• Journal of KIISE:Software and Applications
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• v.27 no.2
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• pp.193-200
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• 2000

The extraction of face regions is required for Head Gesture Interface which is a natural user interface. Recently, many researchers are interested in using color information to detect face regions in image sequences. Two most widely used color models, HSI color model and YIQ color model, were selected for this study. Actually H-component of HSI and I-component of YIQ are used in this research. Given the difference in the color component, this study was aimed to compare the performance of face region detection between the two models. First, we search the optimum range of facial color for each color component, examining the detection accuracy of facial color regions for variant threshold range about facial color. And then, we compare the accuracy of the face box for both color models by using optimal facial color and motion information. As a result, a range of $0^{\circ}{\sim}14^{\circ}$ in the H-component and a range of $-22^{\circ}{\sim}-2^{\circ}$ in the I-component appeared to be the most optimum range for extracting face regions. When the optimal facial color range is used, I-component is better than H-component by about 10% in accuracy to extract face regions. While optimal facial color and motion information are both used, I-component is also better by about 3% in accuracy to extract face regions.

• International Area Studies Review
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• v.21 no.4
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• pp.223-245
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• 2017

This study is examined interaction between carbon market with stock market using a multivariate GARCH(DCC) model. Carbon market is EU ETS EUA price, stock market is the iron and cement stock price which has relatively energy intensive and massive carbon emissions sector in the industrial sector. It also analyzed changes in the correlation between the markets through an analysis of correlation coefficients. Moreover, it checked whether there was marketability expansion(or expansion of carbon emissions reduction) through the analysis above. As a result of empirical tests, it showed that the price spillover effect was insignificant. In addition, it represented that there was a weak correlation between the two markets since the volatility spillover effect disappeared in the second phase by an external shock(a financial crisis). Moreover, it was revealed that there were no significant changes although there was a weak upward trend in terms of the correlation between the carbon market and the stock market. This implies that emission rights could not expand marketability to financial market as a commodity(or did not play its natural role of the reduction of carbon emission).

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.10
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• pp.5011-5017
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• 2012

Background: Overexposure to sunlight in childhood and the adolescent period and associsated sunburns significantly increase the risk of skin cancer in adulthood. In Turkey, the incidence of skin cancer in the general population is 0.8%. The incidence is 0.6% and the mortality rate is 0.4% for men, while these rates are 1.0% and 0.7%, respectively, for women. If skin cancer is found early, its treatment is facilitated. Therefore, personal skin examination is important for early diagnosis. Objectives: Our aim was to determine the effects of training for raising consciousness among adolescents to protect against skin cancer by influencing skin self examination behavior. Method: This quasi experimental intervention study was conducted between February and April 2012 in Izmir. The study population consisted of students attending $6^{th}$, $7^{th}$ and $8^{th}$ classes of a primary school (n:302). No sampling was performed. Data were collected with a form developed by the researchers based on the literature. The first part of form is aimed to determine demographic characteristics of adolescents (3 questions) and their risk status of skin cancer (6 questions). The second part was prepared for skin cancer risks of adolescents (8 questions) and indications of skin cancer (12 questions). The last part was intended to determine their knowledge about skin self examination (4 questions) and behavioral stages of skin self examination (1 question). Data collection was achieved with a questionnaire form in three phases. In the 1st phase, data about demographic characteristics of students, risk status of skin cancer, knowledge level of skin cancer and behavior stages were collected. In the $2^{nd}$ phase, skin self examination training based on the transtheoretical model was performed within the same day just after obtaining preliminary data. In the $3^{rd}$ phase, adolescents were followed up three times to establish the efficacy of the training (on the $15^{th}$ day after training program and at end of the $1^{st}$ and $2^{nd}$ months). Follow-up data were evaluated by questioning skin self examination performing behavior stages through electronic mail. Results: Half of the adolescents (50.5%) are male, and 58.4% of them are 13 years old with a mean age of $12{\pm}1.15$ years. About 29.4% of adolescents had brown hair color, 37.9% had brown/hazel eye color, 29.4% had white skin, and 47.2% had fewer than 10 moles in their body. The pretest mean score on knowledge level about risks of skin cancer was found to be $4.19{\pm}1.96$, while the post-test mean score was $6.79{\pm}1.67$ (min:0, max:8).The pretest mean score about indications of skin cancer was $7.45{\pm}3.76$, while the post-test mean score was $10.7{\pm}2.60$ (min:0, max:12). The increases were statistically significant (p<0.05). The behavior "I do not perform skin self examination regularly in every month and I do not think to perform it in the next 6 months" was reduced from 52.8 to 35.5% after training. Conclusion: The training program organized to raise consciousness among adolescents for protection against skin cancer increased the knowledge level about risks and indications of skin cancer and it also improved the behavior of performing skin self examination.

