• Journal of radiological science and technology
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• v.35 no.2
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• pp.83-92
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• 2012

In anteroposterior projection for cervical vertebra, it is general that the incidence angle of X-ray is $15^{\circ}$ to $20^{\circ}$ degrees to head in order to prevent overlap of mandible and occipital bone and to observe array of cervical interbody and shapes of joints. However, the angle is appropriate for foreigners that was determined by foreign literature review long ago, and there have been few researches of incidence angle for Koreans' body type. The purpose of in this study are to identify the incidence angle appropriate for Koreans and to present methodology. In order to measure the incidence angle, 1,044 patients who visited S Hospital located in Seosan were selected and measured of average length of cervical vertebra, OID, axis angle, and FID. The incidence angle was calculated from the applied formula by measuring average values per age groups and sex (see Formula 1 and 2). The average length of cervical vertebra was 6cm: the length was increased from teenagers to twenties but was decreased since thirties. The difference between males and females was around 1cm (p<.01). The OID was almost the same regardless of age groups and sex. As for axis angle, the slope was increased in teenagers and twenties, but was decreased since thirties. The difference between males and females was around 2 degrees (p<.01). The FID measurements were almost the same regardless of age groups and sex, and when the incidence angle was measured from these values, the teenagers were $15.9^{\circ}$, the twenties were $16.9^{\circ}$, the thirties were $16.6^{\circ}$, the forties were $16.2^{\circ}$, the fifties were $15.9^{\circ}$, and the sixties were $14.5^{\circ}$, indicating that the angle was increased from teenagers to the twenties but decreased since the thirties. While the angles of males and females were measured to be the same in the teenagers, the angle was different between males and females by $2^{\circ}$. When the incidence angle statistically analyzed with measurement of average length of cervical vertebra, OID, axis angle, and FID, all of them were shown to have correlations with the incidence angle (p<.01). Conclusively, it was shown that the incidence angle was measured differently from average length of cervical vertebra, OID, FID, and axis slope, as well as from age and sex. Therefore, it can be suggested that the anteroposterior radiation test for cervical vertebra should be conducted by different incidence angles based on age and sex. The data of this study may be used as reference in determining the incidence angle of cervical vertebra tests for the future.

• Journal of Veterinary Clinics
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• v.32 no.6
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• pp.486-490
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• 2015

Two-demensional echocardiography is routinely used for evaluation of cardiac function. Visualization of the endocardial border is essential for the assessment of global and regional left ventricular with cardiac disease. SonoVue$^{TM}$ is a microbubble contrast agent that consists of sulfur hexafluoride-filled microbubbles in a phospholipid shell. There were many studies about contrast echocardiographic examination using SonoVue$^{TM}$ contrast agent, and various doses of SonoVue$^{TM}$ were used. To our knowledge, in published veterinary medicine, there was not reported for diagnostic efficient dose of SonoVue$^{TM}$ to evaluate contrast enhanced left ventricular endocardial border delineation (LVEBD). The purpose of this study is to compare the visualization time of LVEBD and find efficient dose of SonoVue$^{TM}$ for using various doses in dogs. Ten healthy Beagles were recruited to the study. Three different doses (0.03 ml/kg, 0.05 ml/kg and 0.1 ml/kg) of SonoVue$^{TM}$ were injected. Endocardial segments were assigned based on previously established methodology, where by the four-chamber views of the LV were divided into 6 segments. In this study, Contrast enhancement of the LVEBD after each injection was evaluated visually at the time point of overall contrast enhancement (Segmental scoring 5+) in the LV by three investigators in a blind manner. Statistical analysis was performed with SPSS version 14.0. All data were analyzed using one-way ANOVA, the multiple comparison Scheffe test. When data for the three offsite readers were combined, mean durations of useful contrast were $3.54({\pm}2.14)$, $6.15({\pm}2.61)$, and $24.39({\pm}11.10)$ seconds for the 0.03 ml/kg, 0.05 ml/kg, and 0.1 ml/kg SonoVue$^{TM}$ doses, respectively. After injection of contrast agent, there were no significant change in side effects such as urticaria, angioedema, hypersensitivity reactions, and digestive system disorders. This study suggests that efficient dose of SonoVue$^{TM}$ contrast agent for improvement of the left ventricle visualization is 0.1 ml/kg. The duration of useful enhancement of LVEBD and the reproducibility were also the highest at the 0.1 ml/kg dosage.

