• Korean Journal of Comparative Education
• /
• v.27 no.1
• /
• pp.77-96
• /
• 2017

This study seeks to examine current status and issues on primary education environment and teachers in Cambodia, a country that has a poor education environment and low educational achievement I analysed the features and limitation of education. Major findings revealed the primary school students' low accessibility on education and poor competencies and qualification of primary school teachers, which have hindered a quality of education in Cambodia. Central implications were produced to improve the quality of education and training system for primary school teachers. First, sustainability should be embedded from the initial design to the performance evaluation of the projects. Second, we should carry forward a customized training project that can meet the needs of primary school teachers in Cambodia. Third, the Education ODA project should be institutionalized into the national mechanism of the credit accreditation system, including the incentives of participating. Fourth, in-service training should ensure the inclusiveness and accessibility for the disadvantaged in remote areas. Fifth, short-term workshops for teachers should be avoided, but intensive programs including mentoring should be expanded. Finally, we should support the establishment of autonomous teacher- learning communities based on school level across the Cambodia, which could establish the social capital of the teaching profession in a long term.

• Smart Structures and Systems
• /
• v.15 no.4
• /
• pp.1103-1120
• /
• 2015

A self-sensing magnetorheological (MR) damper with embedded piezoelectric force sensor has recently been devised to facilitate real-time close-looped control of structural vibration in a simple and reliable manner. The development and characterization of the self-sensing MR damper are presented based on experimental work, which demonstrates its reliable force sensing and controllable damping capabilities. With the use of experimental data acquired under harmonic loading, a nonparametric dynamic model is formulated to portray the nonlinear behaviors of the self-sensing MR damper based on NARX modeling and neural network techniques. The Bayesian regularization is adopted in the network training procedure to eschew overfitting problem and enhance generalization. Verification results indicate that the developed NARX network model accurately describes the forward dynamics of the self-sensing MR damper and has superior prediction performance and generalization capability over a Bouc-Wen parametric model.

• Korean Journal of Child Studies
• /
• v.26 no.3
• /
• pp.127-139
• /
• 2005

The subjects of this study were 86 eight- and 76 ten-year-old children(total: 162). Experimental procedures and tools included pre- and post- learning tests and controls for intelligence (Draw-a-Man-Test) and for cognitive styles(Children's Embedded Figures Test). The content of the learning task was the lightning generation process. After various types of seven-minute color animation multimedia presentations about the generation of lightning were screened, post-hoc analysis showed that the rehearsal strategy was effective with field-dependent learners but not with field-independent learners.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1994.10a
• /
• pp.707-712
• /
• 1994

An Enhanced Shopfloor Oriented Programming(AESOP) system is developed as a programming utillity of the CNC turning machine. The developed system is specially designed to give a beginner the convenience for CNC part programming with graphical interaction between a machine operator and the AESOP system. The combination of process-oriented cycles and various contour programming as well as an immediate tool path verification support the easiness and swiftness of a part program generation in the shopfloor. Since the AESOP system has been designed to operate on the basis of MS-Windows in the PC-embedded CNC system, it is also useful for the training of the part programming by utilizing provailing personal computers in the educational department.

• Journal of Biomedical Engineering Research
• /
• v.27 no.3
• /
• pp.101-109
• /
• 2006

It has been known that there is strong relationship between human voices and the movements of the articulatory facial muscles. In this paper, we utilize this knowledge to implement an automatic speech recognition scheme which uses solely surface electromyogram (EMG) signals. The EMG signals were acquired from three articulatory facial muscles. Preliminary, 10 Korean digits were used as recognition variables. The various feature parameters including filter bank outputs, linear predictive coefficients and cepstrum coefficients were evaluated to find the appropriate parameters for EMG-based speech recognition. The sequence of the EMG signals for each word is modelled by a hidden Markov model (HMM) framework. A continuous word recognition approach was investigated in this work. Hence, the model for each word is obtained by concatenating the subword models and the embedded re-estimation techniques were employed in the training stage. The findings indicate that such a system may have a capacity to recognize speech signals with an accuracy of up to 90%, in case when mel-filter bank output was used as the feature parameters for recognition.

• Perspectives in Nursing Science
• /
• v.5 no.1
• /
• pp.45-58
• /
• 2008

The nursing informatics has been booming in Taiwan since 2003 when we started to use the end user computing strategy to promote it. We used Excel 2003, which was well known and used by our clinical nurses, as well as the embedded VBA to teach them how simple information applications could and should be built to meet their information management needs in order to support their professional responsibility. Many cost-effective projects were successfully done and the importance and potentials of nursing informatics started to be noticed. Our training strategy and materials are introduced in this paper.

