• Korean Journal of Culture and Social Issue
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• v.29 no.4
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• pp.537-567
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• 2023

This study compared the nature of disgust caused by the crime scene with that by the stereotype of the sexual-minority defendant, and compared the effect of each type of disgust on evidence evaluation and legal judgment. A total of 600 participants (300 men, average age of 44.40) were randomly assigned to sources of disgust (crime scene, sexual minorities defendant, control condition), the existence of additional evidence of innocence (o/x), and the existence of judicial directives (o/x). As a result of the study, disgust under the condition of a cruel crime scene with strong physical disgust was significantly higher than that of the sexual minority defendant, interpreted the evidence in a more guilty direction, and was more prone to_evaluate that the defendant was guilty. It is noteworthy that evidence evaluation was a significant moderating variable between disgust and probability of guilt under conditions where the source of disgust was a sexual minority, but not under control conditions and crime scene condition. It means that the effect of disgust on legal judgment may not be direct when the defendant is a sexual minority. In addition, the existence of the judicial instruction had a significant inverse effect on the sentence. And simple effect analysis found that presenting judicial instruction lowered probability of guilt only under the control condition. This makes it reasonable to infer that disgust derived from the characteristics of the crime scene and the defendant can be recognized as integral emotions that are difficult to correct with instructions. Finally, pity for the defendant was significantly higher under the conditions of sexual minority which shows that an emotional response of sympathy may occur in addition to disgust for sexual minorities. After examining the nature of disgust (physical & moral), legal judgment according to the source and degree of disgust was reviewed. In addition, the meaning of disgust and sympathy for the sexual minority defendant was discussed.

• Journal of Korea Water Resources Association
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• v.57 no.9
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• pp.633-643
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• 2024

Many coastal countries have developed and used a wide range of technologies and policy measures to protect freshwater aquifers and groundwater resources from seawater intrusion, and have established and implemented a foundation to legally and institutionally support them. This study covers coastal states in the eastern United States, the Netheland, India and Japan. The goal of this study is to analyze each country's legal and policy measures for coastal groundwater management. By introducing Jeju Island's groundwater standard level system, we aim to provide a basis for future discussions on groundwater management measures not only in Jeju Island but also in coastal areas of Korea. As a result of the analysis, despite the various contents and aspects of coastal groundwater management based on local issues and characteristics around the world, in order to achieve the common goal of securing a stable amount of groundwater withdrawal and preventing seawater intrusion and to maximize the efficiency of groundwater management, it is understood that attempts are being made to establish optimal management measures, laws, systems, and policies based on several key factors. First, considering the hydrogeological characteristics and status of coastal groundwater, a separate special management system is being established and implemented within the scope of the national groundwater management system. In addition, preventing and maintaining groundwater level decline through limiting the amount of groundwater withdrawal and preventing seawater intrusion are key policy goals and policy tools, and it is suppored by research and development. Finally, tt was found that synergy effects are being sought by using various other policy tools and measures in a complex manner.

• Korean Journal of Environment and Ecology
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• v.38 no.4
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• pp.388-404
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• 2024

