• Title/Summary/Keyword: scaling training

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Structural effects on stock price forecasting

  • Kim, Steven H.;Kang, Dae-Suk
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1996.10a
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    • pp.207-210
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    • 1996
  • Learning methodologies such as neural networks or genetic algorithms usually require long training times. Case based reasoning, however, attains peak performance swiftly and is often appropriate for learning even with small data sets. Previous work has shown that an extended case reasoning methodology can yield superior performance in the task of predicting financial data series. This paper examines the impact of reasoning procedures on stock price prediction. The following characteristics are evaluated: size of input vector, multiplicity of neighboring states, and a scaling factor for growth. The concepts are illustrated in the context of predicting the price of an individual price.

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Comparative Analysis of Dental Hygiene Course Students' NCS Learning Goals before and after NCS Class

  • Woo, Hee-Sun
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.3
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    • pp.79-84
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    • 2018
  • The government developed National Competency Standards and expands field friendly education for innovation of industrial field based education training. NCS is the national level of standards that the government systemized knowledge, skills and attitudes required to work in industrial fields by each industry and each level. This study was intended to research NCS education contents of an introduction of dental hygienics, which is a basic major subject among subjects of dental hygiene course, to present learning goals accordingly, and to be used as a basic resource of NCS field oriented classes of dental hygienists through the comparison before and after. In case of the dental hygiene course, dental hygienists are performing important core tasks as clinicians at dental offices. Therefore, such comprehensive and professional performance abilities as scaling, oral prophylaxis and oral health education are required at the fields. The education process and education contents for this should be researched continuously.

A Study on Estimation of Human Damage for Shock Wave by Vapor Cloud Explosion using Probit Model (Probit 모델에 의한 증기운폭발 충격파의 인체피해예측)

  • Leem, Sah-Wan;Huh, Yong-Jeong;Lee, Jong-Rark
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.31 no.11
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    • pp.936-941
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    • 2007
  • This paper is on the influence of gas explosion caused by Vapor Cloud Explosion(VCE). Also, it is to understand the influence of the booth for explosion experiment which is installed to let the trainees for legal education which is managed by IGTT(Institute or Gas Technology Training) know the riskiness of explosion. In this study, the influence of explosion shock wave caused by VCE in enclosure was calculated by using the Hopkinson's scaling law and the accident damage was estimated by applying the influence on the adjacent human into the probit model. As a result of the damage estimation conducted by using the probit model, both the damage possibility of explosion overpressure to human 8 meters away and that of shock wave to hurt 15 meters away showed nothing.

Principles and Methodologies for STI Strategy Development: Experience and Best Practices from the Republic of Korea

  • Lee, Jeong Hyop
    • Asian Journal of Innovation and Policy
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    • v.7 no.3
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    • pp.411-437
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    • 2018
  • This paper articulates the STI strategy development principles and methodologies that have been elaborated through iterative processes of STI strategy development cases for the past ten years. The consultation cases include poverty traps in Nepal and Laos, African health challenges in Nigeria and Tanzania, and ASEAN global challenges in Indonesian Water, Vietnamese Green Energy, and Filipino Food, in partnership with some multilateral agencies.The iterative elaboration process has continued with consultation activities on Thailand and on Cambodia, Laos and Myanmar in planning partnership with Thailand. The principles were originally conceptualized from the benchmarking process of the Korean STI development experience. They were further incorporated as methodologies with which relevant planning bodies are guided to address individual and regional challenges through science, technology and innovation strategies. The methodologies are strong in providing plausible holistic perspective scenarios by which various stakeholders can be engaged in the planning and implementation process. But it is heuristic in nature and can be learned only through on-the-job training process. This is the structural limitation for scaling up.

