• International Journal of Concrete Structures and Materials
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• v.6 no.3
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• pp.177-186
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• 2012

The temperature distributions of concrete structures strongly depend on the value of thermal conductivity of concrete. However, the thermal conductivity of concrete varies according to the composition of the constituents and the temperature and moisture conditions of concrete, which cause difficulty in accurately predicting the thermal conductivity value in concrete. For this reason, in this study, back-propagation neural network models on the basis of experimental values carried out by previous researchers have been utilized to effectively account for the influence of these variables. The neural networks were trained by 124 data sets with eleven parameters: nine concrete composition parameters (the ratio of water-cement, the percentage of fine and coarse aggregate, and the unit weight of water, cement, fine aggregate, coarse aggregate, fly ash and silica fume) and two concrete state parameters (the temperature and water content of concrete). Finally, the trained neural network models were evaluated by applying to other 28 measured values not included in the training of the neural networks. The result indicated that the proposed method using a back-propagation neural algorithm was effective at predicting the thermal conductivity of concrete.

• Physical Therapy Korea
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• v.12 no.2
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• pp.37-43
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• 2005

The purpose of this study was to examine the effects of static stretching and Evjenth-Hamberg stretching the on range of motion (ROM) of the knee joint. The subjects were composed of twenty healthy males without weight-training experience. The ROM of the knee joint was measured by using an En-Knee. Three tests (performed on the 1st week, 4th week, and 8th week) were conducted to examine the change of each variable. Data were analyzed with a $2{\times}3$ analysis of variance (group${\times}$test) for repeated measures on last factor through SPSS 10.0. The data analysis revealed the change in the ROM was dependent on the stretching method. The results were as follows: The ROM was improved in both methods by each time, but the E-HS was more improved than the SS. In conclusion, this study indicated that the E-HS is more efficient than the SS on the ROM of the knee joint.

• Journal of the Korean Society of Physical Medicine
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• v.15 no.1
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• pp.1-9
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• 2020

PURPOSE: Many patients with stroke have difficulties in walking with foot-drop. Various types of ankle-foot orthoses (AFOs) have been developed, but their weight needs to be reduced with the assistance of the ankle dorsiflexor. Therefore, an elastic AFO (E-AFO) was devised that not only improves the stability and flexibility of the ankle but also assists with ankle dorsiflexion while walking. This study examined the effects of an E-AFO, on the walking patterns of foot-drop patients with stroke. METHODS: Fourteen patients walked with and without an E-AFO, and the gait parameters were assessed using the GAITRite system. The spatiotemporal data on the gait patterns of stroke patients with foot-drop were compared using paired t-tests; the level of statistical significance was set to α<.05. RESULTS: No significant differences were observed in the velocity (p=.066) and affecte+d step length (p=.980), but the affected and less-affected stance (p=.022, p=.002) and swing time (p=.012, p=.005) were significantly different. The E-AFO produced a significant difference in the less-affected step length (p=.032). CONCLUSION: The E-AFO has a significant effect on the walking patterns of individuals with foot-drop and stroke. The E-AFO could be a useful assistive device for gait training in stroke patients.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1531-1536
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• 2011

We propose an automatic swearword filter system for online game chatting by using Support Vector Machines(SVM). We collected chatting sentences from online games and tagged them as normal sentences or swearword included sentences. We use n-gram syllables and lexical-part of speech (POS) tags of a word as features and select useful features by chi square statistics. Each selected feature is represented as binary weight and used in training SVM. SVM classifies each chatting sentence as swearword included one or not. In experiment, we acquired overall 90.4% of F1 accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.6
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• pp.1213-1220
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• 2011

In this paper, a new ensemble system using dynamic weighting method with added weight information into classifiers is proposed. The weights used in the traditional ensemble system are those after the training phase. Once extracted, the weights in the traditional ensemble system remain fixed regardless of the test data set. One way to circumvent this problem in the gating networks is to update the weights dynamically by adding processes making architectural hierarchies, but it has the drawback of added processes. A simple method to update weights dynamically, without added processes, is proposed, which can be applied to the already established ensemble system without much of the architectural modification. Experiment shows that this method performs better than AdaBoost.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.4
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• pp.767-778
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• 2003

This paper presents a method for generating optimal fuzzy rules using a genetic algorithm. Fuzzy rules are generated from the training data in the first stage. In this stage, fuzzy c-Means clustering method and cluster validity are used to determine the structure and initial parameters of the fuzzy inference system. A cluster validity is used to determine the number of clusters, which can be the number of fuzzy rules. Once the structure is figured out in the first stage, parameters relating the fuzzy rules are optimized in the second stage. Weights and variance parameters are tuned using genetic algorithms. Variance parameters are also managed with left and right for asymmetrical Gaussian membership function. The method ensures convergence toward a global minimum by using genetic algorithms in weight and variance spaces.

