• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.6
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• pp.125-132
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• 2017

Generally, in machining operations, the required machining performance can be obtained by properly combining several machining parameters properly. In this research, we construct a simulation model, which that predicts the relationship between the input variables and output variables in the turning operation. Input variables necessary for the turning operation include cutting speed, feed, and depth of cut. Surface roughness and electrical current consumption are used as the output variables. To construct the simulation model, an Artificial Neural Network (ANN) is employed. With theIn ANN, training is necessary to find appropriate weights, and the Ant Colony Optimization (ACO) technique is used as a training tool. EspeciallyIn particular, for the continuous domain, ACOR is adopted and athe related algorithm is developed. Finally, the effects of the algorithm on the results are identified and analyzsed.

• Quality Improvement in Health Care
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• v.27 no.2
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• pp.83-93
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• 2021

Purpose: This study tested the effectiveness of brochure- and video-based education on managing surgical site infections by operating room health personnel. Methods: From April 20 to May 4, 2021, 34 operating room health personnel were subjected to training on surgical site infection management using brochures and educational videos. A survey was then conducted on knowledge, perception, and adherence regarding surgical site infection management. Results: After receiving training on surgical site infection management, the knowledge score increased significantly (15.15±2.09 vs.19.70±1.96, p<.001). However, the perception and adherence scores were already near perfect before the intervention and did not further increase after the intervention. Conclusion: It is necessary to develop and utilize continuous and substantive educational programs to improve perception and adherence of surgical site infection management.

• Educational Technology International
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• v.6 no.1
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• pp.3-39
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• 2005

Korea and Japan have been making a continuous effort to build information and communication technology (ICT) infrastructure in schools, and integrate ICT into curriculum by training teachers based on own ICT policies in education. ICT policy in education isparticularly diverse and challenging, in part because the rapid development of ICT continues to create new possibilities for use and demands the transformation of the ways we teach and learn. The present study is to analyze ICT policies of Korea and Japan, between 1980's and the present period, in a larger educational and historical context. The study reviews chronological changes in major streamlines of ICT policies of both countries, and discusses in detail changes in two aspects of ICT policies in education, that is, ICT infrastructure and teacher training. The paper points out convergence and diversity of ICT policies in two countries and concludes with a set of guidelines for ICT policy makers.

• Journal of the Korean Society for Library and Information Science
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• v.36 no.3
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• pp.311-330
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• 2002

A public librarian is an occupation, which requires long-term. continuous training and difficult study to acquire and cultivate professional knowledge and skills. It is a necessity to achieve new knowledge, information and skills via appropriate retraining. A training system is the method which gives chances of retraining to public librarians. After examining some of the problems with the existing training system, it is apparent that the direction of training system needs to be decentralized. That is each local branch should be autonomous in terms of new training for librarians. For the method of training system, each autonomous unit would integrate the different theories to apply to the community-at-large and invite practical specialists from the local community to lecture. The training classes would be elective in that the each librarian could choose the classes he/she wants to take and give them credits for that, but the certificate for the class would also go towards completion for the required technical training. Finally, the utilization of cyber-education should be introduced, and the library association's role strengthened, to help public librarians cultivate their specialties.

• The Journal of Korean Physical Therapy
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• v.30 no.5
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• pp.159-165
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• 2018

Purpose: The aims of this study were to determine if game-based training with constraint-induced movement therapy (CIMT) is effective in improving the balance ability in female patients with a total knee replacement, and to provide clinical knowledge of CIMT game-based training that allows the application of total knee replacement. Methods: Thirty-six patients who had undergone a total knee replacement were assigned randomly to CIMT game training (n=12), general game training (n=12), and self-exercise (n=12) groups. All interventions were conducted 3 times a week for 4 weeks. All patients used a continuous passive motion machine 5 times a week and 2 times a day for 4 weeks. The visual analog scale (VAS), muscle strength of knee flexion and extension, and range of motion (ROM) of knee flexion and extension were assessed, and the functional reach test (FRT), and timed up and go (TUG) test were performed to evaluate the balance ability. Results: All 3 groups showed significant improvement in the VAS, knee flexion and extension muscle strength, FRT, and TUG test after the intervention (p<0.05). Post hoc analysis revealed significant differences in FRT, and TUG of the CIMT game training group compared to the other group (p<0.05). Conclusion: Although the general game training and CIMT game training improved both the knee extension muscle strength and dynamic balance ability, CIMT game training had a larger effect on dynamic balance control.

