• Journal of Digital Convergence
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• v.10 no.11
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• pp.691-699
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• 2012

"Information", which is circulated in society by information technology development represented by computer, has brought innovation not only to physical civilization, but also deep into our daily lives. This is to say that information has brought fundamental change to its form of existence, and value system through being faster regarding the circulation and the way of management being diverse. As time goes by, this kind of change would stimulate more changes to be made as the development of scientific civilization. Therefore, informatization is one of the important characteristic that defines modern society's essence, but on the other side, information has been taken advantage of that temperament and abused in a lot of different ways. "The Law Regarding Computer Network Diffusion Expansion and Usage Promotion"(1986), as a counterplan of informatization is our nation's first Act about informatization, which enacts national policy and system about this issue. Since then, many laws has been enacted down to "Private Information Protection Act"(2011), forming a comprehensive system. The basic background of these laws are based upon the premise that even if the place where the information is managed is virtual space, rules that are considered valid in the real world should be basically applied in the virtual space. Therefore, the violation of the law in the real world is also considered the violation in the virtual space. This direction of current law regarding information is shared with both the theories and the reality. However, current law system and notion are based upon the premise that the law regards material objects, thus the characteristic of the information, which is "Immaterial Being" is not reflected. Also, the management and approach to this issue is allopathic, exposing many problems. Thus, this paper examines the way of protecting information stipulated in the current law, contemplates its protection scope and limitation, and seeks the direction of the improvement, based on the critical mind explained above.

• Korean Journal of Optics and Photonics
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• v.24 no.4
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• pp.184-188
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• 2013

Two types of polymer-based optical splitters with $200{\mu}m$ large core are presented for optical multimode networks, such as smart home networks, intelligent automotive networks, etc. Optical splitters that have 1:1 symmetric and 9:1 asymmetric structure were fabricated by a ultra violet(UV)-imprint technology using a deep etched Si(silicon) master by the Bosch process. In this paper, we successfully fabricated the symmetric and asymmetric optical splitters with suitable optical network applications.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.8 no.2
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• pp.159-166
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• 2010

The block-scale groundwater flow system at Olkiluoto site in Finland was simulated. The heterogeneous and anisotropic hydraulic conductivity field for the domain was constructed from the discrete fracture network, which considered only the fractured zones identified in the deep boreholes installed in the study site. The groundwater flow model was calibrated by adjusting the recharge rate and the transmissivities of the fractured zones to fit the calculated hydraulic heads and into- and out-flow rates in the observation intervals of the boreholes with the observed ones. In the calibrated model, the calculated flow rates at some intervals were not in accordance with the observed ones although the calculated hydraulic heads fit well with the observed ones, which revealed that the number of the conduits for groundwater flow is insufficient in the conceptual model for groundwater flow modeling. Therefore, it was recommended that the potential local conduits such as background fractures should be added to the present conceptual model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.169-177
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• 2020

In South Korea, the results of R&D in science and technology are submitted to the National Science and Technology Information Service (NTIS) in reports that have Korea national science and technology standard classification codes (K-NSCC). However, considering there are more than 2000 sub-categories, it is non-trivial to choose correct classification codes without a clear understanding of the K-NSCC. In addition, there are few cases of automatic document classification research based on the K-NSCC, and there are no training data in the public domain. To the best of our knowledge, this study is the first attempt to build a highly performing K-NSCC classification system based on NTIS report meta-information from the last five years (2013-2017). To this end, about 210 mid-level categories were selected, and we conducted preprocessing considering the characteristics of research report metadata. More specifically, we propose a convolutional neural network (CNN) technique using only task names and keywords, which are the most influential fields. The proposed model is compared with several machine learning methods (e.g., the linear support vector classifier, CNN, gated recurrent unit, etc.) that show good performance in text classification, and that have a performance advantage of 1% to 7% based on a top-three F1 score.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.6
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• pp.77-88
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• 2021

Duck industry had a rapid growth in recent years. Nevertheless, researches to improve duck house environment are still not sufficient enough. Moisture generation of duck house litter is an important factor because it may cause severe illness and low productivity. However, the measuring process is difficult because it could be disturbed with animal excrements and other factors. Therefore, it has to be calculated according to the environmental data around the duck house litter. To cut through all these procedures, we built several machine learning regression model forecasting moisture generation of litter by measured environment data (air temperature, relative humidity, wind velocity and water contents). 5 models (Multi Linear Regression, k-Nearest Neighbors, Support Vector Regression, Random Forest and Deep Neural Network). have been selected for regression. By using R-Square, RMSE and MAE as evaluation metrics, the best accurate model was estimated according to the variables for each machine learning model. In addition, to address the small amount of data acquired through lab experiments, bootstrapping method, a technique utilized in statistics, was used. As a result, the most accurate model selected was Random Forest, with parameters of n-estimator 200 by bootstrapping the original data nine times.

