• Proceedings of the IEEK Conference
• /
• 2002.07a
• /
• pp.106-109
• /
• 2002

In the integrated systems, that is integrated digital TV(DTV) internet and home automation, like home server, is needed integration of digital TV video signal and computer graphic signal. The graphic signal is operating at the high speed and has time-divide-stream. So the re-request of data is not easy at the time of error detection. therefore EDAC algorithm is efficient. This paper presents the efficiency error detection auto correction(EDAC) for conversion of graphics signal to DTV video signal. A presented EDAC algorithms use the modified Hamming code for enhancing video quality and reliability. A EDAC algorithm of this paper can detect single error, double error, triple error and more error for preventing from incorrect correction. And it is not necessary an additional memory. In this paper The comparison between digital TV video signal and graphic signal, a EBAC algorithm and a design of conversion graphic signal to DTV signal with EDAC function is described.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.10
• /
• pp.2527-2543
• /
• 2013

A novel steganographic QR code algorithm, which not only coveys the secret into the widely-used QR barcode but also preserves the readability of QR content and the capability of error correction, is presented in this article. Different from the conventional applications for QR barcode, the designed algorithm conceals the secret into the QR modules directly by exploiting the error correction capability. General browsers can read the QR content from the QR code via barcode readers; however, only the authorized receiver can further reveal the secret from the QR code directly. The new mechanism can convey a larger secret payload along with adjustment of the QR version and error correction level. Moreover, the blind property allows the receiver to reveal the secret without the knowledge of the embedded position of modules. Experimental results demonstrate that the new algorithm is secure, efficient and feasible for the low-power QR readers and mobile devices.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.14 no.4
• /
• pp.657-662
• /
• 2019

The power consumption of wearable sensors and electrocardiogram regulators should be very low to extend the network lifetime and anticipated QoS( : Quality of Service) control such as error correction and authentication of data processed by WBAN( : Wireless Body Area Network) nodes is important. Therefore, QoS control is the most urgent concern to implement WBAN in health monitoring regulations. For optimal QoS control, we compare the energy efficiency and the average number of transmissions with IEEE 802.15.6 and the error correction method considering energy efficiency. The performance of the proposed error correction technique shows that the energy efficiency and the transmission rate are improved by adjusting the coding rate appropriately using the channel estimation.

• The Korean Journal of Applied Statistics
• /
• v.35 no.1
• /
• pp.93-104
• /
• 2022

In forecasting realized volatility of the major US stock price indexes (S&P 500, Russell 2000, DJIA, Nasdaq 100), internet search volume reflecting investor's interests and implied volatility are used to improve forecast via a deep learning method of the LSTM. The LSTM method combined with search volume index produces better forecasts than existing standard methods of the vector autoregressive (VAR) and the vector error correction (VEC) models. It also beats the recently proposed vector error correction heterogeneous autoregressive (VECHAR) model which takes advantage of the cointegration relation between realized volatility and implied volatility.

• Proceedings of the IEEK Conference
• /
• 2001.09a
• /
• pp.239-242
• /
• 2001

영상에 워터마크를 삽입하는 것을 통신채널의 입장에서 해석한다면 워터마크는 신호로, 영상은 잡음으로 모델링이 가능하다. 따라서 이러한 잡음 속에서 신호에 대한 에러를 최소화하는 것이 워터마크의 추출을 최대화하는 것이라 할 수 있다. 통상적으로 Error Correction Code는 에러가 많은 통신채널에서 많이 이용되기 때문에 워터마킹 방법에서도 효과를 기대할 수 있다. 본 논문에서는 DCT 기반의 구간화 워터마킹 방법에 Turbo code를 이용하여 강인성 면에서의 향상된 성능을 실험 결과로 보이며, Turbo code의 해밍거리를 이용하여 워터마킹의 보다 효율적인 검출 방법을 제안한다.

