• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.510-514
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• 1994

This paper deals with an application of neural network to camera calibration with wide angle lens and 2-D range finding. Wide angle lens has an advantage of having wide view angles for mobile environment recognition ans robot eye in hand system. But, it has severe radial distortion. Multilayer neural network is used for the calibration of the camera considering lens distortion, and is trained it by error back-propagation method. MLP can map between camera image plane and plane the made by structured light. In experiments, Calibration of camers was executed with calibration chart which was printed by using laser printer with 300 d.p.i. resolution. High distortion lens, COSMICAR 4.2mm, was used to see whether the neural network could effectively calibrate camera distortion. 2-D range of several objects well be measured with laser range finding system composed of camera, frame grabber and laser structured light. The performance of 3-D range finding system was evaluated through experiments and analysis of the results.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.35 no.11
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• pp.487-494
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• 1986

This paper is concerned with the techniques of error check and reduction of state diagram using logic programming. Error check program aims to check not only syntax errors but also semantic errors. And reduction program optimizes the state diagram by finding the redundant equivalence states and removing those from the set of states. The input of both program is state diagram represented as state table form. The output of error check program is error comment. The output of reduction program is equivalence reduced state table. Both programs are implemented using prolog. Prolog has very powerful pattern matching, and its automatic back-tracking capabilities facilitate easy-to-write error check and reduction programs.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.5
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• pp.915-927
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• 1997

In this paper, we propose an error concealment technique using directional interpolation in block-based image compression. In the proposed method the edge direction is determined by finding the maximum correlation coefficients of boundary pixels of blocks neighboring the errored block in spatial domain. Then the errored block is interpolated linearly or bilinearly along the determined edge direction. The proposed method can conceal the block error, the macro block error, and the slice error adaptively. Also, the parameters for the directional interpolation are represented by closed forms. When applied to compressed images, the proposed method shows superior subjective and objective quality to conventional error concealment methods.

• Electronics and Telecommunications Trends
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• v.38 no.5
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• pp.34-50
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• 2023

Quantum error correction is a key technology for achieving fault-tolerant quantum computation. Finding the best decoding solution to a single error syndrome pattern counteracting multiple errors is an NP-hard problem. Consequently, error decoding is one of the most expensive processes to protect the information in a logical qubit. Recent research on quantum error decoding has been focused on developing conventional and neural-network-based decoding algorithms to satisfy accuracy, speed, and scalability requirements. Although conventional decoding methods have notably improved accuracy in short codes, they face many challenges regarding speed and scalability in long codes. To overcome such problems, machine learning has been extensively applied to neural-network-based error decoding with meaningful results. Nevertheless, when using neural-network-based decoders alone, the learning cost grows exponentially with the code size. To prevent this problem, hierarchical error decoding has been devised by combining conventional and neural-network-based decoders. In addition, research on quantum error decoding is aimed at reducing the spacetime decoding cost and solving the backlog problem caused by decoding delays when using hardware-implemented decoders in cryogenic environments. We review the latest research trends in decoders for quantum error correction with high accuracy, neural-network-based quantum error decoders with high speed and scalability, and hardware-based quantum error decoders implemented in real qubit operating environments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.1C
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• pp.8-13
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• 2011

In this paper, we show new method to find error locations of 2 eight bit symbol errors for 2 error correcting Reed-Solomon decoder. New design is much faster and has much simpler logic circuit than the former design method. This optimization was possible by partitioning the 8 bit operations into 4 bit arithgmatic and logic operations. This Reed Solomon decoder can be used for data protection of almost all digital communication and consumer electronic devices.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.1817-1827
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• 2009

