• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.16-22
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• 2019

Off-line programming and robot calibration through simulation are essential when setting up a robot in a robot automation production line. In this study, we developed a new robot calibration method to match the CAD data of the production line with the measurement data on the site using 3D scanner. The proposed method calibrates the robot using 3D point cloud data through Iterative Closest Point algorithm. Registration is performed in three steps. First, vertices connected by three planes are extracted from CAD data as feature points for registration. Three planes are reconstructed from the scan point data located around the extracted feature points to generate corresponding feature points. Finally, the transformation matrix is calculated by minimizing the distance between the feature points extracted through the ICP algorithm. As a result of applying the software to the automobile welding robot installation, the proposed method can calibrate the required accuracy to within 1.5mm and effectively shorten the set-up time, which took 5 hours per robot unit, to within 40 minutes. By using the developed system, it is possible to shorten the OLP working time of the car body assembly line, shorten the precision teaching time of the robot, improve the quality of the produced product and minimize the defect rate.

• Journal of KIISE:Software and Applications
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• v.34 no.9
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• pp.817-827
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• 2007

In the age of ubiquitous environment, huge number of devices and computing services are provided to users. Personalized service, which is modeled according to the character of each and every individual is of particular need. In order to provide various dynamic services according to user's movement, service unit and operating mode should be able to operate automatically with minimum user intervention. In this paper, we discuss the steps of offering approximate service based on user's request in ubiquitous environment. First, we present our simulator designed for modeling the physical resource and computing object in smart space - the infrastructure in ubiquitous. Second, intelligent agents, which we developed based on a FIPA specification compliant multi-agent framework will be discussed. These intelligent agents are developed for achieving the service goal through cooperation between distributed agents. Third, we propose an automated service discovery and composition method in heterogeneous environment using semantic message communication between agents, according to the movement by the user interacting with the service available in the smart space. Fourth, we provide personalized service through agent monitoring anytime, anywhere from user's profile information stored on handhold device. Therefore, our research provides high quality service more than general automated service operation.

• Journal of KIISE:Software and Applications
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• v.31 no.5
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• pp.586-594
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• 2004

Because web documents become creation and disappearance rapidly, users require the recommend system that offers users to browse the web document conveniently and correctly. One largely untapped source of knowledge about large data collections is contained in the cumulative experiences of individuals finding useful information in the collection. Recommendation systems attempt to extract such useful information by capturing and mining one or more measures of the usefulness of the data. The existing Information Filtering system has the shortcoming that it must have user's profile. And Collaborative Filtering system has the shortcoming that users have to rate each web document first and in high-quantity, low-quality environments, users may cover only a tiny percentage of documents available. And dynamic recommendation system using the user browsing pattern also provides users with unrelated web documents. This paper classifies these web documents using the similarity between the web documents under the web document type and extracts the user browsing sequential pattern DB using the users' session information based on the web server log file. When user approaches the web document, the proposed Dynamic recommendation system recommends Top N-associated web documents set that has high similarity between current web document and other web documents and recommends set that has sequential specificity using the extracted informations and users' session information.

• Journal of KIISE:Software and Applications
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• v.27 no.8
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• pp.864-876
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• 2000

This paper proposes a new scene boundary detection scheme for the MPEG System stream using MPEG Audio information and proves its usefulness by extensive experiments. A scene boundary has a characteristic that the audio as well as video information are changed rapidly. This paper first classifies this scene boundary into three cases ; Radical, Gradual, Micro Changes, with respect to the audio changes. The Radical change has a large-scale changing of decibel value and pitch value at a scene boundary, the Gradual change shows the long-time transition of decibel and pitch values from max to min or vice versa, and the Micro change displays a some change of pitch or frequency distribution without decibel changes. Upon this analysis, a new scene change detection algorithm detecting these three cases is proposed in which a progressive window with a time line is used to trace the changes in the audio information. Some experiments with various movies show that proposed algorithm could produce a high detection ratio for Radical change that is the most popular scene change in the movies, while producing a moderate detection ratio for Gradual and Micro changes. The proposed scene boundary detection scheme could be used to build a database for visual information like MPEG System stream.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.4
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• pp.133-142
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• 2021

With the recent advancements of deep learning, companies such as smart home, healthcare, and intelligent transportation systems are utilizing its functionality to provide high-quality services for vehicle detection, emergency situation detection, and controlling energy consumption. To provide reliable services in such sensitive systems, deep learning models are required to have high accuracy. In order to develop a deep learning model for analyzing previously mentioned services, developers should utilize the state of the art deep learning models that have already been verified for higher accuracy. The developers can verify the accuracy of the referenced model by validating the model on the dataset. For this validation, the developer needs structural information to document and apply deep learning models, including metadata such as learning dataset, network architecture, and development environments. In this paper, we propose a description language that represents the network architecture of the deep learning model along with its metadata that are necessary to develop a deep learning model. Through the proposed description language, developers can easily verify the accuracy of the referenced deep learning model. Our experiments demonstrate the application scenario of a deep learning description document that focuses on the license plate recognition for the detection of illegally parked vehicles.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.5
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• pp.211-220
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• 2022

