• Title/Summary/Keyword: cold start

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Analytic study on thermal management operating conditions of balance of 100kW fuel cell power plant for a fuel cell electric vehicle (100kW급 연료전지 열관리 시스템 실도로 운전조건 해석적 연구)

  • Lee, Ho-Seong;Lee, Moo-Yeon;Cho, Choong-Won
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.2
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    • pp.1-6
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    • 2019
  • The objective of this study was to investigate performance characteristics of thermal management system(TMS) in a fuel cell electric vehicle with 100kW Fuel Cell(FC) system. In order to build up analytic modelling for TMS, each component was installed and tested under various operating conditions, such as water pump, radiator, 3-Way valve, COD heater, and FC stack etc. and as the results of them, correlations reflecting component's characteristics with flow rate, air velocity were developed. Developed analytic modelling was carried out under various operating conditions on the road. To verify modelling's accuracy, after prediction for optimum coolant flow rate was fulfilled under certain operating conditions, such as FC system, water pump speed, opening of 3-way valve, and pipe resistance, analytic and experimental values were compared and good agreement was shown. In order to predict cold-start operating performance for analytic modelling, coolant temperature variation was analyzed with $-20^{\circ}C$ ambient temperature and duration was predicted to rise in optimum temperature for FC. Because there is appropriate temperature difference between inlet and outlet of FC stack to operate FC system properly, related analysis was performed with respect to power consumption for TMS and heat rejection rate and performance map was depicted along with FC operating conditions.

Improvement of a Product Recommendation Model using Customers' Search Patterns and Product Details

  • Lee, Yunju;Lee, Jaejun;Ahn, Hyunchul
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.1
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    • pp.265-274
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    • 2021
  • In this paper, we propose a novel recommendation model based on Doc2vec using search keywords and product details. Until now, a lot of prior studies on recommender systems have proposed collaborative filtering (CF) as the main algorithm for recommendation, which uses only structured input data such as customers' purchase history or ratings. However, the use of unstructured data like online customer review in CF may lead to better recommendation. Under this background, we propose to use search keyword data and product detail information, which are seldom used in previous studies, for product recommendation. The proposed model makes recommendation by using CF which simultaneously considers ratings, search keywords and detailed information of the products purchased by customers. To extract quantitative patterns from these unstructured data, Doc2vec is applied. As a result of the experiment, the proposed model was found to outperform the conventional recommendation model. In addition, it was confirmed that search keywords and product details had a significant effect on recommendation. This study has academic significance in that it tries to apply the customers' online behavior information to the recommendation system and that it mitigates the cold start problem, which is one of the critical limitations of CF.

Current Research Trends in Entrepreneurship Based on Topic Modeling and Keyword Co-occurrence Analysis: 2002~2021 (토픽모델링과 동시출현단어 분석을 이용한 기업가정신에 대한 연구동향 분석: 2002~2021)

  • Jang, Sung Hee
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.17 no.3
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    • pp.245-256
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    • 2022
  • The purpose of this study is to provide comprehensive insights on the current research trends in entrepreneurship based on topic modeling and keyword co-occurrence analysis. This study queried Web of Science database with 'entrepreneurship' and collected 14,953 research articles between 2002 and 2021. The study used R program for topic modeling and VOSviewer program for keyword co-occurrence analysis. The results of this study are as follows. First, as a result of keyword co-occurrence analysis, 5 clusters divided: entrepreneurship and innovation cluster, entrepreneurship education cluster, social entrepreneurship and sustainability cluster, enterprise performance cluster, and knowledge and technology transfer cluster. Second, as a result of the topic modeling analysis, 12 topics found: start-up environment and economic development, international entrepreneurship, venture capital, government policy and support, social entrepreneurship, management-related issues, regional city planning and development, entrepreneurship research, and entrepreneurial intention. Finally, the study identified two hot topics(venture capital and entrepreneurship intention) and a cold topic(international entrepreneurship). The results of this study are useful to understand current research trends in entrepreneurship research and provide insights into research of entrepreneurship.

