• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.577-586
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• 2022

Detection and classification of steel surface defects are critical for product quality control in the steel industry. However, due to its low accuracy and slow speed, the traditional approach cannot be effectively used in a production line. The current, widely used algorithm (based on deep learning) has an accuracy problem, and there are still rooms for development. This paper proposes a method of steel surface defect detection combining EfficientNetV2 for image classification and YOLOv5 as an object detector. Shorter training time and high accuracy are advantages of this model. Firstly, the image input into EfficientNetV2 model classifies defect classes and predicts probability of having defects. If the probability of having a defect is less than 0.25, the algorithm directly recognizes that the sample has no defects. Otherwise, the samples are further input into YOLOv5 to accomplish the defect detection process on the metal surface. Experiments show that proposed model has good performance on the NEU dataset with an accuracy of 98.3%. Simultaneously, the average training speed is shorter than other models.

• Journal of Internet Computing and Services
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• v.24 no.2
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• pp.37-45
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• 2023

In line with the 4th Industrial Revolution, facility maintenance technologies for building smart factories are receiving attention and are being advanced. In addition, technology is being applied to smart farms and smart fisheries following smart factories. Among them, in the case of a recirculating aquaculture system, there is a motor pump that circulates water for a stable quality environment in the tank. Motor pump maintenance activities for recirculating aquaculture system are carried out based on preventive maintenance and data obtained from vibration sensor. Preventive maintenance cannot cope with abnormalities that occur before prior planning, and vibration sensors are affected by the external environment. This paper proposes an anomaly detection algorithm that utilizes ADTK, a Python open source, for motor pump anomaly detection based on data collected through current sensors that are less affected by the external environment than noise, temperature and vibration sensors.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1571-1576
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• 2022

This study aims to analyze the interest of modern people in non-face-to-face medical counseling in the medical industrys. Big data was collected on two social platforms, 지식인, a platform that allows experts to receive medical counseling, and YouTube. In addition to the top five keywords of telephone counseling, "internal medicine", "general medicine", "department of neurology", "department of mental health", and "pediatrics", a data set was built from each platform with a total of eight search terms: "specialist", "medical counseling", and "health information". Afterwards, pre-processing processes such as morpheme classification, disease extraction, and normalization were performed based on the crawled data. Data was visualized with word clouds, broken line graphs, quarterly graphs, and bar graphs by disease frequency based on word frequency. An emotional classification model was constructed only for YouTube data, and the performance of GRU and BERT-based models was compared.

• Journal of the Korean earth science society
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• v.22 no.5
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• pp.427-447
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• 2001

Science teachers need to understand what science is, how students learn, how to teach science effectively, and the rationale for their teaching methods. Along this line, this article discusses constructivist learning theory as an alternative to the traditional pedagogy and the origin of various versions of constructivism. Constructivism is defined and used in a variety of contexts including philosophical constructivism, constructivist research paradigm, sociological constructivism, and educational constructivism. Educational constructivism (or psychological constructivism) can be divided into three distinct versions (i.e., individual, radical, and social constructivism) depending on unique ontological and epistemological beliefs that underlie each version. Each version of educational constructivism supports different conceptions of science teaching and learning that are consistent with its specific ontological and epistemological beliefs. In this article, the main tenets of each version of educational constructivism are examined with regard to ontological beliefs, epistemological commitments, and pedagogical beliefs. In addition, two major criticisms on constructivist pedagogy as well as implications for research methods for each version are also discussed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.185-195
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• 2018

As machines have been automated in the field of industries in recent years, it is a paramount importance to manage and maintain the automation machines. When a fault occurs in sensors attached to the machine, the machine may malfunction and further, a huge damage will be caused in the process line. To prevent the situation, the fault of sensors should be monitored, diagnosed and classified in a proper way. In the paper, we propose a sensor fault detection scheme based on SVM and CNN to detect and classify typical sensor errors such as erratic, drift, hard-over, spike, and stuck faults. Time-domain statistical features are utilized for the learning and testing in the proposed scheme, and the genetic algorithm is utilized to select the subset of optimal features. To classify multiple sensor faults, a multi-layer SVM is utilized, and ensemble technique is used for CNN. As a result, the SVM that utilizes a subset of features selected by the genetic algorithm provides better performance than the SVM that utilizes all the features. However, the performance of CNN is superior to that of the SVM.

