• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2004.10a
• /
• pp.596-599
• /
• 2004

The robotic $CO_2$ welding is a manufacturing process to produce high quality joints for metal and it could provide a capability of full automation to enhance productivity. Despite the widespread use in the various manufacturing industries, the full automation of the robotic $CO_2$ welding has not yet been achieved partly because the mathematical model for the process parameters of a given welding task is not fully understood and quantified. Several mathematical models to control welding quality, productivity, microstructure and weld properties in arc welding processes have been studied. However, it is not an easy task to apply them to the various practical situations because the relationship between the process parameters and the bead geometry is non-linear and also they are usually dependent on the specific experimental results. Practically, it is difficult, but important to know how to establish a mathematical model that can predict the result of the actual welding process and how to select the optimum welding condition under a certain constraint. In this research, an attempt has been made to develop an intelligent algorithm to predict the weld geometry (top-bead width, top-bead height, back-bead width and back-bead height) as a function of key process parameters in the robotic $CO_2$welding. To achieve this above objective, Taguchi method was employed using five different process parameters (tip gap, gas flow rate, welding speed, arc current, welding voltage) as a guide for optimization of process parameters.

• Wind and Structures
• /
• v.18 no.6
• /
• pp.693-715
• /
• 2014

Stochastic processes are used to represent phenomena in many diverse fields. Numerical simulation method is widely applied for the solution to stochastic problems of complex structures when alternative analytical methods are not applicable. In some practical applications the stochastic processes show non-Gaussian properties. When the stochastic processes deviate significantly from Gaussian, techniques for their accurate simulation must be available. The various existing simulation methods of non-Gaussian stochastic processes generally can only simulate super-Gaussian stochastic processes with the high-peak characteristics. And these methodologies are usually complicated and time consuming, not sufficiently intuitive. By revealing the inherent coupling effect of the phase and amplitude part of discrete Fourier representation of random time series on the non-Gaussian features (such as skewness and kurtosis) through theoretical analysis and simulation experiments, this paper presents a novel approach for the simulation of non-Gaussian stochastic processes with the prescribed amplitude probability density function (PDF) and power spectral density (PSD) by amplitude modulation and phase reconstruction. As compared to previous spectral representation method using phase modulation to obtain a non-Gaussian amplitude distribution, this non-Gaussian phase reconstruction strategy is more straightforward and efficient, capable of simulating both super-Gaussian and sub-Gaussian stochastic processes. Another attractive feature of the method is that the whole process can be implemented efficiently using the Fast Fourier Transform. Cases studies demonstrate the efficiency and accuracy of the proposed algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2010.05a
• /
• pp.245-249
• /
• 2010

In the stereo vision system, information about an object could be gained by searching through images. Edges which are based on the information about an object are used to find the position of the object and send a message of its position coordinate to a unmanned crain. This thesis proposes an algorithm to find the center point of the object's surface which is connected to the unmanned crain's arm, and to recognize the shape of the object by using two CCD cameras. At first, getting information about the edges, and distinguishing each edge's characteristics depend on user's option, and then find the location information by a set of positions that are proposed. This thesis is expected to be devoted to the development of an automation system of unmanned moving equipment.

• Journal of the Korean Institute of Gas
• /
• v.2 no.3
• /
• pp.49-53
• /
• 1998

It takes quite a long time for an analyzer, such as gas chromatography, to measure a bulk property of a system, which prevents on-line measurements. Also, the cost of installation and maintenance is very high. Consequently, some other means is needed for on-line measurements of properties and the development of soft sensors based on process variables like temperature and pressure is of great interest. In the field of gas industry, the development of a soft sensor which makes indirect on-line measurements of gas compositions and flow rate, is in progress. In this paper, we proposed a hybrid inner model PLS which improved the prediction performance by taking into account the data structure, as an empirical modeling algorithm. When applied to a design of a soft sensor of a distillation tower, the hybrid inner model PLS showed better prediction performance than other methods.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.4
• /
• pp.523-529
• /
• 2021

In the era of the Fourth Industrial Revolution, technological changes are being applied in various fields. Automation digitization and data management are also in the field of bills. There are more than tens of thousands of forms of bills circulating in society and bill recognition is essential for automation, digitization and data management. Currently in order to manage various bills, OCR technology is used for character recognition. In this time, we can increase the accuracy, when firstly recognize the form of the bill and secondly recognize bills. In this paper, a logo that can be used as an index to classify the form of the bill was recognized as an object. At this time, since the size of the logo is smaller than that of the entire bill, FPN was used for Small Object Detection among deep learning technologies. As a result, it was possible to reduce resource waste and increase the accuracy of OCR recognition through the proposed algorithm.

