• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권3호
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• pp.771-791
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• 2022

Protein-protein interaction (PPI) extraction from original text is important for revealing the molecular mechanism of biological processes. With the rapid growth of biomedical literature, manually extracting PPI has become more time-consuming and laborious. Therefore, the automatic PPI extraction from the raw literature through natural language processing technology has attracted the attention of the majority of researchers. We propose a PPI extraction model based on the large pre-trained language model and adversarial training. It enhances the learning of semantic and syntactic features using BioBERT pre-trained weights, which are built on large-scale domain corpora, and adversarial perturbations are applied to the embedding layer to improve the robustness of the model. Experimental results showed that the proposed model achieved the highest F1 scores (83.93% and 90.31%) on two corpora with large sample sizes, namely, AIMed and BioInfer, respectively, compared with the previous method. It also achieved comparable performance on three corpora with small sample sizes, namely, HPRD50, IEPA, and LLL.

• 한국멀티미디어학회논문지
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• 제25권6호
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• pp.886-893
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• 2022

Outlier detection refers to the task of detecting data that deviate significantly from the normal data distribution. Most outlier detection methods compute an outlier score which indicates the degree to which a data sample deviates from normal. However, setting a threshold for an outlier score to determine if a data sample is outlier or normal is not trivial. In this paper, we propose a binary prediction method for outlier detection based on spectral clustering and one-class SVM ensemble. Given training data consisting of normal data samples, a clustering method is performed to find clusters in the training data, and the ensemble of one-class SVM models trained on each cluster finds the boundaries of the normal data. We show how to obtain a threshold for transforming outlier scores computed from the ensemble of one-class SVM models into binary predictive values. Experimental results with high dimensional text data show that the proposed method can be effectively applied to high dimensional data, especially when the normal training data consists of different shapes and densities of clusters.

• 실천공학교육논문지
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• 제13권2호
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• pp.393-403
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• 2021

본 연구의 목적은 훈련 교·강사를 모집단으로 데이터 기반 의사결정을 위한 토대를 마련하고자 직업훈련기관 수준에서의 패널조사 표집설계 방안을 제시하여 지속적이고 체계적인 훈련 교·강사 실태조사의 기초를 제공하는데 있다. 이에 본 연구에서는 체계적인 조사 설계를 위한 요소인 목표 모집단과 표본추출틀을 제안하였으며, 전문가 자문과 실증 자료 분석을 토대로 데이터의 대표성, 자료 수집의 효율성 및 지속가능성 등을 종합적으로 고려하여 표본추출단위, 외층변인과 내층변인을 고려한 표본추출방법 등을 제시하였다. 연구 결과 패널의 단위를 직업훈련기관으로 하여 패널로 선정된 기관과 그 기관에 소속된 훈련 교·강사가 설문조사에 참여할 수 있도록 2단계 층화 비례 표집 방안을 마련하였으며, 이를 바탕으로 패널조사 표본 설계 방안에 대한 시사점을 제시하였다.

• Human Ecology Research
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• 제55권5호
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• pp.555-566
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• 2017

This study analyzes the practical tasks and required competency for technical designers to provide basic data on the training of domestic technical designers. The survey was applied to 21 technical designers of big vendors as well as investigated tasks, task flow, important tasks, time-consuming tasks, and required competencies. The results of the study are as follows. First, the technical designers were in charge of several brands of buyers and distributors of fashion companies, or several lines of the same brand. The main production items were cut and sewn knits. Second, the flow of task and tasks were in the order of buyer comments analysis, sloper decision to matching style, sewing specification, productive sewing method research, size specification suggestion, pattern correction comments, construction decision to matching style & fabric, sample evaluations, fit approval, business e-mail writing, specification & grading confirmation, and communication with buyer. Third, five tasks (analysis of buyer comments analysis, communication with buyer, pattern correction comments, productive sewing methods research, sample evaluation) were important and time-consuming tasks. Fourth, reeducation was required in order of sewing, pattern, English, fabric, and fitting. Fifth, competencies to be a technical designers were fitting, pattern correction, size specification & grading, construction & sewing specification, sewing terms & techniques, and communication skills. In conclusion, technical designer training should focus on technology-based instruction, such as sample evaluation, fitting, pattern correction, and productive sewing methods research of cut and sewn knits.

• 대한간호학회지
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• 제33권5호
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• pp.643-650
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• 2003

Purpose: This study was conducted to examine the effect of a posture training program, including posture education and spinal exercise as implemented on the elementary school students with scoliosis. Method: The design of this study is nonequivalent sample control group pretest-posttest design. The study subjects were elementary school students attending 7 elementary schools located in G city in Gyungsangbuk-Do. Among them, those who had the Cobb angle between 4～10$^{\circ}$ in spine x-ray who agreed to participate in the study program were selected as the study subjects. The research instruments included the degree of spinal scoliosis(cobb angle), the level of knowledge on posture, and an evaluation following the posture training program. The data were collected from March 1, 2002 to July 30, 2002. The collected data were analyzed by frequency, percentile, mean, standard deviation, t-test, i test and Mann-Whitney U test were using SPSS WIN10.0 program. Result: The elementary school students with scoliosis who received the posture training program have a lower Cobb angle and higher level of knowledge of posture than the elementary school students with scoliosis who did not receive the posture training program. Conclusion: The posture training program was effective on the on Cobb angle and Knowledge of posture in the elementary school students with scoliosis in this study. Therefore, the program training program can be usefully utilized for the students with mild scoliosis in the field of school health.