• Ultrasonography
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• v.32 no.1
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• pp.59-65
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• 2013

Purpose: The purpose of this study is to establish the methodology regarding synthesis of ultrasound contrast agent imaging, and to evaluate the characteristics of the synthesized ultrasound contrast agents, including size or degradation interval and image quality. Materials and Methods: The ultrasound contrast agent, composed of liposome and SF6, was synthesized from the mixture solution of $21{\mu}mol$ DPPC (1, 2-Dihexadecanoyl-sn-glycero-3-phosphocholine, $C_{40}H_{80}NO_8P$), $9{\mu}mol$ cholesterol, $1.9{\mu}mol$ of DCP (Dihexadecylphosphate, $[CH_3(CH_2)_{15}O]_2P(O)OH$), and chloroform. After evaporation in a warm water bath and drying during a period of 12-24 hours, the contrast agent was synthesized by the sonication process by addition of buffer and SF6 gas. The size of the contrast agent was controlled by use of either extruder or sonication methods. After synthesis of contrast agents, analysis of the size distribution of the bubbles was performed using dynamic light scattering measurement methods. The degradation curve was also evaluated by changes in the number of contrast agents via light microscopy immediate, 12 hours, 24 hours, 36 hours, 48 hours, 60 hours, 72 hours, and 84 hours after synthesis. For evaluation of the role as an US contrast agent, the echogenicity of the synthesized microbubble was compared with commercially available microbubbles (SonoVue, Bracco, Milan, Italy) using a clinical ultrasound machine and phantom. Results: The contrast agents were synthesized successfully using an evaporation-drying-sonication method. The majority of bubbles showed a mean size of 154.2 nanometers, and they showed marked degradation 24 hours after synthesis. ANOVA test revealed a significant difference among SonoVue, synthesized contrast agent, and saline (p < 0.001). Although no significant difference was observed between SonoVue and the synthesized contrast agent, difference in echogenicity was observed between synthesized contrast agent and saline (p < 0.01). Conclusion: We could synthesize ultrasound contrast agents using an evaporation-drying-sonication method. On the basis of these results, many prospective types of research, such as anticancer drug delivery, gene delivery, including siRNA or microRNA, targeted molecular imaging, and targeted therapy can be performed.

• Journal of Wetlands Research
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• v.20 no.4
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• pp.295-303
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• 2018

Inland wetlands in the Republic of Korea provide key breeding and wintering habitats, while coastal wetlands provide nutrient-rich habitats for stopover sites for East Asia/Australasia Flyway(EAAF) migrants. However, since the 1960's, Korea has reclaimed these coastal wetlands gradually for agriculture and urban expansion. The habitat loss has rippled across global populations of migrant shorebirds in EAAF. To protect a similar loss, the United States, specifically Missouri, developed the moist-soil management technique. Wetland impoundments are constructed from levees with water-flow control gates with specific soils, topography, available water sources, and target goals. The impoundments are subjected to a combination of carefully timed and regulated flooding and drawdown regimes with occasional soil disturbance. This serves a dual purpose of removing undesirable vegetation, while maximizing habitat and forage for wildlife. Flooding and drawdown schedules must be dynamic with constantly shifting climate conditions. Korea's latitude ($N33^{\circ}25^{\prime}{\sim}N38^{\circ}37^{\prime}$) is comparable to Missouri ($N36^{\circ}69^{\prime}{\sim}N40^{\circ}41^{\prime}$); as such, moist-soil management could prove to be an effective wetland restoration technique for Korea. In order to meet specific conservation goals (i.e. shorebird staging site restoration), it is necessary to test the proposed methodology on a site that can meet the required specifications for moist-soil management. Moist-soil management has the potential to not only create key habitat for endangered wildlife, but also provide valuable ecosystem services, including water filtration.