Financial Products Recommendation System Using Customer Behavior Information (고객의 투자상품 선호도를 활용한 금융상품 추천시스템 개발)

  • Hyojoong Kim;SeongBeom Kim;Hee-Woong Kim
    • Information Systems Review
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    • v.25 no.1
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    • pp.111-128
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    • 2023
  • With the development of artificial intelligence technology, interest in data-based product preference estimation and personalized recommender systems is increasing. However, if the recommendation is not suitable, there is a risk that it may reduce the purchase intention of the customer and even extend to a huge financial loss due to the characteristics of the financial product. Therefore, developing a recommender system that comprehensively reflects customer characteristics and product preferences is very important for business performance creation and response to compliance issues. In the case of financial products, product preference is clearly divided according to individual investment propensity and risk aversion, so it is necessary to provide customized recommendation service by utilizing accumulated customer data. In addition to using these customer behavioral characteristics and transaction history data, we intend to solve the cold-start problem of the recommender system, including customer demographic information, asset information, and stock holding information. Therefore, this study found that the model proposed deep learning-based collaborative filtering by deriving customer latent preferences through characteristic information such as customer investment propensity, transaction history, and financial product information based on customer transaction log records was the best. Based on the customer's financial investment mechanism, this study is meaningful in developing a service that recommends a high-priority group by establishing a recommendation model that derives expected preferences for untraded financial products through financial product transaction data.

Recommender Systems using Structural Hole and Collaborative Filtering (구조적 공백과 협업필터링을 이용한 추천시스템)

  • Kim, Mingun;Kim, Kyoung-Jae
    • Journal of Intelligence and Information Systems
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    • v.20 no.4
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    • pp.107-120
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    • 2014
  • This study proposes a novel recommender system using the structural hole analysis to reflect qualitative and emotional information in recommendation process. Although collaborative filtering (CF) is known as the most popular recommendation algorithm, it has some limitations including scalability and sparsity problems. The scalability problem arises when the volume of users and items become quite large. It means that CF cannot scale up due to large computation time for finding neighbors from the user-item matrix as the number of users and items increases in real-world e-commerce sites. Sparsity is a common problem of most recommender systems due to the fact that users generally evaluate only a small portion of the whole items. In addition, the cold-start problem is the special case of the sparsity problem when users or items newly added to the system with no ratings at all. When the user's preference evaluation data is sparse, two users or items are unlikely to have common ratings, and finally, CF will predict ratings using a very limited number of similar users. Moreover, it may produces biased recommendations because similarity weights may be estimated using only a small portion of rating data. In this study, we suggest a novel limitation of the conventional CF. The limitation is that CF does not consider qualitative and emotional information about users in the recommendation process because it only utilizes user's preference scores of the user-item matrix. To address this novel limitation, this study proposes cluster-indexing CF model with the structural hole analysis for recommendations. In general, the structural hole means a location which connects two separate actors without any redundant connections in the network. The actor who occupies the structural hole can easily access to non-redundant, various and fresh information. Therefore, the actor who occupies the structural hole may be a important person in the focal network and he or she may be the representative person in the focal subgroup in the network. Thus, his or her characteristics may represent the general characteristics of the users in the focal subgroup. In this sense, we can distinguish friends and strangers of the focal user utilizing the structural hole analysis. This study uses the structural hole analysis to select structural holes in subgroups as an initial seeds for a cluster analysis. First, we gather data about users' preference ratings for items and their social network information. For gathering research data, we develop a data collection system. Then, we perform structural hole analysis and find structural holes of social network. Next, we use these structural holes as cluster centroids for the clustering algorithm. Finally, this study makes recommendations using CF within user's cluster, and compare the recommendation performances of comparative models. For implementing experiments of the proposed model, we composite the experimental results from two experiments. The first experiment is the structural hole analysis. For the first one, this study employs a software package for the analysis of social network data - UCINET version 6. The second one is for performing modified clustering, and CF using the result of the cluster analysis. We develop an experimental system using VBA (Visual Basic for Application) of Microsoft Excel 2007 for the second one. This study designs to analyzing clustering based on a novel similarity measure - Pearson correlation between user preference rating vectors for the modified clustering experiment. In addition, this study uses 'all-but-one' approach for the CF experiment. In order to validate the effectiveness of our proposed model, we apply three comparative types of CF models to the same dataset. The experimental results show that the proposed model outperforms the other comparative models. In especial, the proposed model significantly performs better than two comparative modes with the cluster analysis from the statistical significance test. However, the difference between the proposed model and the naive model does not have statistical significance.

