• Journal of Dental Rehabilitation and Applied Science
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• v.40 no.2
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• pp.82-90
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• 2024

It often happens that a removable partial denture needs to be repaired due to tissue changes in the remaining alveolar ridge, fracture of the denture, or fracture of the abutment tooth. There are several advantages to retrofitting a customized surveyed crown under the existing RPD. Retrofitting a crown to the RPD decreases the economic burden to the patient and avoids the need for several appointments to fabricate a new RPD. It is difficult for artificial teeth used to repair dentures due to fractured natural teeth to have a shape similar to that of natural teeth, and to repair aesthetic artificial teeth, it is necessary to manufacture customized artificial teeth similar to the shape of each patient's teeth. Recently, CAD/CAM technology has been used to fabricate customized prosthetics on existing RPD to achieve high retention and fitness accuracy, and by manufacturing customized artificial teeth, more aesthetic and harmonious artificial tooth repair is possible. This is a case in which a denture was repaired using a digital method to fabricate a customized prosthesis on an existing partial denture and customized artificial teeth that mirrored the adjacent dentition, saving time and cost, simplifying the process, and achieving aesthetically and functionally satisfactory results.

• Journal of the Korean Applied Science and Technology
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• v.36 no.4
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• pp.1312-1326
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• 2019

The purpose of this study is to examine whether the 12-week Nordic walking can improve the physical function and arthritis pain of elderly women with osteoarthritis This study were divided into randomly assigned Nordic Walking Exercise Group (n=9) and Control Group (n=7) for 16 Elderly women diagnosed with Osteoarthritis (age: 73±3.79 year, height: 154.3±4.09 cm). The exercise group used Nordic sticks to carry out 30 minutes of Nordic walking exercise three times a week for 12 weeks, and the kinetic intensity was set at 40-60% of HRR. The control group maintained daily life for the same period. Body composition (weight, percentage body fat, skeletal muscle mass), muscular strength, Flexibility (muscular strength of upper and lower limbs, flexibility of upper and lower limbs), balance ability (static balance, dynamic balance) and pain level were measured as subordinate variables. These indicators were measured twice before and after the exercise program. The study shows that percentage body fat and skeletal muscle mass in the body composition function over 12 weeks of Nordic walking exercise have significant effects after the exercise than before (p=004)(p=.003), and it also shows significant interaction effects between the groups and timings(p=.018)(p=.005). In muscular strength, Flexibility factors, there were significant effects between the groups and timings in the upper limb muscular strength and the lower limb flexibility (p=.009)(p=.036), and a significant difference between the exercise group and the control group(p=.006) in the lower limb muscular strength. In addition, in the upper limb flexibility, there was a more significant difference after the exercise than before(p=.020). There were improvement effects after the exercise than before in the balance ability and the static balance(p=.016), but no difference in the dynamic balance(p>.05). In pain, there was a significant improvement after the exercise than before(p=.022), and a significant difference between the exercise group and the control group(p=.013). In conclusion, the 12-week Nordic walking exercise has positive effects on the body composition functions of the elderly women with Osteoarthritis, and has a positive effect on the improvement of upper limb muscular strength and lower limb flexibility in the health fitness factors. These effects are believed to have contributed effectively to the improvement of the level of pain by contributing to the improvement of physical and motor functions of the elderly women with Osteoarthritis. Therefore, it is considered that Nordic walking exercise, which enhances stability and balance of the patients with Osteoarthritis by using poles, is an effective exercise method for the improvement of the body and motor functions by lowering the pain of the joints and reducing the muscular strength and percentage body fat.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.99-112
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• 2010

