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A study on the calibration characteristics of organic fatty acids designated as new offensive odorants by cryogenic trapping-thermal desorption technique (유기지방산 신규악취물질에 대한 저온농축 열탈착방식 (Thermal desorber)의 검량특성 연구)

  • Ahn, Ji-Won;Kim, Ki-Hyun;Im, Moon-Soon;Ju, Do-Weon
    • Analytical Science and Technology
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    • v.22 no.6
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    • pp.488-497
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    • 2009
  • In this study, analytical methodology for several organic fatty acids (OFA: propionic acid (PA), butyric acid (BA), isovaleric acid (IA), and valeric acid (VA)) designated as new offensive odorants in Korea (as of year 2010) was investigated along with some odorous VOCs (styrene, toluene, xylene, methyl ethyl ketone, methyl isobutyl ketone, butyl acetate, and isobutyl alcohol). For this purpose, working standards (WS) containing all of these 13 compounds were loaded into adsorption tube filled with Tenax TA, and analyzed by gas chromatography (GC) system thermal desorber interfaced with. The analytical sensitivities of organic fatty acids expressed in terms of detection limit (both in absolute mass (ng) and concentration (ppb)) were lower by 1.5-2 times than other compounds (PA: 0.24 ng (0.16 ppb), BA: 0.19 ng (0.11 ppb), IA: 0.15 ng (0.07 ppb), and VA: 0.28 ng (0.13 ppb)). The precision of BA, IA, and VA, if assessed in terms of relative standard error (RSE), maintained above 5%, while the precison of other compounds were below 5%. The reproducibility of analysis improved with the aid of internal standard calibration (PA: $1.1{\pm}0.4%$, BA: $10{\pm}0.46$, IA; $12{\pm}0.3%$, VA: $4{\pm}0.1%$), respectively. The results of this study showed that organic fatty acid can be analyzed using adsorption tube and thermal desorber in a more reliable way to replace alkali absorption method introduced in the odor prevention law of the Korea Ministry of Environment (KMOE).

Application and Comparative Analysis of River Discharge Estimation Methods Using Surface Velocity (표면유속을 이용한 하천 유량산정방법의 적용 및 비교 분석)

  • Jae Hyun, Song;Seok Geun Park;Chi Young Kim;Hung Soo Kim
    • Journal of Korean Society of Disaster and Security
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    • v.16 no.2
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    • pp.15-32
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    • 2023
  • There are some difficulties such as safety problem and need of manpower in measuring discharge by submerging the instruments because of many floating debris and very fast flow in the river during the flood season. As an alternative, microwave water surface current meters have been increasingly used these days, which are easy to measure the discharge in the field without contacting the water surface directly. But it is also hard to apply the method in the sudden and rapidly changing field conditions. Therefore, the estimation of the discharge using the surface velocity in flood conditions requires a theoretical and economical approach. In this study, the measurements from microwave water surface current meter and rating curve were collected and then analyzed by the discharge estimation method using the surface velocity. Generally, the measured and converted discharge are analyzed to be similar in all methods at a hydraulic radius of 3 m or over or a mean velocity of 2 ㎧ or more. Besides, the study computed the discharge by the index velocity method and the velocity profile method with the maximum surface velocity in the section where the maximum velocity occurs at the high water level range of the rating curve among the target locations. As a result, the mean relative error with the converted discharge was within 10%. That is, in flood season, the discharge estimation method using one maximum surface velocity measurement, index velocity method, and velocity profile method can be applied to develop high-level extrapolation, therefore, it is judged that the reliability for the range of extrapolation estimation could be improved. Therefore, the discharge estimation method using the surface velocity is expected to become a fast and efficient discharge measurement method during the flood season.

Analysis of Respiratory Motional Effect on the Cone-beam CT Image (Cone-beam CT 영상 획득 시 호흡에 의한 영향 분석)

