• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1615-1627
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• 2020

The purpose of this study is to compare and analyze the performance of KOMPSAT-3 Digital Surface Model (DSM) made in overseas testbed area. To that end, we collected the KOMPSAT-3 in-track stereo image taken in San Francisco, the U.S. The stereo geometry elements (B/H, converse angle, etc.) of the stereo image taken were all found to be in the stable range. By applying precise sensor modeling using Ground Control Point (GCP) and DSM automatic generation technique, DSM with 1 m resolution was produced. Reference materials for evaluation and calibration are ground points with accuracy within 0.01 m from Compass Data Inc., 1 m resolution Elevation 1-DSM produced by Airbus. The precision sensor modeling accuracy of KOMPSAT-3 was within 0.5 m (RMSE) in horizontal and vertical directions. When the difference map was written between the generated DSM and the reference DSM, the mean and standard deviation were 0.61 m and 5.25 m respectively, but in some areas, they showed a large difference of more than 100 m. These areas appeared mainly in closed areas where high-rise buildings were concentrated. If KOMPSAT-3 tri-stereo images are used and various post-processing techniques are developed, it will be possible to produce DSM with more improved quality.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.349-359
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• 2022

The purpose of this study is to add and revalidate items of learning cognition and learning emotion factors for online use of the K-LSS for junior college. It is important for self-reflection and improvement of academic achievement to specifically explore and analyze the sub-factors of learning cognition, learning behavior, and learning emotion for each item that can affect the learning strategy of junior college students. The added items are two items for diagnosing the concentration of attention in the learning information processing process of the learning cognitive factor and two questions about the interpersonal anxiety factor for diagnosing the level of anxiety about others in the learning emotional factor. The study area was conducted in 5 areas nationwide, and the subjects of the study were 923 junior college students excluding 327 respondents who answered insincerity. The K-LSS_r scale is a learning strategy diagnosis scale of 52 questions composed of three sub-elements of learning cognition (18 questions), learning emotion (15 questions), and learning behavior (19 questions), and reliability for generalization in this study. As a result of the verification, Cronbach's α coefficient of the entire scale was .896, and Cronbach's α coefficient of the three factors ranged from .876 to .910. The half-segment reliability coefficient of the scale was .858 in total, and the half-segment reliability coefficients of the three factors ranged from .792 to .843. The test-retest reliability verification result for 3 weeks for 350 Junior college Students in 5 regions was .884, and the validity test for generalization also confirmed that the recruitment validity is significant.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.7
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• pp.233-240
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• 2022

Most of the recent AI researches has focused on developing AI models. However, recently, artificial intelligence research has gradually changed from model-centric to data-centric, and the importance of learning data is getting a lot of attention based on this trend. However, it takes a lot of time and effort because the preparation of learning data takes up a significant part of the entire process, and the generation of labeling data also differs depending on the purpose of development. Therefore, it is need to develop a tool with various labeling functions to solve the existing unmetneeds. In this paper, we describe a labeling system for creating precise and fast labeling data of medical images. To implement this, a semi-automatic method using Back Projection, Grabcut techniques and an automatic method predicted through a machine learning model were implemented. We not only showed the advantage of running time for the generation of labeling data of the proposed system, but also showed superiority through comparative evaluation of accuracy. In addition, by analyzing the image data set of about 1,000 patients, meaningful diagnostic indexes were presented for men and women in the diagnosis of sarcopenia.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.429-435
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• 2021

The integrated underground space map shows the underground facility(water supply, sewage, gas, electric power, communication, heating), underground structures (subway, underpass, underground walkway, underground parking lot, underground shopping mall, common ward), ground(drilling, coffin, geology) refers to a map constructed so that a total of 15 types of underground information can be checked at a glance on a three-dimensional basis. The purpose of this study is to develop a technology to correct the problem of curved surface processing and the unevenness of underground facility pipelines that occur in converting 2D underground facility data into 3D-based underground space integrated map(3D underground facility model). do it with. To this end, we first investigated and reviewed the domestic and foreign status of technologies that generate data on underground facilities based on three dimensions, and developed a surface correction algorithm and an unevenness correction algorithm to solve practical problems. Algorithms to verify the developed algorithm This applied correction program was developed. Based on the above process, the three-dimensional model of the underground facility could be produced identically to reality. This study is judged to have significance as a basic study to improve the utilization of the underground spatial integration map.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.323-332
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• 2022

As various services using AI technology are being developed, much attention is being paid to AI service production. Recently, AI technology is acknowledged as one of ICT services, a lot of research is being conducted for general-purpose AI service production. In this paper, I describe the research results in terms of systems for AI service production, focusing on the distribution and production of machine learning models, which are the final steps of general machine learning development procedures. Three different Ubuntu systems were built, and experiments were conducted on the system, using data from 2017 validation COCO dataset in combination of different AI models (RFCN, SSD-Mobilenet) and different communication methods (gRPC, REST) to request and perform AI services through Tensorflow serving. Through various experiments, it was found that the type of AI model has a greater influence on AI service inference time than AI machine communication method, and in the case of object detection AI service, the number and complexity of objects in the image are more affected than the file size of the image to be detected. In addition, it was confirmed that if the AI service is performed remotely rather than locally, even if it is a machine with good performance, it takes more time to infer the AI service than if it is performed locally. Through the results of this study, it is expected that system design suitable for service goals, AI model development, and efficient AI service production will be possible.

