• Asia pacific journal of information systems
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• 제9권3호
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• pp.1-23
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• 1999

The objective of this study is to examine the media richness theory and the social information processing model by analyzing the effect of media experience on media perception and communication process. To accomplish this objective, a laboratory experiment was conducted. The independent variable was text medium experience and a face-to-face medium was added as a control group. The dependent variables were medium perception and communication process. Medium perception includes perceived richness, medium feeling, task satisfaction, and communication satisfaction. Communication processes were also analyzed to compare each treatment group. The results can be summarized into two facts. First, face-to-face group showed higher perceived richness than text medium group. And experienced text medium group perceived their text medium richer than inexperienced text medium group. Second, experienced text medium groups showed more interactions between subjects than inexperienced text medium group. Experienced text medium group also showed more agreements and meta-communication which could be found in face-to-face group. The result of this study supported media richness theory by finding that face-to-face medium was perceived richer than text medium, And the results also proved social information processing model by comparing experienced text medium group and inexperienced text medium group. The text medium, although thought to be the leanest one, could be perceived richer if users had lots of experience on it.

• 대한공간정보학회지
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• 제5권2호
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• pp.207-220
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• 1997

본 연구에서는 항공사진과 지형공간정보체계를 이용하여 수치영상지도를 제작하기 위한 효율적 방안을 고찰하고, 저가의 개인용 컴퓨터시스템을 기본으로 하는 지형공간정보체계를 이용하여 수치항공사진 영상과 수치지형도를 중첩함으로써, 지형판독성과 활용성이 높은 수치영상지도를 제작하는 실험적 방안을 연구한다. 이를 위하여 지상좌표의 결정, 수치영상처리, 수치표고모형의 생성에 대하여 고찰한 다음, 수치영상지도제작에 필요한 영상자료 입출력, 수치편위미분수정, 항공사진을 이용한 정사투영상의 생성에 관련된 방법을 고찰하고, 수치영상지도를 실험제작하여 그 활용방안을 제시하였다.

• 대한원격탐사학회지
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• 제17권4호
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• pp.319-334
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• 2001

Extracting primitives from imagery plays an important task in visual information processing since the primitives provide useful information about characteristics of the objects and patterns. The human visual system utilizes features without difficulty for image interpretation, scene analysis and object recognition. However, to extract and to analyze feature are difficult processing. The ultimate goal of digital image processing is to extract information and reconstruct objects automatically. The objective of this study is to develop robust method to achieve the goal of the image processing. In this study, an adaptive strategy was developed by implementing Gabor filters in order to extract feature information and to segment images. The Gabor filters are conceived as hypothetical structures of the retinal receptive fields in human vision system. Therefore, to develop a method which resembles the performance of human visual perception is possible using the Gabor filters. A method to compute appropriate parameters of the Gabor filters without human visual inspection is proposed. The entire framework is based on the theory of human visual perception. Digital images were used to evaluate the performance of the proposed strategy. The results show that the proposed adaptive approach improves performance of the Gabor filters for feature extraction and segmentation.

• Asia Marketing Journal
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• 제15권3호
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• pp.31-52
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• 2013

The metacognitive experience of the ease or difficulty with which new, external information can be processed, referred to as 'processing fluency,' has been shown to influence a wide range of human judgments including truth judgments, familiarity judgments, risk perception, evaluation, and preference (see Alter and Oppenheimer 2009 for a review). The current research explores the possibility of a consumer's product innovativeness judgment based on the difficulty of processing new information. In specific, this study examines if the inferential link between (dis)fluency-(un)familiarity can feed into the perception of innovativeness. This study also explores how a consumer's processing motivation can moderate the consumer's reliance on processing fluency in judgments and how the influence of fluency can vary depending on judgment task orders. In an experiment, participants rated a new product's innovativeness and then indicated their product attitude (or vice versa depending on the judgment task order condition) after reading a product review article that was printed in either an easy-to-read or a difficult-to-read font (for fluency manipulation). The findings show that low need for cognition individuals infer higher product innovativeness when processing product information is difficult rather than easy, consistent with the common assumption that 'new information is more difficult to process than familiar information.' The findings also suggest that once low fluency is attributed to innovativeness, it may no longer lead to a negative response to the product. High need for cognition individuals' judgments on product innovativeness are not affected by fluency. The findings also demonstrate a judgment task order effect on the use of fluency in judgments (e.g., Xu and Schwarz 2005). This study provides the first evidence that an individual's fluency experience can be used as a source of information in product innovativeness judgments especially under low processing motivation conditions. The findings can help marketers better understand the malleability of consumer judgments and perceptions of product characteristics (e.g., product innovativeness) by demonstrating an interesting interplay of processing fluency, processing motivation, and judgment task-related contextual factors.