Recently, research on smart factories triggered by the 4th industrial revolution is being actively conducted. Accordingly, the manufacturing industry is conducting various studies to improve productivity and quality based on deep learning technology with robust performance. This paper is a study on the method of detecting tire surface defects in the visual inspection stage of the tire manufacturing process, and introduces a tire surface defect detection method using a depth image acquired through a 3D camera. The tire surface depth image dealt with in this study has the problem of low contrast caused by the shallow depth of the tire surface and the difference in the reference depth value due to the data acquisition environment. And due to the nature of the manufacturing industry, algorithms with performance that can be processed in real time along with detection performance is required. Therefore, in this paper, we studied a method to normalize the depth image through relatively simple methods so that the tire surface defect detection algorithm does not consist of a complex algorithm pipeline. and conducted a comparative experiment between the general normalization method and the normalization method suggested in this paper using YOLO V3, which could satisfy both detection performance and speed. As a result of the experiment, it is confirmed that the normalization method proposed in this paper improved performance by about 7% based on mAP 0.5, and the method proposed in this paper is effective.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.149-158
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• 2023

As data utilization is becoming more important recently, the importance of data centers is also increasing. However, the data center is a problem in terms of environment and economy because it is a massive power-consuming facility that runs 24 hours a day. Recently, studies using deep learning techniques to reduce power used in data centers or servers or predict traffic have been conducted from various perspectives. However, the amount of traffic data processed by the server is anomalous, which makes it difficult to manage the server. In addition, many studies on dynamic server management techniques are still required. Therefore, in this paper, we propose a dynamic server management technique based on Long-Term Short Memory (LSTM), which is robust to time series data prediction. The proposed model allows servers to be managed more reliably and efficiently in the field environment than before, and reduces power used by servers more effectively. For verification of the proposed model, we collect transmission and reception traffic data from six of Wikipedia's data centers, and then analyze and experiment with statistical-based analysis on the relationship of each traffic data. Experimental results show that the proposed model is helpful for reliably and efficiently running servers.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.1
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• pp.21-28
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• 2016

The performance of an English-Korean machine translation system depends heavily on its English parser. The parser in this paper is a part of the rule-based English-Korean MT system, which includes many syntactic rules and performs the chart-based parsing. The parser generates too many structures due to many syntactic rules, so much time and memory are required. The rule-based parser has difficulty in analyzing and translating the long sentences including the commas because they cause high parsing complexity. In this paper, we propose the 3-phase parsing method with sentence segmentation to efficiently translate the long sentences appearing in usual. Each phase of the syntactic analysis applies its own independent syntactic rules in order to reduce parsing complexity. For the purpose, we classify the syntactic rules into 3 classes and design the 3-phase parsing algorithm. Especially, the syntactic rules in the 3rd class are for the sentence structures composed with commas. We present the automatic rule acquisition method for 3rd class rules from the syntactic analysis of the corpus, with which we aim to continuously improve the coverage of the parsing. The experimental results shows that the proposed 3-phase parsing method is superior to the prior parsing method using only intra-sentence segmentation in terms of the parsing speed/memory efficiency with keeping the translation quality.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.10
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• pp.465-472
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• 2015

We propose a novel plane detection in disparity space and evaluate its performance. Our method simplifies and makes scenes in disparity space easily dealt with by approximating various surfaces as planes. Moreover, the approximated planes can be represented in the same size as in the real world, and can be employed for obstacle detection and camera pose estimation. Using a stereo matching technique, our method first creates a disparity image which consists of binocular disparity values at xy-coordinates in the image. Slants of disparity values are estimated by exploiting a line simplification algorithm which allows our method to reflect global changes against x or y axis. According to pairs of x and y slants, we label the disparity image. 4-connected disparities with the same label are grouped, on which least squared model estimates plane parameters. N plane models with the largest group of disparity values which satisfy their plane parameters are chosen. We quantitatively and qualitatively evaluate our plane detection. The result shows 97.9%와 86.6% of quality in our experiment respectively on cones and cylinders. Proposed method excellently extracts planes from Middlebury and KITTI dataset which are typically used for evaluation of stereo matching algorithms.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.6
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• pp.243-250
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• 2019

Because of a moving UAV has a lot of potential/kinetic energy, if the UAV falls to the ground, it may have a lot of impact. Because this can lead to human casualities, in this paper, the population density area on the UAV flight path is defined as a dangerous area. The conventional UAV path flight was a passive form in which a UAV moved in accordance with a path preset by a user before the flight. Some UAVs include safety features such as a obstacle avoidance system during flight. Still, it is difficult to respond to changes in the real-time flight environment. Using public Big Data for UAV path flight can improve response to real-time flight environment changes by enabling detection of dangerous areas and avoidance of the areas. Therefore, in this paper, we propose a method to detect and avoid dangerous areas for UAVs by utilizing the Big Data collected in real-time. If the routh is designated according to the destination by the proposed method, the dangerous area is determined in real-time and the flight is made to the optimal bypass path. In further research, we will study ways to increase the quality satisfaction of the images acquired by flying under the avoidance flight plan.