Ensemble learning is a method for improving the performance of classification and prediction algorithms. It is a method for finding a highly accurateclassifier on the training set by constructing and combining an ensemble of weak classifiers, each of which needs only to be moderately accurate on the training set. Ensemble learning has received considerable attention from machine learning and artificial intelligence fields because of its remarkable performance improvement and flexible integration with the traditional learning algorithms such as decision tree (DT), neural networks (NN), and SVM, etc. In those researches, all of DT ensemble studies have demonstrated impressive improvements in the generalization behavior of DT, while NN and SVM ensemble studies have not shown remarkable performance as shown in DT ensembles. Recently, several works have reported that the performance of ensemble can be degraded where multiple classifiers of an ensemble are highly correlated with, and thereby result in multicollinearity problem, which leads to performance degradation of the ensemble. They have also proposed the differentiated learning strategies to cope with performance degradation problem. Hansen and Salamon (1990) insisted that it is necessary and sufficient for the performance enhancement of an ensemble that the ensemble should contain diverse classifiers. Breiman (1996) explored that ensemble learning can increase the performance of unstable learning algorithms, but does not show remarkable performance improvement on stable learning algorithms. Unstable learning algorithms such as decision tree learners are sensitive to the change of the training data, and thus small changes in the training data can yield large changes in the generated classifiers. Therefore, ensemble with unstable learning algorithms can guarantee some diversity among the classifiers. To the contrary, stable learning algorithms such as NN and SVM generate similar classifiers in spite of small changes of the training data, and thus the correlation among the resulting classifiers is very high. This high correlation results in multicollinearity problem, which leads to performance degradation of the ensemble. Kim,s work (2009) showedthe performance comparison in bankruptcy prediction on Korea firms using tradition prediction algorithms such as NN, DT, and SVM. It reports that stable learning algorithms such as NN and SVM have higher predictability than the unstable DT. Meanwhile, with respect to their ensemble learning, DT ensemble shows the more improved performance than NN and SVM ensemble. Further analysis with variance inflation factor (VIF) analysis empirically proves that performance degradation of ensemble is due to multicollinearity problem. It also proposes that optimization of ensemble is needed to cope with such a problem. This paper proposes a hybrid system for coverage optimization of NN ensemble (CO-NN) in order to improve the performance of NN ensemble. Coverage optimization is a technique of choosing a sub-ensemble from an original ensemble to guarantee the diversity of classifiers in coverage optimization process. CO-NN uses GA which has been widely used for various optimization problems to deal with the coverage optimization problem. The GA chromosomes for the coverage optimization are encoded into binary strings, each bit of which indicates individual classifier. The fitness function is defined as maximization of error reduction and a constraint of variance inflation factor (VIF), which is one of the generally used methods to measure multicollinearity, is added to insure the diversity of classifiers by removing high correlation among the classifiers. We use Microsoft Excel and the GAs software package called Evolver. Experiments on company failure prediction have shown that CO-NN is effectively applied in the stable performance enhancement of NNensembles through the choice of classifiers by considering the correlations of the ensemble. The classifiers which have the potential multicollinearity problem are removed by the coverage optimization process of CO-NN and thereby CO-NN has shown higher performance than a single NN classifier and NN ensemble at 1% significance level, and DT ensemble at 5% significance level. However, there remain further research issues. First, decision optimization process to find optimal combination function should be considered in further research. Secondly, various learning strategies to deal with data noise should be introduced in more advanced further researches in the future.

• Proceedings of the Optical Society of Korea Conference
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• 2003.07a
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• pp.60-61
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• 2003