The focus of conserving plant diversity at the national level includes endemic species restricted to specific regions. This study thus aimed to investigate and evaluate the current distribution status of the Pulsatilla tongkangensis Y.N. Lee & T.C. Lee, one of Korea's endemic plants. The study also examined the vegetation environment of its habitat and assessed the structure of each population. Furthermore, the performance variable of each population was comparatively evaluated, and its annual growth characteristics were also observed. The distribution area of the P. tongkangensis is largely divided into limestone cliffs, ridge rocks, mountain peaks in limestone regions, and sandy soil areas resulting from weathering. Plants in the same distribution area were categorized based on their geographical location, which reflected their respective habitats. According to the population structure evaluated using the number of measured leaves numbers, the plants were categorized into stable and relatively unstable populations. A relatively young population was observed at the top of mountains and rocky ridges of limestone areas and sandy soil areas resulting from weathering. The number of mature individuals was the highest in the population observed around limestone cliffs. In contrast, the population near the top of the limestone mountain range had more leaves , but the plants were of short stature and had the fewest inflorescences. The individuals distributed in limestone cliffs grew, produced, and dispersed seeds for an extended period following establishment. The growth of individuals was limited due to environmental factors in the habitat of distribution areas, including ridges, mountain tops in limestone regions, and sandy soil areas resulting from weathering. It was assessed to have a comparatively brief life cycle compared to that of the plants found on limestone cliffs. P. tongkangensis began flowering in early spring, and both fruit maturation and seed dispersal were completed before the onset of summer. The habitats were determined to receive around seven hours of sunlight per day during the summer, which was considered suitable for establishing a life cycle for the P. tongkangensis, a species requiring strong sunlight for growth to establish and success in a dry environment. Considering the status data gathered from this study, the P. tongkangensis was classified as an endangered species (EN). In addition, the collected data are expected to provide important information for the IUCN Red List of Threatened Species. Therefore, we proposed that the P. tongkangensis holds significant value as a core distribution site, given the observation of species with diverse characteristics on limestone cliffs in Pyeongchang-gun and Jeongseon-gun, Gangwon-do.

• Journal of Sinology and China Studies
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• v.81
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• pp.161-197
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• 2019

This paper aims to find out how rhetorical the rhetoric effect is in the speeches of the winners and runners-ups in the final round of the fifth final title. The subjects of this paper are the speeches of the winners and runner-ups who won the 5th and 10th finalist finals of "I Am a Speaker", which aired on Beijing TV on March 6, 2019. These speeches have images as well as texts, so we will look at the rhetorical expressions in the text and the speech and gesture language of the speakers. In addition, photographs presented as background data on stage when the winner and the runner-up each speak will be included in the analysis. In this paper, we will apply the "Rhetorical Sensitivity Scale", which quantifies the ability of persuasion as a methodology, and sets up the evaluation items based on the traditional theory of rhetoric and then analyzes two speeches. The traditional theory of rhetoric can be divided into five areas and three persuasive elements. The five areas include idea, disposition, expression, memory, and action delivery. The three persuasion elements are Ethos, Logos, and Pathos. In order to pursue objectivity as much as possible, this paper will proceed with both text analysis with verbal expression and video analysis with field situations at the time of speech.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.5
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• pp.637-648
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• 2024

The frequency of extreme weather events such as heavy and extreme rainfall has been increasing due to global climate change. Accordingly, it is essential to quantify hydrometeorological variables for efficient water resource management. Among the various hydro-meteorological variables, Land Surface Temperature (LST) and Evapotranspiration (ET) play key roles in understanding the interaction between the surface and the atmosphere. In Korea, LST and ET are mainly observed through ground-based stations, which also have limitation in obtaining data from ungauged watersheds, and thus, it hinders to estimate spatial behavior of LST and ET. Alternatively, remote sensing-based methods have been used to overcome the limitation of ground-based stations. In this study, we evaluated the applicability of the National Aeronautics and Space Administration's (NASA) ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) LST and ET data estimated across Korea (from July 1, 2018 to December 31, 2022). For validation, we utilized NASA's MODerate Resolution Imaging Spectroradiometer (MODIS) data and eddy covariance flux tower observations managed by agencies under the Ministry of Environment of South Korea. Overall, results indicated that ECOSTRESS-based LSTs showed similar temporal trends (R: 0.47~0.73) to MODIS and ground-based observations. The index of agreement also showed a good agreement of ECOSTRESS-based LST with reference datasets (ranging from 0.82 to 0.91), although it also revealed distinctive uncertainties depending on the season. The ECOSTRESS-based ET demonstrated the capability to capture the temporal trends observed in MODIS and ground-based ET data, but higher Mean Absolute Error and Root Mean Square Error were also exhibited. This is likely due to the low acquisition rate of the ECOSTRESS data and environmental factors such as cooling effect of evapotranspiration, overestimation during the morning. This study suggests conducting additional validation of ECOSTRESS-based LST and ET, particularly in topographical and hydrological aspects. Such validation efforts could enhance the practical application of ECOSTRESS for estimating basin-scale LST and ET in Korea.

