• 대한공업교육학회지
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• v.38 no.2
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• pp.218-239
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• 2013

This study aims to understand the status of mandatory military service planning and career barrier recognition as well as to analyze the difference between how students perceive mandatory military service as a potential barrier to their future careers(career barrier recognition) and career preparation behavior by the mandatory military service planning level among male college students. For the purpose, inquiries for the subject were set up as follows. 1. What are the levels of mandatory military service planning and career barrier recognition? 2. Is there a difference in career barrier recognition depending on the level of mandatory military service planning? 3. Is there a difference in career preparation behaviour depending on the level of mandatory military service planning? This study found out the level of mandatory military service, military barrier recognition and career preparation behavior of 284 male students from 4 universities in Daejeon and Chungnam area. Along with that, descriptive statistic, correlation analysis and t-test were conducted with SPSS 17.0 program The results of this study are as follows: First, 79.2% of male students have higher mandatory military service planning than the average value. Meanwhile, considering 3 sub-factors of mandatory military service planning, the ratio of those with high scores in practicality is lower than importance and concreteness. Based on this, it is assumable that they have a low perception for practical and concrete behaviors such as data collection in mandatory military service planning, which indicates their awareness has not developed into concrete behaviors even though they recognize the importance of planning. Also 73.9% of male students responded higher career barrier recognition than the average value shows that they recognize mandatory military service as a barrier relatively highly. Especially, those who answered "Very much" (7 scores) for every inquiry in career barrier recognition accounted for 16.9%, which forms the biggest group. and considering the response by each inquiry, it is ascertained that they consider the absence by mandatory military service time or military service as the biggest difficulty. Second, the difference in career barrier recognition between the top 30% and bottom 30% of mandatory military service planning is not statistically significant. However, in terms of importance and the sub-factor of mandatory military service planning, a significant inter-group difference in career barrier recognition is shown. In other words, to join the military is recognized as an obstacle in their career barrier recognition regardless of the mandatory military service planning level. Also, a group which considers the importance of the mandatory military service planning highly recognizes the military as the bigger obstacle compared to the other groups which are not considered in this way. Third, the difference in career barrier recognition between the top 30% and the bottom 30% of the mandatory military service planning is statistically significant. The need of mandatory military service planning is marked by the fact that those with a high level of mandatory military service planning show stronger career barrier recognition than those without plans. Through the study, the need of mandatory military service planning is suggested to both male students and career consultants considering the mandatory military service from a perspective of career based on Korean reality. Also, as precedent studies on pre-inducted men can be hardly found currently, this study is significant in accumulating empirical data about mandatory military service, a unique characteristic of the Korean career development process.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.111-126
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• 2017