• 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.

• Radiation Oncology Journal
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• v.23 no.1
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• pp.51-60
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• 2005

Purpose : Selective inhibition of multiple molecular targets may improve the antitumor activity of radiation. Two specific inhibitors of selective cyclooxygenase-2 (COX-2) and epidermal growth factor receptor (EGFR) were combined with radiation on the HeLa cell line. To investigate cooperative mechanism with selective COX-2 inhibitor and EGFR blocker, in vitro experiments were done. Materials and Methods : Antitumor effect was obtained by growth inhibition and apoptosis analysis by annexin V-Flous method. Radiation modulation effects were determined by the clonogenic cell survival assay. Surviving fractions at 2 Gy ($SF_2$) and dose enhancement ratio at a surviving fraction of 0.25 were evaluated. To investigate the mechanism of the modulation of radiosensitivity, the cell cycle analyses were done by flow cytometry. The bcl-2 and bax expressions were analyzed by western blot. Results : A cooperative effect were observed on the apoptosis of the HeLa ceil line when combination of the two drugs, AG 1478 and NS 398 with radiation at the lowest doses, apoptosis of $22.70\%$ compare with combination of the one drug with radiation, apoptosis of $8.49\%$. In cell cycle analysis, accumulation of cell on $G_0/G_l$ phase and decrement of S phase fraction was observed from 24 hours to 72 hours after treatment with radiation, AG 1478 and NS 398. The combination of NS 398 and AG 1478 enhanced radiosensitivity on a concentration-dependent manner in HeLa cells with dose enhancement ratios of 3.00 and $SF_2$ of 0.12 but the combination of one drug with radiation was not enhanced radlosensitivity with dose enhancement ratios of 1.12 and SF2 of 0.68 (p=0.005). The expression levels of bcl-2 and bax were reduced when combined with AG 1478 and NS 398. Conclusion : Our results indicate that the selective COX-2 inhibitor and EGFR blocker combined with radiation have potential additive or cooperative effects on radiation treatment and may act through various mechanisms including direct inhibition of tumor cell proliferation, suppression of tumor cell cycle progression and inhibition of anti-apoptotic proteins.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.73-92
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• 2014