• Journal of Oriental Neuropsychiatry
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• v.19 no.1
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• pp.125-146
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• 2008

Objectives : The purpose of this study is to suggest for the following experimental study of dementia by reviewing recent oriental medicine journals that have been published since 2000. Methods: We have investigated various types of studies in relation to dementia through 90 articles that have been published from 2000 to 2007 in recent oriental medicine journals were registered Korea research foundation. Results and Conclusions : 1. Since 2000, 88 articles in relation to dementia have been published and almost of them are herbal medicine-centered studies. Also they show a tendency to increase every year. The journal of oriental neuropsychiatry carries the highest number of studies in relation to dementia. 2. According to the experimental paper, there are 30 cases of using herb simplexes, 48 cases of herb-combined prescription, and 10 cases of other ways. Especially 7 cases of using herb-combined prescription relation to Sasang constitution are all for the Taeumin. 3. There are 85 cases of Animal and cellular experimental, 60 cases of using pathologic model induced cytotoxic activity, a case of using L-NAME, 3 cases of 192 saporin, 4 cases of ibotenic acid, 10 cases of focal cerebral ischemia, 3 cases of alcohol-administered, and one case of natural degradation. 4. Moms water maze, Radial arm maze Passive avoidance learning model were using for examining learning and memory of model animal 5. We propose that following studies of dementia are to he investigated of the applied method of using siRNA with tranceduced gene, sample preparation by water-soaking, oriental medical diagnosis, standardization of differentiating symptom and herb simplexes, building the database by classified prescriptions, and experiment model which are based on precise examining mechanism with cell line as like mouse H19-7 hippocampus, rat HT22 hippocampus, astrocyte, microglia, using the model of animals at APP, PS1, BACE, CT99/PS1, APOE4, Tau, APP/PSI/Tau

• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.177-186
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• 2021

The 2015 revised curriculum is structured around the core competencies of the 21st century, this is in line with the world's flow of education, such as OECD Education 2030. A future practical leading model was studied to provide a variety of creative teaching and learning experiences to elementary and Secondary students using intelligent information technology to cultivate core competencies such as ICT and computing thinking. In order for this practical model to stably settle the school field, the training was planned and operated to strengthen the creative convergence education capacity required by the teachers at the unit school through various types of the training. In particular, a nationwide administrators training program was operated for three years, reflecting the new curriculum, teaching and learning methods, and evaluation that can lead to future convergence talent training. In this paper, the perception of creative convergence education was investigated and analyzed considering the influence that administrators may have on the school field. Based on this, through the three-year operation results of the training, it was intended to establish a new training method for stable access to future creative convergence education under the post-corona era's social issues.

• Journal of Industrial Convergence
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• v.22 no.1
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• pp.137-148
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• 2024

This study aims to analyse the research trends and identify issues in elementary physical education in the new normal era. For this purpose, the taxonomic analysis method proposed by Spradley (2016) was applied, and 43 Korean academic articles were finally categorised and analysed. The findings are as follows. First, due to the changes in the educational environment caused by COVID-19, most of the remote and online physical education classes were conducted as content-oriented classes. It was found that there was a lack of communication between teachers and students in online physical education classes. Second, the difficulties of remote and online physical education classes and online and offline combined physical education classes, as well as research on how to overcome and improve them, were concentrated. Third, the need for evolution of physical education teachers and training of future professionals in line with the methodological transformation of primary physical education and the current situation was raised. In addition, the number of studies utilising blended learning, flipped learning, and new technologies, which have gained attention in primary physical education due to COVID-19, has increased. Based on the findings, we proposed the direction and future tasks of elementary physical education in the new normal era.

• Journal of Advanced Navigation Technology
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• v.5 no.1
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• pp.1-10
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• 2001

Speech has a good characteristics of which car drivers busy to concern with miscellaneous operation can make use in convenient handling and manipulating of devices. By utilizing this, this works proposes a speaker verification method for protecting cars from being stolen and identifying a person trying to access critical on-line services. In this, continuant phonemes recognition which uses language information of speech and MLP(mult-layer perceptron) which has some advantages against previous stochastic methods are adopted. The recognition method, though, involves huge computation amount for learning, so it is somewhat difficult to adopt this in speaker verification application in which speakers should enroll themselves at real time. To relieve this problem, this works presents a solution that introduces speaker cohort models from speaker verification score normalization technique established before, dividing background speakers into small cohorts in advance. As a result, this enables computation burden to be reduced through classifying the enrolling speaker into one of those cohorts and going through enrollment for only that cohort.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.187-194
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• 2005

The background subtraction method is mainly used for the real-time extraction and tracking of moving objects from image sequences. In the outdoor environment, there are many changeable environment factors such as gradually changing illumination, swaying trees and suddenly moving objects , which are to be considered for an adaptive processing. Normally, GMM(Gaussian Mixture Model) is used to subtract the background by considering adaptively the various changes in the scenes, and the adaptive GMMs improving the real-time Performance were Proposed and worked. This paper, for on-line background subtraction, employed the improved adaptive GMM, which uses the small constant for learning rate a and is not able to speedily adapt the suddenly movement of objects, So, this paper Proposed and evaluated the dynamic control method of a using the adaptive selection of the number of component distributions and the global variances of pixel values.