The Systemic Effects of Hypothermic and Normothermic Cardiopulmonary Bypass in Cardiac Surgery (심장수술시 저체온 체외순환과 정상체온 체외순환의 전신 효과에 관한 연구)

  • Park Jae Min;Cho Yong Gil;Hwang Yoon Ho;Lee Yang Haeng;Yoon Young Chul;Junng Hee Jae;Han Il Yong;Choi Seok Cheol;Cho Kwang Hyun
    • Journal of Chest Surgery
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    • v.38 no.1 s.246
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    • pp.29-37
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    • 2005
  • This study was prospectively designed to determine the physiologic effects of normothermic CPB and to compare its influences with hypothermic CPB. Material and Method: Thirty-six adult patients scheduled for el­ective cardiac surgery were randomly assigned to moderate hypothermic (hypothermic group nasopharyngeal tem­perature $26\~28^{\circ}C,\;n=18)$ ornormothermic (normothermic group, nasopharyngeal temperature > $35.5^{\circ}C\;n=18)$ CPB. Arterial blood samples were taken before CPB (Pre-CPB), 10 minutes after the start of CPB (CPB-10), and imme­diately after CPB stop (CPB-off) for determining total leukocyte counts, neuron-specific enolase (NSE), interleukin-6 (IL-6), endothelin-1 (ET-1), cortisol, troponin I (TNI), aspartate aminotransferase (AST), alanine aminotransferase (ALT), creatinine, blood urea nitrogen (BUN), and the pulmonary index $(Pi,\;PaO_{2}/FiO_{2}),$Other parameters such as urine output, mechanical ventilating period, ICU-staying period, postoperative complications and hospitalized days were also evaluated. Result: Total leukocyte counts, increased rate in NSE, in IL-6 and in cortisol at CPB-10 and CPB-off were significantly higher in normothermic group than in hyphothermic group. Urine output during CPB was lower in normothermic group than in hyphothermic group. The duration of mechanical ventilation, ICU-stay, and hospitalization were longer in normothermic group than in hyphothermic group. Conclusion: These findings sug­gested that normothermic CPB caused higher inflammatory and stress responses than hypothermic CPB during car­diac surgery using cold crystalloid cardioplegia. However, further studies with large number of cases should be carried out to validate this hypothesis.

Effects of Precombustion Chamber Shape on the Start ability of Small Diesel Engine under the Cold Weather (소형(小型) 디젤엔진의 예연소실(豫燃焼室) 형상(形狀)이 냉시동성(冷始動性)에 미치는 영향(影響)에 관(關)한 실험적(實驗的) 연구(硏究))