  • Song, Ju-Young;Nah, Byung-Sik;Chung, Woong-Ki;Ahn, Sung-Ja;Nam, Taek-Keun;Yoon, Mi-Sun
    • Progress in Medical Physics
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    • v.18 no.2
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    • pp.81-86
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    • 2007
  • The cone-beam CT (CBCT) which is acquired using on-board imager (OBI) attached to a linear accelerator is widely used for the image guided radiation therapy. In this study, the effect of respiratory motion on the quality of CBCT image was evaluated. A phantom system was constructed in order to simulate respiratory motion. One part of the system is composed of a moving plate and a motor driving component which can control the motional cycle and motional range. The other part is solid water phantom containing a small cubic phantom ($2{\times}2{\times}2cm^3$) surrounded by air which simulate a small tumor volume in the lung air cavity CBCT images of the phantom were acquired in 20 different cases and compared with the image in the static status. The 20 different cases are constituted with 4 different motional ranges (0.7 cm, 1.6 cm, 2.4 cm, 3.1 cm) and 5 different motional cycles (2, 3, 4, 5, 6 sec). The difference of CT number in the coronal image was evaluated as a deformation degree of image quality. The relative average pixel intensity values as a compared CT number of static CBCT image were 71.07% at 0.7 cm motional range, 48.88% at 1.6 cm motional range, 30.60% at 2.4 cm motional range, 17.38% at 3.1 cm motional range The tumor phantom sizes which were defined as the length with different CT number compared with air were increased as the increase of motional range (2.1 cm: no motion, 2.66 cm: 0.7 cm motion, 3.06 cm: 1.6 cm motion, 3.62 cm: 2.4 cm motion, 4.04 cm: 3.1 cm motion). This study shows that respiratory motion in the region of inhomogeneous structures can degrade the image quality of CBCT and it must be considered in the process of setup error correction using CBCT images.

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The Audience Behavior-based Emotion Prediction Model for Personalized Service (고객 맞춤형 서비스를 위한 관객 행동 기반 감정예측모형)

  • Ryoo, Eun Chung;Ahn, Hyunchul;Kim, Jae Kyeong
    • Journal of Intelligence and Information Systems
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    • v.19 no.2
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    • pp.73-85
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    • 2013
  • Nowadays, in today's information society, the importance of the knowledge service using the information to creative value is getting higher day by day. In addition, depending on the development of IT technology, it is ease to collect and use information. Also, many companies actively use customer information to marketing in a variety of industries. Into the 21st century, companies have been actively using the culture arts to manage corporate image and marketing closely linked to their commercial interests. But, it is difficult that companies attract or maintain consumer's interest through their technology. For that reason, it is trend to perform cultural activities for tool of differentiation over many firms. Many firms used the customer's experience to new marketing strategy in order to effectively respond to competitive market. Accordingly, it is emerging rapidly that the necessity of personalized service to provide a new experience for people based on the personal profile information that contains the characteristics of the individual. Like this, personalized service using customer's individual profile information such as language, symbols, behavior, and emotions is very important today. Through this, we will be able to judge interaction between people and content and to maximize customer's experience and satisfaction. There are various relative works provide customer-centered service. Specially, emotion recognition research is emerging recently. Existing researches experienced emotion recognition using mostly bio-signal. Most of researches are voice and face studies that have great emotional changes. However, there are several difficulties to predict people's emotion caused by limitation of equipment and service environments. So, in this paper, we develop emotion prediction model based on vision-based interface to overcome existing limitations. Emotion recognition research based on people's gesture and posture has been processed by several researchers. This paper developed a model that recognizes people's emotional states through body gesture and posture using difference image method. And we found optimization validation model for four kinds of emotions' prediction. A proposed model purposed to automatically determine and predict 4 human emotions (Sadness, Surprise, Joy, and Disgust). To build up the model, event booth was installed in the KOCCA's lobby and we provided some proper stimulative movie to collect their body gesture and posture as the change of emotions. And then, we extracted body movements using difference image method. And we revised people data to build proposed model through neural network. The proposed model for emotion prediction used 3 type time-frame sets (20 frames, 30 frames, and 40 frames). And then, we adopted the model which has best performance compared with other models.' Before build three kinds of models, the entire 97 data set were divided into three data sets of learning, test, and validation set. The proposed model for emotion prediction was constructed using artificial neural network. In this paper, we used the back-propagation algorithm as a learning method, and set learning rate to 10%, momentum rate to 10%. The sigmoid function was used as the transform function. And we designed a three-layer perceptron neural network with one hidden layer and four output nodes. Based on the test data set, the learning for this research model was stopped when it reaches 50000 after reaching the minimum error in order to explore the point of learning. We finally processed each model's accuracy and found best model to predict each emotions. The result showed prediction accuracy 100% from sadness, and 96% from joy prediction in 20 frames set model. And 88% from surprise, and 98% from disgust in 30 frames set model. The findings of our research are expected to be useful to provide effective algorithm for personalized service in various industries such as advertisement, exhibition, performance, etc.