• Journal of information and communication convergence engineering
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• v.16 no.3
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• pp.166-172
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• 2018

A pseudo-random sequence generated by using a primitive polynomial, trace function, and Legendre symbol has been researched in our previous work. Our previous sequence has some interesting features such as period, autocorrelation, and linear complexity. A pseudo-random sequence widely used in cryptography. However, from the aspect of the practical use in cryptographic systems sequence needs to generate swiftly. Our previous sequence generated by utilizing a primitive polynomial, however, finding a primitive polynomial requires high calculating cost when the degree or the characteristic is large. It’s a shortcoming of our previous work. The main contribution of this work is to find some relation between the generated sequence and irreducible polynomials. The purpose of this relationship is to generate the same sequence without utilizing a primitive polynomial. From the experimental observation, it is found that there are (p - 1)/2 kinds of polynomial, which generates the same sequence. In addition, some of these polynomials are non-primitive polynomial. In this paper, these relationships between the sequence and the polynomials are shown by some examples. Furthermore, these relationships are proven theoretically also.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1421-1428
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• 2013

In this paper, we would like to test whether the hit at a particular bat has a dependency with the hitting results at the previous bats in professional baseball games. For this purpose, we used the 2011 Korean Baseball League data. We find out that the hitting percentage at a particular bat has no dependency with the hit at the previous bat, after reviewing the conditional probability of hit at each bat and the lift. From the independence test of hits at consecutive bats, and hit at a particular bat with no hits at previous bats, we can conclude that hits at particular bats are not dependent on the hits at previous bats in most cases. Hence, we can safely conclude that a hit at a particular bat is statistically independent from the hits at the previous bats.

• Journal of Intelligence and Information Systems
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• v.4 no.2
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• pp.117-128
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• 1998

CBR is a knowledge-based system that utilizes the previous knowledge or experience to solve the current problem. In previous CBR research, the emphases are mainly put on the development of more sophisticated indexing mechanism for past cases or the most similar case retrieving methodology out of a group of previous cases. In this paper, discussed is a CBR system that is able to take advantage of the case or knowledge that does not belong to the past in the telecommunications internetworking design area. And the architecture for such CBR system is proposed. Finally, the performance of the CBR system is shown through an ablation experiment.

• The International Journal of Costume Culture
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• v.4 no.2
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• pp.159-164
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• 2001

Illusory Correlation Effect(ICE) is a cognitive error that arises from overestimating particular stimulus of an individual or a group. This may cause formation of stereotypes of the individual or the group and may also lead to generating various biased judgments. this study investigated the Illusory Correlation Effect of clothing style and considered the effect of Preview information. The results Provided evidence for the existence of an illusory correlation between a wearer and clothing style. Also, an illusory correlation was influenced information of stimuli attributes. This implies subjects perceived stimuli more distinctively when previous information was provided.

• Journal of the Korea Society of Computer and Information
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• v.22 no.9
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• pp.17-24
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• 2017

Core citation recognition is to identify influential ones among the prior articles that a scholarly article cite. Previous approaches have employed citing-text occurrence information, textual similarities between citing and cited article, etc. This study proposes a term-based approach to core citation recognition, which exploits the importance of individual terms appearing in in-text citation to calculate influence-strength for each cited article. Term importance is computed using various frequency information such as term frequency(tf) in in-text citation, tf in the citing article, inverse sentence frequency in the citing article, inverse document frequency in a collection of articles. Experiments using a previous test set consisting of computational linguistics articles show that the term-based approach performs comparably with the previous approaches. The proposed technique could be easily extended by employing other term units such as n-grams and phrases, or by using new term-importance formulae.

• Management & Information Systems Review
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• v.25
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• pp.171-201
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• 2008

Previous research on negative contents of verbal message being more influential has a two broad streams as impression formation theory and negative information having an more diagnostic informational value. Therefore, this research was intended to obtain consistent results from researches by message frame segmentation of verbal message and to determine the medium of verbal message. It was proven from the research that objects influencing verbal message are being effected by the participation ratio of products and the positive indication is having more meaningful difference than the negative indication statistically unlike to the results of previous researches. Unlike just a biased positive message or negative message as the result of previous research, it was proven that the positive indication is influential regardless of sequences according to participation ratio and site participation in case of positive and negative being existing together.

