• Kyungpook Mathematical Journal
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• v.52 no.2
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• pp.167-177
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• 2012

In this article, we propose exponentially fitted error correction methods(EECM) which originate from the error correction methods recently developed by the authors (see [10, 11] for examples) for solving nonlinear stiff initial value problems. We reduce the computational cost of the error correction method by making a local approximation of exponential type. This exponential local approximation yields an EECM that is exponentially fitted, A-stable and L-stable, independent of the approximation scheme for the error correction. In particular, the classical explicit Runge-Kutta method for the error correction not only saves the computational cost that the error correction method requires but also gives the same convergence order as the error correction method does. Numerical evidence is provided to support the theoretical results.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.4
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• pp.721-728
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• 2018

This paper introduces various linear block error correction code and compares performances of the correction circuits. As the risk of errors due to power noise has increased, ECC(: Error Correction Code) has been introduced to prevent the bit error. There are two representatives of ECC structures which are SEC-DED(: Single Error Correction Double Error Detection) and SEC-DED-DAEC(: Double Adjacent Error Correction). According to simulation results, the SEC-DED circuit has advantages of small area and short delay time compared to SEC-DED-DAEC circuits. In case of SED-DED-DAEC, there is no big difference between Dutta's and Pedro's from performance point of view. Therefore, Pedro's code is more efficient than Dutta' code since the correction rate of Pedro's code is higher than that of Dutta's code.

• International Journal of Knowledge Content Development & Technology
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• v.5 no.2
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• pp.75-101
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• 2015

In this paper, we investigate the notion of error correction memory applied to technical texts. The main purpose is to introduce flexibility and context sensitivity in the detection and the correction of errors related to Constrained Natural Language (CNL) principles. This is realized by enhancing error detection paired with relatively generic correction patterns and contextual correction recommendations. Patterns are induced from previous corrections made by technical writers for a given type of text. The impact of such an error correction memory is also investigated from the point of view of the technical writer's cognitive activity. The notion of error correction memory is developed within the framework of the LELIE project an experiment is carried out on the case of fuzzy lexical items and negation, which are both major problems in technical writing. Language processing and knowledge representation aspects are developed together with evaluation directions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1559-1562
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• 2022

As electronic devices technology scales down into the deep-submicron to achieve high-density, low power and high performance integrated circuits, multiple bit upsets by soft errors have become a major threat to on-chip memory systems. To address the soft error problem, single error correction, double error detection and double adjacent error correction (SEC-DED-DAEC) codes have been recently proposed. But these codes do not troubleshoot mis-correction problem. We propose the SEC-DED_DAEC code with without mis-correction. The decoder for proposed code is implemented as hardware and verified. The results show that there is no mis-correction in the proposed codes and the decoder can be employed on-chip memory system.

• Journal of the Semiconductor & Display Technology
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• v.19 no.3
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• pp.112-117
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• 2020

NAND flash memory is a non-volatile memory that retains stored data even without power supply. Internal memory used as a data storage device and solid-state drive (SSD) is used in portable devices such as smartphones and digital cameras. However, NAND flash memory carries the risk of electric shock, which can cause errors during read/write operations, so use error correction codes to ensure reliability. It efficiently recovers bad block information, which is a defect in NAND flash memory. BBT (Bad Block Table) is configured to manage data to increase stability, and as a result of experimenting with the error correction code algorithm, the bit error rate per page unit of 4Mbytes memory was on average 0ppm, and 100ppm without error correction code. Through the error correction code algorithm, data stability and reliability can be improved.

• Kyungpook Mathematical Journal
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• v.55 no.2
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• pp.301-311
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• 2015

In this paper, we present the error control techniques for the error correction methods (ECM) which is recently developed by P. Kim et al. [8, 9]. We formulate the local truncation error at each time and calculate the approximated solution using the solution and the formulated truncation error at previous time for achieving uniform error bound which enables a long time simulation. Numerical results show that the error controlled ECM provides a clue to have uniform error bound for well conditioned problems [1].

• Journal of the Korea Society of Computer and Information
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• v.15 no.10
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• pp.165-172
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• 2010

There are two method of error correction in vocabulary recognition system. one error pattern matting base on method other vocabulary mean pattern base on method. They are a failure while semantic of key-word problem for error correction. In improving, in this paper is propose system of key-word error correction using algorithm of syllable restoration. System of key-word error correction by processing of semantic parse through recognized phoneme meaning. It's performed restore by algorithm of syllable restoration phoneme apply fluctuation before word. It's definitely parse of key-word and reduced of unrecognized. Find out error correction rate using phoneme likelihood and confidence for system parse. When vocabulary recognition perform error correction for error proved vocabulary. system performance comparison as a result of recognition improve represent 2.3% by method using error pattern learning and error pattern matting, vocabulary mean pattern base on method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1747-1750
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• 2022

As shrinking the semiconductor process into the deep sub-micron to achieve high-density, low power and high performance integrated circuits, MBU (multiple bit upset) by soft errors is one of the major challenge of on-chip memory systems. To address the MBU, single error correction, double error detection and double adjacent error correction (SEC-DED-DAEC) codes have been recently proposed. But these codes do not resolve mis-correction. We propose the SEC-DED-DAEC-TAED(triple adjacent error detection) code without mis-corrections. The generated H-matrix by the proposed heuristic algorithm to accomplish the proposed code is implemented as hardware and verified. The results show that there is no mis-correction in the proposed codes and the 2-stage pipelined decoder can be employed on-chip memory system.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.4
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• pp.284-295
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• 2003

The servo tracks of disk drives are constructed at the time of manufacture with the equipment of servo track writer. Because of the imperfection of servo track writer, disk vibrations and head fluctuations during servo track writing process, the constructed servo tracks might deviate from perfect circles and take eccentric shapes. The servo track writing error should be corrected because it might cause interference with adjacent tracks and irrecoverable operation error of disk drives. The servo track writing error is repeated every disk rotation and so is periodic time function. In this paper, we propose a new correction algorithm of servo track writing error based on iterative teaming approach. Our correction algorithm can learn iteratively the servo track writing error as accurately as is desired. Furthermore, our algorithm is robust to system model errors, is computationally simple, and has fast convergence rate. In order to demonstrate the generality and practical use of our work, we present the convergence analysis of our correction algorithm and some simulation results.

• International Journal of Contents
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• v.5 no.3
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• pp.65-70
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• 2009

This paper describes ongoing work on the correction of adverb errors committed by Korean learners studying English as a foreign language (EFL), using an automated English writing assessment system. Adverb errors are commonly found in learners 'writings, but handling those errors rarely draws an attention in natural language processing due to complicated characteristics of adverb. To correctly detect the errors, adverbs are classified according to their grammatical functions, meanings and positions within a sentence. Adverb errors are collected from learners' sentences, and classified into five categories adopting a traditional error analysis. The error classification in conjunction with the adverb categorization is implemented into a set of mal-rules which automatically identifies the errors. When an error is detected, the system corrects the error and suggests error specific feedback. The feedback includes the types of errors, a corrected string of the error and a brief description of the error. This attempt suggests how to improve adverb error correction method as well as to provide richer diagnostic feedback to the learners.