• MISULJARYO - National Museum of Korea Art Journal
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• v.97
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• pp.14-54
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• 2020

The overall study of Samsaebulhoedo (painting of the Assembly of Buddhas of Three Ages) at Yongjusa Temple has focused on dating it, analyzing the painting style, identifying its painter, and scrutinizing the related documents. However, its greater coherence could be achieved through additional support from empirical evidence and logical consistency. Recent studies on Samsaebulhoedo at Yongjusa Temple that postulate that the painting could have been produced by a monk-painter in the late nineteenth century and that an original version produced in 1790 could have been retouched by a painter in the 1920s using a Western painting style lack such empirical proof and logic. Although King Jeongjo's son was not yet installed as crown prince, the Samsaebulhoedo at Yongjusa Temple contained a conventional written prayer wishing for a long life for the king, queen, and crown prince: "May his majesty the King live long / May her majesty the Queen live long / May his highness the Crown Prince live long" (主上殿下壽萬歲, 王妃殿下壽萬歲, 世子邸下壽萬歲). Later, this phrase was erased using cinnabar and revised to include unusual content in an exceptional order: "May his majesty the King live long / May his highness the King's Affectionate Mother (Jagung) live long / May her majesty the Queen live long / May his highness the Crown Prince live long" (主上殿下壽萬歲, 慈宮邸下壽萬歲, 王妃殿下壽萬歲, 世子邸下壽萬歲). A comprehensive comparison of the formats and contents in written prayers found on late Joseon Buddhist paintings and a careful analysis of royal liturgy during the reign of King Jeongjo reveal Samsaebulhoedo at Yongjusa Temple to be an original version produced at the time of the founding of Yongjusa Temple in 1790. According to a comparative analysis of formats, iconography, styles, aesthetic sensibilities, and techniques found in Buddhist paintings and paintings by Joseon court painters from the eighteenth and nineteenth centuries, Samsaebulhoedo at Yongjusa Temple bears features characteristic of paintings produced around 1790, which corresponds to the result of analysis on the written prayer. Buddhist paintings created up to the early eighteenth century show deities with their sizes determined by their religious status and a two-dimensional conceptual composition based on the traditional perspective of depicting close objects in the lower section and distant objects above. This Samsaebulhoedo, however, systematically places the Buddhist deities within a threedimensional space constructed by applying a linear perspective. Through the extensive employment of chiaroscuro as found in Western painting, it expresses white highlights and shadows, evoking a feeling that the magnificent world of the Buddhas of the Three Ages actually unfolds in front of viewers. Since the inner order of a linear perspective and the outer illusion of chiaroscuro shading are intimately related to each other, it is difficult to believe that the white highlights were a later addition. Moreover, the creative convergence of highly-developed Western painting style and techniques that is on display in this Samsaebulhoedo could only have been achieved by late-Joseon court painters working during the reign of King Jeongjo, including Kim Hongdo, Yi Myeong-gi, and Kim Deuksin. Deungun, the head monk of Yongjusa Temple, wrote Yongjusa sajeok (History of Yongjusa Temple) by compiling the historical records on the temple that had been transmitted since its founding. In Yongjusa sajeok, Deungun recorded that Kim Hongdo painted Samsaebulhoedo as if it were a historical fact. The Joseon royal court's official records, Ilseongnok (Daily Records of the Royal Court and Important Officials) and Suwonbu jiryeong deungnok (Suwon Construction Records), indicate that Kim Hongdo, Yi Myeong-gi, and Kim Deuksin all served as a supervisor (gamdong) for the production of Buddhist paintings. Since within Joseon's hierarchical administrative system it was considered improper to allow court painters of government position to create Buddhist paintings which had previously been produced by monk-painters, they were appointed as gamdong in name only to avoid a political liability. In reality, court painters were ordered to create Buddhist paintings. During their reigns, King Yeongjo and King Jeongjo summoned the literati painters Jo Yeongseok and Kang Sehwang to serve as gamdong for the production of royal portraits and requested that they paint these portraits as well. Thus, the boundary between the concept of supervision and that of painting occasionally blurred. Supervision did not completely preclude painting, and a gamdong could also serve as a painter. In this light, the historical records in Yongjusa sajeok are not inconsistent with those in Ilseongnok, Suwonbu jiryeong deungnok, and a prayer written by Hwang Deok-sun, which was found inside the canopy in Daeungjeon Hall at Yongjusa Temple. These records provided the same content in different forms as required for their purposes and according to the context. This approach to the Samsaebulhoedo at Yongjusa Temple will lead to a more coherent explanation of dating the painting, analyzing its style, identifying its painter, and interpreting the relevant documents based on empirical grounds and logical consistency.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.95-108
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• 2017