  • Moon, Gyeh Song;Kim, Yong Whan;Lee, Seung Kyu
    • Journal of Biosystems Engineering
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    • v.6 no.2
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    • pp.9-19
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    • 1982
  • The aim of this study was to improve the startability of the diesel engine at low temperature. The specific objective was to determine the optimum type of precombustion chamber. The eight different types of precombustion chamber and two different types of the cylinder head were designed and tested by $2^7$ factorial experiments with four replications. The lowest starting temperature for first operation, the maximum output, and the specific fuel consumption at full load and overload were checked and analyzed. The results of the study are summarized as follows; 1. The lowest starting temperature was lowered as much as $2.4^{\circ}C$ and the maximum output was increased as much as 0.3 ps with respect to the difference in the relative angle of the main passageway against the piston head from 20 degree to 18 degree. 2. The lowest starting temperature and the maximum out-put were lowered as much as $3.3^{\circ}C$ and 0.3 ps respectively with respect to the difference in the angle of the cylinder head groove from 20 degree to 18 degree. 3. The lowest starting temperature and the maximum out put were lowered as much as $2^{\circ}C$ and 0.2 ps respectively with respect to the difference in the length of the precombustion chamber from 17.5 mm to 15.5mm. 4. There was no significant difference in the startability but the maximum output was increased as much as 0.2 ps with respect to the difference in the diameter of the main passageway from 4.8mm to 4.5mm. 5. The lowest starting temperature was obtained under the condition at 47 degree in the angle of the main passageway and at 18 degree in the angle of the cylinder head groove. The maximum output and the minimum specific fuel consumption was obtained under the condition at 4.5mm in the diameter of the main passageway and at 17.5mm in the length of the precombustion chamber. 6. The angle of the cylinder head groove and the main passageway appeared to the major factors affecting the startability significantly. The interaction between the diameter of the main pass ageway and the length of the precombustion chamber had an significant influence on the maximum output. So it would be recommended to study further on the interaction between two factors mentioned above by expanding their levels. 7. The optimum condition suggested by this study could lower the starting temperature by $6^{\circ}C$ compared to the conventional precombustion chambers.

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Social Network Analysis for the Effective Adoption of Recommender Systems (추천시스템의 효과적 도입을 위한 소셜네트워크 분석)

  • Park, Jong-Hak;Cho, Yoon-Ho
    • Journal of Intelligence and Information Systems
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    • v.17 no.4
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    • pp.305-316
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    • 2011
  • Recommender system is the system which, by using automated information filtering technology, recommends products or services to the customers who are likely to be interested in. Those systems are widely used in many different Web retailers such as Amazon.com, Netfix.com, and CDNow.com. Various recommender systems have been developed. Among them, Collaborative Filtering (CF) has been known as the most successful and commonly used approach. CF identifies customers whose tastes are similar to those of a given customer, and recommends items those customers have liked in the past. Numerous CF algorithms have been developed to increase the performance of recommender systems. However, the relative performances of CF algorithms are known to be domain and data dependent. It is very time-consuming and expensive to implement and launce a CF recommender system, and also the system unsuited for the given domain provides customers with poor quality recommendations that make them easily annoyed. Therefore, predicting in advance whether the performance of CF recommender system is acceptable or not is practically important and needed. In this study, we propose a decision making guideline which helps decide whether CF is adoptable for a given application with certain transaction data characteristics. Several previous studies reported that sparsity, gray sheep, cold-start, coverage, and serendipity could affect the performance of CF, but the theoretical and empirical justification of such factors is lacking. Recently there are many studies paying attention to Social Network Analysis (SNA) as a method to analyze social relationships among people. SNA is a method to measure and visualize the linkage structure and status focusing on interaction among objects within communication group. CF analyzes the similarity among previous ratings or purchases of each customer, finds the relationships among the customers who have similarities, and then uses the relationships for recommendations. Thus CF can be modeled as a social network in which customers are nodes and purchase relationships between customers are links. Under the assumption that SNA could facilitate an exploration of the topological properties of the network structure that are implicit in transaction data for CF recommendations, we focus on density, clustering coefficient, and centralization which are ones of the most commonly used measures to capture topological properties of the social network structure. While network density, expressed as a proportion of the maximum possible number of links, captures the density of the whole network, the clustering coefficient captures the degree to which the overall network contains localized pockets of dense connectivity. Centralization reflects the extent to which connections are concentrated in a small number of nodes rather than distributed equally among all nodes. We explore how these SNA measures affect the performance of CF performance and how they interact to each other. Our experiments used sales transaction data from H department store, one of the well?known department stores in Korea. Total 396 data set were sampled to construct various types of social networks. The dependant variable measuring process consists of three steps; analysis of customer similarities, construction of a social network, and analysis of social network patterns. We used UCINET 6.0 for SNA. The experiments conducted the 3-way ANOVA which employs three SNA measures as dependant variables, and the recommendation accuracy measured by F1-measure as an independent variable. The experiments report that 1) each of three SNA measures affects the recommendation accuracy, 2) the density's effect to the performance overrides those of clustering coefficient and centralization (i.e., CF adoption is not a good decision if the density is low), and 3) however though the density is low, the performance of CF is comparatively good when the clustering coefficient is low. We expect that these experiment results help firms decide whether CF recommender system is adoptable for their business domain with certain transaction data characteristics.

