• (The)Study of the Eastern Classic
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• no.57
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• pp.359-382
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• 2014

This paper is an essay on Chaekmun(Answer papers of official examination in Pre-modern period). Especially I tried to point out the possibility of practical use in the field of politics. For this purpose, I analyzed an examination paper written by Lee Ga-hwan, and the title is "a debate about construction of the Miang palace". Exquisite writing skill is also important in Chaekmun, but it is not everything. The subject of Chaekmun concerns various fields such like politics, economy, society, culture, and history. So that writers should have sufficient knowledge and opinion. The King, as an examiner, wants to test retainers' ability both in writing and politics. In this paper, I focused on using in field of politics between the King and the retainers. And as an good example, I analyzed a paper which dealt the event of building huge palace named Miang palace. That is because the King reflects his concerns by setting exam questions. And his concerns also could not be free of contemporary political conditions. Therefore we should be careful of reading those articles. Regarding this, Lee Ga-hwan's article had a distinctive characteristic. Unlike any other articles dealing with same event, he tried to access through creative point of view. And his thought were much close to the King's heart.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.3
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• pp.17-26
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• 2003

Recently, as the internet is widespread rapidly among the public, people can use a variety of useful information services through the internet. Accordingly, the protection of information supplied by computer networks 5 has become a matter of primary concern on the whole world. To accede to the realistic demands, it has been worked out some countermeasures to cultivate the experts in information security by the government and many educational facilities. Already the government authority has carried out the each kinds of concerning projects under the framed a policy, Five-Year Development Plan for Information Security Technology. Also, many domestic universities perceives such an international trend, and so they frame their plans to train for the experts in this field, including to found a department with respect to the information security. They are ready to execute their tangible works, such as establishment of educational goal, development of teaching materials, planning curriculum, construction of laboratories and ensuring instructors. Moreover, such universities lead to their students who want to be information security experts to get the fundamental knowledge to lay the foundation for acquiring the information security technology in their bachelor course. In this note, we survey and analyze the curricula of newly-established or member-extended departments with respect to information security fields of some leading universities in the inside and outside of the country, and in conclusion, we propose the effective model of curriculum and educational goal to train the students for the information security experts.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.801-807
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• 2021

In various industrial fields and infrastructure based on electronic components, such as communication equipment, transportation, computer networks, and military equipment, the need for electromagnetic pulse shielding has increased. Two methods for applying electromagnetic pulse shielding are effective. The first is construction using shielding materials, such as shielding concrete, shielding doors, and shielding windows. The other is coating shielding paints on non-shielding structures. Electromagnetic pulse shielding paints are made using conductive materials, such as carbon nanotubes, graphite, carbon black, and carbon fiber. In this paint, electromagnetic pulse shielding performance is added to the commonly used water-based paint. In this study, the shielding effectiveness and bonding performance of paints using conductive graphite and carbon black as shielding materials were evaluated to develop electromagnetic pulse shielding inorganic paints. The shielding effectiveness and bonding performance were evaluated by applying six mixtures composed of different kinds and amounts of shielding material. The mixture of conductive graphite and carbon black at a weight ratio of 1:0.2 was the most effective in shielding as 33.6 dB. Furthermore, the mixture produced using conductive graphite only showed the highest bonding performance of 1.06 MPa.

• Tunnel and Underground Space
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• v.31 no.6
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• pp.494-507
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• 2021

With the increasing use of TBM, research has recently been conducted in Korea to analyze TBM data with machine learning techniques to predict the ground in front of TBM, predict the exchange cycle of disk cutters, and predict the advance rate of TBM. In this study, classification prediction of rock characteristics of slurry shield TBM sites was made by combining traditional rock classification techniques and machine learning techniques widely used in various fields with machine data during TBM excavation. The items of rock characteristic classification criteria were set as RQD, uniaxial compression strength, and elastic wave speed, and the rock conditions for each item were classified into three classes: class 0 (good), 1 (normal), and 2 (poor), and machine learning was performed on six class algorithms. As a result, the ensemble model showed good performance, and the LigthtGBM model, which showed excellent results in learning speed as well as learning performance, was found to be optimal in the target site ground. Using the classification model for the three rock characteristics set in this study, it is believed that it will be possible to provide rock conditions for sections where ground information is not provided, which will help during excavation work.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1183-1193
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• 2021

Low flow affects various fields such as river water supply management and planning, and irrigation water. A sufficient period of flow data is required to calculate the Flow Duration Curve. However, in order to calculate the Flow Duration Curve, it is essential to secure flow data for more than 30 years. However, in the case of rivers below the national river unit, there is no long-term flow data or there are observed data missing for a certain period in the middle, so there is a limit to calculating the Flow Duration Curve for each river. In the past, statistical-based methods such as Multiple Regression Analysis and ARIMA models were used to predict sulfur in the unmeasured watershed, but recently, the demand for machine learning and deep learning models is increasing. Therefore, in this study, we present the DNN technique, which is a machine learning technique that fits the latest paradigm. The DNN technique is a method that compensates for the shortcomings of the ANN technique, such as difficult to find optimal parameter values in the learning process and slow learning time. Therefore, in this study, the Flow Duration Curve applicable to the unmeasured watershed is calculated using the DNN model. First, the factors affecting the Flow Duration Curve were collected and statistically significant variables were selected through multicollinearity analysis between the factors, and input data were built into the machine learning model. The effectiveness of machine learning techniques was reviewed through statistical verification.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.3
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• pp.241-264
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• 2022

