• Journal of Digital Convergence
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• v.10 no.10
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• pp.215-220
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• 2012

This paper proposes a ontology of tree structure approach for adaptive object recognition in a situation-variant environment. In this paper, we introduce a new concept, ontology of tree structure ontology, for context sensitivity, as we found that many developed systems work in a context-invariant environment. Due to the effects of illumination on a supreme obstinate designing context-sensitive recognition system, we have focused on designing such a context-variant system using ontology of tree structure. Ontology can be defined as an explicit specification of conceptualization of a domain typically captured in an abstract model of how people think about things in the domain. People produce ontologies to understand and explain underlying principles and environmental factors. In this research, we have proposed context ontology, context modeling, context adaptation, and context categorization to design ontology of tree structure based on illumination criteria. After selecting the proper light-ontology domain, we benefit from selecting a set of actions that produces better performance on that domain. We have carried out extensive experiments on these concepts in the area of object recognition in a dynamic changing environment, and we have achieved enormous success, which will enable us to proceed on our basic concepts.

• The Journal of Korea Robotics Society
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• v.19 no.3
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• pp.293-310
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• 2024

In this paper, we propose an agent model for Language-Driven Zero-Shot Object Navigation (L-ZSON) tasks, which takes in a freeform language description of an unseen target object and navigates to find out the target object in an inexperienced environment. In general, an L-ZSON agent should able to visually ground the target object by understanding the freeform language description of it and recognizing the corresponding visual object in camera images. Moreover, the L-ZSON agent should be also able to build a rich spatial context map over the unknown environment and decide efficient exploration actions based on the map until the target object is present in the field of view. To address these challenging issues, we proposes AML (Agent Model for L-ZSON), a novel L-ZSON agent model to make effective use of AI foundation models such as Large Language Model (LLM) and Vision-Language model (VLM). In order to tackle the visual grounding issue of the target object description, our agent model employs GLEE, a VLM pretrained for locating and identifying arbitrary objects in images and videos in the open world scenario. To meet the exploration policy issue, the proposed agent model leverages the commonsense knowledge of LLM to make sequential navigational decisions. By conducting various quantitative and qualitative experiments with RoboTHOR, the 3D simulation platform and PASTURE, the L-ZSON benchmark dataset, we show the superior performance of the proposed agent model.

• Asia pacific journal of information systems
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• v.18 no.2
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• pp.15-40
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• 2008

With the explosive growth of the Internet, Internet shopping malls have become recognized as one of the major purchasing channels for consumers, as well as one of the competitive distribution channels for companies that allow them to contact with customers without intermediaries. It has motivated information systems(IS) researchers to examine the factors influencing consumer behavior and the purchase decision process in the context of Internet shopping malls. Despite the extensive research that has been conducted on the purchase decision process of consumers in online shopping malls, the results have demonstrated a need for further understanding of consumer behavior due to the unique features of virtual space and the characteristics of online consumers. Previous studies from marketing and consumer behavior domains have suggested that the concept of involvement plays an important role in explaining consumers' purchase behavior. Despite the critical role of involvement and the explosive growth of e-commerce, little research has examined the role of involvement in the Internet shopping mall context. With this motivation, this study has two research objectives. First, it introduces and tests an theoretical model capable of better explaining consumers' intention to purchase in the Internet shopping mall context. The proposed model extends and integrates existing models on purchase intention by incorporating purchase experience, innovativeness, and perceived self-control as the consumer factors, along with perceived risk, information provision, and perceived price as the Internet shopping mall factors. Second, this study examines how involvement differences may affect consumers' intention to purchase. For this purpose, two factors from involvement theory, involvement type and involvement level, are introduced into the research model as moderating variables. In order to test the proposed model, the overall approach employed was a field study using the structural equation model. We developed our data collection instrument by adopting existing validated questions wherever possible. All question items were measured with a seven-point, Likert-type scale, with anchors ranging from 'strongly disagree' to 'strongly agree.' Two IS researchers reviewed the instrument and checked its face validity. We collected empirical data for this study over a period of two weeks from subjects who had purchase experiences through Internet shopping malls. A total of 473 complete and valid responses were obtained. We carried out data analysis using a two-step methodology with AMOS 4.0. The first step in the data analysis was to establish the convergent and discriminant validity of the constructs. In the second step, we examined the structural model based on the cleansed measurement model. The empirical results partly support the proposed model and identify the moderating effect of involvement differences. Theoretical and practical implications of the study are discussed, along with its limitations.