• Korean Journal of Heritage: History & Science
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• v.43 no.3
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• pp.306-333
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• 2010

Previous studies on Wolseong fortress have focused on capital system of Silla Dynasty and on the recreation of Wolseong fortress due to the excavations in and around Wolseong moat. Since the report on the Geographical Survey of Wolseong fortress was published and GPR survey in Wolseong fortress was executed as a trial test in 2004, the academic interest in the site has now expanded to the inside of the fortress. From such context, the preliminary research on the fortress including geophysical survey had been commenced. GPR survey had been conducted for a year from March, 2007. The principal purpose of the recent 3D GPR survey was to provide visualization of subsurface images of the entire Wolseong fortress area. In order to obtain 3D GPR data, dense profile lines were laid in grid-form. The total area surveyed was $112,535m^2$. Depth slice was applied to analyse each level to examine how the layers of the remains had changed and overlapped over time. In addition, slice overlay analysis methodology was used to gather reflects of each depth on a single map. Isolated surface visualization, which is one of 3D analysis methods, was also employed to gain more in-depth understanding and more accurate interpretations of the remain The GPR survey has confirmed that there are building sites whose archaeological features can be classified into 14 different groups. Three interesting areas with huge public building arrangement have been found in Zone 2 in the far west, Zone 9 in the middle, and Zone 14 in the far east. It is recognized that such areas must had been used for important public functions. This research has displayed that 3D GPR survey can be effective for a vast area of archaeological remains and that slice overlay images can provide clearer image with high contrast for objects and remains buried the site.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.864-881
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• 2021

Purpose: This study aims is to provide a total care solution preventing disaster based on Big Data and AI technology and to service safety considered by individual situations and various risk characteristics. The purpose is to suggest a method that customized comprehensive index services to prevent and respond to safety accidents for calculating the living safety index that quantitatively represent individual safety levels in relation to daily life safety. Method: In this study, we use method of mixing AHP(Analysis Hierarchy Process) and Likert Scale that extracted from consensus formation model of the expert group. We organize evaluation items that can evaluate life safety prevention services into risk indicators, vulnerability indicators, and prevention indicators. And We made up AHP hierarchical structure according to the AHP decision methodology and proposed a method to calculate relative weights between evaluation criteria through pairwise comparison of each level item. In addition, in consideration of the expansion of life safety prevention services in the future, the Likert scale is used instead of the AHP pair comparison and the weights between individual services are calculated. Result: We obtain result that is weights for life safety prevention services and reflected them in the individual risk index calculated through the artificial intelligence prediction model of life safety prevention services, so the comprehensive index was calculated. Conclusion: In order to apply the implemented model, a test environment consisting of a life safety prevention service app and platform was built, and the efficacy of the function was evaluated based on the user scenario. Through this, the life safety index presented in this study was confirmed to support the golden time for diagnosis, response and prevention of safety risks by comprehensively indication the user's current safety level.

• Journal of Service Research and Studies
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• v.14 no.2
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• pp.48-68
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• 2024

Due to the global pandemic aftermath of the coronavirus, the importance of health care is being emphasized more socially. Due to the influence of these changes, domestic pharmaceutical companies have introduced regular drug delivery services, that is, drug and health functional food subscription services. Currently, this market is continuously growing. However, these regular services are causing new environmental problems in which the number of waste drugs increases due to the presence of unused drugs. Therefore, this study proposes a service that not only promotes health management through regular medication adherence to reduce the amount of pharmaceutical waste but also aims to improve awareness and practices regarding proper medication disposal. As a preliminary survey for service design, a preliminary survey was conducted on 51 adults to confirm their perception of drug use habits and waste drug collection. Based on the Honey Comb model, a guideline for service design was created, and a prototype was produced by specifying the service using the preliminary survey results and service design methodology. In order to verify the effectiveness of the prototype, a first user task survey was conducted to identify the problems of the prototype, and after improving this, a second usability test was conducted on 49 adults to confirm the versatility of the service. Usability verification was conducted using SPSS Mac version 29.0. For the evaluation results of the questionnaire, Spearmann Correlation Analysis was conducted to confirm the relationship between frequency analysis and evaluation items. This study presents specific solutions to the problem of waste drugs due to the spread of drug subscription services.