An Adaptive Clustering-based Collaborative Filtering Technique was proposed to solve the fundamental problems of collaborative filtering, such as cold-start problems, scalability problems and data sparsity problems. Previous collaborative filtering techniques were carried out according to the recommendations based on the predicted preference of the user to a particular item using a similar item subset and a similar user subset composed based on the preference of users to items. For this reason, if the density of the user preference matrix is low, the reliability of the recommendation system will decrease rapidly. Therefore, the difficulty of creating a similar item subset and similar user subset will be increased. In addition, as the scale of service increases, the time needed to create a similar item subset and similar user subset increases geometrically, and the response time of the recommendation system is then increased. To solve these problems, this paper suggests a collaborative filtering technique that adapts a condition actively to the model and adopts the concepts of a context-based filtering technique. This technique consists of four major methodologies. First, items are made, the users are clustered according their feature vectors, and an inter-cluster preference between each item cluster and user cluster is then assumed. According to this method, the run-time for creating a similar item subset or user subset can be economized, the reliability of a recommendation system can be made higher than that using only the user preference information for creating a similar item subset or similar user subset, and the cold start problem can be partially solved. Second, recommendations are made using the prior composed item and user clusters and inter-cluster preference between each item cluster and user cluster. In this phase, a list of items is made for users by examining the item clusters in the order of the size of the inter-cluster preference of the user cluster, in which the user belongs, and selecting and ranking the items according to the predicted or recorded user preference information. Using this method, the creation of a recommendation model phase bears the highest load of the recommendation system, and it minimizes the load of the recommendation system in run-time. Therefore, the scalability problem and large scale recommendation system can be performed with collaborative filtering, which is highly reliable. Third, the missing user preference information is predicted using the item and user clusters. Using this method, the problem caused by the low density of the user preference matrix can be mitigated. Existing studies on this used an item-based prediction or user-based prediction. In this paper, Hao Ji's idea, which uses both an item-based prediction and user-based prediction, was improved. The reliability of the recommendation service can be improved by combining the predictive values of both techniques by applying the condition of the recommendation model. By predicting the user preference based on the item or user clusters, the time required to predict the user preference can be reduced, and missing user preference in run-time can be predicted. Fourth, the item and user feature vector can be made to learn the following input of the user feedback. This phase applied normalized user feedback to the item and user feature vector. This method can mitigate the problems caused by the use of the concepts of context-based filtering, such as the item and user feature vector based on the user profile and item properties. The problems with using the item and user feature vector are due to the limitation of quantifying the qualitative features of the items and users. Therefore, the elements of the user and item feature vectors are made to match one to one, and if user feedback to a particular item is obtained, it will be applied to the feature vector using the opposite one. Verification of this method was accomplished by comparing the performance with existing hybrid filtering techniques. Two methods were used for verification: MAE(Mean Absolute Error) and response time. Using MAE, this technique was confirmed to improve the reliability of the recommendation system. Using the response time, this technique was found to be suitable for a large scaled recommendation system. This paper suggested an Adaptive Clustering-based Collaborative Filtering Technique with high reliability and low time complexity, but it had some limitations. This technique focused on reducing the time complexity. Hence, an improvement in reliability was not expected. The next topic will be to improve this technique by rule-based filtering.

• KSBB Journal
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• v.14 no.1
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• pp.82-90
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• 1999

In order to eventually fabricate an analytical system for infectious microorganisms, we synthesized major immunochemical components, utilized them for the construction of model system, and investigated an assay concept for bacterial whole cells. For the preparation of system components, a polyclonal antibody, against Salmonella thompson as model analyte, purified by immuno-affinity chromatography was used to chemically link to streptavidin or an enzyme, horseradish peroxidase(HRP). The antibody and streptavidin was modified with sulfosuccinimidyl 4-[N-maleimidomethyl]cyclohexane-1-carboxylate and N-succinimidyl-3-[2-pyridyldithio]propionate(subsequently activated by dithiotheritol), respectively. The modified components were reacted to synthesize antibody-streptavidin conjugates which were then purified on a two-layer chromatography column of diaminobiotin gel and Sephadex G-100. For antibody-HRP conjugates, HRP molecules were activated by $NalO_4$ oxidation and then coupled to immunoglobulin. After stabilizing with ($NaCNBH_3$, the conjugates were purified by size exclusion chromatography on Biogel A5M column. To devise a model system, such produced components were combined with a dot-blotter in which a nitrocellulose membrane($12{\mu}m$ pre size) with immobilized biotin was already located. The analyte (S. thompson cells) was reacted with the both antibody conjugates in a liquid phase, and the complexes formed were captured on the membrane surfaces by applying vacuum in the bottom compartment of the blotter to invoke biotin-streptavidin reaction. Under optimal conditions, the system enabled to identify the analytical concept for bacterial whole cells, and the lower limit of detection was approximately $1{\mu}g/m{\ell}$($10^5-10^6$ cells/m$m{\ell}$). The controlling factors were the concentrations of each antibody conjugate that caused agglutination in the presence of analyte as they increased.

• Agribusiness and Information Management
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• v.3 no.2
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• pp.43-62
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• 2011

