• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.383-386
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• 2019

4 차산업혁명의 발달은 전 세계가 건강한 삶에 관련된 스마트시티 및 맞춤형 치료에 큰 관심을 갖게 하였고, 특히 기계학습 기술은 암을 극복하기 위한 유전체 기반의 정밀 의학 연구에 널리 활용되고 있어 암환자의 예후 예측 및 예후에 따른 맞춤형 치료 전략 수립 등을 가능케하였다. 하지만 암 예후 예측 연구에 주로 사용되는 유전자 발현량 데이터는 약 17,000 개의 유전자를 갖는 반면에 샘플의 수가 200 여개 밖에 없는 문제를 안고 있어, 예후 예측을 위한 신경망 모델의 일반화를 어렵게 한다. 이러한 문제를 해결하기 위해 본 연구에서는 고차원의 유전자 발현량 데이터를 신경망 모델이 효과적으로 학습할 수 있도록 2D 이미지로 표현하는 기법을 제안한다. 길이 17,000 인 1 차원 유전자 벡터를 64×64 크기의 2 차원 이미지로 사상하여 입력크기를 압축하였다. 2 차원 평면 상의 유전자 좌표를 구하기 위해 유전자 네트워크 데이터와 Node2Vec 이 활용되었고, 이미지 기반의 암 예후 예측을 수행하기 위해 합성곱 신경망 모델을 사용하였다. 제안하는 기법을 정확하게 평가하기 위해 이중 교차 검증 및 무작위 탐색 기법으로 모델 선택 및 평가 작업을 수행하였고, 그 결과로 베이스라인 모델인 고차원의 유전자 벡터를 입력 받는 다층 퍼셉트론 모델보다 더 높은 예측 정확도를 보여주는 것을 확인하였다.

• Journal of Engineering Education Research
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• v.22 no.5
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• pp.49-55
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• 2019

Folded structure is widely applied in various engineering fields. Many of the Japanese folding fans in the Edo era (1603-1868) have been successfully blended with the processing technology of "natural materials" that is the origin of Japan's "Monodzukuri" (craftsmanship) and its application "artistic originality". The charm of a fan lies in the diversity of stereoscopic expression not born in plane representation. For example, the effects of folds, the expression of the front and back sides flowing from the front to the back by double-sided description, and the two-layer effect of raising the backside from the surface using the permeability of Japanese paper, the calculated depiction are also seen. Moreover, by handling the fan, it also produced an illusion effect which skillfully calculated the change due to movement of the viewpoint. Students experience the natural materials such as Japanese paper, bamboo and starch paste, which are the materials of paint and fan at the time, and processing method, and know the difference with the current one. This study is to verify the effectiveness of engineering education which gains experience by making concrete fans and to understand deeply this traditional technology with the artistry of a Japanese fan at the same time. And we can learn from the characteristics of the fan to Japan's history and culture.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.5
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• pp.209-214
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• 2021

Panoptic segmentation, which is now widely used in computer vision such as medical image analysis, and autonomous driving, helps understanding an image with holistic view. It identifies each pixel by assigning a unique class ID, and an instance ID. Specifically, it can classify 'thing' from 'stuff', and provide pixel-wise results of semantic prediction and object detection. As a result, it can solve both semantic segmentation and instance segmentation tasks through a unified single model, producing two different contexts for two segmentation tasks. Semantic segmentation task focuses on how to obtain multi-scale features from large receptive field, without losing low-level features. On the other hand, instance segmentation task focuses on how to separate 'thing' from 'stuff' and how to produce the representation of detected objects. With the advances of both segmentation techniques, several panoptic segmentation models have been proposed. Many researchers try to solve discrepancy problems between results of two segmentation branches that can be caused on the boundary of the object. In this survey paper, we will introduce the concept of panoptic segmentation, categorize the existing method into two representative methods and explain how it is operated on two methods: top-down method and bottom-up method. Then, we will analyze the performance of various methods with experimental results.

• Journal of Korean Elementary Science Education
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• v.37 no.4
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• pp.416-429
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• 2018

In social constructivist teaching, knowledge construction is achieved through learners' collective social interaction. Vygotsky argued that this process is mediated with language use, and the development of higher order thinking is realized through the transition from inter-personal psychological functions to intra-personal psychological functions. In so doing scientific concepts are internalized to learners. This study examined the third grade elementary students' inter/intra-personal psychological functions and their internalization processes during social constructivist teaching plan about strata and fossils. The lessons were designed along with Wells' dialogic inquiry and Leach and Scott's social constructivist teaching-learning sequences. Results showed that a teacher's utterances of talking with questioning to switch attention, creating cognitive disequilibrium, and expanding the width of students' opinions could make effective inter-personal psychological function. In addition, a learner's inner speech expressed into social discourse through talking about personal experiences, comparing epistemic idea with visual representation, or applying to different situation showed his/her intra-personal psychological function. Some cases of learners' internalization through language use could be at the stage of knowledge building and understanding of the spiral of knowing, but not all. Thus it is argued that a teacher's deeper insight into Vygotskian social constructivist teaching can make elementary science classroom teaching more effective in their inter/intra-psychological functions.

• Structural Engineering and Mechanics
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• v.68 no.6
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• pp.691-700
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• 2018

Ground granulated blast furnace slag (GGBS) is a by product obtained from iron and steel industries, useful in the design and development of high quality cement paste/mortar and concrete. This paper investigates the applicability of relevance vector machine (RVM) based regression model to predict the compressive strength of various GGBS based concrete mixes. Compressive strength data for various GGBS based concrete mixes has been obtained by considering the effect of water binder ratio and steel fibres. RVM is a machine learning technique which employs Bayesian inference to obtain parsimonious solutions for regression and classification. The RVM is an extension of support vector machine which couples probabilistic classification and regression. RVM is established based on a Bayesian formulation of a linear model with an appropriate prior that results in a sparse representation. Compressive strength model has been developed by using MATLAB software for training and prediction. About 70% of the data has been used for development of RVM model and 30% of the data is used for validation. The predicted compressive strength for GGBS based concrete mixes is found to be in very good agreement with those of the corresponding experimental observations.

• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.12-19
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• 2018

This article aims to discuss the transition of the Kazakh writing system from Cyrillic to Latin. First, the study investigates the relationship between the Kazakh Cyrillic alphabet and phonology, in order to linguistically evaluate the efficiency of the writing system. Second, the process of determining the Kazakh Latin alphabet is discussed in terms of the Kazakh phonological system. Third, the factors that determined the Latin alphabet of Kazakh language are analyzed. In Kazakh, the phonemic system is subject to controversy among linguists, but it can be said that the phonological system basically follows the one-to-one correspondence to the Russian and Kazakh phonemes. As for the depth of orthographies, Kazakh Cyrillic writing system is not based on the shallow orthographies, so it incorporates morphophonemic information to make skilled readers understand easier. The political and social aspects are considered as a cause of the alphabet change. Although there are studies suggesting the conversion of the writing system is caused by the extrinsic factors rather than the intrinsic factors, the five criteria of Smalley (1964), which compromise the intrinsic and extrinsic factors, are also persuasive. The five factors are 1) Maximum motivation for the learner, 2) Maximum representation of speech, 3) Maximum ease of learning, 4) Maximum transfer, 5) Maximum ease of reproduction.

• Genomics & Informatics
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• v.17 no.2
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• pp.20.1-20.5
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• 2019

Entity normalization, or entity linking in the general domain, is an information extraction task that aims to annotate/bind multiple words/expressions in raw text with semantic references, such as concepts of an ontology. An ontology consists minimally of a formally organized vocabulary or hierarchy of terms, which captures knowledge of a domain. Presently, machine-learning methods, often coupled with distributional representations, achieve good performance. However, these require large training datasets, which are not always available, especially for tasks in specialized domains. CONTES (CONcept-TErm System) is a supervised method that addresses entity normalization with ontology concepts using small training datasets. CONTES has some limitations, such as it does not scale well with very large ontologies, it tends to overgeneralize predictions, and it lacks valid representations for the out-of-vocabulary words. Here, we propose to assess different methods to reduce the dimensionality in the representation of the ontology. We also propose to calibrate parameters in order to make the predictions more accurate, and to address the problem of out-of-vocabulary words, with a specific method.

• Journal of Korea Multimedia Society
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• v.22 no.3
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• pp.335-348
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• 2019

Cell segmentation and counting represent one of the most important tasks required in order to provide an exhaustive understanding of biological images. Conventional features suffer the lack of spatial consistency by causing the joining of the cells and, thus, complicating the cell counting task. We propose, in this work, a cascade of networks that take as inputs different versions of the original image. After constructing a Gaussian pyramid representation of the microscopy data, the inputs of different size and spatial resolution are given to a cascade of deep convolutional autoencoders whose task is to reconstruct the segmentation mask. The coarse masks obtained from the different networks are summed up in order to provide the final mask. The principal and main contribution of this work is to propose a novel method for the cell counting. Unlike the majority of the methods that use the obtained segmentation mask as the prior information for counting, we propose to utilize the hidden latent representations, often called the high-level features, as the inputs of a neural network based regressor. While the segmentation part of our method performs as good as the conventional deep learning methods, the proposed cell counting approach outperforms the state-of-the-art methods.

• East Asian mathematical journal
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• v.35 no.2
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• pp.115-139
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• 2019

In problem solving education, sentence problems are a tool for comprehensive evaluation of mathematical ability. The sentence problems refer to the problem expressed in sentence form rather than simply a numerical representation of mathematical problems. In order to solve sentence problems with a mixture of mathematical terms and general language, problem-solving ability including the ability to understand the meaning of sentences as well as the mathematical computation ability is required. Therefore, it is important to analyze syntactic elements from the linguistic aspects in sentence problems. The purpose of this study is to investigate the complexity of sentence problems in the length of sentences and the grammatical complexity of the sentences in the depth of the sentences by analyzing the 51 sentence problems presented in the $4^{th}$ grade mathematics textbook(2015 revised curriculum). As a result, it was confirmed that it is necessary to examine the length and depth of the sentence more carefully in the teaching and learning of sentence problems. Especially in elementary mathematics, the sentence problems requires a linguistic understanding of the sentence, and therefore it is necessary to consider syntactic elements in the process of developing and teaching sentence problems in mathematics textbook.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.1405-1416
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• 2021

The study uses an innovative management perspective to investigate the environment of higher education institutions to ensure the survival of universities in Cambodia. This has led Cambodian universities to expand their educational offerings to students in Years 2, 3 and 4. The data was collected through a Google Forms survey to facilitate and accelerate data collection. The sample of 500 students come from three higher education institution by employing multi-stage sampling technique of probability and non-probability sampling methods to ensure representation of the research population. The data were analyzed by using Confirmatory Factor Analysis (CFA) and Structural Equation Model (SEM) to investigate the impact of these determinants on students' satisfaction and loyalty, via answering 54 questions. The results showed that the three Cambodian universities perform well in terms of satisfactory conditions such as transformative quality and university image. There are four issues to which universities need to pay attention, namely, teaching methods, infrastructure facilities, learning material, and academic environment that are yet to meet the needs of students. This study contributes to the principle of innovative management in the context of Cambodian academic environment. The results help to fathom the depth of enhancing quality and institutional survival.