• Asian Pacific Journal of Cancer Prevention
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• 제17권2호
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• pp.545-552
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• 2016

Background: The purpose of this study was to explore the effectiveness of a spiritual care training package in maternal caregivers of children with cancer. Materials and Methods: This study was a quasi-experimental study with pretest and posttest design consisting of a sample of 42 mothers of children diagnosed as having cancer. Participants were randomly assigned to either an experimental or a control group. The training package consisted of seven group training sessions offered in a children's hospital in Tehran. All mothers completed the Spirituality & Spiritual Care Rating Scale (SSCRS) and the Depression, Anxiety and Stress Scale (DASS-21) at pre and post test and after a three month follow up. Results: There was significant difference between anxiety and spiritual, religious, Personalized care and total scores spiritual care between the intervention and control groups at follow-up (P<0.001).There was no statistically significant difference in stress and depression scores between the intervention and the control groups at follow-up. Conclusions: Findings show that spiritual care training program promotes spirituality, personalized care, religiosity and spiritual care as well as decreasing anxiety in mothers of children with cancer and decreases anxiety. It may be concluded that spiritual care training could be used effectively in reducing distressful spiritual challenges in mothers of children with cancer.

• Journal of Sport and Applied Science
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• 제4권4호
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• pp.1-6
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• 2020

Purpose: The purpose of this study is to identify the effect of 24-week sensory integration activity training on fitness of children with intellectual disability. Research design, data, and methodology: The subjects were 10 children with intellectual disability, 60 min training of sensory integration activity for 24 weeks. Obesity, cardiovascular endurance, muscular strength and muscle endurance were measured pre and post training. Frist, characteristics of subjects were measured with age, height, weight, IQ and SQ. Second, the subjects then performed sensory integration activity training for 24 weeks. Last, weight, strength, endurance, cardiovascular endurance and flexibility were measured. Data were calculated for average and standard deviation by SPSS 25.0 statistic program, and dependent sample t-test was processed to analyze the change between pre and post training. All statistical significance level was set to 0.5. Results: The result was shown that weight, strength and endurance changes between pre and post were significant. However, cardiovascular endurance, flexibility changes between pre and post were not significant. Conclusions: The lack of training frequency of 60 minute per week were acknowledged per week from this result. In future research, increased intensity and frequency are need for an in-depth and meaningful study and the measured data can be used basic information for the study.

• 아태비즈니스연구
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• 제12권4호
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• pp.241-251
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• 2021

Purpose - Drawing on the content-process approach, this study examines the effect of employees' perceived utility of education and training in small and medium enterprises (SMEs) on their satisfaction. In addition, this study investigates how the human resource management department' activities moderate the relationship between employees' perceived utility of education and training and satisfaction. Design/methodology/approach - This study predicts the positive relationship between employees' perceived utility of education and training and satisfaction, and HR activities strengthens this positive relationship. To test these hypotheses, this study utilized Human Capital Corporate Panel (HCCP) datasets, especially 2017 data at the individual level. The number of the final sample is 425 for the test. Moreover, this study used the hierarchical regression model with SPSS. Finding - As predicted, the analytical results with the hierarchical regression model showed that employees' percieved utility of education and training and satisfaction were positively related. In addition, HR activities strengthened this relationship between employees' percieved utility of education and training and satisfaction. Research implications or Originality - This study will provide academic and practical implications for future research on human resource development, especially SMEs by deepening an understanding of the important factors in order to increase employees' satisfaction of education and training. the number of viewers is found in most American films released in Korea.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권10호
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• pp.3378-3393
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• 2014

We have witnessed the rapid development of information technology in recent years. One of the key phenomena is the fast, near-exponential increase of data. Consequently, most of the traditional data classification methods fail to meet the dynamic and real-time demands of today's data processing and analyzing needs--especially for continuous data streams. This paper proposes an improved incremental learning algorithm for a large-scale data stream, which is based on SVM (Support Vector Machine) and is named DS-IILS. The DS-IILS takes the load condition of the entire system and the node performance into consideration to improve efficiency. The threshold of the distance to the optimal separating hyperplane is given in the DS-IILS algorithm. The samples of the history sample set and the incremental sample set that are within the scope of the threshold are all reserved. These reserved samples are treated as the training sample set. To design a more accurate classifier, the effects of the data volumes of the history sample set and the incremental sample set are handled by weighted processing. Finally, the algorithm is implemented in a cloud computing system and is applied to study user behaviors. The results of the experiment are provided and compared with other incremental learning algorithms. The results show that the DS-IILS can improve training efficiency and guarantee relatively high classification accuracy at the same time, which is consistent with the theoretical analysis.

• Near Infrared Analysis
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• 제1권2호
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• pp.1-8
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• 2000

Using the net analyte signal, hybrid linear analysis was proposed to predict chemical concentration. In this paper, we select a sample from training set and apply orthogonal signal correction to obtain an improved pseudo unit spectrum for hybrid least analysis. using the mean spectrum of a calibration training set, we first show the calibration by hybrid least analysis is effective to the prediction of not only chemical concentrations but also physical property variables. Then, a pseudo unit spectrum from a training set is also tested with and without orthogonal signal correction. We use two data sets, one including five chemical concentrations and the other including ten physical property variables, to compare the performance of partial least squares and modified hybrid least analysis calibration methods. The results show that the hybrid least analysis with a selected training spectrum instead of well-measured pure spectrum still gives good performances, which is a little better than partial least squares.