• 대한전자공학회논문지
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• 제26권12호
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• pp.1975-1983
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• 1989

Implementing the linguistic theories on computer, we resolve the problems for restrictions of computer and increase processing efficiency for systemization not for linguistic theory itself. Thus, we modify the grammatical theory to be applied to systems. This paper reports the various problems about constructing dictionaies, defining rules, and appling universal principles and metarules, which is caused to implement the systems based on GPSG. In semantic interpretations, logical expressions which correspond Montague grammar are acquired, and we make a rule connect with several logical expressions. And we show the efficiency of the this method through implementing parser.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -2
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• pp.823-826
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• 2000

Motion detection is an important step in computer vision and image processing. Traditional motion detection systems are classified into two categories, namely, feature based and gradient based. In feature based motion detection, features in consecutive frames are detected and matched. Gradient based methods assume that the intensity varies linearly and locally. The method, which we propose, is neither feature nor gradient based but uses the electric field theory. The pixels in an image are modeled as point charges and motion is detected by using the variations between the two electric fields produced by the charges corresponding to the two images.

• 한국지능시스템학회논문지
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• 제11권5호
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• pp.441-447
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• 2001

In general, Rough Set theory is used for classification, inference, and decision analysis of incomplete data by using approximation space concepts in information system. Information system can include quantitative attribute values which have interval characteristics, or incomplete data such as multiple or unknown(missing) data. These incomplete data cause tole inconsistency in information system and decrease the classification ability in system using Rough Sets. In this paper, we present various types of incomplete data which may occur in information system and propose INcomplete information Processing System(INiPS) which converts incomplete information system into complete information system in using Rough Sets.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 추계학술대회 학술발표 논문집
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• pp.243-251
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• 2000

In general, Rough Set theory is used for classification, inference, and decision analysis of incomplete data by using approximation space concepts in information system. Information system can include quantitative attribute values which have interval characteristics, or incomplete data such as multiple or unknown(missing) data. These incomplete data cause the inconsistency in information system and decrease the classification ability in system using Rough Sets. In this paper, we present various types of incomplete data which may occur in information system and propose INcomplete information Processing System(INiPS) which converts incomplete information system into complete information system in using Rough Sets.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.1001-1004
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• 1993

The Multisensor Fusion Problem (MFP) deals with the methodologies involved in effectively combining together homogeneous or non-homegeneous information obtained from multiple redundant or disparate sensors in order to perform a task more accurately, efficiently, and reliably. The inherent uncertainties in the sensory information are represented using Fuzzy Numbers, -numbers, and the Uncertainty-Reductive Fusion Technique (URFT) is introduced to combine the multiple sensory information into one consensus -number. The MFP is formulated from the Information Theory perspective where sensors are viewed as information sources with a fixed output alphabet and systems are modeled as a network of information processing and processing and propagating channels. The performance of the URFT is compared with other fusion techniques in solving the 3-Sensor Problem.

• Journal of information and communication convergence engineering
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• 제7권3호
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• pp.412-417
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• 2009

With ubiquitous computing aid, it can improve human being's life quality if all people have more convenient medical service under pervasive computing environment. In this paper, for a pervasive health care application for diabetes patient, we've implemented a health care system, which is composed of three parts. Various sensors monitor both outer and inner environment of human such as temperature, blood pressure, pulse, and glycemic index, etc. These sensors form zigbee-based sensor network. And as a backend, medical information server accumulates sensing data and performs back-end processing. To simply transfer these sensing values to a medical team may be a low level's medical service. So, we've designed a model with context awareness for more improved medical service which is based on ART(adaptive resonance theory) neural network. Our experiments show that a proposed healthcare system can provide improved medical service because it can recognize current context of patient more concretely.