• Journal of Global Scholars of Marketing Science
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• v.18 no.3
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• pp.59-88
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• 2008

Digital Convergence means integration between industry, technology, and contents, and in marketing, it usually comes with creation of new types of product and service under the base of digital technology as digitalization progress in electro-communication industries including telecommunication, home appliance, and computer industries. One can see digital convergence not only in instruments such as PC, AV appliances, cellular phone, but also in contents, network, service that are required in production, modification, distribution, re-production of information. Convergence in contents started around 1990. Convergence in network and service begins as broadcasting and telecommunication integrates and DMB(digital multimedia broadcasting), born in May, 2005 is the symbolic icon in this trend. There are some positive and negative expectations about DMB. The reason why two opposite expectations exist is that DMB does not come out from customer's need but from technology development. Therefore, customers might have hard time to interpret the real meaning of DMB. Time is quite critical to a high tech product, like DMB because another product with same function from different technology can replace the existing product within short period of time. If DMB does not positioning well to customer's mind quickly, another products like Wibro, IPTV, or HSPDA could replace it before it even spreads out. Therefore, positioning strategy is critical for success of DMB product. To make correct positioning strategy, one needs to understand how consumer interprets DMB and how consumer's interpretation can be changed via communication strategy. In this study, we try to investigate how consumer perceives a new product, like DMB and how AD strategy change consumer's perception. More specifically, the paper segment consumers into sub-groups based on their DMB perceptions and compare their characteristics in order to understand how they perceive DMB. And, expose them different printed ADs that have messages guiding consumer think DMB in specific ways, either cellular phone or personal TV. Research Question 1: Segment consumers according to perceptions about DMB and compare characteristics of segmentations. Research Question 2: Compare perceptions about DMB after AD that induces categorization of DMB in direction for each segment. If one understand and predict a direction in which consumer perceive a new product, firm can select target customers easily. We segment consumers according to their perception and analyze characteristics in order to find some variables that can influence perceptions, like prior experience, usage, or habit. And then, marketing people can use this variables to identify target customers and predict their perceptions. If one knows how customer's perception is changed via AD message, communication strategy could be constructed properly. Specially, information from segmented customers helps to develop efficient AD strategy for segment who has prior perception. Research framework consists of two measurements and one treatment, O1 X O2. First observation is for collecting information about consumer's perception and their characteristics. Based on first observation, the paper segment consumers into two groups, one group perceives DMB similar to Cellular phone and the other group perceives DMB similar to TV. And compare characteristics of two segments in order to find reason why they perceive DMB differently. Next, we expose two kinds of AD to subjects. One AD describes DMB as Cellular phone and the other Ad describes DMB as personal TV. When two ADs are exposed to subjects, consumers don't know their prior perception of DMB, in other words, which subject belongs 'similar-to-Cellular phone' segment or 'similar-to-TV' segment? However, we analyze the AD's effect differently for each segment. In research design, final observation is for investigating AD effect. Perception before AD is compared with perception after AD. Comparisons are made for each segment and for each AD. For the segment who perceives DMB similar to TV, AD that describes DMB as cellular phone could change the prior perception. And AD that describes DMB as personal TV, could enforce the prior perception. For data collection, subjects are selected from undergraduate students because they have basic knowledge about most digital equipments and have open attitude about a new product and media. Total number of subjects is 240. In order to measure perception about DMB, we use indirect measurement, comparison with other similar digital products. To select similar digital products, we pre-survey students and then finally select PDA, Car-TV, Cellular Phone, MP3 player, TV, and PSP. Quasi experiment is done at several classes under instructor's allowance. After brief introduction, prior knowledge, awareness, and usage about DMB as well as other digital instruments is asked and their similarities and perceived characteristics are measured. And then, two kinds of manipulated color-printed AD are distributed and similarities and perceived characteristics for DMB are re-measured. Finally purchase intension, AD attitude, manipulation check, and demographic variables are asked. Subjects are given small gift for participation. Stimuli are color-printed advertising. Their actual size is A4 and made after several pre-test from AD professionals and students. As results, consumers are segmented into two subgroups based on their perceptions of DMB. Similarity measure between DMB and cellular phone and similarity measure between DMB and TV are used to classify consumers. If subject whose first measure is less than the second measure, she is classified into segment A and segment A is characterized as they perceive DMB like TV. Otherwise, they are classified as segment B, who perceives DMB like cellular phone. Discriminant analysis on these groups with their characteristics of usage and attitude shows that Segment A knows much about DMB and uses a lot of digital instrument. Segment B, who thinks DMB as cellular phone doesn't know well about DMB and not familiar with other digital instruments. So, consumers with higher knowledge perceive DMB similar to TV because launching DMB advertising lead consumer think DMB as TV. Consumers with less interest on digital products don't know well about DMB AD and then think DMB as cellular phone. In order to investigate perceptions of DMB as well as other digital instruments, we apply Proxscal analysis, Multidimensional Scaling technique at SPSS statistical package. At first step, subjects are presented 21 pairs of 7 digital instruments and evaluate similarity judgments on 7 point scale. And for each segment, their similarity judgments are averaged and similarity matrix is made. Secondly, Proxscal analysis of segment A and B are done. At third stage, get similarity judgment between DMB and other digital instruments after AD exposure. Lastly, similarity judgments of group A-1, A-2, B-1, and B-2 are named as 'after DMB' and put them into matrix made at the first stage. Then apply Proxscal analysis on these matrixes and check the positional difference of DMB and after DMB. The results show that map of segment A, who perceives DMB similar as TV, shows that DMB position closer to TV than to Cellular phone as expected. Map of segment B, who perceive DMB similar as cellular phone shows that DMB position closer to Cellular phone than to TV as expected. Stress value and R-square is acceptable. And, change results after stimuli, manipulated Advertising show that AD makes DMB perception bent toward Cellular phone when Cellular phone-like AD is exposed, and that DMB positioning move towards Car-TV which is more personalized one when TV-like AD is exposed. It is true for both segment, A and B, consistently. Furthermore, the paper apply correspondence analysis to the same data and find almost the same results. The paper answers two main research questions. The first one is that perception about a new product is made mainly from prior experience. And the second one is that AD is effective in changing and enforcing perception. In addition to above, we extend perception change to purchase intention. Purchase intention is high when AD enforces original perception. AD that shows DMB like TV makes worst intention. This paper has limitations and issues to be pursed in near future. Methodologically, current methodology can't provide statistical test on the perceptual change, since classical MDS models, like Proxscal and correspondence analysis are not probability models. So, a new probability MDS model for testing hypothesis about configuration needs to be developed. Next, advertising message needs to be developed more rigorously from theoretical and managerial perspective. Also experimental procedure could be improved for more realistic data collection. For example, web-based experiment and real product stimuli and multimedia presentation could be employed. Or, one can display products together in simulated shop. In addition, demand and social desirability threats of internal validity could influence on the results. In order to handle the threats, results of the model-intended advertising and other "pseudo" advertising could be compared. Furthermore, one can try various level of innovativeness in order to check whether it make any different results (cf. Moon 2006). In addition, if one can create hypothetical product that is really innovative and new for research, it helps to make a vacant impression status and then to study how to form impression in more rigorous way.

