• International Journal of Advanced Culture Technology
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• v.9 no.2
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• pp.86-90
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• 2021

Sentiment refers to a person's thoughts, opinions, and feelings toward an object. Sentiment analysis is a process of collecting opinions on a specific target and classifying them according to their emotions, and applies to opinion mining that analyzes product reviews and reviews on the web. Companies and users can grasp the opinions of public opinion and come up with a way to do so. Recently, natural language processing models using the Transformer structure have appeared, and Google's BERT is a representative example. Afterwards, various models came out by remodeling the BERT. Among them, the Facebook AI team unveiled the XLM-R (XLM-RoBERTa), an upgraded XLM model. XLM-R solved the data limitation and the curse of multilinguality by training XLM with 2TB or more refined CC (CommonCrawl), not Wikipedia data. This model showed that the multilingual model has similar performance to the single language model when it is trained by adjusting the size of the model and the data required for training. Therefore, in this paper, we study the improvement of Korean sentiment analysis performed using a pre-trained XLM-R model that solved curse of multilinguality and improved performance.

• Smart Structures and Systems
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• v.29 no.1
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• pp.53-62
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• 2022

The deployment of advanced structural health monitoring (SHM) systems in large-scale civil structures collects large amounts of data. Note that these data may contain multiple types of anomalies (e.g., missing, minor, outlier, etc.) caused by harsh environment, sensor faults, transfer omission and other factors. These anomalies seriously affect the evaluation of structural performance. Therefore, the effective analysis and mining of SHM data is an extremely important task. Inspired by the deep learning paradigm, this study develops a novel generative adversarial network (GAN) and convolutional neural network (CNN)-based data anomaly detection approach for SHM. The framework of the proposed approach includes three modules : (a) A three-channel input is established based on fast Fourier transform (FFT) and Gramian angular field (GAF) method; (b) A GANomaly is introduced and trained to extract features from normal samples alone for class-imbalanced problems; (c) Based on the output of GANomaly, a CNN is employed to distinguish the types of anomalies. In addition, a dataset-oriented method (i.e., multistage sampling) is adopted to obtain the optimal sampling ratios between all different samples. The proposed approach is tested with acceleration data from an SHM system of a long-span bridge. The results show that the proposed approach has a higher accuracy in detecting the multi-pattern anomalies of SHM data.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.77-82
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• 2022

GUI(Graphical User Interface)를 대신하는 차세대 인터페이스로서 NUI(Natural User Interace)에 기대가 모이는 것은 자연스러운 흐름이다. 본 연구는 NUI의 손가락 관절을 포함한 손동작 전체를 인식시키기 위해 웹캠과 카메라를 활용하여 다양한 배경과 각도의 손동작 데이터를 수집한다. 수집된 데이터는 전처리를 거쳐 데이터셋을 구축하며, ResNet50 모델을 활용하여 전이학습한 합성곱 신경망(Convolutional Neural Network) 알고리즘 분류기를 설계한다. 구축한 데이터셋을 입력시켜 분류학습 및 예측을 진행하며, 실시간 영상에서 인식되는 손동작을 설계한 모델에 입력시켜 나온 결과를 통해 가위바위보 게임을 구현한다.

• Advances in Traditional Medicine
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• v.7 no.2
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• pp.182-190
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• 2007

Alzheimer's disease is a neurodegenerative disorder associated with a decline in cognitive abilities. Dementia is one of the aged related mental problems and a characteristic symptom of Alzheimer's disease. Nootropic agents like piracetam and cholinesterase inhibitors like $Donepezil^{\circledR}$ are used in situations where there is organic disorder in learning abilities, but the resulting side-effects associated with these agents have limited their utility. Foeniculum (F.) vulgare Linn. is widely used in Indian traditional systems of medicines and also as a house remedy for nervous debility. The present work was undertaken to assess the potential of F. vulgare as a nootropic and anti-cholinesterase agent in mice. Exteroceptive behavioral models such as Elevated plus maze and Passive avoidance paradigm were employed to assess short term and long term memory in mice. To delineate the possible mechanism through which F. vulgare elicits the anti-amnesic effects, its influence on central cholinergic activity was studied by estimating the whole brain acetylcholinesterase activity. Pretreatment of methanolic extract of fruits of F. vulgare Linn. for 8 successive days, ameliorated the amnesic effect of scopolamine (0.4 mg/kg) and aging induced memory deficits in mice. F. vulgare extract significantly decreased transfer latencies of young mice and aged mice, increased step down latency and exhibited significant anti-acetyl cholinesterase effects, when compared to piracetam, scopolamine and control groups of mice. F. vulgare might prove to be a useful memory restorative agent in the treatment of dementia seen in the elderly.