Recommender systems based on association rule mining significantly contribute to seller's sales by reducing consumers' time to search for products that they want. Recommendations based on the frequency of transactions such as orders can effectively screen out the products that are statistically marketable among multiple products. A product with a high possibility of sales, however, can be omitted from the recommendation if it records insufficient number of transactions at the beginning of the sale. Products missing from the associated recommendations may lose the chance of exposure to consumers, which leads to a decline in the number of transactions. In turn, diminished transactions may create a vicious circle of lost opportunity to be recommended. Thus, initial sales are likely to remain stagnant for a certain period of time. Products that are susceptible to fashion or seasonality, such as clothing, may be greatly affected. This study was aimed at expanding association rules to include into the list of recommendations those products whose initial trading frequency of transactions is low despite the possibility of high sales. The particular purpose is to predict the strength of the direct connection of two unconnected items through the properties of the paths located between them. An association between two items revealed in transactions can be interpreted as the interaction between them, which can be expressed as a link in a social network whose nodes are items. The first step calculates the centralities of the nodes in the middle of the paths that indirectly connect the two nodes without direct connection. The next step identifies the number of the paths and the shortest among them. These extracts are used as independent variables in the regression analysis to predict future connection strength between the nodes. The strength of the connection between the two nodes of the model, which is defined by the number of nodes between the two nodes, is measured after a certain period of time. The regression analysis results confirm that the number of paths between the two products, the distance of the shortest path, and the number of neighboring items connected to the products are significantly related to their potential strength. This study used actual order transaction data collected for three months from February to April in 2016 from an online commerce company. To reduce the complexity of analytics as the scale of the network grows, the analysis was performed only on miscellaneous goods. Two consecutively purchased items were chosen from each customer's transactions to obtain a pair of antecedent and consequent, which secures a link needed for constituting a social network. The direction of the link was determined in the order in which the goods were purchased. Except for the last ten days of the data collection period, the social network of associated items was built for the extraction of independent variables. The model predicts the number of links to be connected in the next ten days from the explanatory variables. Of the 5,711 previously unconnected links, 611 were newly connected for the last ten days. Through experiments, the proposed model demonstrated excellent predictions. Of the 571 links that the proposed model predicts, 269 were confirmed to have been connected. This is 4.4 times more than the average of 61, which can be found without any prediction model. This study is expected to be useful regarding industries whose new products launch quickly with short life cycles, since their exposure time is critical. Also, it can be used to detect diseases that are rarely found in the early stages of medical treatment because of the low incidence of outbreaks. Since the complexity of the social networking analysis is sensitive to the number of nodes and links that make up the network, this study was conducted in a particular category of miscellaneous goods. Future research should consider that this condition may limit the opportunity to detect unexpected associations between products belonging to different categories of classification.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.147-168
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• 2017

There have been many studies on accurate stock market forecasting in academia for a long time, and now there are also various forecasting models using various techniques. Recently, many attempts have been made to predict the stock index using various machine learning methods including Deep Learning. Although the fundamental analysis and the technical analysis method are used for the analysis of the traditional stock investment transaction, the technical analysis method is more useful for the application of the short-term transaction prediction or statistical and mathematical techniques. Most of the studies that have been conducted using these technical indicators have studied the model of predicting stock prices by binary classification - rising or falling - of stock market fluctuations in the future market (usually next trading day). However, it is also true that this binary classification has many unfavorable aspects in predicting trends, identifying trading signals, or signaling portfolio rebalancing. In this study, we try to predict the stock index by expanding the stock index trend (upward trend, boxed, downward trend) to the multiple classification system in the existing binary index method. In order to solve this multi-classification problem, a technique such as Multinomial Logistic Regression Analysis (MLOGIT), Multiple Discriminant Analysis (MDA) or Artificial Neural Networks (ANN) we propose an optimization model using Genetic Algorithm as a wrapper for improving the performance of this model using Multi-classification Support Vector Machines (MSVM), which has proved to be superior in prediction performance. In particular, the proposed model named GA-MSVM is designed to maximize model performance by optimizing not only the kernel function parameters of MSVM, but also the optimal selection of input variables (feature selection) as well as instance selection. In order to verify the performance of the proposed model, we applied the proposed method to the real data. The results show that the proposed method is more effective than the conventional multivariate SVM, which has been known to show the best prediction performance up to now, as well as existing artificial intelligence / data mining techniques such as MDA, MLOGIT, CBR, and it is confirmed that the prediction performance is better than this. Especially, it has been confirmed that the 'instance selection' plays a very important role in predicting the stock index trend, and it is confirmed that the improvement effect of the model is more important than other factors. To verify the usefulness of GA-MSVM, we applied it to Korea's real KOSPI200 stock index trend forecast. Our research is primarily aimed at predicting trend segments to capture signal acquisition or short-term trend transition points. The experimental data set includes technical indicators such as the price and volatility index (2004 ~ 2017) and macroeconomic data (interest rate, exchange rate, S&P 500, etc.) of KOSPI200 stock index in Korea. Using a variety of statistical methods including one-way ANOVA and stepwise MDA, 15 indicators were selected as candidate independent variables. The dependent variable, trend classification, was classified into three states: 1 (upward trend), 0 (boxed), and -1 (downward trend). 70% of the total data for each class was used for training and the remaining 30% was used for verifying. To verify the performance of the proposed model, several comparative model experiments such as MDA, MLOGIT, CBR, ANN and MSVM were conducted. MSVM has adopted the One-Against-One (OAO) approach, which is known as the most accurate approach among the various MSVM approaches. Although there are some limitations, the final experimental results demonstrate that the proposed model, GA-MSVM, performs at a significantly higher level than all comparative models.

• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.5
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• pp.631-640
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• 2014

The inhibitory effects of Boswellia serrata (BW) extracts on degenerative osteoarthritis were investigated in primary-cultured rat cartilage cells and a monosodium-iodoacetate (MIA)-induced osteoarthritis rat model. To identify the protective effects of BW extract against $H_2O_2$ ($800{\mu}M$, 2 hr) in vitro, cell survival was measured by MTT assay. Cell survival after $H_2O_2$ treatment was elevated by BW extract at a concentration of $20{\mu}g/mL$. In addition, BW extract treatment significantly reduced and normalized the productions of pro-inflammatory factors, nuclear transcription factor ${\kappa}B$, cyclooxygenase-2, tumor necrosis factor-${\alpha}$, and interleukin-6 at a concentration of $20{\mu}g/mL$. Treatment of chondrocytes with BW extract significantly reduced 5-lipoxygenase activity and production of prostaglandin E2, especially at a concentration of $10{\sim}20{\mu}g/mL$. For the in vivo animal study, osteoarthritis was induced by intra-articular injection of MIA into knee joints of rats. Consumption of a diet containing BW extract (100 and 200 mg/kg) for 35 days significantly inhibited the development and severity of osteoarthritis in rats. To determine the genetic expression of arthritic factors in articular cartilage, real-time PCR was applied to measure matrix metalloproteinases (MMP-3, MMP-9, and MMP-13), collagen type I, collagen type II, and aggrecan, and BW extract had protective effects at a concentration of 200 mg/kg. In conclusion, BW extract was able to inhibit articular cartilage degeneration by preventing extracellular matrix degradation and chondrocyte injury. One can consider that BW extract may be a potential therapeutic treatment for degenerative osteoarthritis.

• 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.

• Journal of Korean Medical classics
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• v.20 no.4
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• pp.91-117
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• 2007

