• Korean Journal of Cognitive Science
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• v.21 no.2
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• pp.359-386
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• 2010

In order to evaluate the domain-specific model and process-specific model of spatial and nonspatial working memory (WM), this study manipulated the memory load of the delayed response task and examined how the neural correlates of memory load effect was influenced by the stimulus domain (face and location) at the maintenance stage of WM using an event-related fMRI experiment. One or three face stimuli were presented as target stimuli and participants were asked to maintain the face itself (face WM) or the location of face stimuli (spatial WM). The results of recognition judgment accuracy showed no difference between face WM and spatial WM, and showed equivalent memory load effects of both WM. As a result of brian image analysis, memory load effect at maintenance stage showed that inferior, middle, and superior PFC were recruited by both face WM and spatial WM, and showed that VLPFC was the commonly activated area by both WM, supporting functional specialization of PFC by process components of WM. This study provides evidence for process-specific model in which maintenance of WM is associated with VLPFC.

• Journal of Gifted/Talented Education
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• v.24 no.5
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• pp.851-876
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• 2014

As an empirical test of a model of giftedness with learning disabilities (Song & Porath, 2011), this paper investigated domain thoughts of gifted students without learning disabilities and gifted students with learning disabilities (GLD) in reading, writing, and math. Gifted students in each group were interviewed and the data were analyzed for domain thoughts. The results showed that the former group of gifted students exhibited domain thoughts in a more balanced manner, whereas GLD students showed large discrepancies between domain thoughts; they showed weak specific domain thoughts in contrast to strong other domain thoughts. They also showed ambivalent attitudes even in a domain activity; they presented positive and negative thoughts at the same time. With a comprehensive explanation of the differences between the two groups of gifted students through a cognitive mechanism presented in the model of GLD model, this paper provides new approaches for identification and education of gifted students and GLD students.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.75-88
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• 2023

In a specific domain, experts have different understanding of domain knowledge or different purpose of constructing ontology. These will lead to multiple different ontologies in the domain. This phenomenon is called the ontology heterogeneity. For research fields that require cross-ontology operations such as knowledge fusion and knowledge reasoning, the ontology heterogeneity has caused certain difficulties for research. In this paper, we propose a novel ontology matching model that combines word embedding and a concatenated continuous bag-of-words model. Our goal is to improve word vectors and distinguish the semantic similarity and descriptive associations. Moreover, we make the most of textual and structural information from the ontology and external resources. We represent the ontology as a graph and use the SimRank algorithm to calculate the structural similarity. Our approach employs a similarity queue to achieve one-to-many matching results which provide a wider range of insights for subsequent mining and analysis. This enhances and refines the methodology used in ontology matching.

• Speech Sciences
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• v.11 no.3
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• pp.7-21
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• 2004

The present study aims to investigate domain-initial strengthening phenomenon, which refers to strengthening of articulatory gestures at the initial positions of prosodic domains. More specifically, this paper presents the result of an experimental study of initial syllables with onset consonants (initial-syllable vowels henceforth) of various prosodic domains in English and Hamkyeong Korean, a pitch accent dialect spoken in the northern part of North Korea. The durations of initial-syllable vowels are compared to those of second vowels in real-word tokens for both languages, controlling both stress and segmental environment. Hamkyeong Korean, like English, tuned out to strengthen the domain-initial consonants. With regard to vowel durations, no significant prosodic effect was found in English. On the other hand, Hamkyeong Korean showed significant differences between the durations of initial and non-initial vowels in the higher prosodic domains. The theoretical implications of the findings are as follows: The potentially universal phenomenon of initial strengthening is shown to be subject to language specific variations in its implementation. More importantly, the distinct phonetics- phonology model (Pierrehumbert & Beckman, 1998; Keating, 1990; Cohn, 1993) is better equipped to account for the facts in the present study.

• Journal of Information Processing Systems
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• v.14 no.2
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• pp.377-395
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• 2018

Aiming at the problem of service reliability in resource reservation in cloud computing environments, a model of dynamic cloud resource reservation based on trust is proposed. A domain-specific cloud management architecture is designed in which resources are divided into different management domains according to the types of service for easier management. A dynamic resource reservation mechanism (DRRM) is used to test users' reservation requests and reserve resources for users. According to user preference, several resources are chosen to be candidate resources by fuzzy cluster analysis. The fuzzy evaluation method and a two-way trust evaluation mechanism are adopted to improve the availability and credibility of the model. An analysis and simulation experiments show that this model can increase the flexibility of resource reservation and improve user satisfaction.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.58-65
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• 2023