A new approach to reduce the computation time of genetic algorithm (GA) for making binary phase holograms is described. Synthesized holograms having diffraction efficiency of 75.8% and uniformity of 5.8% are proven in computer simulation and experimentally demonstrated. Recently, computer-generated holograms (CGHs) having high diffraction efficiency and flexibility of design have been widely developed in many applications such as optical information processing, optical computing, optical interconnection, etc. Among proposed optimization methods, GA has become popular due to its capability of reaching nearly global. However, there exits a drawback to consider when we use the genetic algorithm. It is the large amount of computation time to construct desired holograms. One of the major reasons that the GA' s operation may be time intensive results from the expense of computing the cost function that must Fourier transform the parameters encoded on the hologram into the fitness value. In trying to remedy this drawback, Artificial Neural Network (ANN) has been put forward, allowing CGHs to be created easily and quickly (1), but the quality of reconstructed images is not high enough to use in applications of high preciseness. For that, we are in attempt to find a new approach of combiningthe good properties and performance of both the GA and ANN to make CGHs of high diffraction efficiency in a short time. The optimization of CGH using the genetic algorithm is merely a process of iteration, including selection, crossover, and mutation operators [2]. It is worth noting that the evaluation of the cost function with the aim of selecting better holograms plays an important role in the implementation of the GA. However, this evaluation process wastes much time for Fourier transforming the encoded parameters on the hologram into the value to be solved. Depending on the speed of computer, this process can even last up to ten minutes. It will be more effective if instead of merely generating random holograms in the initial process, a set of approximately desired holograms is employed. By doing so, the initial population will contain less trial holograms equivalent to the reduction of the computation time of GA's. Accordingly, a hybrid algorithm that utilizes a trained neural network to initiate the GA's procedure is proposed. Consequently, the initial population contains less random holograms and is compensated by approximately desired holograms. Figure 1 is the flowchart of the hybrid algorithm in comparison with the classical GA. The procedure of synthesizing a hologram on computer is divided into two steps. First the simulation of holograms based on ANN method [1] to acquire approximately desired holograms is carried. With a teaching data set of 9 characters obtained from the classical GA, the number of layer is 3, the number of hidden node is 100, learning rate is 0.3, and momentum is 0.5, the artificial neural network trained enables us to attain the approximately desired holograms, which are fairly good agreement with what we suggested in the theory. The second step, effect of several parameters on the operation of the hybrid algorithm is investigated. In principle, the operation of the hybrid algorithm and GA are the same except the modification of the initial step. Hence, the verified results in Ref [2] of the parameters such as the probability of crossover and mutation, the tournament size, and the crossover block size are remained unchanged, beside of the reduced population size. The reconstructed image of 76.4% diffraction efficiency and 5.4% uniformity is achieved when the population size is 30, the iteration number is 2000, the probability of crossover is 0.75, and the probability of mutation is 0.001. A comparison between the hybrid algorithm and GA in term of diffraction efficiency and computation time is also evaluated as shown in Fig. 2. With a 66.7% reduction in computation time and a 2% increase in diffraction efficiency compared to the GA method, the hybrid algorithm demonstrates its efficient performance. In the optical experiment, the phase holograms were displayed on a programmable phase modulator (model XGA). Figures 3 are pictures of diffracted patterns of the letter "0" from the holograms generated using the hybrid algorithm. Diffraction efficiency of 75.8% and uniformity of 5.8% are measured. We see that the simulation and experiment results are fairly good agreement with each other. In this paper, Genetic Algorithm and Neural Network have been successfully combined in designing CGHs. This method gives a significant reduction in computation time compared to the GA method while still allowing holograms of high diffraction efficiency and uniformity to be achieved. This work was supported by No.mOl-2001-000-00324-0 (2002)) from the Korea Science & Engineering Foundation.

• Tuberculosis and Respiratory Diseases
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• v.43 no.6
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• pp.976-986
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• 1996

BACKGROUND : Dyspnea is common among patients with cardiopulmonary disease, and "daily disability" is defined as a functional impairment resulting from exercise intolerance. The maximal oxygen uptake(VO2max) during exhausting work is not only the best single physical indicator of the capacity of a man for sustaining hard muscular work, but also the most objective method by which one can determine the physical fitness of an individual as reflected by his cardiovascular system. However, the expense, time and personnel requirements make this procedure prohibitive for testing large group. The walking test is well-known type of exercise and it cost nothing to perform and have good reproducibility. Thus we performed the walking test and investigated correlations with spirometry, ABG and exercise test. METHOD: We observed the walking test and exercise test by cycle ergometer in 37 patients who visited our hospital because of dyspnea. Arterial blood gas analysis and spiromety, dyspnea index were performed, too. RESULT : (1) The VO2max was significantly lower in patients with COPD and cardiovascular disease than asthma and dyspnea on exertion group(p<0.05). The walking test distance was also lower in former. (2) The 12 minute walking test was significantly correlated with VO2max, PaCO2, FVC(%), FEV1(%) in all patients(p<0.05), and the walking test was only conelated with VO2max in patients with COPD(p<0.05). (3) In COPD patients, the VO2max was best correlated with FEV1(%) and FVC(%) and significantly correlated with walking test. But there was no correlation between walking test and FEV1(%) & FVC(%). (4) The 6 minute walking test was well correlated with 12 minute walking test(r=0.92. p<0.01). CONCLUSION : The walking test is the simple method for assessing exercise performance in patient with cardiopulmonary disease and a reliable indicator for VO2max. And the walking test is practical method for assessing on everyday disability rather than maximal exercise capacity. The 6 minute walking test is highly correlated with 12 minute walking test and a less exhausting for the patients and a time-saving for the investigator.