Through a simple study of the medical classics in the '$\bar{A}yurveda$', we have summarized them as follows. 1) Traditional Indian medicine started in the Ganges river area at about 1500 B. C. E. and traces of medical science can be found in the "Rigveda" and "Atharvaveda". 2) The "Charaka" and "$Su\acute{s}hruta$(妙聞集)", ancient texts from India, are not the work of one person, but the result of the work and errors of different doctors and philosophers. Due to the lack of historical records, the time of Charaka or $Su\acute{s}hruta$(妙聞)s' lives are not exactly known. So the completion of the "Charaka" is estimated at 1st${\sim}$2nd century C. E. in northwestern India, and the "$Su\acute{s}hruta$" is estimated to have been completed in 3rd${\sim}$4th century C. E. in central India. Also, the "Charaka" contains details on internal medicine, while the "$Su\acute{s}hruta$" contains more details on surgery by comparison. 3) '$V\bar{a}gbhata$', one of the revered Vriddha Trayi(triad of the ancients, 三醫聖) of the '$\bar{A}yurveda$', lived and worked in about the 7th century and wrote the "$A\d{s}\d{t}\bar{a}nga$ $A\d{s}\d{t}\bar{a}nga$ $h\d{r}daya$ $sa\d{m}hit\bar{a}$ $samhit\bar{a}$(八支集)" and "$A\d{s}\d{t}\bar{a}nga$ Sangraha $samhit\bar{a}$(八心集)", where he tried to compromise and unify the "Charaka" and "$Su\acute{s}hruta$". The "$A\d{s}\d{t}\bar{a}nga$ Sangraha $samhit\bar{a}$" was translated into Tibetan and Arabic at about the 8th${\sim}$9th century, and if we generalize the medicinal plants recorded in each the "Charaka", "$Su\acute{s}hruta$" and the "$A\d{s}\d{t}\bar{a}nga$ Sangraha $samhit\bar{a}$", there are 240, 370, 240 types each. 4) The 'Madhava' focused on one of the subjects of Indian medicine, '$Nid\bar{a}na$' ie meaning "the cause of diseases(病因論)", and in one of the copies found by Bower in 4th century C. E. we can see that it uses prescriptions from the "BuHaLaJi(布哈拉集)", "Charaka", "$Su\acute{s}hruta$". 5) According to the "Charaka", there were 8 branches of ancient medicine in India : treatment of the body(kayacikitsa), special surgery(salakya), removal of alien substances(salyapahartka), treatment of poison or mis-combined medicines(visagaravairodhikaprasamana), the study of ghosts(bhutavidya), pediatrics(kaumarabhrtya), perennial youth and long life(rasayana), and the strengthening of the essence of the body(vajikarana). 6) The '$\bar{A}yurveda$', which originated from ancient experience, was recorded in Sanskrit, which was a theorization of knowledge, and also was written in verses to make memorizing easy, and made medicine the exclusive possession of the Brahmin. The first annotations were 1060 for the "Charaka", 1200 for the "$Su\acute{s}hruta$", 1150 for the "$A\d{s}\d{t}\bar{a}nga$ Sangraha $samhit\bar{a}$", and 1100 for the "$Nid\bar{a}na$", The use of various mineral medicines in the "Charaka" or the use of mercury as internal medicine in the "$A\d{s}\d{t}\bar{a}nga$ Sangraha $samhit\bar{a}$", and the palpation of the pulse for diagnosing in the '$\bar{A}yurveda$' and 'XiZhang(西藏)' medicine are similar to TCM's pulse diagnostics. The coexistence with Arabian 'Unani' medicine, compromise with western medicine and the reactionism trend restored the '$\bar{A}yurveda$' today. 7) The "Charaka" is a book inclined to internal medicine that investigates the origin of human disease which used the dualism of the 'Samkhya', the natural philosophy of the 'Vaisesika' and the logic of the 'Nyaya' in medical theories, and its structure has 16 syllables per line, 2 lines per poem and is recorded in poetry and prose. Also, the "Charaka" can be summarized into the introduction, cause, judgement, body, sensory organs, treatment, pharmaceuticals, and end, and can be seen as a work that strongly reflects the moral code of Brahmin and Aryans. 8) In extracting bloody pus, the "Charaka" introduces a 'sharp tool' bloodletting treatment, while the "$Su\scute{s}hruta$" introduces many surgical methods such as the use of gourd dippers, horns, sucking the blood with leeches. Also the "$Su\acute{s}hruta$" has 19 chapters specializing in ophthalmology, and shows 76 types of eye diseases and their treatments. 9) Since anatomy did not develop in Indian medicine, the inner structure of the human body was not well known. The only exception is 'GuXiangXue(骨相學)' which developed from 'Atharvaveda' times and the "$A\d{s}\d{t}\bar{a}nga$ Sangraha $samhit\bar{a}$". In the "$A\d{s}\d{t}\bar{a}nga$ Sangraha $samhit\bar{a}$"'s 'ShenTiLun(身體論)' there is a thorough listing of the development of a child from pregnancy to birth. The '$\bar{A}yurveda$' is not just an ancient traditional medical system but is being called alternative medicine in the west because of its ability to supplement western medicine and, as its effects are being proved scientifically it is gaining attention worldwide. We would like to say that what we have researched is just a small fragment and a limited view, and would like to correct and supplement any insufficient parts through more research of new records.