• Journal of information and communication convergence engineering
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• v.11 no.2
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• pp.118-123
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• 2013

This paper proposes an efficient hardware architecture for high efficiency video coding (HEVC), which is the next generation video compression standard. It adopts several new coding techniques to reduce the bit rate by about 50% compared with the previous one. Unlike the previous H.264/AVC 6-tap interpolation filter, in HEVC, a one-dimensional seven-tap and eight-tap filter is adopted for luma interpolation, but it also increases the complexity and gate area in hardware implementation. In this paper, we propose a parallel architecture to boost the interpolation performance, achieving a luma $4{\times}4$ block interpolation in 2-4 cycles. The proposed architecture contains shared operations reducing the gate count increased due to the parallel architecture. This makes the area efficiency better than the previous design, in the best case, with the performance improved by about 75.15%. It is synthesized with the MagnaChip $0.18{\mu}m$ library and can reach the maximum frequency of 200 MHz.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.05a
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• pp.329-337
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• 2007

Case-based reasoning (CBR) methods are applied to various target problems on the supposition that previous cases are sufficiently similar to current target problems, and the results of previous similar cases support the same result consistently. However, these assumptions are not applicable for some target cases. There are some target cases that have no sufficiently similar cases, or if they have, the results of these previous cases are inconsistent. That is, the appropriateness of CBR is different for each target case, even though they are problems in the same domain. Thus, applying CBR to whole datasets in a domain is not reasonable. This paper presents a new hybrid datamining technique called two-step filtering CBR and Rule Induction (TSFCR), which dynamically selects either CBR or RI for each target case, taking into consideration similarities and consistencies of previous cases. We apply this method to three medical diagnosis datasets and one credit analysis dataset in order to demonstrate that TSFCR outperforms the genuine CBR and RI.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.5
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• pp.1396-1412
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• 2023

Conversation modeling is an important and challenging task in the field of natural language processing because it is a key component promoting the development of automated humanmachine conversation. Most recent research concerning conversation modeling focuses only on the current utterance (considered as the current question) to generate a response, and thus fails to capture the conversation's logic from its beginning. Some studies concatenate the current question with previous conversation sentences and use it as input for response generation. Another approach is to use an encoder to store all previous utterances. Each time a new question is encountered, the encoder is updated and used to generate the response. Our approach in this paper differs from previous studies in that we explicitly separate the encoding of the question from the encoding of its context. This results in different encoding models for the question and the context, capturing the specificity of each. In this way, we have access to the entire context when generating the response. To this end, we propose a deep neural network-based model, called the Context Model, to encode previous utterances' information and combine it with the current question. This approach satisfies the need for context information while keeping the different roles of the current question and its context separate while generating a response. We investigate two approaches for representing the context: Long short-term memory and Convolutional neural network. Experiments show that our Context Model outperforms a baseline model on both ConvAI2 Dataset and a collected dataset of conversational English.

• Journal of the Korea Society of Computer and Information
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• v.23 no.8
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• pp.9-16
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• 2018

In this paper, a kidnapping detection scheme in which human pose estimation is used to classify accurately between kidnapping cases and normal ones is proposed. To estimate human poses from input video, human's 10 joint information is extracted by OpenPose library. In addition to the features which are used in the previous study to represent the size change rates and the regularities of human activities, the human pose estimation features which are computed from the location of detected human's joints are used as the features to distinguish kidnapping situations from the normal accompanying ones. A frame-based kidnapping detection scheme is generated according to the selection of J48 decision tree model from the comparison of several representative classification models. When a video has more frames of kidnapping situation than the threshold ratio after two people meet in the video, the proposed scheme detects and notifies the occurrence of kidnapping event. To check the feasibility of the proposed scheme, the detection accuracy of our newly proposed scheme is compared with that of the previous scheme. According to the experiment results, the proposed scheme could detect kidnapping situations more 4.73% correctly than the previous scheme.