Bibliographic metadata can help researchers effectively utilize essential publications that they need and grasp academic trends of their own fields. With the manual creation of the metadata costly and time-consuming. it is nontrivial to effectively automatize the metadata construction using rule-based methods due to the immoderate variety of the article forms and styles according to publishers and academic societies. Therefore, this study proposes a two-step extraction process based on rules and deep neural networks for generating bibliographic metadata of scientific articlles to overcome the difficulties above. The extraction target areas in articles were identified by using a deep neural network-based model, and then the details in the areas were analyzed and sub-divided into relevant metadata elements. IThe proposed model also includes a model for generating reference summary information, which is able to separate the end of the text and the starting point of a reference, and to extract individual references by essential rule set, and to identify all the bibliographic items in each reference by a deep neural network. In addition, in order to confirm the possibility of a model that generates the bibliographic information of academic papers without pre- and post-processing, we conducted an in-depth comparative experiment with various settings and configurations. As a result of the experiment, the method proposed in this paper showed higher performance.

• Journal of Navigation and Port Research
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• v.45 no.6
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• pp.333-345
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• 2021

Amid the rapidly changing logistics environment and demand changes in the post-corona-19 era, the importance of the cold chain logistics sector is being highlighted. The scope of cold chain is not limited to food, but is expanding to various fields such as pharmaceuticals, semiconductors, and flowers. The demand on the storage and transportation of corona vaccines is rapidly increasing. The rapid increase in domestic low-temperature facility construction and renovation may lead to the saturation of the cold chain related industry in the future and slow growth. In preparation for this, it is necessary to accumulate infrastructure know-how using IT technologies, and to consider entering into the UN procurement market as a potential niche market, by taking advantage of Korea's recent global status. The demand for cold chain in the UN procurement market is increasing mainly in underdeveloped countries, and it is expected to continue to grow. In this paper, the capabilities of domestic cold chain related companies were analyzed, domestic and overseas cold chain logistics market trends and overseas market entry status were investigated. An in-depth survey was conducted to present strategies for domestic cold chain logistics related companies to enter the UN procurement market.

• Land and Housing Review
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• v.14 no.2
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• pp.125-135
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• 2023

Drones are used in various fields, including land survey, transportation, forestry/agriculture, marine, environment, disaster prevention, water resources, cultural assets, and construction, as their industrial importance and market size have increased. In this study, image data for deep learning was collected using a mavic3 drone capturing images at a shooting altitude was 20 m with ×7 magnification. Swin Transformer and UperNet were employed as the backbone and architecture of the deep learning model. About 800 sheets of labeled data were augmented to increase the amount of data. The learning process encompassed three rounds. The Cross-Entropy loss function was used in the first and second learning; the Tversky loss function was used in the third learning. In the future, when the crack detection model is advanced through convergence with the Internet of Things (IoT) through additional research, it will be possible to detect patching or potholes. In addition, it is expected that real-time detection tasks of drones can quickly secure the detection of pavement maintenance sections.

• Journal of Aerospace System Engineering
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• v.16 no.1
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• pp.49-55
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• 2022

The role of drones has been expanded to various fields such as agriculture, construction, and logistics. In particular, agriculture drones are emerging as an effective alternative to solve the problem of labor shortage and reduce the input cost. In this study therefore, we proposed the fruit recognition algorithm and harvesting mechanism for fruit harvesting drone system that can safely harvest fruits at high positions. In the fruit recognition algorithm, we employ "You-Only-Look-Once" which is a deep learning-based object detection algorithm and verify its feasibility by establishing a virtual simulation environment. In addition, we propose the fruit harvesting mechanism which can be operated by a single driving motor. The rotational motion of the motor is converted into a linear motion by the scotch yoke, and the opened gripper moves forward, grips a fruit and rotates it for harvesting. The feasibility of the proposed mechanism is verified by performing Multi-body dynamics analysis.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.212-215
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• 2022

In the era of so-called digital transformation today, the need for the construction and utilization of big data in various fields has increased. Today, a lot of data is produced and stored in a digital device and media-friendly manner, but the production and storage of data for a long time in the past has been dominated by print books. Therefore, the need for Optical Character Recognition (OCR) technology to utilize the vast amount of print books accumulated for a long time as big data was also required in line with the need for big data. In this study, a system for digitizing the structure and content of a document object inside a scanned book image is proposed. The proposal system largely consists of the following three steps. 1) Recognition of area information by document objects (table, equation, picture, text body) in scanned book image. 2) OCR processing for each area of the text body-table-formula module according to recognized document object areas. 3) The processed document informations gather up and returned to the JSON format. The model proposed in this study uses an open-source project that additional learning and improvement. Intelligent OCR proposed as a system in this study showed commercial OCR software-level performance in processing four types of document objects(table, equation, image, text body).