• Journal of Communications and Networks
• /
• v.14 no.5
• /
• pp.540-545
• /
• 2012

In this paper, the lagged cross-correlation of two probability density functions constructed by kernel density estimation is proposed, and by maximizing the proposed function, adaptive filtering algorithms for supervised and unsupervised training are also introduced. From the results of simulation for blind equalization applications in multipath channels with impulsive and slowly varying direct current (DC) bias noise, it is observed that Gaussian kernel of the proposed algorithm cuts out the large errors due to impulsive noise, and the output affected by the DC bias noise can be effectively controlled by the lag ${\tau}$ intrinsically embedded in the proposed function.

• Journal of Information Processing Systems
• /
• v.18 no.3
• /
• pp.344-358
• /
• 2022

Text summarization is the task of producing a shorter version of a long document while accurately preserving the main contents of the original text. Abstractive summarization generates novel words and phrases using a language generation method through text transformation and prior-embedded word information. However, newly coined words or out-of-vocabulary words decrease the performance of automatic summarization because they are not pre-trained in the machine learning process. In this study, we demonstrated an improvement in summarization quality through the contextualized embedding of BERT with out-of-vocabulary masking. In addition, explicitly providing precise pointing and an optional copy instruction along with BERT embedding, we achieved an increased accuracy than the baseline model. The recall-based word-generation metric ROUGE-1 score was 55.11 and the word-order-based ROUGE-L score was 39.65.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.45 no.6
• /
• pp.117-122
• /
• 2008

Although the pulse diagnosis is the one of the most important diagnostic process to traditional medical doctors, there is no proper communication tool between experts and trainees. In this paper, we have developed a indentation training system which consists of a hardware measuring indent pressure on artificial arm quantitatively and a software providing a indentation training program. The hardware for measurement of indent pressure profile includes 3 load cells embedded in the artificial arm, signal amplification part and digitization part, NI-USB 6009 with 200Hz sampling rate. For setting up a relationship table between weights and output voltages, 8 standard weights were used. To evaluate this hardware, 3 oriental medical specialists were involved and their indent pressure profile were recorded three times respectively. From these, it was found that pulse diagnosis process could be divided into 3 periods and the maximum load were $500g{\cdot}f$ approximately while doctors perform a pulse diagnosis. The indentation training program was implemented with LabView and designed to monitor the differences between the pressure profile of a expert and that of a trainee so to offer some visual feedback to the trainee. Also, this program could provide the trends of training performances. With this developed system, the education of pulse diagnosis is expected to be more quantitative and effective.

• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.22
• /
• pp.9739-9745
• /
• 2014

Purpose: We aimed to evaluate the effects of hormone receptor, HER2, and epidermal growth factor receptor (EGFR) expression on epithelial ovarian cancer (EOC) prognosis and investigate whether or not phenotypic subtypes might exist. Materials and Methods: The medical records of 82 patients who were diagnosed with EOC between 2003 and 2012 and treated by platinum-based chemotherapy were retrospectively evaluated. Expression of EGFR, oestrogen (ER), progesterone (PR), and cerbB2 (HER2) receptors were assessed immunohistochemically on paraffin-embedded tissues of these patients. Three phenotypic subtypes were defined according to ER, PR, and HER2 expression and associations of these with EGFR expression, clinicopathologic features, platinum sensitivity, and survival were investigated. Results: When we classified EOC patients into three subtypes, 63.4% had hormone receptor positive (HR(+)) (considering breast cancer subtypes, luminal A), 18.3% had triple negative, and 18.3% had HER2(+) disease. EGFR positivity was observed in 37 patients (45.1%) and was significantly more frequent with advanced disease (p=0.013). However, no significant association with other clinicopathologic features and platinum sensitivity was observed. HER2(+) patients had significantly poorer outcomes than HER2(-) counterparts (triple negative and HR positive patients) (p=0.019). Multivariate analysis demonstrated that the strongest risk factor for death was residual disease after primary surgery. Conclusions: Triple negative EOC may not be an aggressive phenotype as in breast cancer. The HER2 positive EOC has more aggressive behaviour compared to triple negative and HR(+) phenotypes. EGFR expression is more frequent in advanced tumours, but is not related with poorer outcome. Additional ovarian cancer molecular subtyping using gene expression analysis may provide more reliable data.