• The Mathematical Education
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• v.52 no.2
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• pp.203-215
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• 2013

We explored implications of storytelling in learning and teaching mathematics and examined examples of storytelling for deep understanding of the educational meanings of storytelling and new direction of storytelling approach to mathematics teachers. Mathematics had been commonly considered as the subject irrelevant to the narrative mode of thinking and only relevant to the paradigmatic mode of thinking that has rigorous logical forms and independent from human mind. As a result, this common sense forced a transmission pedagogy of mathematics: only the teachers as owners of the objective and logical truth of mathematics could transmit mathematical truths to students. Storytelling is highlighted as an alternative to the common teaching practices of mathematics focused only on the paradigmatic mode of thinking. Although a lot of research about the educational uses of storytelling mainly focused on the development and modification of stories, we suggested that the educational interest about storytelling should move to the elements or techniques for the positive effect of storytelling.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.94-99
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• 2008

In the pattern classification problem, feature selection is an important technique to improve performance of the classifiers. Particularly, in the case of classifying with a large number of features or variables, the accuracy of the classifier can be improved by using the relevant feature subset to remove the irrelevant, redundant, or noisy data. In this paper we propose a feature selection method using genetic algorithm and information theory. Experimental results show that this method can achieve better performance for pattern recognition problems than conventional ones.

• Phonetics and Speech Sciences
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• v.13 no.3
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• pp.21-29
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• 2021

The present study investigated how one's cognitive resources are related to speech perception by examining Korean speakers' executive function (EF) capacity and its association with voice onset time (VOT) and f0 sensitivity in identifying Korean stop laryngeal categories (/t'/ vs. /t/ vs. /t^h/). Previously, Kong et al. (under revision) reported that Korean listeners (N = 154) in Seoul and Changwon (Gyeongsang) showed differential group patterns in dialect-specific cue weightings across educational institutions (college, high school, and elementary school). We follow up this study by further relating their EF control (working memory, mental flexibility, and inhibition) to their speech perception patterns to examine whether better cognitive ability would control attention to multiple acoustic dimensions. Partial correlation analyses revealed that better EFs in Korean listeners were associated with greater sensitivity to available acoustic details and with greater suppression of irrelevant acoustic information across subgroups, although only a small set of EF components turned out to be relevant. Unlike Seoul participants, Gyeongsang listeners' f0 use was not correlated with any EF task scores, reflecting dialect-specific cue primacy using f0 as a secondary cue. The findings confirm the link between speech perception and general cognitive ability, providing experimental evidence from Korean listeners.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.32 no.2
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• pp.51-62
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• 2021

Objectives: Tic disorder is a neurodevelopmental disorder characterized by multiple involuntary movements of muscles or vocalization. Although tic symptoms subside as the patient ages, some patients suffer from significant functional impairments related to severe tic symptoms. This manuscript aimed to review the latest scientific evidences for the effect of cognitive-behavioral interventions on tic disorder. Methods: The relevant studies were identified by searching medical research databases. We focused our search on studies published between 2000 and 2020 in order to reflect the latest scientific evidence. A total of 821 articles were identified in the initial database search and 27 articles were finally included for the review after the exclusion of duplicated and irrelevant articles. Results: Behavioral therapies including habit reversal training, Comprehensive Behavioral Intervention for Tics, and exposure and response prevention were the most widely studied interventions for tic disorder and are recommended as first-line treatments for tic disorders with high confidence. Cognitive psychophysiologic approaches were also reported to be effective. Conclusion: Further studies are needed to support the future treatment of tics with low-cost and more widely available treatments, in order to ensure better treatment outcomes.