Precise segmentation of fetal head in ultrasound images using improved U-Net model

  • Vimala Nagabotu;Anupama Namburu
    • ETRI Journal
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    • v.46 no.3
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    • pp.526-537
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    • 2024
  • Monitoring fetal growth in utero is crucial to anomaly diagnosis. However, current computer-vision models struggle to accurately assess the key metrics (i.e., head circumference and occipitofrontal and biparietal diameters) from ultrasound images, largely owing to a lack of training data. Mitigation usually entails image augmentation (e.g., flipping, rotating, scaling, and translating). Nevertheless, the accuracy of our task remains insufficient. Hence, we offer a U-Net fetal head measurement tool that leverages a hybrid Dice and binary cross-entropy loss to compute the similarity between actual and predicted segmented regions. Ellipse-fitted two-dimensional ultrasound images acquired from the HC18 dataset are input, and their lower feature layers are reused for efficiency. During regression, a novel region of interest pooling layer extracts elliptical feature maps, and during segmentation, feature pyramids fuse field-layer data with a new scale attention method to reduce noise. Performance is measured by Dice similarity, mean pixel accuracy, and mean intersection-over-union, giving 97.90%, 99.18%, and 97.81% scores, respectively, which match or outperform the best U-Net models.

The Musculoskeletal Pain and Inconvenient Feeling During Hand Instruments with Mannequin and Intra-oral Cavity in Dental Hygiene Students (치위생학과 학생들의 구강 내와 마네킹에서 기구 조작시 근골격계 통증과 불편감)

  • Yoo, Jae-Hae;Ro, Hyo-Lyun;Lee, Min-Young
    • Journal of the Korean Society of Physical Medicine
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    • v.3 no.4
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    • pp.247-254
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    • 2008
  • Purpose : The purpose of this study was to analyze some factors that can cause incidence of the muscle and skeletal system trouble, by which Dental Hygiene Students examine the pain and the inconvenient feeling according to kinds in manual implements and the usability in the level of manipulating and maintaining the manual implement, in the actual training of the intra oral cavity along with mannequin given the scaling practice. Methods : Targeting 18 female juniors for the department of dental hygiene, who had directly practiced oral prophylaxis for 2 years, the questionnaire research was carried out right after the mutual practice in the intra oral cavity along with mannequin. Results : It was indicated that there is no big difficulty both in intra oral cavity and mannequin in terms of manipulating implement with a method of maintaining the rightly hand fixing or of grasping the trans formative pencil and of controlling force given manipulating the implement. How to grasp a trans formative pencil was indicated to be more difficult in the intra-oral manipulation(p<.05). Pain and inconvenient-feeling level, which occur in muscle and skeletal system during practicing the scaling in mannequin, were indicated to be in order of shoulder, wrist, neck, waist, elbow, and headache. Conclusion : There was no big difference in the pain and the inconvenient feeling in muscle and skeletal system according to mannequin and intra-oral environment given manipulating tile manual implement. However, there was difference in manipulating the implement with a method of grasping transformative pencil. The pain and inconvenient feeling in muscle and skeletal system were the highest both in shoulder and wrist.

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Rough Set Analysis for Stock Market Timing (러프집합분석을 이용한 매매시점 결정)

  • Huh, Jin-Nyung;Kim, Kyoung-Jae;Han, In-Goo
    • Journal of Intelligence and Information Systems
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    • v.16 no.3
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    • pp.77-97
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    • 2010
  • Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.

Prediction of Uniaxial Compressive Strength of Rock using Shield TBM Machine Data and Machine Learning Technique (쉴드 TBM 기계 데이터 및 머신러닝 기법을 이용한 암석의 일축압축강도 예측)

