• Journal of agricultural medicine and community health
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• v.26 no.2
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• pp.15-41
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• 2001

Since medical clients and the community they live in are expected to be center of future public health and medical care system, new service programs must be developed with patients focused on in line with widening public access of information and social participation. Patients- focused service shall mean the area- oriented provision of public health service. In this study, health officers working at public health centers, public health sub- centers and medical offices in Jeonbuk- do area were taken for population in order to investigate their attitudes toward and knowledge about the service area assigning system under the public health programs. Findings from the survey to 260 health officers, divided by general category, are as follows : Government officers at public health organizations appeared to have high grade of understanding to the service area assigning system and also great appreciation for the necessity of it. Regarding the timing for the system to be introduced, they support the gradual implementation and, as for the type of service to be provided, they preferred home nursing and treatment of chronic diseases. Highly positive responses were centered on the health classes under the health promotion projects, and as far as health projects for the old are concerned, services for home nursing, for the disabled and for home- alone people are favored most. On the other hand, budgeting, manpower and reorganization are rated as prerequisite to establishment of the service area assigning system. From the viewpoint of system side, the improvement of working conditions is rendered as most urgent, while the information system for establishing the service area assigning system is conceived far from satisfactory. Proper assignment of specialists was noted as mostly important to establish the delivery system for medical service through the service area assigning system by team. As merits of the service area assigning system, it is pointed out that, through the system, health clients can better be managed and the nursing quality will be improved thank to the enhanced specialization. It is also perceived that the district health service is not well prepared to respond to the increased and diversified needs of community people and, furthermore, service programs of health centers have not been fully developed. The most serious problem standing in the way to expansion of health projects is, it is noted, uniformity (formality) of the project. Based on the results of the survey which suggest time has ripen to introduce the service area assigning system, following strategies are proposed to anchor down the system as soon as possible: First, we should introduce the system gradually, starting from the area selected, and in consideration of area specialities, refraining from the hitherto stereotyped way of providing health service. Second, we should seek to properly assign the specialists and improve the working conditions of the assigned officers by securing sufficient budget, since it is a most urgent step to lay foundation for the service area assigning system. Third, best service program should be developed to meet the satisfaction of community people by responding to their needs and solidifying the management of medical clients. Fourth, wide scope of study should further be conducted in order to help this system take roots in the central living of community residents since pilot project on the experimental base attended by specialists only can not win popularity among the masses.

• Korean Journal of Agricultural Science
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• v.8 no.1
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• pp.97-107
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• 1981

This study was carried out in order to provide the basic data necessary to develop the effective and desirable cooking method on large scale for investigating the physical characteristics of cooked rices and studying optimum cooking conditions by pressure in kettle cooking rices. Milyang-15, local Japonica type and Milyang-23, high yielding Indica type major varieties cultivated in Korea were used as cooking sample after polishing 70% and 90% respectively, and the results obtained are summarized as follows. 1. The average moisture content of cooked rice by open kettle and pressure kettle method in typical households were 65.17% and 64.52%, respectively. 2. In water absorption capacity of rice grain Milyang-23 was 4.5% higher than Milyang-15, and maximum water content after absorption in Milyang-23 was 29.14%. 3. The expansion volume of cooked rice was changed proportionally by water absorption, heating temperature and time, and maximum expansion volume of cooked rice was 3.2 times greater than rice grain. 4. The gelatinization degree of cooked rice intensively concerning in hardness of rice grain was increased as water-to-rice ratio, heating temperature and time increased, and it was 0.44 in Milyang-23 and 0.64 in Milyang-15 under the optimum cooking conditions as 160% water-to-rice ratio, $0.2kg/cm^2$ cooking pressure and 25 minutes cooking time. 5. The hardness of cooked rice was decreased as water-to-rice ratio, heating temperature and time increased, and it showed 2.35kg/wt in 90% polished Milyang-23 and 2.0kg/wt in 90 polished Milyang-15 under optimum cooking conditions. For maintaining the same level of hardness of cooking rice Milyang-23 required 25% much more water than Milyang-15. 6. The elasticity of cooked rice was changed proportionally by water-to-rice ratio, heating temperature and time, and it appeared 19.2mm and 15.7mm in 90% polished Milyang-15 and Milyang-23 respectively. 7. The gumminess of cooked rice was decreased as water-to-rice ratio, heating temperature and time increased, and it showed 60 and 73 in 90% polished Milyang-23 and Milyang-15, respectively. 8. The optimum cooking time on differerent pressure in kettle took 25 minutes at $0.2kg/cm^2$, 20 minutes at $0.4kg/cm^2$, 15 minutes at $0.6kg/cm^2$, and 10 minutes at $0.8kg/cm^2$.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.85-109
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• 2018

Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.

• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.867-879
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• 2020

As the era of space technology utilization is approaching, the launch of CAS (Compact Advanced Satellite) 500-1/2 satellites is scheduled during 2021 for acquisition of high-resolution images. Accordingly, the increase of image usability and processing efficiency has been emphasized as key design concepts of the CAS 500-1/2 ground station. In this regard, "CAS 500-1/2 Image Acquisition and Utilization Technology Development" project has been carried out to develop core technologies and processing systems for CAS 500-1/2 data collecting, processing, managing and distributing. In this paper, we introduce the results of the above project. We developed an operation system to generate precision images automatically with GCP (Ground Control Point) chip DB (Database) and DEM (Digital Elevation Model) DB over the entire Korean peninsula. We also developed the system to produce ortho-rectified images indexed to 1:5,000 map grids, and hence set a foundation for ARD (Analysis Ready Data)system. In addition, we linked various application software to the operation system and systematically produce mosaic images, DSM (Digital Surface Model)/DTM (Digital Terrain Model), spatial feature thematic map, and change detection thematic map. The major contribution of the developed system and technologies includes that precision images are to be automatically generated using GCP chip DB for the first time in Korea and the various utilization product technologies incorporated into the operation system of a satellite ground station. The developed operation system has been installed on Korea Land Observation Satellite Information Center of the NGII (National Geographic Information Institute). We expect the system to contribute greatly to the center's work and provide a standard for future ground station systems of earth observation satellites.

• Information Systems Review
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• v.16 no.3
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• pp.161-177
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• 2014

Corporate credit rating assessment consists of complicated processes in which various factors describing a company are taken into consideration. Such assessment is known to be very expensive since domain experts should be employed to assess the ratings. As a result, the data-driven corporate credit rating prediction using statistical and artificial intelligence (AI) techniques has received considerable attention from researchers and practitioners. In particular, statistical methods such as multiple discriminant analysis (MDA) and multinomial logistic regression analysis (MLOGIT), and AI methods including case-based reasoning (CBR), artificial neural network (ANN), and multiclass support vector machine (MSVM) have been applied to corporate credit rating.2) Among them, MSVM has recently become popular because of its robustness and high prediction accuracy. In this study, we propose a novel optimized MSVM model, and appy it to corporate credit rating prediction in order to enhance the accuracy. Our model, named 'GAMSVM (Genetic Algorithm-optimized Multiclass Support Vector Machine),' is designed to simultaneously optimize the kernel parameters and the feature subset selection. Prior studies like Lorena and de Carvalho (2008), and Chatterjee (2013) show that proper kernel parameters may improve the performance of MSVMs. Also, the results from the studies such as Shieh and Yang (2008) and Chatterjee (2013) imply that appropriate feature selection may lead to higher prediction accuracy. Based on these prior studies, we propose to apply GAMSVM to corporate credit rating prediction. As a tool for optimizing the kernel parameters and the feature subset selection, we suggest genetic algorithm (GA). GA is known as an efficient and effective search method that attempts to simulate the biological evolution phenomenon. By applying genetic operations such as selection, crossover, and mutation, it is designed to gradually improve the search results. Especially, mutation operator prevents GA from falling into the local optima, thus we can find the globally optimal or near-optimal solution using it. GA has popularly been applied to search optimal parameters or feature subset selections of AI techniques including MSVM. With these reasons, we also adopt GA as an optimization tool. To empirically validate the usefulness of GAMSVM, we applied it to a real-world case of credit rating in Korea. Our application is in bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. The experimental dataset was collected from a large credit rating company in South Korea. It contained 39 financial ratios of 1,295 companies in the manufacturing industry, and their credit ratings. Using various statistical methods including the one-way ANOVA and the stepwise MDA, we selected 14 financial ratios as the candidate independent variables. The dependent variable, i.e. credit rating, was labeled as four classes: 1(A1); 2(A2); 3(A3); 4(B and C). 80 percent of total data for each class was used for training, and remaining 20 percent was used for validation. And, to overcome small sample size, we applied five-fold cross validation to our dataset. In order to examine the competitiveness of the proposed model, we also experimented several comparative models including MDA, MLOGIT, CBR, ANN and MSVM. In case of MSVM, we adopted One-Against-One (OAO) and DAGSVM (Directed Acyclic Graph SVM) approaches because they are known to be the most accurate approaches among various MSVM approaches. GAMSVM was implemented using LIBSVM-an open-source software, and Evolver 5.5-a commercial software enables GA. Other comparative models were experimented using various statistical and AI packages such as SPSS for Windows, Neuroshell, and Microsoft Excel VBA (Visual Basic for Applications). Experimental results showed that the proposed model-GAMSVM-outperformed all the competitive models. In addition, the model was found to use less independent variables, but to show higher accuracy. In our experiments, five variables such as X7 (total debt), X9 (sales per employee), X13 (years after founded), X15 (accumulated earning to total asset), and X39 (the index related to the cash flows from operating activity) were found to be the most important factors in predicting the corporate credit ratings. However, the values of the finally selected kernel parameters were found to be almost same among the data subsets. To examine whether the predictive performance of GAMSVM was significantly greater than those of other models, we used the McNemar test. As a result, we found that GAMSVM was better than MDA, MLOGIT, CBR, and ANN at the 1% significance level, and better than OAO and DAGSVM at the 5% significance level.