• Journal of information and communication convergence engineering
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• v.19 no.4
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• pp.234-240
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• 2021

As the number of pet dog-related businesses is rising rapidly, there is an increasing need for reliable pet dog health information systems for casual pet owners, especially those caring for older dogs. Our goal is to implement a mobile pre-diagnosis system that can provide a first-hand pre-diagnosis and an appropriate coping strategy when the pet owner observes abnormal symptoms. Our previous attempt, which is based on the fuzzy C-means family in inference, performs well when only relevant symptoms are provided for the query, but this assumption is not realistic. Thus, in this paper, we propose a hybrid inference structure that combines fuzzy association memory and a double-layered fuzzy C-means algorithm to infer the probable disease with robustness, even when noisy symptoms are present in the query provided by the user. In the experiment, it is verified that our proposed system is more robust when noisy (irrelevant) input symptoms are provided and the inferred results (probable diseases) are more cohesive than those generated by the single-phase fuzzy C-means inference engine.

• Journal of Biomedical Engineering Research
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• v.43 no.2
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• pp.109-115
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• 2022

Purpose: Medical records classification using vectorization techniques plays an important role in natural language processing. The purpose of this study was to investigate proper vectorization techniques for electronic medical records classification. Material and methods: 403 electronic medical documents were extracted retrospectively and classified using the cosine similarity calculated by Scikit-learn (Python module for machine learning) in Jupyter Notebook. Vectors for medical documents were produced by three different vectorization techniques (TF-IDF, latent sematic analysis and Word2Vec) and the classification precisions for three vectorization techniques were evaluated. The Kruskal-Wallis test was used to determine if there was a significant difference among three vectorization techniques. Results: 403 medical documents were relevant to 41 different diseases and the average number of documents per diagnosis was 9.83 (standard deviation=3.46). The classification precisions for three vectorization techniques were 0.78 (TF-IDF), 0.87 (LSA) and 0.79 (Word2Vec). There was a statistically significant difference among three vectorization techniques. Conclusions: The results suggest that removing irrelevant information (LSA) is more efficient vectorization technique than modifying weights of vectorization models (TF-IDF, Word2Vec) for medical documents classification.

• Korean Journal of Cognitive Science
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• v.35 no.1
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• pp.49-95
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• 2024

Polygraph examination, statement validity analysis and P300-based concealed information test are major three examination tools, which are use to determine a person's truthfulness and credibility in criminal procedure. Although polygraph examination is most common in criminal procedure, but it has little admissibility of evidence due to the weakness of scientific basis. In 1990s to support the weakness of scientific basis about polygraph, Farwell and Donchin proposed the P300-based concealed information test technique. The P300-based concealed information test has two strong points. First, the P300-based concealed information test is easy to conduct with polygraph. Second, the P300-based concealed information test has plentiful scientific basis. Nevertheless, the utilization of P300-based concealed information test is infrequent, because of the quantity of probe stimulus. The probe stimulus contains closed information that is relevant to the crime or other investigated situation. In tradition P300-based concealed information test protocol, three or more probe stimuli are necessarily needed. But it is hard to acquire three or more probe stimuli, because most of the crime relevant information is opened in investigative situation. In addition, P300-based concealed information test uses oddball paradigm, and oddball paradigm makes imbalance between the number of probe and irrelevant stimulus. Thus, there is a possibility that the unbalanced number of probe and irrelevant stimulus caused systematic underestimation of P300 amplitude of irrelevant stimuli. To overcome the these two limitation of P300-based concealed information test, one-probe P300-based concealed information test protocol is explored with various machine learning algorithms. According to this study, parameters of the modified one-probe protocol are as follows. In the condition of female and male face stimuli, the duration of stimuli are encouraged 400ms, the repetition of stimuli are encouraged 60 times, the analysis method of P300 amplitude is encouraged peak to peak method, the cut-off of guilty condition is encouraged 90% and the cut-off of innocent condition is encouraged 30%. In the condition of two-syllable word stimulus, the duration of stimulus is encouraged 300ms, the repetition of stimulus is encouraged 60 times, the analysis method of P300 amplitude is encouraged peak to peak method, the cut-off of guilty condition is encouraged 90% and the cut-off of innocent condition is encouraged 30%. It was also conformed that the logistic regression (LR), linear discriminant analysis (LDA), K Neighbors (KNN) algorithms were probable methods for analysis of P300 amplitude. The one-probe P300-based concealed information test with machine learning protocol is helpful to increase utilization of P300-based concealed information test, and supports to determine a person's truthfulness and credibility with the polygraph examination in criminal procedure.

