• The Korean Journal of Nuclear Medicine
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• v.34 no.3
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• pp.183-198
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• 2000

Purpose: The purpose of this study was to evaluate alterations of regional cerebral blood flow (CBF) and cerebrovascular reserve (CVR), and correlation between these alternations and cognitive dysfunction in patients with chronic traumatic brain injury (TBI) and normal brain MRI findings. Materials and Methods: Thirty TBI patients and 19 healthy volunteers underwent rest/acetazolamide brain SPECT using Tc-99m HMPAO. Korean-Wechsler Adult Intelligence scale test was also performed in the patient group. Statistical analysis was performed with statistical parametric mapping software (SPM'97) Results: CBF was diminished in the left hemisphere including Wernicke's area in all patients with lower verbal scale scores. In addition, a reduction in CBF in the right frontal, temporal and parietal cortices was related with depressed scores in information, digital span, arithmetic and similarities. In patients with lower performance scale scores, CBF was mainly diminished in the right hemisphere including superior temporal and supramarginal gyri, premotor, primary somatomotor and a part of prefrontal cortices, left frontal lobe and supramarginal gyrus. CVR was diminished in sixty-four Brodmann's areas compared to control. A reduction in CVR was demonstrated bilaterally in the frontal and temporal lobes in patients with lower scores in both verbal and performance tests, and in addition, both inferior parietal and occipital lobes in information subset. Conclusion: Alterations of CBF and CVR were demonstrated in the symptomatic TBI patients with normal MRI finding. These alterations were correlated with the change of intelligence, of which the complex functions are subserved by multiple interconnected cortical structures.

• Science of Emotion and Sensibility
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• v.15 no.4
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• pp.503-516
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• 2012

According to the researches of robot and software agent until now, computational emotion model is dependent on system, so it is hard task that emotion models is separated from existing systems and then recycled into new systems. Therefore, I introduce the Engine of computational Emotion model (shall hereafter appear as EE) to integrate with any robots or agents. This is the engine, ie a software for independent form from inputs and outputs, so the EE is Emotion Generation to control only generation and processing of emotions without both phases of Inputs(Perception) and Outputs(Expression). The EE can be interfaced with any inputs and outputs, and produce emotions from not only emotion itself but also personality and emotions of person. In addition, the EE can be existed in any robot or agent by a kind of software library, or be used as a separate system to communicate. In EE, emotions is the Primary Emotions, ie Joy, Surprise, Disgust, Fear, Sadness, and Anger. It is vector that consist of string and coefficient about emotion, and EE receives this vectors from input interface and then sends its to output interface. In EE, each emotions are connected to lists of emotional experiences, and the lists consisted of string and coefficient of each emotional experiences are used to generate and process emotional states. The emotional experiences are consisted of emotion vocabulary understanding various emotional experiences of human. This study EE is available to use to make interaction products to response the appropriate reaction of human emotions. The significance of the study is on development of a system to induce that person feel that product has your sympathy. Therefore, the EE can help give an efficient service of emotional sympathy to products of HRI, HCI area.

• Journal of KIISE:Software and Applications
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• v.35 no.5
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• pp.313-324
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• 2008

A sentence reduction is the information compression process which removes extraneous words and phrases and retains basic meaning of the original sentence. Most researches in the sentence reduction have required a large number of lexical and syntactic resources and focused on extracting or removing extraneous constituents such as words, phrases and clauses of the sentence via the complicated parsing process. However, these researches have some problems. First, the lexical resource which can be obtained in loaming data is very limited. Second, it is difficult to reduce the sentence to languages that have no method for reliable syntactic parsing because of an ambiguity and exceptional expression of the sentence. In order to solve these problems, we propose the sentence reduction method which uses templates and POS(part of speech) information without a parsing process. In our proposed method, we create a new sentence using both Sentence Reduction Templates that decide the reduction sentence form and Grammatical POS-based Reduction Rules that compose the grammatical sentence structure. In addition, We use Viterbi algorithms at HMM(Hidden Markov Models) to avoid the exponential calculation problem which occurs under applying to Sentence Reduction Templates. Finally, our experiments show that the proposed method achieves acceptable results in comparison to the previous sentence reduction methods.