• Fashion & Textile Research Journal
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• v.15 no.4
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• pp.554-564
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• 2013

We provide an empirical assessment that examines the differences in appearance management behavior, life satisfaction and demographic variables between groups classified by individual lifestyle. Questionnaires were administered to 513 female and male adults over 17 years of age in the Daegu and Kyungbok metropolitan regions. Descriptive statistics, cluster analysis, Cronbach's ${\alpha}$, ANOVA, Duncan test and ${\chi}^2$ test were applied to analyze data from 513 respondents. The results are as follows. First, we did a cluster analysis on the appearance management behavior of weight training, skin care, hair care, make-up and clothing selection. Four groups (passive, rational, fashion oriented, and active typed) where classified according to individual lifestyle. Second, the rational and active groups were more interested in the social life, environmental stability, health, fashion and economic seeking life. They were also more involved in appearance management behavior and in a higher level of life satisfaction. However, the differences of life satisfaction among the lifestyle group (male) were not statistically significant. Third, females with higher level of income and education (among the demographic variables) belonged to the active group. We found significant differences in appearance management behavior, life satisfaction and demographic variables among male and female groups classified by lifestyle.

• Journal of Mechanical Science and Technology
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• v.18 no.6
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• pp.904-914
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• 2004

The fiber reinforced composite material is widely used in the multi-industrial field because of their high specific modulus and specific strength. It has two main merits which are to cut down energy by reducing weight and to prevent explosive damage proceeding to the sudden bursting which is generated by the pressure leakage condition. Therefore, Pressure vessels using this composite material can be applied in the field such as defence industry and aerospace industry. In this paper, for nonlinear finite element analysis of E-glass/epoxy filament winding of composite vessel subjected to internal pressure, the standard interpretation model is developed by using the ANSYS with AutoLISP and ANSYS APDL languages, general commercial software, which is verified as useful characteristic of the solution. Among the modules of the system, both the process planning module for carrying out the process planning of filament wound composite pressure vessel and the autofrettage process module for obtaining higher residual stress will minimize trial and error and reduce the period for developing new products. The system can serve as a valuable system for experts and as a dependable training aid for beginners.

• Journal of the Korean Society of Clothing and Textiles
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• v.38 no.4
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• pp.528-539
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• 2014

This study analyzed the influence of self-construal on sociocultural attitude toward physical appearance, body satisfaction, and appearance management behavior through a structural equation model. The empirical study was based on the response of 369 adult females between the ages of 20 and 49 in Seoul. Self-construal was presented as an independent self-construal and interdependent self-construal, respectively. The sociocultural attitude toward physical appearance as an intermediate variable in the research model was composed of two sub-factors that included internalization and awareness. The other (body satisfaction) was measured by two factors (body and face). Appearance management behavior (as a final outcome variable) were composed of various factors that included clothing concern, skin care, hair care, and weight training. The findings of this study were: 1) the effect of independent self-construal on the sociocultural attitude toward physical appearance was not significantly meaningful; however, interdependent self-construal influenced it positively. 2) Sociocultural attitude toward physical appearance appeared to have a negative effect on body satisfaction. 3) The body satisfaction also had a negative effect on appearance management behavior in this study.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.364-380
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• 2016

The most popular approach in object classification is based on the bag of visual-words model, which has several fundamental problems that restricting the performance of this method, such as low time efficiency, the synonym and polysemy of visual words, and the lack of spatial information between visual words. In view of this, an object classification based on weakly supervised E2LSH and saliency map weighting is proposed. Firstly, E2LSH (Exact Euclidean Locality Sensitive Hashing) is employed to generate a group of weakly randomized visual dictionary by clustering SIFT features of the training dataset, and the selecting process of hash functions is effectively supervised inspired by the random forest ideas to reduce the randomcity of E2LSH. Secondly, graph-based visual saliency (GBVS) algorithm is applied to detect the saliency map of different images and weight the visual words according to the saliency prior. Finally, saliency map weighted visual language model is carried out to accomplish object classification. Experimental results datasets of Pascal 2007 and Caltech-256 indicate that the distinguishability of objects is effectively improved and our method is superior to the state-of-the-art object classification methods.