• Journal of Nutrition and Health
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• v.42 no.2
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• pp.135-145
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• 2009

This study was performed to investigate added sugar intakes from processed food-snacks and participation behaviors of special event days sharing sweet foods among adolescents in Korea. Questionnaire survey (n = 959), dietary survey (n = 71) by food record method for 3 days, and snack survey (n = 230) for 3 days were carried out, and subjects were overlapped among three surveys. As a result, middle school students (MS) preferred milks and fermented milks while high school students (HS) preferred breads and fast foods as a snack (p < 0.01). MS and HS took snacks three to six times a week, and HS took snacks more frequently than MS (p < 0.05). Most subjects participated in special event days sharing sweet foods such as friend's birthday (68.4%), Peppro's day (61.5%) and Valentine's day (42.6%). As for merits of these events, MS said ‘they could get along with their friends' and ‘relieve stress', while HS said ‘they could enjoy their own events' and ‘confess their affection to whom they like' (p < 0.01). A group of cookies, biscuits, breads and, cakes was major source of added sugars followed by beverages, sweet jellies of red bean, chocolates and candies for subjects. For MS and HS, daily total added sugar intakes from whole processed food-snacks were $30.5{\pm}23.5g/d$ (3.0-137.9 g/d) and $31.7{\pm}23.2g/d$ (1.2-126.1 g/d), and ratios of daily total energy taken from added sugars of whole processed food-snacks in proportion to daily total energy taken from diet (energy percent of added sugars from snacks) were $6.3{\pm}4.7%$ (0.6-26.1%) and $6.3{\pm}4.4%$ (0.3-23.9%), respectively. These results showed that subjects frequently participated in special event days sharing sweet foods. In addition, energy percent of added sugars from snacks was more than the UL suggested by WHO/FAO for some subjects. Therefore, it is highly critical to monitor adolescents' sugar intakes on a long-term basis and to take nutritional management on their high sugar intakes.

• Journal of Oral Medicine and Pain
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• v.36 no.1
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• pp.39-51
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• 2011

The aims of this study were to investigate whether the facial skeletal patterns previously reported to be related to temporomandibular disorder (TMD) in other studies could be consistently observed in the TMD patients diagnosed according to Research Diagnostic Criteria for Temporomandibular Disorder (RDC/TMD) Axis I and evaluate its usability in the orthodontic clinics to examine the patients with TMD related symptoms. The clinical records and radiographs of female patients who visited the TMD and Orofacial Pain Clinic of Seoul National University Dental Hospital and were diagnosed as TMD were consecutively filed for this study. Patients were clinically examined and diagnosed according to the revised diagnostic algorithms of RDC/TMD Axis I and the lateral cephalogram, panoramic orthopantomogram, temporomandibular joint (TMJ) orthopantomogram, and transcranial radiograph of each patient were taken and digitalized. The data of patients who were under 18 years of age or had any systemic disease, trauma history involving the TMJ, or skeletal deformity at the time of the first examination were excluded. The remaining data of 96 female patients were finally analyzed. The obtained results were as follows: 1. There are no significant differences of cephalometric measurements between RDC I (muscle disorders) diagnostic groups. 2. Only the articular angle of the RDC group IIc (disk displacement without reduction without limited opening) patients was larger than patients of the no diagnosis of RDC II group (disk displacement). 3. Larger articular angle and smaller facial height ratio were observed in RDC IIIc group (osteoarthrosis) compared to IIIa group (arthralgia). Larger articular angle, larger Bjork sum, smaller posterior facial height, and smaller facial height ratio were observed in RDC group IIIc compared to no diagnosis of RDC III group (arthralgia, arthritis, and arthrosis). 4. According to the results of cephalometric analysis in simplified RDC groups, smaller overjet was observed in muscle disorders (MD) group. Facial height ratio and IMPA were smaller and articular angle was larger in disk displacements (DD) group than in no diagnosis of DD group. In arthrosis (AR) group, posterior facial height, and facial height ratio were smaller, and articular angle, gonial angle, facial convexity, FMA, Bjork sum, and ANB were larger than in no diagnosis of AR group. In joint pain (JP) group, only posterior facial height was smaller than no diagnosis of JP group. In conclusion, Facial morphologic patterns showing posterior-rotated mandible and lower posterior facial height is related to RDC group II and III diagnosis of the TMJ in female TMD patients. RDC/TMD Axis I diagnosis can provide a good clinical diagnostic tool for the standardized examination of the TMJ in orthodontic clinics.