• Korean Journal of Cognitive Science
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• v.23 no.2
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• pp.225-248
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• 2012

The summed-similarity model of visual short-term recognition proposes that the estimated amount of summed similarity between remembered items and a recognition probe determines recognition judgement decision (Kahan & Sekuler, 2002). This study examined the effect of a task-irrelevant location change on the recognition decision against two remembered Gabor gratings differing in their spatial frequencies. On each trial in Experiment, participants reported if two gratings displayed across the visual fields are the same or not as the probe grating displayed after about a second of memory delay. The probe grating would be the same as or different from the memory items (lure) by 1 or 4 JND units. The location of the probe would also vary randomly across the left and right visual field with respect to the location of the corresponding memory item. The participants were instructed to perform their recognition task exclusively to the spatial frequencies of the memory items and the probe while ignoring the potential location change of the probe. The results showed that false-recognition rates of the lure probe increased as the summed similarity between the memory items and the probe increased. The rates also further increased in the condition where the probe location was different from the location of the corresponding memory item compared to the condition where the probe location was the same. The increased false-recognition rates indicate that information stored into visual short-term memory is represented as a form of well-bound visual features rather than independent features.

• Journal of Distribution Science
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• v.14 no.11
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• pp.61-73
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• 2016

Purpose - Marketing scholars have developed various types of mathematical models for describing marketing phenomenon, because there is no single model comprehensive enough to incorporate all the relevant marketing phenomena. This study tries to summarize the behavioral foundations and the mathematical derivations of the most widely used marketing models and discusses their strategic implications. This study selected four representative marketing models: multinomial logit(MNL) model, elimination-by-aspects(EBA) model, Hauser and Shugan model and Bass diffusion model. Especially, this study focuses on Hauser and Shugan(1983)'s Defender model and discusses the model's behavioral foundation and its implications. Research design, data, and methodology - Of the four selected model, the multinomial logit model is selected as the basic normative model and the other three models are described as descriptive models in contrast. Starting the discussion from the multinomial logit model, this study explains what important strategic variables are incorporated in each of the four models. The IIA(independence of irrelevant alternatives) axiom and Luce choice model is also discussed in relation to the multinomial logit model. The concept of 'efficient frontier' is discussed in relation to Hauser and Shugan's model. Graphs and tables are used to represent the key implications. No empirical study is included. Results - The analyses of the mathematical marketing models are shown to be very useful in understanding the essence of positioning strategy. The multinomial logit model implies the importance of increasing utility or consumer preference level. The EBA model implies the importance of lowering the inter-brand similarity and dominating the competitors. Hauser and Shugan model implies the importance of considering customer heterogeneity distribution in selecting the target market. Conclusions - It is shown that the concepts of 'efficient frontier' is useful in understanding the effectiveness of positioning strategy. Market positioning can be understood as occupying some place on the efficient frontier. The important strategic implications can be summarized as follows: Always try to increase customer preference by providing what they value, and differentiate from competing alternatives as much as possible. The best positioning strategy is to dominate all the competitors and the worst is to be dominated by the competitors.

• Science of Emotion and Sensibility
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• v.16 no.3
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• pp.409-416
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• 2013

Attention is one of important cognitive functions in human affecting on the selectional concentration of relevant events and ignorance of irrelevant events. The discrimination of attentional and inattentional status is the first step to manage human's attentional capability using computer assisted device. In this paper, we newly combine the non-linear recurrence pattern analysis and spectrum analysis to effectively extract features(total number of 13) from the electroencephalographic signal used in the input to classifiers. The performance of diverse types of attention-inattention classifiers, including supporting vector machine, back-propagation algorithm, linear discrimination, gradient decent, and logistic regression classifiers were evaluated. Among them, the support vector machine classifier shows the best performance with the classification accuracy of 81 %. The use of spectral band feature set alone(accuracy of 76 %) shows better performance than that of non-linear recurrence pattern feature set alone(accuracy of 67 %). The support vector machine classifier with hybrid combination of non-linear and spectral analysis can be used in later designing attention-related devices.