• Clinical and Experimental Pediatrics
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• v.52 no.5
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• pp.557-566
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• 2009

Purpose : To evaluate the clinical features and characteristics of childhood periodic syndromes (CPS) in Korea using the new criteria of the International Classification of Headache Disorders (ICHD)-II. Methods : The study was conducted at pediatric neurology clinics of five urban tertiary-care medical centers in Korea from January 2006 to December 2007. Patients (44 consecutive children and adolescents) were divided into three groups (cyclic vomiting syndrome [CVS], abdominal migraine [AM], and benign paroxysmal vertigo of childhood [BPVC]) by recurrent paroxysmal episodes of vomiting, abdominal pain, dizziness, and/or vertigo using the ICHD-II criteria and their characteristics were compared. Results : Totally, 16 boys (36.4%) and 28 girls (63.6%) were examined (aged 4-18 yr), with 20 CVS (45.5%), 8 AM (18.2%), and 16 BPVC (36.4%) patients. The mean age at symptom onset was $6.3{\pm}3.6$ yr, $8.5{\pm}2.7$ yr, and $8.5{\pm}2.9$ yr in the CVS, AM, and BPVC groups, respectively, showing that symptoms appeared earliest in the CVS group. The mean age at diagnosis was $8.0{\pm}3.4$ yr, $10.5{\pm}2.6$ yr, and $10.1{\pm}3.2$ yr the CVS, AM, and BPVC groups, respectively. Of the 44 patients, 17 (38.6%) had a history of recurrent headaches and 11 (25.0%) showed typical symptoms of migraine headache, with 5 CVS (25.0%), 2 AM (25.0%), and 4 BPVC (25.0%) patients. Family history of migraine was found in 9 patients (20.4%): 4 in the CVS group (20.0%), 2 in the AM group (25.0%), and 3 in the BPVC group (18.8%). Conclusion : The significant time lag between the age at symptom onset and final diagnosis possibly indicates poor knowledge of CPS among pediatric practitioners, especially in Korea. A high index of suspicion may be the first step toward caring for these patients. Furthermore, a population-based longitudinal study is necessary to determine the incidence and natural course of these syndromes.