• Journal of Korean Society of Environmental Engineers
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• v.30 no.6
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• pp.642-652
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• 2008

The aim of our research was to apply experimental design methodology in the optimization condition of Photo-Fenton oxidation of the residual livestock wastewater after the coagulation process. The reactions of Photo-Fenton oxidation were mathematically described as a function of parameters amount of Fe(II)($x_1$), $H_2O_2(x_2)$ and pH($x_3$) being modeled by the use of the Box-Behnken method, which was used for fitting 2nd order response surface models and was alternative to central composite designs. The application of RSM using the Box-Behnken method yielded the following regression equation, which is an empirical relationship between the removal(%) of livestock wastewater and test variables in coded unit: Y = 79.3 + 15.61x$_1$ - 7.31x$_2$ - 4.26x$_3$ - 18x$_1{^2}$ - 10x$_2{^2}$ - 11.9x$_3{^2}$ + 2.49x$_1$x$_2$ - 4.4x$_2$x$_3$ - 1.65x$_1$x$_3$. The model predicted also agreed with the experimentally observed result(R$^2$ = 0.96) The results show that the response of treatment removal(%) in Photo-Fenton oxidation of livestock wastewater were significantly affected by the synergistic effect of linear terms(Fe(II)($x_1$), $H_2O_2(x_2)$, pH(x$_3$)), whereas Fe(II) $\times$ Fe(II)(x$_1{^2}$), $H_2O_2$ $\times$ $H_2O_2$(x$_2{^2}$) and pH $\times$ pH(x$_3{^2}$) on the quadratic terms were significantly affected by the antagonistic effect. $H_2O_2$ $\times$ pH(x$_2$x$_3$) had also a antagonistic effect in the cross-product term. The estimated ridge of the expected maximum response and optimal conditions for Y using canonical analysis were 84 $\pm$ 0.95% and (Fe(II)(X$_1$) = 0.0146 mM, $H_2O_2$(X$_2$) = 0.0867 mM and pH(X$_3$) = 4.704, respectively. The optimal ratio of Fe/H$_2O_2$ was also 0.17 at the pH 4.7.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.1-19
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• 2018

