquakes on the Korean Peninsula and statistical self-similarity. In addition, the problem solved through this paper was the first to investigate the relationship between earthquake data occurring on the Korean Peninsula and statistical self-similarity. As a result of measuring the degree of self-similarity of earthquakes on the Korean Peninsula using three quantitative estimation methods, the self-similarity parameter H value (0.5 < H < 1) was found to be above 0.8 on average, indicating a high degree of self-similarity. And through graph visualization, it can be easily figured out in which region earthquakes occur most often, and it is expected that it can be used in the development of a prediction system that can predict damage in the event of an earthquake in the future and minimize damage to property and people, as well as in earthquake data analysis and modeling research. Based on the findings of this study, the self-similar process is expected to help understand the patterns and statistical characteristics of seismic activities, group and classify similar seismic events, and be used for prediction of seismic activities, seismic risk assessments, and seismic engineering.