• Journal of Soil and Groundwater Environment
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• v.14 no.3
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• pp.40-46
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• 2009

The applicability of a well-type autotrophic sulfur-oxidizing reactive barrier (L $\times$ W $\times$ D = $3m\;{\times}\;4\;m\;{\times}\;2\;m$) as a long-term treatment option for nitrate removal in groundwater was evaluated. Pilot-scale (L $\times$ W $\times$ D = $8m\;{\times}\;4\;m\;{\times}\;2\;m$) flow-tank experiments were conducted to examine remedial efficacy of the well-type reactive barrier. A total of 80 kg sulfur granules as an electron donor and Thiobacillus denitrificans as an active bacterial species were prepared. Thiobacillus denitrificans was successfully colonized on the surface of the sulfur granules and the microflora transformed nitrate with removal efficiency of ~12% (0.07 mM) for 11 days, ~24% (1.3 mM) for 18 days, ~45% (2.4 mM) for 32 days, and ~52% (2.8 mM) for 60 days. Sulfur granules attached to Thiobacillus denitrificans were used to construct the well-type reactive barrier comprising three discrete barriers installed at 1-m interval downstream. Average initial nitrate concentrations were 181 mg/L for the first 28 days and 281 mg/L for the next 14 days. For the 181 mg/L (2.9 mM) plume, nitrate concentrations decreased by ~2% (0.06 mM), ~9% (0.27 mM), and ~15% (0.44 mM) after $1^{st}$, $2^{nd}$, and $3^{rd}$ barriers, respectively. For the 281 mg/L (4.5 mM) plume, nitrate concentrations decreased by ~1% (0.02 mM), ~6% (0.27 mM), and ~8% (0.37 mM) after $1^{st}$, $2^{nd}$, and $3^{rd}$ barriers, respectively. Nitrate plume was flowed through the flow-tank for 49 days by supplying $1.24\;m^3/d$ of nitrate solution. During nitrate treatment, flow velocity (0.44 m/d), pH (6.7 to 8.3), and DO (0.9~2.8 mg/L) showed little variations. Incomplete destruction of nitrate plume was attributed to the lack of retention time, rarely transverse dispersion, and inhibiting the activity of denitrification enzymes caused by relatively high DO concentrations. For field applications, it should be considered increments of retention time, modification of well placements, and intrinsic DO concentration.

• Asia pacific journal of information systems
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• v.21 no.2
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• pp.89-116
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• 2011