Recently, AlphaGo which is Bakuk (Go) artificial intelligence program by Google DeepMind, had a huge victory against Lee Sedol. Many people thought that machines would not be able to win a man in Go games because the number of paths to make a one move is more than the number of atoms in the universe unlike chess, but the result was the opposite to what people predicted. After the match, artificial intelligence technology was focused as a core technology of the fourth industrial revolution and attracted attentions from various application domains. Especially, deep learning technique have been attracted as a core artificial intelligence technology used in the AlphaGo algorithm. The deep learning technique is already being applied to many problems. Especially, it shows good performance in image recognition field. In addition, it shows good performance in high dimensional data area such as voice, image and natural language, which was difficult to get good performance using existing machine learning techniques. However, in contrast, it is difficult to find deep leaning researches on traditional business data and structured data analysis. In this study, we tried to find out whether the deep learning techniques have been studied so far can be used not only for the recognition of high dimensional data but also for the binary classification problem of traditional business data analysis such as customer churn analysis, marketing response prediction, and default prediction. And we compare the performance of the deep learning techniques with that of traditional artificial neural network models. The experimental data in the paper is the telemarketing response data of a bank in Portugal. It has input variables such as age, occupation, loan status, and the number of previous telemarketing and has a binary target variable that records whether the customer intends to open an account or not. In this study, to evaluate the possibility of utilization of deep learning algorithms and techniques in binary classification problem, we compared the performance of various models using CNN, LSTM algorithm and dropout, which are widely used algorithms and techniques in deep learning, with that of MLP models which is a traditional artificial neural network model. However, since all the network design alternatives can not be tested due to the nature of the artificial neural network, the experiment was conducted based on restricted settings on the number of hidden layers, the number of neurons in the hidden layer, the number of output data (filters), and the application conditions of the dropout technique. The F1 Score was used to evaluate the performance of models to show how well the models work to classify the interesting class instead of the overall accuracy. The detail methods for applying each deep learning technique in the experiment is as follows. The CNN algorithm is a method that reads adjacent values from a specific value and recognizes the features, but it does not matter how close the distance of each business data field is because each field is usually independent. In this experiment, we set the filter size of the CNN algorithm as the number of fields to learn the whole characteristics of the data at once, and added a hidden layer to make decision based on the additional features. For the model having two LSTM layers, the input direction of the second layer is put in reversed position with first layer in order to reduce the influence from the position of each field. In the case of the dropout technique, we set the neurons to disappear with a probability of 0.5 for each hidden layer. The experimental results show that the predicted model with the highest F1 score was the CNN model using the dropout technique, and the next best model was the MLP model with two hidden layers using the dropout technique. In this study, we were able to get some findings as the experiment had proceeded. First, models using dropout techniques have a slightly more conservative prediction than those without dropout techniques, and it generally shows better performance in classification. Second, CNN models show better classification performance than MLP models. This is interesting because it has shown good performance in binary classification problems which it rarely have been applied to, as well as in the fields where it's effectiveness has been proven. Third, the LSTM algorithm seems to be unsuitable for binary classification problems because the training time is too long compared to the performance improvement. From these results, we can confirm that some of the deep learning algorithms can be applied to solve business binary classification problems.