  • Kim, Tae-Hwan;Ko, Tae Young;Park, Yang Soo;Kim, Taek Kon;Lee, Dae Hyuk
    • Tunnel and Underground Space
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    • v.30 no.3
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    • pp.214-225
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    • 2020
  • Uniaxial compressive strength (UCS) of rock is one of the important factors to determine the advance speed during shield TBM tunnel excavation. UCS can be obtained through the Geotechnical Data Report (GDR), and it is difficult to measure UCS for all tunneling alignment. Therefore, the purpose of this study is to predict UCS by utilizing TBM machine driving data and machine learning technique. Several machine learning techniques were compared to predict UCS, and it was confirmed the stacking model has the most successful prediction performance. TBM machine data and UCS used in the analysis were obtained from the excavation of rock strata with slurry shield TBMs. The data were divided into 8:2 for training and test and pre-processed including feature selection, scaling, and outlier removal. After completing the hyper-parameter tuning, the stacking model was evaluated with the root-mean-square error (RMSE) and the determination coefficient (R2), and it was found to be 5.556 and 0.943, respectively. Based on the results, the sacking models are considered useful in predicting rock strength with TBM excavation data.

A Study on Estimation of Overpressure Damage Caused by Rupture of Butane Can (volume : 34 g) (부탄 캔(용량 : 34 g)파열로 인한 과압의 피해예측에 관한 연구)

  • Leem Sa Hwan;Choi Ic Whoan;Lim Dong Yeon
    • Journal of the Korean Institute of Gas
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    • v.9 no.2 s.27
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    • pp.8-15
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    • 2005
  • With the introduction of 40 hour working week system, more households enjoy picnics on weekends. More gas accidents take place on Saturdays and on Sundays than any other days of week. As of October, 2004 casualties resulted from butane can accidents increased 1.5 times compared to the same period of the previous year. In this study, the influence of explosion over-pressure caused by the rupture of butane can thrown away after use was calculated by using the Hopkinson's Scaling Law and the accident damage was estimated by applying the influence on the adjacent structures and people into the Probit model. As a result of the damage estimation conducted by using the Probit model, both the damage possibility of explosion over-pressure to structures 50 meters away and that of over-pressure to people 10 meters away showed nothing. The explosion efficiency used was 100 percent. As a result of this, the actual damage influenced by the rupture of butane can would be lower than the value calculated in this study and expected to be safer.

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Contamination of operator's clothing by aerosols during scaling (스케일링 시 에어로졸에 의한 술자의 의복 오염도)

  • Kang, Kyung-Hee;Kim, Ye-Jin;Min, Ji-Yeon;Park, Seul-Gi;Woo, Ju-Hee;Goong, Haw-Soo
    • Journal of Korean Academy of Dental Administration
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    • v.5 no.1
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    • pp.31-37
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    • 2017
  • Recently interest in infection control is increasing in hospitalsnfection control has become more important in the overall health care practiceental hospital also requires thorough infection control. There are various kinds of vectormedical clothing. Contaminated clothing of a hospital staff can be a vector of nosocomial infecton. actual case of nosocomial infecton caused by contaminated medical clothing, nursing students were measuring contamination levels of uniforms and pathogenic microorganism wdetected in front of the uniform and pocket. There is also a high risk of exposure to contamination in the dental hospital. We conducted a study to enhance awareness about infection and proper clothing management by comparing before and after contamination of clothing caused by aerosols produced during scaling. Subjects were scaling operators' uniforms in the department of dental hygiene, K University located in Daejeon. Before scaling, the uniform was sterilized by autoclavecaling was performed times in the same place (an average of 60 minutes per person, a total of 180 minutes). ive parts of the uniform (sleeves, chest, belly, thigh, edge of pants) contracted Rodak-plate for 15 seconds. After incubating the contacted Rodak-plate at 37℃ incubator, contamination levels by measuring the number of colonies. As a result, all parts increased number of colonies. ontamination order chestedge of pants thigh belly sleeves. Increase rate of colonies was also high in the order chest edge of pants thigh belly sleeves. This study showed seriousness of clothing contaminationcaused by aerol produced during scalingcontamination of clothing can be a path to nosocomial infecton. According to th study, infection control for clothing as well as dental instruments should be implemented and thorough infection control training needed for dental staff. In further researches, practical infection prevention supplementing clothing management method.