• International Journal of Industrial Entomology and Biomaterials
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• v.3 no.2
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• pp.127-133
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• 2001

With an objective of evolving quantitatively and qualitatively superior bivoltine breeds/hybrids of silkworm Bombyx mori L. for tropical conditions, breeding work was initiated in Central Sericultural Research and Training Institute, Mysore during 1992 by utilizing two Japanese hybrids namely BNl8$\times$BCS25 and Shunrei$\times$Shogetsu along with Indian evolved breed, KA. The breed CSR12 which is characterized with sex-limited larval marking and white oval cocoons was evolved from the Japanese hybrid BNl8 ${\times}$ BCS25 by crossing with KA, while the breed CSR6 which is characterized with normal marking (marked larvae) and white dumbbell cocoons was extracted from the Japanese commercial hybrid Shunrei${\times}$Shogetsu through continuous inbreeding coupled with selection. After fixation, these breeds along with other newly evolved breeds were subjected to hybrid study under optimum environmental conditions in the laboratory for expression of full potential of the genotypes. These hybrids were evaluated by Multiple Trait Evaluation Index (Mano et al., 1993). The hybrid CSR12${\times}$CSR6 was selected based multiple trait evaluation index value. The hybrid CSR12$\times$CSR6 recorded survival of 96.0%, shell weight of 50.0 cg, shell ratio of 24.3%, raw silk percentage of 19.6, filament length of 1,216 m, boil off loss of 22.4% and renditta of 5.1. On the other hand, the control hybrid (KA ${\times}$ NB4D2) has recorded survival of 90.6%, shell weight of 42.1 cg, shell ratio of 20.4%, raw silk percentage of 15.9, filament length of 999 m, boil off loss of 24.8% and renditta of 6.3. The hybrid CSR12$\times$CSR6 was authorized during 1997 by Central Silk Board, Government of India for commercial exploitation during favourable months based on national level race authorization test.

• Archives of Plastic Surgery
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• v.49 no.2
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• pp.207-214
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• 2022

Background Fellowship training is becoming more popular in plastic surgery, with over half of residents pursuing advanced training. Here, we investigate how clinical and research fellowship training impacts career trajectory and scholastic achievement in academic plastic surgery. Methods Plastic surgery faculty members, from programs recognized by the American Council of Academic Plastic Surgeons, were identified using institutional Web sites. Data extracted included faculty demographics, training history, academic positions, and research productivity. Continuous and categorical variables were compared using t-tests and chi-square, respectively. Results In total, 949 faculty members were included, with 657 (69%) having completed fellowship training. Integrated program residents were more likely to complete a fellowship when compared with independent residents (p < 0.0001). Fellowship trained faculty were more likely to have graduated from a higher ranked residency program, in terms of both overall and research reputation (p = 0.005 and p = 0.016, respectively). When controlling for years in practice, there was no difference found in number of publications, Hirsch index (h-index), or National Institutes of Health funding between faculty between the two cohorts (p > 0.05). In a subanalysis comparing hand, craniofacial, microsurgery, and research fellowships, those who completed a research fellowship had higher h-indices and were more likely to reach full professor status (p < 0.001 and p = 0.001, respectively). Fellowship training had no effect on being promoted to Chief/Chair of departments (p = 0.16). Conclusion Fellowship training is common among academic plastic surgeons. In this study, both clinical and research fellowships were associated with various aspects of academic success. However, fellowship training alone did not affect attainment of leadership positions.

• MALSORI
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• no.64
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• pp.137-153
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• 2007

The pronunciation lexicon of a continuous speech recognition system should contain enough pronunciation variations to be used for building a search space large enough to contain a correct path, whereas the size of the pronunciation lexicon needs to be constrained for effective decoding and lower perplexities. This paper describes a procedure for selecting pronunciation variations to be included in the lexicon based on the frequencies of the corresponding phonetic rules observed in the training corpus. Likelihood of a phonetic rule's application is estimated using the observation frequency of the rule and is used to control the construction of a pronunciation lexicon. Experiments with various pronunciation lexica show that the proposed method is helpful to improve the speech recognition performance.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.1
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• pp.10-16
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• 2015

In this study, we suggest a method to predict probability distribution of a new customer's degree of loyalty using C-CRF that reflects the RFM score and similarity to the neighbors of the customer. An RFM score prediction model is introduced to construct the first feature function of C-CRF. Integrating demographical similarity, purchasing characteristic similarity and purchase history similarity, we make a unified similarity variable to configure the second feature function of C-CRF. Then parameters of each feature function are estimated and we train our C-CRF model by training data set and suggest a probabilistic distribution to estimate a new customer's degree of loyalty. An example is provided to illustrate our model.

• Journal of Multimedia Information System
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• v.9 no.2
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• pp.93-102
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• 2022

Dependency parsing is a decision problem of the syntactic relation between words in a sentence. Recently, deep learning models are used for dependency parsing based on the word representations in a continuous vector space. However, it causes a mislabeled tagging problem for the proper nouns that rarely appear in the training corpus because it is difficult to express out-of-vocabulary (OOV) words in a continuous vector space. To solve the OOV problem in dependency parsing, we explored the proper noun embedding method according to the embedding unit. Before representing words in a continuous vector space, we replace the proper nouns with a special token and train them for the contextual features by using the multi-layer bidirectional LSTM. Two models of the syllable-based and morpheme-based unit are proposed for proper noun embedding and the performance of the dependency parsing is more improved in the ensemble model than each syllable and morpheme embedding model. The experimental results showed that our ensemble model improved 1.69%p in UAS and 2.17%p in LAS than the same arc-eager approach-based Malt parser.