• Korean Journal of Psychosomatic Medicine
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• v.8 no.2
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• pp.212-227
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• 2000

This study was designed to testify the reliability and validation on the Korean version of the Social Adaptation Self-rating Scale(SASS) which was developed from Bose et al. for the evaluation of social motivation and behavior of depressed patients in 1997. Interests for the social world, those of social functioning, of patients were involved in the addition of new measure of disturbance. And those were distinct from abnormalities of thought, mood and symptoms of patients with major depression. As the previous reports there were several evidences that treatments may be less likely to be effective if the system they act on is dysfunctional. Thus, a better social situation favoured better outcome. As a matter of fact, however, those reports were developed in the course of the evaluation of interpersonal therapy(IPT) and cognitive therapy. Accordingly the conversed question -whether pharmacological therapy with antidepressants can impact on social functioning in addition to addressing the core features of illness- has been addressed. To date, anyhow, it is accepted that enhancement of social functioning may be a therapeutic principle in its own right and illness rarely divorced from social context. In terms of those concepts the introduction of an assessment of social functioning into pharmacotherapeutic studies of depression has been welcomed and might be a potent instrument for evaluating the relative pharmacoeconomic benefits of different treatments. Despite of many scales which were applied for the evaluation of symptoms in the patients with depression, however, the scale for the evaluation of social functiong has not been introduced in Korea yet. Thus, this study was designed to introduce the concepts of social functioning in the patients with depression and to testify the reliability and validation on Korean version of SASS. This Korean version of SASS was submitted to a reliability and validation procedure based on the data from healthy general population survey in 291 individuals and 40 patients with major depression. Cronbach a was 0.790 in total subjects group and the correlation of test-retest was statistically significant(y=0.653, p<0.0l). Thus, the Korean version of SASS might be shown to be valid and reliable. The results of multivariate analyses allowed the identification of 3 principle factors(factor 1 = intersts in social activities, factor 2 = active interpersonal relationship, factor 3 = selfesteem) in normal group, however, it could be counted as only one factor in the depression group because nearly total items of SASS were involved in factor 1. In the view of these results, the Korean version of SASS may be useful additional tool for the evaluation of social functioning in depression.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• Radiation Oncology Journal
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• v.23 no.3
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• pp.186-193
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• 2005

Purpose: To improve the management of a medical linear accelerator, the records of operational failures of a Varian CL2l00C over a ten year period were retrospectively analyzed. Materials and Methods: The failures were classified according to the involved functional subunits, with each class rated Into one of three levels depending on the operational conditions. The relationships between the failure rate and working ratio and between the failure rate and outside temperature were investigated. In addition, the average life time of the main part and the operating efficiency over the last 4 years were analyzed. Results: Among the recorded failures (total 587 failures), the most frequent failure was observed in the parts related with the collimation system, including the monitor chamber, which accounted for $20\%$ of all failures. With regard to the operational conditions, 2nd level of failures, which temporally interrupted treatments, were the most frequent. Third level of failures, which interrupted treatment for more than several hours, were mostly caused by the accelerating subunit. The number of failures was increased with number of treatments and operating time. The average life-times of the Klystron and Thyratron became shorter as the working ratio increased, and were 42 and $83\%$ of the expected values, respectively. The operating efficiency was maintained at $95\%$ or higher, but this value slightly decreased. There was no significant correlation between the number of failures and the outside temperature. Conclusion: The maintenance of detailed equipment problems and failures records over a long period of time can provide good knowledge of equipment function as well as the capability of predicting future failure. Wore rigorous equipment maintenance Is required for old medical linear accelerators for the advanced avoidance of serious failure and to improve the qualify of patient treatment.