• Clinics in Shoulder and Elbow
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• v.12 no.1
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• pp.53-60
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• 2009

Purpose: Primary osteoarthritis on the elbow is the result of the growth of osteophytes and contracture of the capsule. It often causes disability on joint motion and pain while exercising. As arthroscopy has developed, the arthroscopic diagnosis and treatment of the elbow have recently become more generalized as well. Therefore, we like to report on arthroscopy for treating elbow arthritis and its results. Materials and Methods: This study includes 23 cases of elbow arthritis that were seen between 2005 June to 2007 June and these patients didn't response to conservative treatment. From this we excluded 18 cases that underwent arthroscopic surgery and among these 18 cases, 6 cases underwent ulnar nerve transfer. The average observation time was 21.3 months and the average age was 48.4 years (range: 22-66 years). The pre and post operative pain was evaluated with using the Visual Analogue Scale (VAS) and functional evaluation was done with using the Mayo elbow Performance Score (MEPS) with the range of joint motion. Results: The VAS score at the last follow up was significantly decreased from 3.4 to 1.9 compare to the preoperative score. The range of joint motion was improved by 25 (0-40) to 8.5 (0-20) in extension and 101.7 (80-140) to 125.2 (85-140) in flexion (p<0.05). The MEPS always showed significant improvement by showing an increase from 65.4 (40-85) to 87.9 (55-100). However, 3 cases showed a decreased range of motion after the operation. One case showed ulnar nerve symptoms after surgery. Conclusion: An arthroscopic procedure can treat the pathologic processes associated with arthritis of the elbow and it was safe and effective in this series.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.62 no.4
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• pp.333-345
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• 2017

The potato tuber is known as a rich source of essential nutrients, used throughout the world. Although potato-breeding programs share some priorities, the major objective is to increase the genetic potential for yield through breeding or to eliminate hazards that reduce yield. Glycoalkaloids, which are considered a serious hazard to human health, accumulate naturally in potatoes during growth, harvesting, transportation, and storage. Here, we used the AMMI (additive main effects and multiplicative interaction) and GGE (Genotype main effect and genotype by environment interaction) biplot model, to evaluate tuber yield stability and glycoalkaloid content in six potato cultivars across three locations during 2012/2013. The environment on tuber yield had the greatest effect and accounted for 33.0% of the total sum squares; genotypes accounted for 3.8% and $G{\times}E$ interaction accounted for 11.1% which is the nest highest contribution. Conversely, the genotype on glycoalkaloid had the greatest effect and accounted for 82.4% of the total sum squares), whereas environment and $G{\times}E$ effects on this trait accounted for only 0.4% and 3.7%, respectively. Furthermore, potato genotype 'Superior', which covers most of the cultivated area, exhibited high yield performance with stability. 'Goun', which showed lower glycoalkaloid content, was the most suitable and desirable genotype. Results showed that, while tuber yield was more affected by the environment, glycoalkaloid content was more dependent on genotype. Further, the use of the AMMI and GGE biplot model generated more interactive visuals, facilitated the identification of superior genotypes, and suggested decisions on a variety of recommendations for specific environments.

• Cartoon and Animation Studies
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• s.36
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• pp.237-257
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• 2014

This study is the process of performing the interdisciplinary fusion study between multiple fields by identifying the status on the previous artistic education considering the brain scientific mechanism of image creativity and brain-based learning principles. In recent years, producing the educational methods of each field as the fusion study activities are emerging as the trend and thanks to such, the results of brain-based educational fusion studies are being presented for each field. It includes artistic fields such as music, art and dance. In other words, the perspective is that by understanding the operating principles of the brain while creativity and learning is taking place, when applying various principles that can develop the corresponding functions as a teaching method, it can effectively increase the artistic performance ability and creativity. Since the animation drawing should be able to intuitively recognize the elements of movement and produce the communication with the target beyond the delineative perspective of simply drawing the objects to look the same, it requires the development of systematic educational method including the methods of communication, elements of higher cognitive senses as well as the cognitive perspective of form implementation. Therefore, this study proposes a literature study results on the artistic education applied with brain-based principles in order to design the educational model considering the professional characteristics of animation drawing. Therefore, the overseas and domestic trends of the cases of brain-based artistic education were extracted and analyzed. In addition, the cases of artistic education studies applied with brain-based principles and study results from cases of drawing related education were analyzed. According to the analyzed results, the brain-based learning related to the drawing has shown a common effect of promoting the creativity and changes of positive emotion related to the observation, concentration and image expression through the training of the right brain. In addition, there was a case of overseas educational application through the brain wave training where the timing ability and artistic expression have shown an enhancement effect through the HRV training, SMR, Beta 1 and neuro feedback training that strengthens the alpha/seta wave and it was proposing that slow brain wave neuro feedback training contributes significantly in overcoming the stress and enhancing the creative artistic performance ability. The meaning of this study result is significant in the fact that it was the case that have shown the successful application of neuro feedback training in the environment of artistic live education beyond the range of laboratory but the use of the machine was shown to have limitations for being applied to the teaching methods so its significance can be found in providing the analytical foundation for applying and designing the brain-based learning principles for future animation drawing teaching methods.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• Journal of the Korean Institute of Landscape Architecture
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• v.45 no.2
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• pp.109-123
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• 2017