Although human error is recognized as the primary cause of railway accidents and incidents, there have been limitations in finding the root causes of errors and developing effective corrective actions in the Korean railway industry, due to the absence of a systematic method and lack of professional knowledge and skills of investigators. Therefore, there has been a strong need for a systematic methodology for human error analysis. This paper introduces a methodology for analyzing human error m railway operations, called HEAR (Human Error Analysis and Reduction). HEAR is intended to help analysts identify the sequences and various levels of causes of operators' erroneous actions in railway accidents or incidents and make recommendations to eliminate or reduce the future possibility of similar errors and accidents. It was developed based on a thorough investigation of various techniques for human errors analysis and feedback from field investigators.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.4
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• pp.8-14
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• 2008

This paper aims at finding out dominant robot configurations with maximal position errors, which can be attributed to the parameter errors, by using Monte-Carlo simulation for error analysis of a 3-axis SCARA(Selective Compliance Assembly Robot Arm) type robot. In particular, the Monte-Carlo simulation is used for virtually measuring on the position errors, instead of physical measurement. In order to measure the observability of the model parameters with respect to a set of robot configurations, we propose the observability index which is defined as the product of singular values for error propagation matrices. Thus the index can be used for discriminating dominant robot configurations from a set of simulated ones in conjunction with standard deviation of positional errors, This paper analyzed error by robot positional error.

• ETRI Journal
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• v.29 no.5
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• pp.569-595
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• 2007

Particularly in wireless communications, link errors severely affect the quality of the services due to the high error probability and the specific error characteristics (burst errors) in the radio access part of the network. In this work, we show that thorough analysis and appropriate modeling of radio-link error behavior are essential to evaluate and optimize higher layer protocols and services. They are also the basis for finding network-aware cross-layer processing algorithms which are capable of exploiting the specific properties of the link error statistics, such as predictability. This document presents the analysis of the radio link errors based on measurements in live Universal Mobile Telecommunication System (UMTS) radio access networks as well as new link error models originating from that analysis. It is shown that the knowledge of the specific link error characteristics leads to significant improvements in the quality of streamed video by applying the proposed novel network- and content-aware cross-layer scheduling algorithms. Although based on live UMTS network experience, many of the conclusions in this work are of general validity and are not limited to UMTS only.

• Asia-Pacific Journal of Business
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• v.13 no.4
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• pp.163-175
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• 2022

Purpose - This study introduces a methodology for finding the optimal tracking error of active stock funds. Tracking error is commonly used in risk budgeting techniques as a concept of cost for alpha creation. Design/methodology/approach - This study uses a post-optimal smart beta portfolio that maximizes alpha under the given tracking error constraint. Findings - As a result of the analysis, the smart beta strategy that maximized alpha under the constraint of 0.15% daily tracking error shows the highest IR. This means the maximum theoretically achievable efficiency. In this regard, a fixed-effect panel regression analysis is conducted to evaluate the active efficiency of domestic stock funds. In addition to control variables based on previous studies, the effect of tracking error on alpha is analyzed. The alpha used in this model is calculated using the smart beta portfolio according to the size of the constraint of the tracking error as a benchmark. Contrary to theoretical estimates, in Korea, the alpha performance is maximized under a daily tracking error of 0.1%. This indicates that the active efficiency of domestic equity funds is lower than the theoretical maximum. Research implications or Originality - Based on this study, it is expected that it can be used for active risk management of pension funds and performance evaluation of active strategies.

• The Journal of Korea Robotics Society
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• v.6 no.4
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• pp.334-343
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• 2011

This paper presents a new approach for mobile robot heading detection using MEMS Gyro north finding method in the indoor environment. Based on this, the robot heading angle measurement scheme is proposed; improved north finding theory and algorithm are also explained. Several approaches are applied to confirm system's precision and effectiveness. In order to find out the heading angle, a single axis MEMS gyroscope to sense the angle between the robot heading direction and the north is used. To reach enough estimation accuracy and reduce detection time, the least square method (LSM) for the signal fitting and parameter estimation is applied. Through a turn-table, we setup a carouseling system to decrease the substantial bias effect on gyroscope's heading angle. For the evaluation of the proposed method, this system is implemented to the Pioneer robot platform. The performance and heading error are analyzed after the test. From the simulation and experimental results, system's accuracy, usefulness and adaptability are shown.