• Journal of the Korean School Mathematics Society
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• v.16 no.4
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• pp.797-820
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• 2013

This study intended on analyzing the error patterns of mathematic problem posing sentences by the 100 elementary pre-teachers and discussing about the solutions. The results showed that the problem posing sentences have five error patterns: phonological error patterns, word error patterns, sentence error patterns, meaning error patterns, and notation error patterns. Divided into fourteen specific error patterns, they are as in the following. 1) Phonological error patterns are consisted of the 'ㄹ' addition error pattern and the abbreviated word error pattern. 2) Words error patterns are divided with the inappropriate usage of word error pattern and the inadequate abbreviation error pattern, which are formulized four subgroups such as the case maker, ending of the word, inappropriate usage of word, and inadequate abbreviation of article or word error pattern in detail. 3) Sentence error patterns are assumed four kinds of forms: the reference, ellipsis of sentence component, word order, and incomplete sentence error pattern. 4) Meaning error patterns are composed the logical contradiction and the ambiguous meaning. 5) Notation error patterns are formed four patterns as the spacing, punctuation, orthography of Hangul, and spelling rules of foreign words in Korean. Furthermore, the solutions for these error patterns were discussed: First, it has to be perceived the differences between spoken and written language. Second, it has to be rejected the spoken expressions in written contexts. Third, it should be focused on the learning of the basic sentence patterns during the class. Forth, it is suggested that the word meaning should have the logical development perception based on what it means. Finally, it is proposed that the system of spelling of Korean has to be learned. In addition to these suggestions, a new understanding is necessary regarding writing education for college students.

• Science of Emotion and Sensibility
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• v.15 no.2
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• pp.297-306
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• 2012

In this study we investigated emotional characteristics of various whites which have slightly different nuances to suggest guidelines that help designers to select appropriate colors when designing white based products. The study involved three different procedures. In experiment 1, we selected 20 emotional words through a survey (N=30) among 60 words, which we picked from literature review that was thought to be appropriate to evaluate product colors. In experiment 2, we evaluated the emotional characteristics of 13 basic colors from the I.R.I Hue & Tone 120 system (N=30) using previously selected emotional words, to find relative emotional positions of white in comparison to other colors. Based on the ratings, factor analysis was conducted and consequently four factors were extracted: flamboyant, elegant, clear, and soft. Accordingly, the emotional characteristics of the 13 colors were profiled and compared with those of white. Finally, in experiment 3, we conducted an evaluation of emotional characteristics on 25 whites with different nuances facilitating the four factors obtained in experiment 2. The color stimuli used in experiments were measured in terms of CIE 1976 $L^*a^*b^*$, and regression analysis was performed in order to predict the emotional characteristics through the L, a, and b values of a color, as long as that is perceived as a white. Throughout three empirical studies, we observed three overruling tendencies : First, there are four important factors when evaluating product color - flamboyant, elegance, clearness and softness; second, white is dominantly the most elegant in comparison to other colors; third, the emotional factors of the study were affected by some combinations of attributes of colors rather than by all three-hue, saturation and brightness. In addition, the equations derived from the regression analysis in experiment 3, it is expected that designers may predict the emotional distinction between nuances of white.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.127-146
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• 2022

Recently, as word embedding has shown excellent performance in various tasks of deep learning-based natural language processing, researches on the advancement and application of word, sentence, and document embedding are being actively conducted. Among them, cross-language transfer, which enables semantic exchange between different languages, is growing simultaneously with the development of embedding models. Academia's interests in vector alignment are growing with the expectation that it can be applied to various embedding-based analysis. In particular, vector alignment is expected to be applied to mapping between specialized domains and generalized domains. In other words, it is expected that it will be possible to map the vocabulary of specialized fields such as R&D, medicine, and law into the space of the pre-trained language model learned with huge volume of general-purpose documents, or provide a clue for mapping vocabulary between mutually different specialized fields. However, since linear-based vector alignment which has been mainly studied in academia basically assumes statistical linearity, it tends to simplify the vector space. This essentially assumes that different types of vector spaces are geometrically similar, which yields a limitation that it causes inevitable distortion in the alignment process. To overcome this limitation, we propose a deep learning-based vector alignment methodology that effectively learns the nonlinearity of data. The proposed methodology consists of sequential learning of a skip-connected autoencoder and a regression model to align the specialized word embedding expressed in each space to the general embedding space. Finally, through the inference of the two trained models, the specialized vocabulary can be aligned in the general space. To verify the performance of the proposed methodology, an experiment was performed on a total of 77,578 documents in the field of 'health care' among national R&D tasks performed from 2011 to 2020. As a result, it was confirmed that the proposed methodology showed superior performance in terms of cosine similarity compared to the existing linear vector alignment.