Bankruptcy is a significant risk for start-up companies, but with the help of cutting-edge artificial intelligence technology, we can now predict bankruptcy with detailed explanations. In this paper, we implemented the Category Boosting algorithm following data cleaning and editing using OpenRefine. We further explained our model using the Shapash library, incorporating domain knowledge. By leveraging the 5C's credit domain knowledge, financial analysts in banks or investors can utilize the detailed results provided by our model to enhance their decision-making processes, even without extensive knowledge about AI. This empowers investors to identify potential bankruptcy risks in their business models, enabling them to make necessary improvements or reconsider their ventures before proceeding. As a result, our model serves as a "glass-box" model, allowing end-users to understand which specific financial indicators contribute to the prediction of bankruptcy. This transparency enhances trust and provides valuable insights for decision-makers in mitigating bankruptcy risks.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.828-833
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• 2009

WWW which is an applicable massive set of document on the Web is a thesaurus of various information for users. However, Search engines spend a lot of time to retrieve necessary information and to filter out unnecessary information for user. In this paper, we propose the EFAM(the Extended Fuzzy AHP Method) model to manage the Web resource efficiently, and to make a decision in the problem of specific domain definitely. The EFAM model is concerned with the emotion analysis based on the domain corpus information, and it composed with systematic common concept grids by the knowledge of multiple experts. Therefore, The proposed the EFAM model can extract the documents by considering on the emotion criteria in the semantic context that is extracted concept from the corpus of specific domain and confirms that our model provides more efficient decision-making through an experiment than the conventional methods such as AHP and Fuzzy AHP which describe as a hierarchical structure elements about decision-making based on the alternatives, evaluation criteria, subjective attribute weight and fuzzy relation between concept and object.

• Journal of Korean Public Health Nursing
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• v.12 no.2
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• pp.107-121
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• 1998

The purpose of this study was to test the revised Health Promotion Model of Pender and to determine the factors to promote health behavior for adolescents' smoking behavior. The subjects of the study was 783 boys of 4 high school students. among 39. schools locating in Daejeon metropolitan city. The data was collected from July 1st to 15th. 1997 by school health nurse The research tool were HPLP of Walker. Pender. General self-efficacy scale of Sherer. control scale was measured by subconcept of hardiness scale of Pollock. and perceived barrier. perceived benefit. activity-related-affect tool were made by researcher via literature review The data were analyzed by SAS program using frequency. t-test. ANOVA. Schefee test. regression. The results were as follows 1. The mean of total health promoting behavior was $2.27\pm.35$. Among sub domain of health promoting behavior, the highest score was interpersonal support$(2.72\pm.60)$. and the lowest was health responsibility $(1.58\pm.44)$. 2. There were statistically significant difference in total health promoting behavior according to religion. parenting style. school performance. girl friend. father's smoking of individual characteristics. 3. The socioeconomic status. smoking, parent pattern. family structure of individual characteristics and experience domain associated with perceived benefit. perceived barrier. activity-related affect. interpersonal influence of behavior-specific cognition and affect domain. The perceived barrier. self-efficacy. girl friend and father's smoking of interpersonal influence. and control explained $25.8\%$ of variance of health promoting behavior. From above results school health nurse has to emphasize on health responsibility for health promotion of adolescent. But they couldn't intervene for parent pattern. socioeconomic status. family structure of individual characteristics and experience domain. it could be possible for school health nurse to promote health of adolescents through improving perceived barrier. also develop program to increase self-efficacy and through parent health class for fathers. Above results point to the importance of including parents in smoking prevention effort targeting adolescents. Because increasing control also promotes health of adolescents. it should be studied further about the specific measure. To verify the variables for increasing the fitness of health promoting model. it needs further replication of the research.

• Journal of Computing Science and Engineering
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• v.6 no.4
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• pp.243-256
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• 2012

In this paper we present a framework for a novel kind of context-aware preference query composition whereby queries for the Preference SQL system are created. We choose a commercial e-business platform for outdoor activities as a use case and develop a context model for this domain within our framework. The suggested model considers explicit user input, domain-specific knowledge, contextual knowledge and location-based sensor data in a comprehensive approach. Aside from the theoretical background of preferences, the optimization of preference queries and our novel generator based model we give special attention to the aspects of the implementation and the practical experiences. We provide a sketch of the implementation and summarize our user studies which have been done in a joint project with an industrial partner.

• Convergence Security Journal
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• v.23 no.5
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• pp.65-72
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• 2023

This paper proposes a method for detecting malicious domains considering human habitual characteristics by building a Deep Learning model based on LSTM (Long Short-Term Memory). DGA (Domain Generation Algorithm) malicious domains exploit human habitual errors, resulting in severe security threats. The objective is to swiftly and accurately respond to changes in malicious domains and their evasion techniques through typosquatting to minimize security threats. The LSTM-based Deep Learning model automatically analyzes and categorizes generated domains as malicious or benign based on malware-specific features. As a result of evaluating the model's performance based on ROC curve and AUC accuracy, it demonstrated 99.21% superior detection accuracy. Not only can this model detect malicious domains in real-time, but it also holds potential applications across various cyber security domains. This paper proposes and explores a novel approach aimed at safeguarding users and fostering a secure cyber environment against cyber attacks.