• Research in Mathematical Education
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• v.22 no.4
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• pp.245-259
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• 2019

I examine the discussions of studies related to feminist mathematics education and the implications of mathematics education in South Korea. In particular, I attempt to answer the following questions through literature reviews on feminist mathematics: What is the epistemological background of feminist mathematics education? How is feminist mathematics education defined and implemented? What does feminist mathematics education suggest in South Korea's mathematics curriculum? From the analysis of the literatures, I found that feminist mathematics education reflects not just the rights of female's rights but also a paradigm shift in epistemology of mathematics and philosophy of mathematics education. In this regard, feminist mathematics questions the existing mathematics education related to the female students who were marginalized in the composition and delivery of mathematics. Feminist mathematics education points out that in the course of the transfer of mathematical knowledge in schools, female students understand unilateral information procedurally without understanding the concept. Mathematics educators should consider alternative curricula that reflect the views of female students regarding the nature of mathematics. Students should be able to receive equal mathematics education in a school regardless of their gender. In this case, equal mathematics education refers to education methods that are suitable for both male and female students. The existing mathematics content and its teaching methods were designed based on the learning experiences of male students, which made them relatively difficult for female students to understand.

• 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.

• Journal of the Korean Society of Earth Science Education
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• v.4 no.2
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• pp.89-101
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• 2011

Science, Mathematics, Engineering, and Technology (STEM) integrated education has been spotlighted as a new approach for promoting students' conceptual understanding and supporting their future career in STEM field. There is increasing evidence of the positive impact of using a whole design process that can be an example of STEM integrated activities to improve students' conceptual understanding and problem solving skills. However, there is a lack of information on how teachers should accomplish science and engineering integration activities in their classroom and what process they should pay attention. To answer this question, we research the relationship between an design process and students' conceptual understanding using an engineering design activity, called 'Save the Penguins', and study on how each step in an engineering design process in this activity enhance students' conceptual knowledge in science. We found that testing their prototypes and discussing with their peers were the most important process for students to understand and apply science concept for their design, even though the whole engineering design process (demonstration about radiation, discussion about examples in our lives, and testing and reviewing their prototypes, and making final design) helps the students understand the scientific concepts.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.4
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• pp.130-137
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• 2010

This paper analyzes the main factors affecting user selection of a small-sum electronic payment system using survey data of 396 users. Several findings emerge. First, users consider three pillars and eight factors in adopting a new system : system features(stability, security, and flexibility), transaction cost(payment commission and settlement period), and financial capability of provider(stability of financial structure, risk management capability, and funding capability). Second, the stability of the financial structure of the system provider is the most important factor to user acceptance of a new e-payment system. Users tend to consider uncertainty risk more seriously than transaction cost. This reflects the reality that electronic payment system service industry has not fully fledged yet. Third, some moderating effects exist according to payment methods and business usages. As for payment methods, speedy settlement cycle for wired/wireless phone payment, system stability for credit card and account transfer payment, and security for advance payment means are crucial factors. As for business usages, the stability of financial structure for online game content, system stability for music and video content, proxy payment commission for e-learning content, flexibility of the payment system for digital adult content, and security for public services are decisive ones.

• Structural Engineering and Mechanics
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• v.63 no.2
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• pp.237-249
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• 2017

The Self-Organization Feature Map as an unsupervised network is very widely used these days in engineering science. The applied network in this paper is the Self Organization Feature Map with constant weights which includes Kohonen Network. In this research, Reinforced Concrete Shear Wall buildings with different stories and heights are analyzed and a database consisting of measured fundamental periods and characteristics of 78 RC SW buildings is created. The input parameters of these buildings include number of stories, height, length, width, whereas the output parameter is the fundamental period. In addition, using Genetic Algorithm, the structure of the Self-Organization Feature Map algorithm is optimized with respect to the numbers of layers, numbers of nodes in hidden layers, type of transfer function and learning. Evaluation of the SOFM model was performed by comparing the obtained values to the measured values and values calculated by expressions given in building codes. Results show that the Self-Organization Feature Map, which is optimized by using Genetic Algorithm, has a higher capacity, flexibility and accuracy in predicting the fundamental period.

• Journal of Information Processing Systems
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• v.19 no.1
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• pp.109-117
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• 2023

Defect detection is one of the key factors in fabric quality control. To improve the speed and accuracy of denim fabric defect detection, this paper proposes a defect detection algorithm based on cascading feature extraction architecture. Firstly, this paper extracts these weight parameters of the pre-trained VGG16 model on the large dataset ImageNet and uses its portability to train the defect detection classifier and the defect recognition classifier respectively. Secondly, retraining and adjusting partial weight parameters of the convolution layer were retrained and adjusted from of these two training models on the high-definition fabric defect dataset. The last step is merging these two models to get the defect detection algorithm based on cascading architecture. Then there are two comparative experiments between this improved defect detection algorithm and other feature extraction methods, such as VGG16, ResNet-50, and Xception. The results of experiments show that the defect detection accuracy of this defect detection algorithm can reach 94.3% and the speed is also increased by 1-3 percentage points.