• Journal of Korean Society of Forest Science
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• v.109 no.4
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• pp.477-483
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• 2020

We constructed a stand yield table for Chamaecyparis obtusa based on data from an actual forest. The previous stand yield table had a number of disadvantages because it was based on actual forest information. In the present study we used data from more than 200 sampling plots in a stand of Chamaecyparis obtusa. The analysis included theestimation, recovery and prediction of the distribution of values for diameter at breast height (DBH), and the result is a valuable process for the preparation ofstand yield tables. The DBH distribution model uses a Weibull function, and the site index (base age: 30 years), the standard for assessing forest productivity, was derived using the Chapman-Richards formula. Several estimation formulas for the preparation of the stand yield table were considered for the fitness index, and the optimal formula was chosen. The analysis shows that the site index is in the range of 10 to 18 in the Chamaecyparis obtusa stand. The estimated stand volume of each sample plot was found to have an accuracy of 62%. According to the residuals analysis, the stands showed even distribution around zero, which indicates that the results are useful in the field. Comparing the table constructed in this study to the existing stand yield table, we found that our table yielded comparatively higher values for growth. This is probably because the existing analysis data used a small amount of research data that did not properly reflect. We hope that the stand yield table of Chamaecyparis obtusa, a representative species of southern regions, will be widely used for forest management. As these forests stabilize and growth progresses, we plan to construct an additional yield table applicable to the production of developed stands.

• Tuberculosis and Respiratory Diseases
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• v.42 no.6
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• pp.900-912
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• 1995

Background: Although graded exercise stress tests are widely used for the evaluation of cardiorespiratory performance, normal standards on respiratory gas exchange and ventilatory functions at maximal exercise in Koreans have not been well established. The purpose of this study is to provide reference values on these by sex and age, along with derivation of some of their prediction equations. Method: Symptom-limited maximal exercise test was carried out by Bruce protocol in 1,000 healthy adults consisting of 603 males and 397 females, aged 20~66 years. Among them VC, $FEV_1$ and MVV were also determined in 885 cases. All the subjects were members of a health center, excluding athletes. During the exercise, subjects were allowed to hold on to front hand rail of the treadmill for safety purpose. Results: The $VO_2\;max/m^2$, $VCO_2\;max/m^2$ and $V_E\;max/m^2$ were greater in males than in females and decreased with age. The RR max in men and women was similar but decreased slightly with age. The $V_T$ max was markedly greater in men but showed no significant changes with age in either gender. The mean of $V_T$ max/VC, $V_E$ max/MVV and BR revealed that there were considerable ventilatory reserves at maximal exercise even in older females. The regression equations of the cardinal parameters obtained using exercise time(ET, min), age(A, yr), height(Ht, cm), weight(W, kg), sex(S, 0=male; 1=female), VC(L), $FEV_1$(L) and $V_E$ max(L) as variables are as follows: $VO_2\;max/m^2$(L/min)=1.449+0.073 ET-0.007A+0.010W-0.006Ht-0.209S, $VCO_2\;max/m^2$(L/min)=1.672+0.063ET-0.008A+0.010W-0.005Ht-0.319S, VE max/$m^2$(L/min)=58.161+1.503ET-0.315A-9.871S or VE max/$m^2$(L/min)=47.873+6.548 $FEV_1$-5.715 S, and VT max(L)=1.497+0.223VC-0.493S. Conclusion: Respiratory gas exchange and ventilatory variables at maximal exercise were studied in 1,000 non-athletes by Bruce protocol. During exercise, the subjects were allowed to hold on to hand rail of the treadmill for safety purpose. We feel that our results would provide ideal target values for patients and healthy individuals to be achieved, since our study subjects were members of a health center whose physical fitness levels were presumably higher than ordinary population.