• Journal of Korean Society for Quality Management
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• v.25 no.3
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• pp.1-10
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• 1997

In the context of accelerated life tests, procedures are given for estimating the parameters in the modified Arrhenius model and for estimating mean life at a given future stress level. The conditional confidence intervals are obtained by conditioning on ancillary statistics and pivotal quantity. Using the data of Tobias and Trindada(1986), we illustrate conditional confidence interval for parameters under use condition in the modified Arrhenius model.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.611-614
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• 2001

Voice is one of the most efficient communication media and it includes several kinds of factors about speaker, context emotion and so on. Human emotion is expressed is expressed in the speech, the gesture, the physiological phenomena(the breath, the beating of the pulse, etc). In this paper, the emotion recognition method model using neuro-fuzzy in order to have cognizance of emotion from voice signal is presented and simulated.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.180-185
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• 2008

A new method for relative error continuous and discrete time model order reduction is proposed. The reduction technique is based on two recently developed methods, namely frequency domain balanced truncation within a frequency bound and inner-outer factorization techniques. The proposed method is of interest for practical model order reduction because in this context it shows to keep the accuracy of the approximation as high as possible without sacrificing the computational efficiency. Numerical results show the accuracy and efficiency enhancement of the method.

• Information and Communications Magazine
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• v.7 no.3
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• pp.16-26
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• 1990

본 논문은 음성인식을 위한 neural network의 하나인 TRACE model에 대하여 기술한다. TRACE model은 HEARSAY 음성이해 system의 blackboard 구조와 유사한 trace 구조를 사용하여 정보처리 unit들간의 자극성 내지 억제성 연결에 의한 상호작용의 결과로서 음성을 인식한다. TRACE model은 특징층, 음소층 그리고 단어층의 3층으로 구성되며 층간의 unit들이 상호작용할 뿐 아니라 동일층의 unit들이 상호경쟁함으로써 음성인식에 있어서의 context 효과, segmentation 및 잡음 등의 문제를 해결할 수 있다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.1278-1281
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• 2022

현재 Action classification model은 computational resources의 제약으로 인해 video전체의 frame으로 학습하지 못한다. Model에 따라 다르지만, 대부분의 경우 하나의 action을 학습시키기 위해 보통 많게는 32frame, 적게는 8frame으로 model을 학습시킨다. 본 논문에서는 이 한계를 극복하기 위해 하나의 video의 많은 frame들을 mix-up과정을 거쳐 한장의 frame에 여러장의 frame 정보를 담고자 한다. 이 과정에서 video의 시간에 따른 변화(temporal- dynamics)를 손상시키지 않기 위해 linear mix-up이라는 방법을 제안하고 그 성능을 증명하며, 여러장의 frame을 mix-up시켜 모델의 성능을 향상시키는 가능성에 대해 논하고자 한다.

• Geomechanics and Engineering
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• v.31 no.2
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• pp.159-166
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• 2022

The model of two-dimensional plane waves is analyzed in a micropolar-thermoelastic solid with microtemperatures in the context of the three-phase-lag model, dual-phase-lag model, and the Green-Naghdi theory of type III. Harmonic wave analysis is used to hold the solution to the problem. Numerical results of the physical fields are visualized to show the effects of the gravity field, magnetic field, and viscosity. The expression for the field variables is obtained generally and represented graphically for a particular medium.

• Information Systems Review
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• v.15 no.2
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• pp.41-58
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• 2013

The purpose of the present study is to theoretically assess IT Implementation Model of Cooper and Zmud (1990) in a hospital IS use context. A case study was applied to analogical study by interview from several end-users of the information systems at a university hospital. This study presented an EMR(Electronic Medical Record) systems how is initially implemented at an initial stage, continually adopted, adapted, accepted at an adoption stage, and finally rountinized and infused into an organization. Our study also elaborated IT Implementation Model as defining EMR development and its impact on nature of IS use in a hospital. This case study explained the characteristics of EMR and hospital organization context conceptually.