• Journal of the Semiconductor & Display Technology
• /
• v.21 no.4
• /
• pp.65-70
• /
• 2022

In manufacturing and semiconductor industries, transfer robots increase productivity through accurate and continuous work. Due to the nature of the semiconductor process, there are environments where humans cannot intervene to maintain internal temperature and humidity in a clean room. So, transport robots take responsibility over humans. In such an environment where the manpower of the process is cutting down, the lack of maintenance and management technology of the machine may adversely affect the production, and that's why it is necessary to develop a technology for the machine failure diagnosis system. Therefore, this paper tries to identify various causes of failure of transport robots that are widely used in semiconductor automation, and the Prognostics and Health Management (PHM) method is considered for determining and predicting the process of failures. The robot mainly fails in the driving unit due to long-term repetitive motion, and the core components of the driving unit are motors and gear reducer. A simulation drive unit was manufactured and tested around this component and then applied to 6-axis vertical multi-joint robots used in actual industrial sites. Vibration data was collected for each cause of failure of the robot, and then the collected data was processed through signal processing and frequency analysis. The processed data can determine the fault of the robot by utilizing machine learning algorithms such as SVM (Support Vector Machine) and KNN (K-Nearest Neighbor). As a result, the PHM environment was built based on machine learning algorithms using SVM and KNN, confirming that failure prediction was partially possible.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.9
• /
• pp.25-37
• /
• 2024

This study proposes a novel automation system that integrates Optical Character Recognition (OCR) and Retrieval-Augmented Generation (RAG) technologies to enhance the efficiency of the ESG (Environmental, Social, and Governance) document review process. The proposed system improves text recognition accuracy by applying an ensemble model-based image preprocessing algorithm and hybrid information extraction models in the OCR process. Additionally, the RAG pipeline optimizes information retrieval and answer generation reliability through the implementation of layout analysis algorithms, re-ranking algorithms, and ensemble retrievers. The system's performance was evaluated using certificate images from online portals and corporate internal regulations obtained from various sources, such as the company's websites. The results demonstrated an accuracy of 93.8% for certification reviews and 92.2% for company regulations reviews, indicating that the proposed system effectively supports human evaluators in the ESG assessment process.

• International Journal of Control, Automation, and Systems
• /
• v.6 no.6
• /
• pp.809-817
• /
• 2008

Program plagiarism is widespread due to intelligent software and the global Internet environment. Consequently the detection of plagiarized source code and software is becoming important especially in academic field. Though numerous studies have been reported for detecting plagiarized pairs of codes, we cannot find any profound work on understanding the underlying mechanisms of plagiarism. In this paper, we study the evolutionary process of source codes regarding that the plagiarism procedure can be considered as evolutionary steps of source codes. The final goal of our paper is to reconstruct a tree depicting the evolution process in the source code. To this end, we extend the well-known bioinformatics approach, a local alignment approach, to detect a region of similar code with an adaptive scoring matrix. The asymmetric code similarity based on the local alignment can be considered as one of the main contribution of this paper. The phylogenetic tree or evolution tree of source codes can be reconstructed using this asymmetric measure. To show the effectiveness and efficiency of the phylogeny construction algorithm, we conducted experiments with more than 100 real source codes which were obtained from East-Asia ICPC(International Collegiate Programming Contest). Our experiments showed that the proposed algorithm is quite successful in reconstructing the evolutionary direction, which enables us to identify plagiarized codes more accurately and reliably. Also, the phylogeny construction algorithm is successfully implemented on top of the plagiarism detection system of an automatic program evaluation system.

• International Journal of Control, Automation, and Systems
• /
• v.2 no.1
• /
• pp.107-117
• /
• 2004

A new algorithm for planning a collision-free path based on an algebraic curve as well as the concept of path space is developed. Robot path planning has so far been concerned with generating a single collision-free path connecting two specified points in a given robot workspace with appropriate constraints. In this paper, a novel concept of path space (PS) is introduced. A PS is a set of points that represent a connection between two points in Euclidean metric space. A geometry mapping (GM) for the systematic construction of path space is also developed. A GM based on the 2$^{nd}$ order base curve, specifically Bezier curve of order two is investigated for the construction of PS and for collision-free path planning. The Bezier curve of order two consists of three vertices that are the start, S, the goal, G, and the middle vertex. The middle vertex is used to control the shape of the curve, and the origin of the local coordinate (p, $\theta$) is set at the centre of S and G. The extreme locus of the base curve should cover the entire area of actual workspace (AWS). The area defined by the extreme locus of the path is defined as quadratic workspace (QWS). The interference of the path with obstacles creates images in the PS. The clear areas of the PS that are not mapped by obstacle images identify collision-free paths. Hence, the PS approach converts path planning in Euclidean space into a point selection problem in path space. This also makes it possible to impose additional constraints such as determining the shortest path or the safest path in the search of the collision-free path. The QWS GM algorithm is implemented on various computer systems. Simulations are carried out to measure performance of the algorithm and show the execution time in the range of 0.0008 ~ 0.0014 sec.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.15 no.7
• /
• pp.1510-1516
• /
• 2011

As emergence of the ubiquitous society, it is possible to access the network for services needed to us in anytime and anywhere. The phenomena has been accelerated by revitalization of the sensor network offering the sensing information and data. Currently, sensor network contributes the convenience for various services such as environment monitoring, health care and home automation. However, sensor network has a weak point compared to traditional network, which is easily exposed to attacker. For this reason, messages communicated over the sensor network, are encrypted with symmetric key and transmitted. A number of symmetric cryptography algorithms have been researched. Among of them HIGHT algorithm in hardware and software implementation are more efficient than tradition AES in terms of speed and chip size. Therefore, it is suitable to resource constrained devices including RFID tag, Sensor node and Smart card. In the paper, we present the optimized software implementation on the ultra-light symmetric cryptography algorithm, HIGHT.