The goal of this study is to determine, based on survey results, the underlying factors that affect the intention of the farmers who have not adopted the Hazard Analysis and Critical Control Points (HACCP) system for the rearing phase of pig production to adopt this system in the future. The research model for this study was con structed based on strategic contingency theory, the theory of the diffusion of innovation, and the technology acceptance model (TAM). Using structural equation modeling with partial least squares (PLS), this study analyzes the effects of the intensity of competition, the environmental uncertainty, the innovativeness and self-efficacy of the individual farmers, and the impact of the credibility of the Agricultural Technology Service Center (ATSC), which acts as the principal agent of technology dissemination and as a leader of change, on the perceived usefulness of technology and the farmers' intention to adopt the system. The results of the analysis are as follows. First, with regard to the underlying factors affecting the intention to adopt the new system, the intensity of competition within the industry and the institutional credibility of the ATSC were inferred to underlie the perceived usefulness. Second, institutional credibility has a positive impact on the perceived usefulness of the system, and the perceived usefulness, in turn, has a positive impact on the intention to adopt. The perceived ease of use also has a positive impact on the intention to adopt. Because the factor that has the biggest impact on the intention of a farm to adopt is the credibility of the ATSC, it is crucial for extension organizations, such as the ATSC, to make greater efforts to promote the expansion of the HACCP system. Because farmers feel that the implementation of the HACCP system is an instrumental strategy for coping with the high intensity of competition within the industry, they attempt to gain a competitive edge through the production of safe livestock products.

• Journal of the Korea Society for Simulation
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• v.15 no.2
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• pp.59-69
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• 2006

Component-based software development is introduced as a new development paradigm in software development method. This approach is different from existing software development approach because it is based on reusable and autonomous unit, component. Therefore, component-based development(CBD)is divided into two stages; component development process and component assembly process; application development process. Component development process is the core of CBD because component has a key for good software. Currently many methodologies or tools have been introduced by various academies or industries. However, those don't suggest systematic and flexible modeling techniques adaptable easily into component development project. Existing approaches have a unique orarbitrary modeling technique or provide heuristic guidelines for component modeling. As a result, many component developers are faced with a difficult problems; how to developcomponent models, when develop which diagrams, and so on. In order to address this problem, we suggest a meta-model driven approach for component development in this paper. We provide meta-models according to both layer and development phase. We expect that suggested meta-models allow component developers to develop appropriate models of the time.

• Journal of Physiology & Pathology in Korean Medicine
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• v.20 no.6
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• pp.1636-1648
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• 2006

There are detailed descriptions of the clinical experiences and prescriptions of asthma in traditional Korean medicine. Zedoariae rhizoma is one of the Korean herbal medicines used to treat bronchial asthma and allergic rhinitis for centuries. However, the therapeutic mechanisms of this medication are still far from clear, In this study, a house-dust-mite (Dermatophagoides pteronyssinus [Der p])-sensitized murine model of asthma was used to evaluate the immunomodulatory effect of Zedoariae rhizoma on the allergen-induced airway inflammation in asthma. Three different protocols were designed to evaluate the treatment and/or long-term prophylacitic effect of Zedoariae rhizoma in Der p-sensitized mice. Cellular infiltration and T-cell subsets in the bronchoalveolar lavage fluid (BALF)of allergen-challenged mice were analyzed. Intrapulmonary lymphocytes were also isolated to evaluate their response to allergen stimulation. When Zedoariae rhizoma was administered to the sensitized mice before AC (groups A and C), it suppressed airway inflammation by decreasing the number of total cells and eosinophil infiltration in the BALF, and downregulated the allergen- or mitogen-induced intrapulmonary lymphocyte response of sensitized mice as compared to those of controls. This immunomodulatory effect of Zedoariae rhizoma may be exerted through the regulation of T-cell subsets by elevation or activation of the CD8+ and double-negative T-cell population in the lung. However, the administration of Zedoariae rhizoma to sensitized mice 24 h after AC (group B) did not have the same inhibitory effect on the airway inflammation as Zedoariae rhizoma given before AC. Thus, the administration of Zedoariae rhizoma before AC has the immunomodulatory effect of reducing bronchial inflammation in the allergen-sensitized mice. On the other hand, to determine the potentiality of prophylactic and/or therapeutic approaches using a traditional herbal medicine, Zedoariae rhizoma, for the control of allergic disease, we examined the effects of oral administration of Zedoariae rhizoma on a murine model of asthma allergic responses. When oral administration of Zedoariae rhizoma was begun at the induction phase immediately after OVA sensitization, eosinophilia and Th2-type cytokine production in the airway were reduced in OVA-sensitized mice following OVA inhalation. These results suggest that the oral administration of Zedoariae rhizoma dichotomously modulates allergic inflammation in murine model for asthma, thus offering a different approach for the treatment of allergic disorders.