한국농촌의 식품금기에 관한 연구

  • 모수미
    • Journal of the Korean Home Economics Association
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    • v.5 no.1
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    • pp.733-739
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    • 1966
  • A 371 agricultural households from 26 different communities in South Korea was subjected on a study of food taboos in January of 1966. To the pregnant women, those to whom a high protein diet is particurally important, as many as 14 different kinds of foods, mostly portein rich foods, were avoided to eat. It is believed that if duck is eaten while pregnant her baby may walk like a duck in later life. Some mother have a strong aversion to the rabbit meat that her unborn baby must be a harelip. It is feared to eat chicken, shark or carp by the pregnant mother for her baby may get a gooseflesh appearance, or fish scale-like skin in later life. It is thought that if mother eats soup made of meat borns, especially chicken bones, a disfigured baby may be born. Some area informed that if mother eats crab meat her future baby will always bubble. To the child-bearing mothers 13 different kinds of foods were avoided to eat. Some believe that if raddish kimchi, soybean curd, squash are eaten while dilivery that mother may get dental decay or to lose all her teeth. Other think that highly spiced raddish kimchi cause delivery difficult. To the lactating mothers 7 different items of foods were not recommended to eat. It is a common belief that eating green vegetables, especially fresh lettuce, are restricted that her baby may stool greenish. It is said that eating ginsen-chicken soup, or ginsen tea during lactating reduces breast milk secretion. To the weaning babies 7 different kinds of foods were prohibited to fee. Eggs are not eaten because mothers think her babies will start to talk very late. Eight different items of foods in cases of gastro-intestinal diseases, 5 items for liver disease, 7 items for high blood pressure as well as for paralysis were respectively restricted. It is said that meats including pork, beef, and chicken are neither desirable for the patients of high blood pressure nor those of paralysis. To the measles children 10 varieties of foods were restricted. Especially soybean products and meats were not encouraged to use for avoiding asecond attack of measles. For the common cold 8 different kinds of foods were aversed and men think that eating of soup of undria delays a recovery. For the tuberculosis 4 kinds of foods were prohibited to eat. It is said that wine, red pepper and ginsen will stimulate lung bleeding. Many mothers had a strong aversion to fermented shrimp and fish in case of style. and 5 different items of foods were restricted. In case of menstration not so many foods were restricted as other cases, but meat soup is not eaten in this condition in some areas. Majority of food taboos in Korean villages are neither based on tribal nor religious factors. But no one knows how, since what ages, from where, these food taboos have been transmitted and spread over the country. This survey found a great variety of food taboos, aversions, traditional beliefs and prohibitions latent unknown reseasons, or non-scientific conceptions, or completely different ideas from the modern medical aspect, or somewhat fallacious and superstitious beliefs. For the vascular disease contrasting approach were found between modern the oritical therapy and popular remedy among the rural populations who largely depend on the eastern medication. Further scientific study on either side should be done to lead the patient proper way. Many restricted foods such as rabbit, duck, chicken and fish are best resources of protein rich foods which are available in the village. Emphasis should be laid upon breaking down fallacious and supersititious food taboos through the extended nutrition education activities in order to improve food habit and good eating pattern for healthier and stronger generations of Korea.

