• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.326-341
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• 2020

Based on theoretical background of Situational Theory of Problem Solving(STOPS), we have examined the role of STOPS variables on a group of online public in their issue recognition and communicative behavior on Korea's nationwide civil boycott movement of Japanese goods. Results from 524 survey cases from a Korea's major online community show that two independent variables(Problem Recognition, Referent Criterion) revealed positive in their effect on mediating variable(Situational Motivation in Problem Solving). Situational Motivation also revealed positive in its effect on six dependent variables(Information Forefending, Information Permitting, Information Forwarding, Information Sharing, Information Seeking, Information Attending) of Communicative Behavior. Involvement Recognition and Constraint Recognition revealed positive without proper statistical significance. As a result, study on the case of online public in Korea supports STOPS theory as high-level of Problem Recognition and Referent Criterion effects on Communicative Behavior in positive way via Situational Motivation. Implications from the findings have discussed and proposed suggestions for government public relations and further studies.

• Journal of Korean Elementary Science Education
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• v.36 no.3
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• pp.208-218
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• 2017

This study was to investigate factors and disclose causal model of the scientific literacy competency about the motivation for science and the scientific literacy competency. The 3 grade university students and the 1 grade university students as pre-service elementary teachers were participated to questionnaire investigation. The data were analyzed by the factor analysis method and the structural equation model method, and the following results were obtained. First, the 3 grade university students and the 1 grade university students perceived the science interest factors and science usefulness factors as the motivation for science, and also revealed the scientific problem recognition factor and the scientific evidence use factor as the scientific literacy competency. Second, the science interest factor had a greater effect on the scientific problem recognition factor than the scientific evidence use factor in both the 3 grade and 1 grade university students. In the path from the science usefulness factor to the scientific problem recognition factor, the science usefulness factor of the 3 grade university students had a greater influence on the direct route to the scientific problem recognition factor than that of the 1 grade university students. In the path from the science usefulness factor to the scientific evidence use factor, the science usefulness factor of the 1 grade university students influenced more on the direct route to the scientific evidence use factor than that of the 3 grade university students.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.95-100
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• 2003

In this paper, we propose solutions to resolve the problem of many spelling variants and the problem of lack of annotated corpus for training, which are two among the main difficulties in named entity recognition in biomedical domain. To resolve the problem of spotting valiants, we propose a use of edit-distance as a feature for SVM. And we propose a use of virtual examples to automatically expand the annotated corpus to resolve the lack-of-corpus problem. Using virtual examples, the annotated corpus can be extended in a fast, efficient and easy way. The experimental results show that the introduction of edit-distance produces some improvements in protein name recognition performance. And the model, which is trained with the corpus expanded by virtual examples, outperforms the model trained with the original corpus. According to the proposed methods, we finally achieve the performance 75.80 in F-measure(71.89% in precision,80.15% in recall) in the experiment of protein name recognition on GENIA corpus (ver.3.0).

• Journal of Digital Convergence
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• v.12 no.1
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• pp.163-170
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• 2014

The purpose of this study was to explore the effect of need for closure on college students' problem recognition and communication behavior. Specifically, this research examined differences about situation recognitions and communication behaviors across level of need for closure factors (preference for order and structure, preference for predictability, decisiveness, discomfort with ambiguity, closed-mindeness). The results show that the participants with higher level of discomfort with ambiguity and low level of closed-mindeness are more likely to high problem recognition, constraint recognition, involvement recognition, and doing active communication behaviors.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.769-776
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• 2003

DNA computing has used to solve MCP (Maximal Clique Problem). However, when current DNA computing is applied to MCP. it can't efficiently express vertices and edges and it has a problem that can't look for solutions, by misusing wrong restriction enzyme. In this paper we proposed ACO (Algorithm for Code Optimization) that applies DNA coding method to DNA computing to solve MCP's problem. We applied ACO to MCP and as a result ACO could express DNA codes of variable lengths and generate codes without unnecessary vertices than Adleman's DNA computing algorithm could. In addition, compared to Adleman's DNA computing algorithm, ACO could get about four times as many as Adleman's final solutions by reducing search time and biological error rate by 15%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.6
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• pp.1187-1192
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• 2012

This paper describes a method to detect QR-code finders by four-direction scanning. The finder recognition is the first step in the QR-code recognition. If the finder is missing, QR-code recognition fails. The existing QR-code recognition method has a problem that the recognition performance decreases for perspectively distored images. To overcome the problem, we introduce four-direction scanning and a candidate set image to accurately detect QR-code finders. Using morphological operations detect the QR-code finder in the candidate set image robustly. To show the effectiveness of our method, we compared our method with the well-known existing method. The experimental result indicates that the proposed method is superior to the existing method in terms of the finder recognition performance.

• Journal of information and communication convergence engineering
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• v.9 no.5
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• pp.607-609
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• 2011

In this work, we present solutions of two problems. First, the representation of pattern recognition problem in the standard $T_{nml}$ table of the algorithm estimate calculation was considered. Second, the problem of finding the model, consisting of the optimal parameters of an algorithm was considered. Such procedure is carried out by the selection optimal values of the parameters of extreme algorithms. This serves to reduce the number of calculations in the algorithms of estimate calculation and to increase the quality of recognition process. The algorithmic data base of the developed system was based on mathematical apparatus of pattern recognition.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4556-4572
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• 2015

Dynamic texture (DT) recognition is a challenging problem in numerous applications. In this study, we propose a new algorithm for DT recognition based on group sparsity structure in conjunction with chaotic feature vector. Bag-of-words model is used to represent each video as a histogram of the chaotic feature vector, which is proposed to capture self-similarity property of the pixel intensity series. The recognition problem is then cast to a group sparsity model, which can be efficiently optimized through alternating direction method of multiplier algorithm. Experimental results show that the proposed method exhibited the best performance among several well-known DT modeling techniques.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.1
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• pp.8-16
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• 2014

We consider the visual barcode recognition problem in a noisy video data setup. Unlike most existing single-frame recognizers that require considerable user effort to acquire clean, motionless and blur-free barcode signals, we eliminate such extra human efforts by proposing a robust video-based barcode recognition algorithm. We deal with a sequence of noisy blurred barcode image frames by posing it as an online filtering problem. In the proposed dynamic recognition model, at each frame we infer the blur level of the frame as well as the digit class label. In contrast to a frame-by-frame based approach with heuristic majority voting scheme, the class labels and frame-wise noise levels are propagated along the frame sequences in our model, and hence we exploit all cues from noisy frames that are potentially useful for predicting the barcode label in a probabilistically reasonable sense. We also suggest a visual barcode tracking approach that efficiently localizes barcode areas in video frames. The effectiveness of the proposed approaches is demonstrated empirically on both synthetic and real data setup.

• Communications of Mathematical Education
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• v.20 no.4 s.28
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• pp.551-559
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• 2006

Pattern Recognition measures the ability of learners to distinguish between two sets of shapes or figures. Locating similar patterns on either side of the presented problem determines a learner's capacity or aptitude for science over general studies. At Ajou University's Institute for Scientifically Enabled Youth, we conducted research using a sample composed of middle school students with general and scientific backgrounds. The result proved that Pattern Recognition measures a different creative talent other than problem solving. In our opinion, Pattern Recognition would be a method better suited to elementary learners over those in middle or high school.