Due to the positive effect of forest space for child development, the creation and operation of forest activity space of various organizations is increasing in quantity; however, the research on practical space design and management program is insufficient. Therefore, the purpose of this study is to evaluate the space and management programs of the forest experience centers through the post-occupancy evaluation of teachers and preschoolers participating in forest activities. To do this, we analyzed the selected twelve sites through field survey, class observation, and interviews with forest education specialists, and then surveyed 115 forest education experts and childcare teachers for importance, performance, overall satisfaction, and space preference. In addition, we accessed overall satisfaction and space preference of twenty-nine preschoolers through interviews, photo-simulation, and questionnaires. As a result, the importance and performance of management program area was rated higher than the spatial characteristics area. In terms of group comparison, the group with active structured program rated two areas higher than the groups with free play. Preschoolers with structured programs preferred facility space, but preschoolers with free play preferred nature. Two preschooler groups rated forest activity as satisfactory. Based on the analysis results: 1) The composition of the forest activity space should ensure accessibility, safety, diversity of diversity, water space, connect to the forest road, and secure various terrains, trees, and natural materials; 2) The management program should ensure that forest activity programs have the proportional balance of structural programs and free play; also. management programs should plan for sufficient free playtime and a high share of play in the forest; and 3) Ensure the role and expertise of forestry specialists and run a program to increase the autonomy of preschoolers.

• The KIPS Transactions:PartA
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• v.13A no.2 s.99
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• pp.123-136
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• 2006

The prefetching technique is an effective way to reduce the latency caused memory access. However, excessively aggressive prefetch not only leads to cache pollution so as to cancel out the benefits of prefetch but also increase bus traffic leading to overall performance degradation. In this thesis, a prefetch filtering scheme is proposed which dynamically decides whether to commence prefetching by referring a filtering table to reduce the cache pollution due to unnecessary prefetches In this thesis, First, prefetch hashing table 1bitSC filtering scheme(PHT1bSC) has been shown to analyze the lock problem of the conventional scheme, this scheme such as conventional scheme used to be N:1 mapping, but it has the two state to 1bit value of each entries. A complete block address table filtering scheme(CBAT) has been introduced to be used as a reference for the comparative study. A prefetch block address lookup table scheme(PBALT) has been proposed as the main idea of this paper which exhibits the most exact filtering performance. This scheme has a length of the table the same as the PHT1bSC scheme, the contents of each entry have the fields the same as CBAT scheme recently, never referenced data block address has been 1:1 mapping a entry of the filter table. On commonly used prefetch schemes and general benchmarks and multimedia programs simulates change cache parameters. The PBALT scheme compared with no filtering has shown enhanced the greatest 22%, the cache miss ratio has been decreased by 7.9% by virtue of enhanced filtering accuracy compared with conventional PHT2bSC. The MADT of the proposed PBALT scheme has been decreased by 6.1% compared with conventional schemes to reduce the total execution time.

• Korean Journal of Poultry Science
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• v.7 no.1
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• pp.31-42
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• 1980