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A Case of the Shoulder-Hand Syndrome Caused by a Crush Injury of the Shoulder (견관절부 외상후 발생된 Shoulder-Hand Syndrome)

  • Jeon, Jae-Soo;Lee, Sung-Keun;Song, Hoo-Bin;Kim, Sun-Jong;Park, Wook;Kim, Sung-Yell
    • The Korean Journal of Pain
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    • v.2 no.2
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    • pp.155-166
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    • 1989
  • Bonica defined, that reflex sympathetic dystrophy (RSD) may develop pain, vasomotor abnoramalities, delayed functional recovery, and dystrophic changes on an affected area without major neurologic injury following trauma, surgery or one of several diseased states. This 45 year old male patient had been crushed on his left shoulder by a heavily laden rear car, during his job street cleaning about 10 years ago (1978). At first the pain was localizea only to the site of injury, but with time, it spreaded from the shoulder to the elbow and hand, with swelling. X-ray studies in the local clinic, showed no bone abnormalities of the affected site. During about 10 years following the injury, the had recieved several types of treatments such as nonsteroidal analgesics, steroid injections into the glenoidal cavity (10 times), physical therapy, some oriental herb medicines, and acupuncture over a period of 1~3 months annually. His shoulder pain and it's joint dysfunction persisted with recurrent paroxysmal aggrevation because of being mismanaged or neglected for a sufficiently long period these fore permiting progression of the sympathetic imbalance. On July 14 1988 when he visited our clinic. He complained of burning, aching and had a hyperpathic response or hyperesthesia in touch from the shoulder girdle to the elbow and the hand. Also the skin of the affected area was pale, cold, and there was much sweating of the axilla and palm, but no edema. The shoulder girdle was unable to move due to joint pain with marked weakness. We confirmed skin temperatures $5^{\circ}C$ lower than those of the unaffected axilla, elbow and palm of his hand, and his nails were slightly ridged with lateral arching and some were brittle. On X-ray findings of both the shoulder AP & lateral view, the left humerus and joint area showed diffuse post-traumatic osteoporosis and fibrous ankylozing with an osteoarthritis-like appearance. For evaluating the RSD and it's relief of pain, the left cervical sympathetic ganglion was blocked by injecting 0.5% bupivacaine 5 ml with normal saline 5 ml (=SGB). After 15 minutes following the SGB, the clinical efficacy of the block by the patients subjective score of pain intensity (=PSSPI), showed a 50% reduction of his shoulder and arm pain, which was burning in quality, and a hyperpathic response against palpation by the examiner. The skin temperatures of the axilla and palm rose to $4{\sim}5^{\circ}C$ more than those before the SGB. He felt that his left face and upper extremity became warmer than before the SGB, and that he had reduced sweating on his axilla and his palm. Horner's sign was also observed on his face and eyes. But his deep shoulder joint pain was not improved. For the control of the remaining shoulder joint pain, after 45 minutes following the SGB, a somatic sensory block was performed by injecting 0.5% bupivacaine 6 ml mixed with salmon calcitonin, $Tridol^{(R)}$, $Polydyn^{(R)}$ and triamcinolone into the fossa of the acromioclavicular joint region. The clinical effect of the somatic block showed an 80% releif of the deep joint pain by the PSSPI of the joint motion. Both blocks, as the above mentioned, were repeated a total of 28 times respectively, during 6 months, except the steroid was used just 3 times from the start. For maintaining the relieved pain level whilst using both blocks, we prescribed a low dose of clonazepam, prazocin, $Etravil^{(R)}$, codeine, etodolac micronized and antacids over 6 months. The result of the treatments were as follows; 1) The burning, aching and hyperpathic condition which accompanied with vaosmotor and pseudomotor dysfunction, disappeared gradually to almost nothing, within 3 weeks from the starting of the blocks every other day. 2) The joint disability of the affected area was improved little by little within 6 months. 3) The post-traumatic osteoporosis, fibrous ankylosis and marginal sclerosis with a narrowed joint, showed not much improvement on the X-ray findings (on April 25, 1989) 10 months later in the follow-up. 4) Now he has returned to his job as a street cleaner.

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