Large amount of data is now available for research and business sectors to extract knowledge from it. This data can be in the form of unstructured data such as audio, text, and image data and can be analyzed by deep learning methodology. Deep learning is now widely used for various estimation, classification, and prediction problems. Especially, fashion business adopts deep learning techniques for apparel recognition, apparel search and retrieval engine, and automatic product recommendation. The core model of these applications is the image classification using Convolutional Neural Networks (CNN). CNN is made up of neurons which learn parameters such as weights while inputs come through and reach outputs. CNN has layer structure which is best suited for image classification as it is comprised of convolutional layer for generating feature maps, pooling layer for reducing the dimensionality of feature maps, and fully-connected layer for classifying the extracted features. However, most of the classification models have been trained using online product image, which is taken under controlled situation such as apparel image itself or professional model wearing apparel. This image may not be an effective way to train the classification model considering the situation when one might want to classify street fashion image or walking image, which is taken in uncontrolled situation and involves people's movement and unexpected pose. Therefore, we propose to train the model with runway apparel image dataset which captures mobility. This will allow the classification model to be trained with far more variable data and enhance the adaptation with diverse query image. To achieve both convergence and generalization of the model, we apply Transfer Learning on our training network. As Transfer Learning in CNN is composed of pre-training and fine-tuning stages, we divide the training step into two. First, we pre-train our architecture with large-scale dataset, ImageNet dataset, which consists of 1.2 million images with 1000 categories including animals, plants, activities, materials, instrumentations, scenes, and foods. We use GoogLeNet for our main architecture as it has achieved great accuracy with efficiency in ImageNet Large Scale Visual Recognition Challenge (ILSVRC). Second, we fine-tune the network with our own runway image dataset. For the runway image dataset, we could not find any previously and publicly made dataset, so we collect the dataset from Google Image Search attaining 2426 images of 32 major fashion brands including Anna Molinari, Balenciaga, Balmain, Brioni, Burberry, Celine, Chanel, Chloe, Christian Dior, Cividini, Dolce and Gabbana, Emilio Pucci, Ermenegildo, Fendi, Giuliana Teso, Gucci, Issey Miyake, Kenzo, Leonard, Louis Vuitton, Marc Jacobs, Marni, Max Mara, Missoni, Moschino, Ralph Lauren, Roberto Cavalli, Sonia Rykiel, Stella McCartney, Valentino, Versace, and Yve Saint Laurent. We perform 10-folded experiments to consider the random generation of training data, and our proposed model has achieved accuracy of 67.2% on final test. Our research suggests several advantages over previous related studies as to our best knowledge, there haven't been any previous studies which trained the network for apparel image classification based on runway image dataset. We suggest the idea of training model with image capturing all the possible postures, which is denoted as mobility, by using our own runway apparel image dataset. Moreover, by applying Transfer Learning and using checkpoint and parameters provided by Tensorflow Slim, we could save time spent on training the classification model as taking 6 minutes per experiment to train the classifier. This model can be used in many business applications where the query image can be runway image, product image, or street fashion image. To be specific, runway query image can be used for mobile application service during fashion week to facilitate brand search, street style query image can be classified during fashion editorial task to classify and label the brand or style, and website query image can be processed by e-commerce multi-complex service providing item information or recommending similar item.