• The Journal of the Acoustical Society of Korea
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• v.18 no.5
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• pp.44-51
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• 1999

This paper presents a massively parallel computational model for the efficient integration of speech and natural language understanding. The phoneme model is based on continuous Hidden Markov Model with context dependent phonemes, and the language model is based on a knowledge base approach. To construct the knowledge base, we adopt a hierarchically-structured semantic network and a memory-based parsing technique that employs parallel marker-passing as an inference mechanism. Our parallel speech recognition algorithm is implemented in a multi-Transputer system using distributed-memory MIMD multiprocessors. Experimental results show that the parallel speech recognition system performs better in recognition accuracy than a word network-based speech recognition system. The recognition accuracy is further improved by applying code-phoneme statistics. Besides, speedup experiments demonstrate the possibility of constructing a realtime parallel speech recognition system.

• Journal of Fisheries and Marine Sciences Education
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• v.26 no.5
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• pp.1108-1118
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• 2014

The purpose of this study was to spread the education of human creativity program and its possibility of consistency, and its application to school system by exploring the evaluation system that determines the valuable and useful decisions. This study was based on the evaluation system according to CIPP model regarding the program's general ideas and its role. The interest of the education of human creativity was increasing as well as its progress of program, and we searched 13 figures and 55 evaluation index according to increase the program's effectiveness and nation-wise situation of evaluation model. The conclusion of this study was that the human creativity program's evaluation was composed of six compartments. And the context evaluation was composed of three evaluation models and eleven index, and input evaluation was composed of three evaluation model and 15 index, while process evaluation is composed of three evaluation models and thirteen evaluation index. Lastly, output evaluation had four evaluation model and sixteen index.

• Journal of The Korean Association For Science Education
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• v.32 no.3
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• pp.486-501
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• 2012

The aims of this study are to investigate two main problems for the hypothetico-deduction method and to develop a scientific inquiry model to resolve these problems. The structure of this scientific inquiry model consists of accounts of the context of discovery and justification that the hypothetico-deduction holds as two main problems : 1) the heuristic flaw in the hypothetico-deduction method is that there is no limit to creating hypotheses to explain natural phenomena; 2) Logically, this brings into question affirming the consequent and modus tollens. The features of the model are as follows: first, the generation of hypotheses using an analogical abduction and the selection of hypotheses using consilience and simplicity; second, the expansion phase as resolution for the fallacy of affirming the consequent and the recycle phase as resolution for modus tollens involving auxiliary hypotheses. Finally, we examine the establishment process of Copernicus's Heliocentric Hypothesis and the main role of the history of science for the historical invalidity of this scientific inquiry model based on three examples of If/and/then type of explanation testing suggested by Lawson (International journal of science and Mathematics Education, 2005a, 3(1): 1-5) We claim that this hypotheticho-deduction process involving abduction approach produced favorable in scientific literacy rising for science teacher as well as students.

• Korean Medical Education Review
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• v.16 no.1
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• pp.25-31
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• 2014

As a preliminary approach to developing a bedside teaching program, this study analyzed the instructional models that have been suggested for bedside teaching. The objects of analysis were four models: the 'Cox model,' which is composed of an experience cycle and an explanation cycle; the 'best teaching practice model' by Janicik and Fletcher; the 'twelve tips to improve bedside teaching' by Ramani; and the SNNAPS model for outpatient education by Wolpaw, Wolpaw, and Papp. This study was conducted in three steps. First, we identified the major components of each model and analyzed their characteristics and limitations. Second, we compared each model in terms of four aspects: the learner, learning interaction, learning context, and organization management. Third, on the basis of prior analysis, the possibilities and potential problems of the models were explored. Based on this review of the existing instructional design models, we proposed an additional four key elements for designing a bedside teaching program: multi-layered learners, various learning environments and contexts, time management by using media, and self-directed design.

• Journal of Mechanical Science and Technology
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• v.15 no.1
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• pp.88-97
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• 2001

The present study numerically investigates the fuel-air mixing characteristics, flame structure, and pollutant emission inside a double-swirler combustor. A PSR(Perfectly Stirred Reactor) based microstructural model is employed to account for the effects of finite rate chemistry on the flame structure and NO formation. The turbulent combustion model is extended to nonadiabatic flame condition with radiation by introducing an enthalpy variable, and the radiative heat loss is calculated by a local, geometry-independent model. The effects of turbulent fluctuation are taken into account by the joint assumed PDFs. Numerical model is based on the non-orthogonal body-fitted coordinate system and the pressure/velocity coupling is handled by PISO algorithm in context with the finite volume formulation. The present PSR-based turbulent combustion model has been applied to analyze the highly intense turbulent nonpremixed flame field in the double swirler combustor. The detailed discussions were made for the flow structure, combustion effects on flow structure, flame structure, and emission characteristics in the highly intense turbulent swirling flame of the double swirler burner.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.6
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• pp.527-533
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• 2008

This paper proposes a product data model and associated process for CAE activities in context of integrated product development. The data model and process enable Product Lifecycle Management(PLM) systems to integrate currently separated CAE activities into the main product development process. The product view concept in the proposed product data model supports independent CAE activities including analysis of various alternatives based on shared product structures with design departments and seamless translation of the CAE result to design product views. The proposed model is validated through an implementation of a prototype PLM system that can integrate and synchronize CAE process with the company-wide product development process.