• Journal of the Korean Statistical Society
• /
• v.34 no.4
• /
• pp.345-366
• /
• 2005

This paper considers the cointegrating vector estimator in the error correction model with stationary covariates, which combines the stationary vector autoregressive model and the nonstationary error correction model. The cointegrating vector estimator is shown to follow the locally asymptotically mixed normal distribution. The variance of the estimator depends on the co­variate effect of stationary regressors, and the asymptotic efficiency improves as the magnitude of the covariate effect increases. An economic application of the money demand equation is provided.

• Journal of Korea Multimedia Society
• /
• v.25 no.3
• /
• pp.493-501
• /
• 2022

This paper is a study on context-sensitive spelling error correction and uses the Korean WordNet (KorLex)[1] that defines the relationship between words as a graph to improve the performance of the correction[2] based on the vector information of the word embedded in the correction technique. The Korean WordNet replaced WordNet[3] developed at Princeton University in the United States and was additionally constructed for Korean. In order to learn a semantic network in graph form or to use it for learned vector information, it is necessary to transform it into a vector form by embedding learning. For transformation, we list the nodes (limited number) in a line format like a sentence in a graph in the form of a network before the training input. One of the learning techniques that use this strategy is Deepwalk[4]. DeepWalk is used to learn graphs between words in the Korean WordNet. The graph embedding information is used in concatenation with the word vector information of the learned language model for correction, and the final correction word is determined by the cosine distance value between the vectors. In this paper, In order to test whether the information of graph embedding affects the improvement of the performance of context- sensitive spelling error correction, a confused word pair was constructed and tested from the perspective of Word Sense Disambiguation(WSD). In the experimental results, the average correction performance of all confused word pairs was improved by 2.24% compared to the baseline correction performance.

• KIPS Transactions on Software and Data Engineering
• /
• v.4 no.1
• /
• pp.45-56
• /
• 2015

In this paper, we present a method that can detect context-sensitive word errors and generate correction candidates. Spelling error detection is one of the most widespread research topics, however, the approach proposed in this paper is adjusted for an automated English scoring system. A common strategy in context-sensitive word error detection is using a pre-defined confusion set to generate correction candidates. We automatically generate a confusion set in order to consider the characteristics of sentences written by second-language learners. We define a word error that cannot be detected by a conventional grammar checker because of part-of-speech ambiguity, and propose how to detect the error and generate correction candidates for this kind of error. An experiment is performed on the English writings composed by junior-high school students whose mother tongue is Korean. The f1 value of the proposed method is 70.48%, which shows that our method is promising comparing to the current-state-of-the art.

• Korean Journal of Remote Sensing
• /
• v.27 no.2
• /
• pp.99-105
• /
• 2011

This research presents the correction method to correct the location error of cloud caused by parallax error, and how the method can reduce the position error. The procedure has two steps: first step is to retrieve the corrected satellite zenith angle from the original satellite zenith angle. Second step is to adjust the location of the cloud with azimuth angle and the corrected satellite zenith angle retrieved from the first step. The position error due to parallax error can be as large as 60km in case of 70 degree of satellite zenith angle and 15 km of cloud height. The validation results by MODIS(Moderate-Resolution Imaging Spectrometer) show that the correction method in this study properly adjusts the original cloud position error and can increase the utilization of geostationary satellite data.

• Journal of the Korea Society of Computer and Information
• /
• v.15 no.7
• /
• pp.83-90
• /
• 2010

In vocabulary recognition system has reduce recognition rate unrecognized error cause of similar phoneme recognition and due to provided inaccurate vocabulary. Input of inaccurate vocabulary by feature extraction case of recognition by appear result of unrecognized or similar phoneme recognized. Also can't feature extraction properly when phoneme recognition is similar phoneme recognition. In this paper propose vocabulary recognition post-process error correction system using phoneme likelihood based on phoneme feature. Phoneme likelihood is monophone training phoneme data by find out using MFCC and LPC feature extraction method. Similar phoneme is induced able to recognition of accurate phoneme due to inaccurate vocabulary provided unrecognized reduced error rate. Find out error correction using phoneme likelihood and confidence when vocabulary recognition perform error correction for error proved vocabulary. System performance comparison as a result of recognition improve represent MFCC 7.5%, LPC 5.3% by system using error pattern and system using semantic.