• The Journal of the Acoustical Society of Korea
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• v.40 no.3
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• pp.234-240
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• 2021

In this paper, the mask-based speech enhancement is improved for effective speech recognition in noise environments. In the mask-based speech enhancement, enhanced spectrum is obtained by multiplying the noisy speech spectrum by the mask. The VoiceFilter (VF) model is used as the mask estimation, and the Spectrogram Inpainting (SI) technique is used to remove residual noise of enhanced spectrum. In this paper, we propose a combined loss to further improve speech enhancement. In order to effectively remove the residual noise in the speech, the positive part of the Triplet loss is used with the component loss. For the experiment TIMIT database is re-constructed using NOISEX92 noise and background music samples with various Signal to Noise Ratio (SNR) conditions. Source to Distortion Ratio (SDR), Perceptual Evaluation of Speech Quality (PESQ), and Short-Time Objective Intelligibility (STOI) are used as the metrics of performance evaluation. When the VF was trained with the mean squared error and the SI model was trained with the combined loss, SDR, PESQ, and STOI were improved by 0.5, 0.06, and 0.002 respectively compared to the system trained only with the mean squared error.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.4
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• pp.58-70
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• 2019

In the case of a pedestrian traffic accident, it has a large-scale danger directly connected by a fatal accident at the time of the accident. The domestic ITS is not used for intelligent risk classification because it is used only for collecting traffic information despite of the construction of good quality traffic infrastructure. The CNN based pedestrian detection classification model, which is a major component of the proposed system, is implemented on an embedded system assuming that it is installed and operated in a restricted environment. A new model was created by improving YOLO's artificial neural network, and the real-time detection speed result of average accuracy 86.29% and 21.1 fps was shown with 20,000 iterative learning. And we constructed a protocol interworking scenario and implementation of a system that can connect with the ITS. If a pedestrian accident prevention system connected with ITS will be implemented through this study, it will help to reduce the cost of constructing a new infrastructure and reduce the incidence of traffic accidents for pedestrians, and we can also reduce the cost for system monitoring.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.3
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• pp.95-105
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• 2019

In recent years, image processing techniques for detecting road surface damaged spot have been actively researched. Especially, it is mainly used to acquire images through a smart phone or a black box that can be mounted in a vehicle and recognize the road surface damaged region in the image using several algorithms. In addition, in conjunction with the GPS module, the exact damaged location can be obtained. The most important technology is image processing algorithm. Recently, algorithms based on artificial intelligence have been attracting attention as research topics. In this paper, we will also discuss artificial intelligence image processing algorithms. Among them, an object detection method based on an region-based convolution neural networks method is used. To improve the recognition performance of road surface damage objects, 600 road surface damaged images and 1500 general road driving images are added to the learning database. Also, supervised learning using background object recognition method is performed to reduce false alarm and missing rate in road surface damage detection. As a result, we introduce a new method that improves the recognition performance of the algorithm to 8.66% based on average value of mAP through the same test database.

• Korean Journal of Heritage: History & Science
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• v.48 no.4
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• pp.74-93
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• 2015

Geophysical survey of Korea was introduced in Nara National Research Institute of Cultural Heritage in 1995. At that time, it has been activated geophysical survey of architecture and civil engineering in Korea. But there was no exploration experts to be combined the archaeology. For this reason, National Research Institute of Cultural Heritage has introduced the physical exploration. Through the expert exchanges South Korea and Japan carried out joint exploration. And it has increased the reliability of the exploration method and exploration results. It is GPR the most method commonly in geophysical exploration. There are many usability before excavation because of good resolution. However, the shallow GPR penetration depth has limitations in large mounds. We were able to take advantage of the resistivity analysis program to study the underground structure to deep through the experts exchange. We was able to get a good result that overcomes the limitations of GPR exploration in a number of burial mounds including Naju bokamri by the resistivity analysis program. In particular, we confirmed the location of the burial main body by compares the results of exploration and excavation results. In the future we will perform a convergence research of exploration and archaeology through a variety of joint research. In addition we will have to build a new network of archaeological science.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.5
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• pp.675-687
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• 2019

In recent years, the needs for double deck-tunnels have increased in large cities due to the increase in traffic volume and high land compensation costs. In Korea, a network type tunnel which is smaller than general road tunnels and crosses another tunnel underground is planned. In the shield tunnel joints between the existing shield tunnel and the box-type enlargement section, a partial steel-concrete joint is proposed where the bending moment is large instead of the existing full-section steel joint. In order to analysis the enlargement section of the shield tunnel diverged section to reflect the three-dimensional effect, the two-dimensional analysis model is considered to consider the column effect and the stiffness effect of the longitudinal member. A two-dimensional analysis method is proposed to reflect the stiffness of the longitudinal member and the column effect of the longitudinal point by considering the rigidity of the longitudinal member as the elastic spring point of the connecting part in the lateral model. As a result of the analysis of the model using the longitudinal member, it was considered that the structural safety of the partial steel-concrete joint can be secured by reducing the bending moment of the joint and the box member by introducing the longitudinal member having the stiffness equal to or greater than a certain value.