In order to identify the best superior cross combination of breeder stocks for broiler production, combining ability test and analyses of phenotypic performances for parent stocks were examined on records of 1,440 broiler chicken which were produced from 4 parental strains and 3 maternal strains at Hanhyup Poultry Breeding Farm from September 28, 1978 to January 5, 1979. The results obtained were as follows; 1. There was not found heterosis effect in viability but it seems to be desirable to select Hubbard strain in paternal line to improve viability. 2. As the paternal and maternal lines, selection of Ross strain showed the best paternal and maternal performance and the best general combining ability in body weight at 8 weeks of age is expected to be able to improve body weight of it s crossbred And the most superior cross combinations based on the specific combining ability and performance of rack crossbred were identified as Hubbard x Ross ana Ross x Hypeco crossbreds. 3. The best paternal and maternal lines on the smallest feed consumption for 8 weeks were Hubbard and Ross strains, and Hypeco strain, respectively. Especially Hubbard x Hypeco cross combination was proved as the smallest feed consumption compared with other cross combinations. 4. In feed requirement per Kg body weight increase, Hubbard strain for paternal line, Hypeco strain for naternal line, and cross combinations of Hubbard x Hypeco, Hubbard x Ross and Ross x Hypeco were certified as the most superiors. 5. Also superior cross combinations of Hubbard x Hypeco and Hubbard x Ross earned the most profit per bird through economic analysis. According to results as shown above, this experiment seems to be able to reach a such conclusion that production of superior cross combinations Hubbard x Ross, Hubbard x Hypeco and Ross x Hypeco through selection of Ross and Hubbard strains to paternal line and Hypeco and Ross strains for maternal line may become to considerable improvement for important economic characters of broiler; viability, body weight, feed consumption and feed requirement.

• Journal of Korean Society of Forest Science
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• v.90 no.1
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• pp.43-54
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• 2001

Genetic differentiation of populations is resulted from the environmental and the genetic effects, and the interactions between them. Whereas, the major factors influencing to the genetic differentiation within populations are the gene flow induced by seed or pollen dispersial, the microsite heterogeneity, and the density-dependent distribution of individuals. For the purpose of studying spatial genetic structure and the distribution pattern of Korean pines(Pinus koraiensis), we set up one $100{\times}100m$ plot at a Korean pine stand in Quercus mongolica community on Mt. Jumbong in Korea. To estimate the coefficient of spatial autocorrelation as Moran's index and an analogue, simple block distance, isozyme markers were analyzed in 325 Korean pines. For 11 polymorphic loci observed in 9 enzyme systems, the average percentage of polymorphic loci, the observed and expected heterozygocity were 72.2% 0.200, and 0.251, respectively. It was revealed the excess of homozygotes was observed in the plot, which suggests that here may be more number of consanguineous trees than expected. On the basis of isozyme genotypes observed in this study, 325 trees were classified into 147 groups in which the maximum number of trees for one group was 34. From the distance class of 24-32m, the genetic heterogeneity began to increase. The variation of simple block distance against the growth performance by tree height and diameter also showed the same trend at 24~32m class. According to high fixation index(F=0.204), the spatial genetic structure within a stand, the analysis of the growth performance, and the distribution patterns of identical genotypes, we inferred that the genetic structure of a Korean pine stand in Mt. Jumbong has been maintained rather density-dependent mechanism than the gene flow, such as the pollen dispersial or the heavy input of seeds following the forest gaps. The genetic patchy size was determined between 24~32m, which suggests that the selection of individuals for the ex situ conservation of Korean pine in Mt. Jumbong may be desirable to be made with the spatial distance over 37 meters between trees.

• 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.

• Journal of Korean Society of Forest Science
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• v.110 no.3
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• pp.322-340
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• 2021

Due to climate change and its consequential spring temperature rise, flowering time of Robinia pseudoacacia has advanced and a simultaneous blooming phenomenon occurred in different regions in South Korea. These changes in flowering time became a major crisis in the domestic beekeeping industry and the demand for accurate prediction of flowering time for R. pseudoacacia is increasing. In this study, we developed and compared performance of four different models predicting flowering time of R. pseudoacacia for the entire country: a Single Model for the country (SM), Modified Single Model (MSM) using correction factors derived from SM, Group Model (GM) estimating parameters for each region, and Local Model (LM) estimating parameters for each site. To achieve this goal, the bloom date data observed at 26 points across the country for the past 12 years (2006-2017) and daily temperature data were used. As a result, bloom dates for the north central region, where spring temperature increase was more than two-fold higher than southern regions, have advanced and the differences compared with the southwest region decreased by 0.7098 days per year (p-value=0.0417). Model comparisons showed MSM and LM performed better than the other models, as shown by 24% and 15% lower RMSE than SM, respectively. Furthermore, validation with 16 additional sites for 4 years revealed co-krigging of LM showed better performance than expansion of MSM for the entire nation (RMSE: p-value=0.0118, Bias: p-value=0.0471). This study improved predictions of bloom dates for R. pseudoacacia and proposed methods for reliable expansion to the entire nation.