• Journal of Oral Medicine and Pain
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• v.32 no.4
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• pp.441-447
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• 2007

Internal derangement of the temporomandibular joint(TMJ) is defined as an abnormal relationship of the articular disc to the condyle. Mandibular manipulation is one of the conservative treatments to be considered first to manage the patients with anterior disc displacement without reduction. Mandibular manipulation is used to increase articular mobility and to restore the displaced disc into an anatomically normal position. While Farrar's technique has been popularly used, Minagi et al., Mongini and Suarez introduced the manipulation technique conducted by the patients themselves. But there is no study on the efficacy of self-manipulation technique, comparing with conventional one. The aim of this study was to investigate the efficacy of the conventional and self-manipulation technique, which was modified to complement the previously described technique by Minagi et al., in the treatment of patients with anterior disc displacement without reduction. TMD patients, who visited Department of Oral Medicine of Seoul National University Dental Hospital from December, 2002 to November, 2004 and were diagnosed as anterior disc displacement without reduction by TMJ magnetic resonance imaging (MRI) were enrolled. Conservative treatments including physical therapy, exercise, behavioral therapy, stabilization splint therapy, and manipulation therapy were done to every single patient until the symptomsimproved enough to discharge the patient. The charts were reviewed retrospectively according to the type of manipulation. In the results, patients whose maximum mouth opening was more than 40 mm was higher in the self-manipulation group(69.9%) than in the conventional manipulation group(42.9%). But difference between two groups was not significant. According to the fact that we decided to discharge the patients whentheir mouth opening increased to more than 40 mm and subjective symptoms such as pain and discomfort were improved as well, treatment period of discharged patients was significantly shorter in the self-manipulation group($29.2{\pm}12.3$ weeks) than in the conventional manipulation group ($61.0{\pm}38.0$ weeks) (p<0.01). In conclusion, in the treatment of TMD patients with anterior disc displacement without reduction, the self-manipulation technique which is performed by patients themselves is an effective treatment modality for increasing the range of mouth opening and shortening the total treatment period.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.27 no.3
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• pp.239-249
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• 2001

The purpose of this study is to evaluate the relationship of the factors which could be influenced by orthognathic surgery especillay SSRO. We measured the amounts of the maximum opening, lateral movements, maximum velocity and pattern of mandibular path during the opening and closing of mandible at the following times ; preoperative, 1 month after operation, 6 months after operation respectively using MKG. And the results were compared according to the categorized subgroups. Following results were obtained : 1. The change of the amounts of mandibular lateral movement and maximum opening velocity were statistically different between male and female (p<0.05), but the others were not. 2. According to the method of operation, there was no difference in the change of the mandibular movements between the group of SSRO and SSRO plus LeFort I osteotomy (p>0.05). 3. According to the amounts of mandibular movement, the recovery of left lateral movement of the group of $6{\sim}10mm$ was better than the other groups (p<0.05). 4. In the frontal pattern of the opening and closing of the mandible, the complex deflected type (F5), simple deflected type (F4), complex deviated type (F3), simple deviated type (F2), straight type (F1) were obtained in order at the time of preoperative, simple deflected type, simple deviated type, complex deviated type, straight type, complex deflected type in order at the time of 1 month after surgery, and the result at the time of 6 months after surgery was the same with that of the time of preoperative. In the sagittal pattern, non-coincident type (S2) was predominant at the time of preoperative, and coincident type (S1) was predominant at the time of 1 month after surgery. After 6 months, the result was also the same with that of the preoperative in sagittal pattern. 5. There was not a statistical difference in the change of the mandibular movement between group of presence of the preoperative TMJ symptoms and non-presence group (p>0.05). 6. There was not a statistical difference in the change of the mandibular movement between repositioning device applied group and non-applied group (p>0.05). 7. Sixty three percents of the patients who had preoperative TMJ symptoms were improved after surgery and preoperative TMJ symptoms were more improved after operation in the repositioning device non-applied group statistically (p<0.05).