• Journal of Korean Society of Disaster and Security
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• v.15 no.3
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• pp.79-88
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• 2022

Cable-supported bridges, as important large infrastructures, require a long-term and systematic maintenance strategy. In particular, various methods have been proposed to secure safety for the bridges, such as installing various types of sensor on members in the bridges, and setting management thresholds. It is evidently necessary to propose a strategic plan to efficiently manage increasing number of cable-supported bridges and data collected from a number of sensors. This study aims to develop an analysis tool that can automatically remove abnormal signals and calculate statistical results for the purpose of efficiently analyzing a wide range of data collected from a long span bridge measurement system. To develop the tool, basic information such as the types and quantity of sensors installed in long span bridges and signal characteristics of the collected data were analyzed. Thereafter, the Humpel filtering method was used to determine the presence or absence of an abnormality in the signal and then filtered. The statistical results with filtered data were shown. Finally, one cable-stayed bridge and one suspension bridge currently in use were chosen as the target bridges to verify the performance of the developed tool. Signal processing and statistical analysis with the tool were performed. The results are similar to the results reported in the existing work.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.381-386
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• 2023

Many existing test case generation researchers extract test cases from models. However, research on generating test cases from natural language requirements is required in practice. For this purpose, the combination of natural language analysis and requirements engineering is very necessary. However, Requirements analysis written in Korean is difficult due to the diverse meaning of sentence expressions. We research test case generation through natural language requirement definition analysis, C3Tree model, cause-effect graph, and decision table steps as one of the test case generation methods from Korean natural requirements. As an intermediate step, this paper generates test cases from C3Tree model-based decision tables using meta-modeling. This method has the advantage of being able to easily maintain the model-to-model and model-to-text transformation processes by modifying only the transformation rules. If an existing model is modified or a new model is added, only the model transformation rules can be maintained without changing the program algorithm. As a result of the evaluation, all combinations for the decision table were automatically generated as test cases.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.3
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• pp.141-148
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• 2023

Accurate overlay metrology is essential to achieve high yields of semiconductor products. Overlay metrology performance is greatly affected by overlay target design and measurement method. Therefore, in order to improve the performance of the overlay target, measurement methods applicable to various targets are required. In this study, we propose a new algorithm that can measure image-based overlay. The proposed measurement algorithm can estimate the sub-pixel position by using a motion vector. The motion vector may estimate the position of the sub-pixel unit by applying a quadratic equation model through polynomial expansion using pixels in the selected region. The measurement method using the motion vector can calculate the stacking error in all directions at once, unlike the existing correlation coefficient-based measurement method that calculates the stacking error on the X-axis and the Y-axis, respectively. Therefore, more accurate overlay measurement is possible by reflecting the relationship between the X-axis and the Y-axis. However, since the amount of computation is increased compared to the existing correlation coefficient-based algorithm, more computation time may be required. The purpose of this study is not to present an algorithm improved over the existing method, but to suggest a direction for a new measurement method. Through the experimental results, it was confirmed that measurement results similar to those of the existing method could be obtained.

• The Korean Journal of Franchise Management
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• v.2 no.2
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• pp.70-83
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• 2011

The number of agricultural products due to open in response to international competitiveness of the farming press and the need for structural adjustment in agriculture and in agricultural crops receive a fair market price, fair trade, such as improving efficiency sidaejeo appropriate response to the request of the government must have. For this purpose, compared to the communist bojaphan agricultural water efficiently changing the structure of the distribution, agricultural products originating from the acquisition phase choice of shipping a stable product supply and plans to expand production system to induce a smooth supply of agricultural products, expand processing capacity and sales control should be. Also, in the distribution process by eliminating various immoral conduct commerce retail establishment and enforcement of policies for efficient and accurate distribution statistics, information is needed. The ultimate goal of agricultural restructuring and ensure fair price for producers sangpuui and improvement of production facilities for maximizing and affordable for consumers, according to your preferences to receive the best offer will be Foo. Therefore, management increases the efficiency of just distribution costs, or margins, lowering the improvement is not practical to restructure the distribution structure of costs for the best product and must supply the next country of agricultural products, strengthen the consumer's purchase desire to meet will be.

• Asia Marketing Journal
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• v.13 no.1
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• pp.113-141
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• 2011

Companies are competing each other, and as the competitions became higher, consumer's information processing for purchase became more complicated. Consumer confusion problem is getting more serious, but there are still not much considerations on this problem. The purpose of this study is to find out that the consumer confusion can causes consumer's negative emotion(anger). This research studied the mediation effect of negative emotion on the relationship between consumer confusion, which was classified into three categories, and two consequences, word-of-mouth and trust. And also it concentrates on moderating effects of negative affectivity and intolerance of uncertainty in the relationship between consumer confusion and negative emotion. For the empirical study, we carried out a survey targeting consumers who live in the Dae-gu metropolitan area. The specific results of this study are as follows. First, all sub-dimensions of the consumer confusion had a positive effect on anger. Second, anger had a positive effect on word of mouth and on the other hand, anger had a negative effect on trust. Third, negative affectivity had a moderating effects on the links between overload and ambiguity confusion with anger, and intolerance of uncertainty only had a moderating effects on the links between overload confusion and anger.