In collaborative tagging systems such as Delicious.com and Flickr.com, users assign keywords or tags to their uploaded resources, such as bookmarks and pictures, for their future use or sharing purposes. The collection of resources and tags generated by a user is called a personomy, and the collection of all personomies constitutes the folksonomy. The most significant need of the folksonomy users Is to efficiently find useful resources or experts on specific topics. An excellent ranking algorithm would assign higher ranking to more useful resources or experts. What resources are considered useful In a folksonomic system? Does a standard superior to frequency or freshness exist? The resource recommended by more users with mere expertise should be worthy of attention. This ranking paradigm can be implemented through a graph-based ranking algorithm. Two well-known representatives of such a paradigm are Page Rank by Google and HITS(Hypertext Induced Topic Selection) by Kleinberg. Both Page Rank and HITS assign a higher evaluation score to pages linked to more higher-scored pages. HITS differs from PageRank in that it utilizes two kinds of scores: authority and hub scores. The ranking objects of these pages are limited to Web pages, whereas the ranking objects of a folksonomic system are somewhat heterogeneous(i.e., users, resources, and tags). Therefore, uniform application of the voting notion of PageRank and HITS based on the links to a folksonomy would be unreasonable, In a folksonomic system, each link corresponding to a property can have an opposite direction, depending on whether the property is an active or a passive voice. The current research stems from the Idea that a graph-based ranking algorithm could be applied to the folksonomic system using the concept of mutual Interactions between entitles, rather than the voting notion of PageRank or HITS. The concept of mutual interactions, proposed for ranking the Semantic Web resources, enables the calculation of importance scores of various resources unaffected by link directions. The weights of a property representing the mutual interaction between classes are assigned depending on the relative significance of the property to the resource importance of each class. This class-oriented approach is based on the fact that, in the Semantic Web, there are many heterogeneous classes; thus, applying a different appraisal standard for each class is more reasonable. This is similar to the evaluation method of humans, where different items are assigned specific weights, which are then summed up to determine the weighted average. We can check for missing properties more easily with this approach than with other predicate-oriented approaches. A user of a tagging system usually assigns more than one tags to the same resource, and there can be more than one tags with the same subjectivity and objectivity. In the case that many users assign similar tags to the same resource, grading the users differently depending on the assignment order becomes necessary. This idea comes from the studies in psychology wherein expertise involves the ability to select the most relevant information for achieving a goal. An expert should be someone who not only has a large collection of documents annotated with a particular tag, but also tends to add documents of high quality to his/her collections. Such documents are identified by the number, as well as the expertise, of users who have the same documents in their collections. In other words, there is a relationship of mutual reinforcement between the expertise of a user and the quality of a document. In addition, there is a need to rank entities related more closely to a certain entity. Considering the property of social media that ensures the popularity of a topic is temporary, recent data should have more weight than old data. We propose a comprehensive folksonomy ranking framework in which all these considerations are dealt with and that can be easily customized to each folksonomy site for ranking purposes. To examine the validity of our ranking algorithm and show the mechanism of adjusting property, time, and expertise weights, we first use a dataset designed for analyzing the effect of each ranking factor independently. We then show the ranking results of a real folksonomy site, with the ranking factors combined. Because the ground truth of a given dataset is not known when it comes to ranking, we inject simulated data whose ranking results can be predicted into the real dataset and compare the ranking results of our algorithm with that of a previous HITS-based algorithm. Our semantic ranking algorithm based on the concept of mutual interaction seems to be preferable to the HITS-based algorithm as a flexible folksonomy ranking framework. Some concrete points of difference are as follows. First, with the time concept applied to the property weights, our algorithm shows superior performance in lowering the scores of older data and raising the scores of newer data. Second, applying the time concept to the expertise weights, as well as to the property weights, our algorithm controls the conflicting influence of expertise weights and enhances overall consistency of time-valued ranking. The expertise weights of the previous study can act as an obstacle to the time-valued ranking because the number of followers increases as time goes on. Third, many new properties and classes can be included in our framework. The previous HITS-based algorithm, based on the voting notion, loses ground in the situation where the domain consists of more than two classes, or where other important properties, such as "sent through twitter" or "registered as a friend," are added to the domain. Forth, there is a big difference in the calculation time and memory use between the two kinds of algorithms. While the matrix multiplication of two matrices, has to be executed twice for the previous HITS-based algorithm, this is unnecessary with our algorithm. In our ranking framework, various folksonomy ranking policies can be expressed with the ranking factors combined and our approach can work, even if the folksonomy site is not implemented with Semantic Web languages. Above all, the time weight proposed in this paper will be applicable to various domains, including social media, where time value is considered important.

• Journal of Chest Surgery
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• v.39 no.1 s.258
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• pp.18-27
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• 2006