• Journal of KIISE
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• v.43 no.12
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• pp.1376-1384
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• 2016

Computers require analytic and processing capability for all possibilities of human expression in order to process sentences like human beings. Linguistic information processing thus forms the initial basis. When analyzing a sentence syntactically, it is necessary to divide the sentence into components, find obligatory arguments focusing on predicates, identify the sentence core, and understand semantic relations between the arguments and predicates. In this study, the method applied a case frame dictionary based on The Korean Standard Dictionary of The National Institute of the Korean Language; in addition, we used a CRF Model that constructed subcategorization of predicates as featured in Korean Lexical Semantic Network (UWordMap) for semantic role labeling. Automatically tagged semantic roles based on the CRF model, which established the information of words, predicates, the case-frame dictionary and hypernyms of words as features, were used. This method demonstrated higher performance in comparison with the existing method, with accuracy rate of 83.13% as compared to 81.2%, respectively.

• Journal of Korean Library and Information Science Society
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• v.50 no.4
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• pp.137-158
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• 2019

This study aims to develop metadata elements and vocabularies of 'Chosunsibo' issued in Korea during the Japanese colonial era. Despite the vast amount and historical values, newspaper articles in Chosunsibo are still unsearchable and difficult to access. To the end, this study includes as follows: (1) analyzed the DB construction and metadata elements of newspapers issued in Korea during the Japanese colonial, (2) investigated the morphological characteristics and content of 'Chosunsibo', and (3) derived metadata elements, encoding schemes and controlled vocabularies for 'Chosunsibo'. The final draft was verified in three methods: (1) review and revise through data input tests, (2) consulting by a DB expert agency, and (3) drawing up of crosswalks with metadata standards and related cases. The scope of this study is to design the metadata schema of the historical newspaper 'Chosunsibo' and develop a data input system based on that schema.

• Archives of design research
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• v.17 no.2
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• pp.209-220
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• 2004

This research was conducted to see the effect of color combination and layout in the design of web sites. Eight color combination samples and four basic layouts were selected and web pages designed from their combinations were used in the experiment. The main sensibility effects were found in the 'light, soft, and rich' color combination and in the 'light, dear, simple, warm, neat, and soft layout, respectively. Among the combinations of two factors, the combination of 'dark, hard, and simple' color combination and 'cold, somber, hard, and urban' layout had the sensibility effect. The results showing sensibility word with the sensibility of color combinations in themselves appeared first implies that much of the sensibility effects were caused by the color combinations. In case of layout, as it went from layout A to layout B, to layout C, and to layout D, that is, as the layout got more complicated, it had a 'rich and urban' impression. As a result, the sensibility effect caused by color combination was bigger than the sensibility effect caused by layout. However, layout is crucial in color combinations, it is also important in the design of web sites.

• The Journal of the Acoustical Society of Korea
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• v.18 no.1
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• pp.53-60
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• 1999

This paper is a study on the korean broadcasting speech recognition. Here we present the methods for the large vocabuary continuous speech recognition. Our main concerns are the language modeling and the search algorithm. The used acoustic model is the uni-phone semi-continuous hidden markov model and the used linguistic model is the N-gram model. The search algorithm consist of three phases in order to utilize all available acoustic and linguistic information. First, we use the forward Viterbi beam search to find word end frames and to estimate related scores. Second, we use the backword Viterbi beam search to find word begin frames and to estimate related scores. Finally, we use A/sup */ search to combine the above two results with the N-grams language model and to get recognition results. Using these methods maximum 96.0% word recognition rate and 99.2% syllable recognition rate are achieved for the speaker-independent continuous speech recognition problem with about 12,000 vocabulary size.