• STI Policy Review
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• v.1 no.1
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• pp.93-109
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• 2010

Over the last decade, some Korean enterprises have emerged to become global players in their specialized products. How have they achieved such tremendous technological progress in a short period of time? This paper explores that question by examining the characteristics of technological innovation activities at major Korean enterprises. The paper begins with a brief review of the stages of economic growth and science and technology development in Korea. Then, the existing literature, explaining the Korean innovation model, is analyzed in order to establish a new framework for the Korean innovation model. Specifically, Korean firms have experienced three sequential phases, and thus, the Korean model, at the firm level, can be coined as "path-following," "path-revealing," and "path-creating." Then, the stylized facts in the first phase (path-following) and the second phase (path-revealing) are discussed, in the context of empirical evidence from the areas of memory chips, automobiles, shipbuilding, and steel. In terms of technology development, the Korean model has evolved as "collective learning" in the first phase, "collective recombination" of existing knowledge and technology in the second phase, and is assumed as "collective creativity" in the third phase. Ultimately, all three can be classified as "collective creation". Korean firms now face a transition in the modes of technological innovation in order to efficiently implement the third phase. To achieve remarkable progress again, as they did in the past, and to sustain the growth momentum, Korean firms should challenge new dimensions such as creative technological ideas, distinctive technological capabilities, and unique innovation systems -- all of which connote 'uniqueness'. Finally, some lessons from the Korean technological innovation experience are addressed.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.238-246
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• 2021

The rapid rise of the Internet and social media has resulted in a large number of text-based reviews being placed on sites such as social media. In the age of social media, utilizing machine learning technologies to analyze the emotional context of comments aids in the understanding of QoS for any product or service. The classification and analysis of user reviews aids in the improvement of QoS. (Quality of Services). Machine Learning algorithms have evolved into a powerful tool for analyzing user sentiment. Unlike traditional categorization models, which are based on a set of rules. In sentiment categorization, Bidirectional Long Short-Term Memory (BiLSTM) has shown significant results, and Convolution Neural Network (CNN) has shown promising results. Using convolutions and pooling layers, CNN can successfully extract local information. BiLSTM uses dual LSTM orientations to increase the amount of background knowledge available to deep learning models. The suggested hybrid model combines the benefits of these two deep learning-based algorithms. The data source for analysis and classification was user reviews of Indian Railway Services on Twitter. The suggested hybrid model uses the Keras Embedding technique as an input source. The suggested model takes in data and generates lower-dimensional characteristics that result in a categorization result. The suggested hybrid model's performance was compared using Keras and Word2Vec, and the proposed model showed a significant improvement in response with an accuracy of 95.19 percent.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4706-4724
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• 2020

With various structured data, such as the company size, loan balance, and savings accounts, the voice of customer (VOC), which is text data containing contact history and counseling details was analyzed in this study. To analyze unstructured data, the term frequency-inverse document frequency (TF-IDF) analysis, semantic network analysis, sentiment analysis, and a convolutional neural network (CNN) were implemented. A performance comparison of the models revealed that the predictive model using the CNN provided the best performance with regard to predictive power, followed by the model using the TF-IDF, and then the model using semantic network analysis. In particular, a character-level CNN and a word-level CNN were developed separately, and the character-level CNN exhibited better performance, according to an analysis for the Korean language. Moreover, a systematic selection model for optimal text mining techniques was proposed, suggesting which analytical technique is appropriate for analyzing text data depending on the context. This study also provides evidence that the results of previous studies, indicating that individual customers leave when their loyalty and switching cost are low, are also applicable to corporate customers and suggests that VOC data indicating customers' needs are very effective for predicting their behavior.

• The Transactions of the Korea Information Processing Society
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• v.13 no.2
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• pp.18-25
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• 2024

This study proposes the utilization of a model registry to secure interoperability among urban domain information models. It reviews urban information and data sharing along with related standards and standardization activities. By analyzing registry use cases in the context of Spatial Data Infrastructure (SDI), it presents the concept of a model registry for facilitating information sharing and exchange among urban domain information models. An use case linking urban domain information models using the model registry is developed with a prerequisite of seamless implementation of smart city services. The paper discusses technical requirements and outlines technology implementation and validation through prototype development, highlighting them as future research tasks.