Background: Anomalous origin of the left coronary artery from the pulmonary artery (ALCAPA) is a rare congenital anomaly, but is one of the most common causes of myocardial ischemia which would result in high mortality within the first year of life. This is our early result of the surgical management for these patients. Material and Method: From June 1989 to July 2003, 6 patients with ALCAPA and one patient with ARCAPA (Anomalous origin of the Right coronary artery from the pulmonary artery) underwent surgical repair. We have reviewed the all medical records, electrocardiogram, chest X-ray and echocardiography retrospectively. Result: Three of the patients were boys and four were girls. The median age at the operation was 5.4 months (Range: 3$\∼$33 months). The average body weight of at the operation was 6.7 kg (Range: 3.7$\∼$11.3 kg). A mean follow up period was 18 months. Only 3 patients were initially diagnosed as ALCAPA. And 3 patients had moderate mitral regurgitation. Immediate coronary artery reimplantation on diagnosis with the aim of restoring a two-coronary system circulation was done. The average bypass time was 114$\pm$37 minutes, and the average aortic cross clamping time was 55$\pm$22 minutes. The average stay of intensive care unit was 5$\pm$3 days, the mean mechanical ventilator time was 38$\pm$45 hours and the hospital stay after operation was 12$\pm$5 days. There were significant improvements in electrocardiogram and chest X-ray of the all patients except one late death patient. The ventricular function showed almost normal recovery after operation; the EF (Ejection Fraction) increased from 41.2$\pm$ 10.3$\%$ to 60.5$\pm$ 15.8$\%$ within 1 month and to 59.8$\pm$13.9$\%$ within 1 year after operation, the SF (Shortening Fraction) increased from 23.6$\pm$4.7$\%$ to 38.6$\pm$8.4$\%$ within 1 month and to 37.4$\pm$7.9$\%$ within 1 year after operation, LVEDDI (Left Ventricular End-diastolic Dimension Index) decreased from 100.8$\pm$25.6 mm/$m^{2}$ to 90.3$\pm$ 19.2 mm/$m^{2}$ within f month and to 79.3$\pm$ 15.8 mm/$m^{2}$ within 1 year after operation. Concomitant mitral repair was done in two patients with anterior mitral leaflet prolapse. In every patient, mitral valve showed less than mild regurgitation during follow up. One late death occurred in which patient Dor procedure was applied 10 months after initial operation due to the dilated cardiomyopathy Conclusion: In the management of this rare and could be fatal Anomalous origin of the left coronary artery from the pulmonary artery (ALCAPA), early suspicion and correct diagnosis is of most important. But, after diagnosis, immediate restoration of 2 coronary systems could result in good outcome.

• Journal of radiological science and technology
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• v.30 no.3
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• pp.205-212
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• 2007

To evaluate the feasibility and efficacy of a pulsatile aortic aneurysm phantoms for in-vitro study. The phantoms consisted of a pulsating motor part(heart part) and an aortic aneurysm part, which mimicked true physiologic conditions. The heart part was created from a high-pressured water pump and a pulsatile flow solenoid valve for the simulation of aortic flow. The aortic aneurysm part was manufactured from paper clay, which was placed inside a acrylic plastic square box, where liquid silicone was poured. After the silicone was formed, the clay was removed, and a silicone tube was used to connect the heart and aneurysm part. We measured the change in pressure as related to the opening time(pulse rate, Kruskal-Wallis method) and pressure before and after the stent-graft implantation(n = 5, Wilcoxon's signed ranks test). The changes in blood pressures according to pulse rate were all statistically significant(p<0.05). The systolic/diastolic pressures at the proximal aorta, the aortic aneurysm, and the distal aorta of the model were $157.80{\pm}1.92/130.20{\pm}1.92$, $159.40{\pm}1.14/134.00{\pm}2.92$, and $147.20{\pm}1.480/129.60{\pm}2.70\;mmHg$, respectively, when the pulse rate was 0.5 beat/second. The pressures changed to $161.40{\pm}1.34/90.20{\pm}1.64$, $175.00{\pm}1.58/93.00{\pm}1.58$, and $176.80{\pm}1.48/90.80{\pm}1.92\;mmHg$, respectively, when the pulse rate was 1.0 beat/second, and $159.40{\pm}1.82/127.20{\pm}1.48$, $166.60{\pm}1.67/138.00{\pm}1.87$, and $161.00{\pm}1.22/135.40{\pm}1.67\;mmHg$, respectively, when it was 1.5 beat/second. When pulse rate was set at 1.0 beat/second, the pressures were $143.60{\pm}1.67/90.20{\pm}1.64$, $147.20{\pm}1.92/84.60{\pm}1.82$, and $137.40{\pm}1.52/88.80{\pm}1.64\;mmHg$ after stent-graft implantation. The changes of pressure before and after stent-graft implantation were statistically significant(p<0.05) except the diastolic pressures at the proximal(p =1.00) and distal aorta(p=0.157). The aortic aneurysm phantoms seems to be useful for the evaluation of the efficacy of stent-graft before animal or clinical studies because of its easy reproducibility and ability to display a wide range of pressures.