• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제8권8호
• /
• pp.2881-2894
• /
• 2014

In complicated environment, context information plays an important role in image segmentation/labeling. The recently proposed auto-context algorithm is one of the effective context-based methods. However, the standard auto-context approach samples the context locations utilizing a fixed radius sequence, which is sensitive to large scale-change of objects. In this paper, we present a scale invariant auto-context (SIAC) algorithm which is an improved version of the auto-context algorithm. In order to achieve scale-invariance, we try to approximate the optimal scale for the image in an iterative way and adopt the corresponding optimal radius sequence for context location sampling, both in training and testing. In each iteration of the proposed SIAC algorithm, we use the current classification map to estimate the image scale, and the corresponding radius sequence is then used for choosing context locations. The algorithm iteratively updates the classification maps, as well as the image scales, until convergence. We demonstrate the SIAC algorithm on several image segmentation/labeling tasks. The results demonstrate improvement over the standard auto-context algorithm when large scale-change of objects exists.

• 가정과삶의질연구
• /
• 제8권1호
• /
• pp.31-47
• /
• 1990

The purpose of this study were to investigate: 1) The level of information-processing competencies of children consumers. 2) The differences of information-processing competencises of children consumers according to the cognitive development stage, the variables related to social learning and the socio-ecomonic variables. 3) The independent influences of variables related to information-processing competencies of children consumers. 4) The independent influences of variables related to information-processing competencies of children consumers according to the cognitive development stage. For these purposes, a survey was conducted using questionaires. The questionaires consisted of mother's and child's were distributed to children of second and 6th grade and their mothers of 5 elementary schools in Seoul 634 cases were selected for data analysis. Then, these data were analyzed with statistical methods such as Frequency Distribution, Percentile, Mean, One-way Anova, Scheff -Test, T-Test, Pearson's Correlation and Multiple Regression Analysis. From these finding, the follawing suggestions are made. First, to improve information processing competencies of children consumers, children consumers should be offered the consumer information that is suitable to child's cognitive development stage. Second, the consumer education and learning practical discriminatory competencies on TV ads. should be conducted for children consumers and his mothers. Third, children consumers should have the opportunities to practice as a consumer. The last, children consumers in low-income should be offered the specially educational program.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
• /
• pp.526-528
• /
• 2004

This paper describes the SAR data processing S/W package it will be able to process the SAR image. This package constructs the several modules: SAR Image processing module, measuring module of surface displacement using differential interferometric SAR method, classification module using the POLSAR data, SAR Focusing module. In this paper, briefly describe the algorithm that is adopted to the functions, and module architecture.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
• /
• 한국정보과학회언어공학연구회 1996년도 제8회 한글 및 한국어 정보처리 학술대회
• /
• pp.313-321
• /
• 1996

본 논문에서는 실용적인 기계번역 시스템을 위하여 다양한 입력 형태에서 나타나는 여러 현상을 전처리하는 기법을 설명한다. 전처리기는 문장 분리, Title 및 나열문 인식, HTML Tag의 처리, 하이픈처리, 숫자 표현 처리, 대소문자의 정규화, 고유명사 인식, 복합단위 인식 등을 수행하여 형태소 분석기의 처리 부담을 줄인다.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
• /
• 한국정보과학회언어공학연구회 2002년도 제14회 한글 및 한국어 정보처리 학술대회
• /
• pp.111-117
• /
• 2002

개체명 인식은 질의응답(QA), 정보 주줄(IE), 텍스트 마이닝 시스템의 성능 향상에 중요한 역할을 담당한다. 이 논문에서는 교사학습 기반의 한국어 개체명 인식에 대해 설명한다. 한국어에서 많은 개체명들이 하나 이상의 단어로 구성되어 있으며, 개체명을 구성하는 단어 사이에는 의존 관계가 존재하고, 개체명과 개체명 주위의 단어 사이에도 문맥적 의존관계를 가지고 있다. 본 논문에서는 가변길이의 개체명과 주변 문맥의 학습을 위해 트라이그램을 이용한 HMM을 사용하였으며, 자료 부족 문제를 해소하기 위해 어휘 기반이 아닌 부개체 유형 기반의 학습을 수행하였다. 학습된 개체명 인식 시스템을 이용하여 경제 분야의 신문 기사에 대한 실험 결과, 84.4%의 정확률과 90.9%의 재현률을 보였다.

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

• 대한음성학회:학술대회논문집
• /
• 대한음성학회 2007년도 한국음성과학회 공동학술대회 발표논문집
• /
• pp.217-220
• /
• 2007

This study outlines a small-sized dialog style ETRI Korean TTS system which applies a HMM based speech synthesis techniques. In order to build the VoiceFont, dialog-style 500 sentences were used in training HMM. And the context information about phonemes, syllables, words, phrases and sentence were extracted fully automatically to build context-dependent HMM. In training the acoustic model, acoustic features such as Mel-cepstrums, logF0 and its delta, delta-delta were used. The size of the VoiceFont which was built through the training is 0.93Mb. The developed HMM-based TTS system were installed on the ARM720T processor which operates 60MHz clocks/second. To reduce computation time, the MLSA inverse filtering module is implemented with Assembly language. The speed of the fully implemented system is the 1.73 times faster than real time.

• 정보교육학회논문지
• /
• 제12권1호
• /
• pp.1-8
• /
• 2008

본 연구는 초등학교에서 정보처리 능력 향상을 위한 교수 방법에 대한 연구이다. 현 시대의 학생들은 정보의 홍수 속에서 '정보를 활용하여 새로운 지식을 창출해 낼 수 있느냐?' 하는 정보 처리 능력이 중요하게 요구된다. 그러나 초등컴퓨터 교육 현장은 '정보 처리 능력'에 대한 교육이 미비한 실정이다. 본 연구는 Barrow의 문제해결학습 모형을 적용하여 정보처리 능력을 신장 시킬 수 있는 방안을 제안하고 적용하였다. 학생들은 컴퓨터를 이용하여 주어진 문제들을 해결하는 과정 속에서 자연스럽게 새로운 정보를 창출할 수 있고, 정보의 연관성을 표현할 수 있는 능력을 기르도록 하였다. 연구방법은 부산의 초등학교 5학년 23명을 대상으로 8개월간 적용하여, 적용 전후를 비교하는 실험연구를 중심으로 하였다. 연구 결과 '정보의 정선', '정보의 신뢰성 확보', '정보의 분류 분석 비교', '정보의 내면화' 등에서 주목할 만한 발전적인 변화가 있었다.

• 대한원격탐사학회지
• /
• 제33권4호
• /
• pp.339-350
• /
• 2017

In recent, cloud computing paradigm and open source as a huge trend in the Information Communication Technology (ICT) are widely applied, being closely interrelated to each other in the various applications. The integrated services by both technologies is generally regarded as one of a prospective web-based business models impacting the concerned industries. In spite of progressing those technologies, there are a few application cases in the geo-based application domains. The purpose of this study is to develop a cloud-based service system for satellite image processing based on the pure and full open source. On the OpenStack, cloud computing open source, virtual servers for system management by open source stack and image processing functionalities provided by OTB have been built or constructed. In this stage, practical image processing functions for KOMPSAT within this service system are thresholding segmentation, pan-sharpening with multi-resolution image sets, change detection with paired image sets. This is the first case in which a government-supporting space science institution provides cloud-based services for satellite image processing functionalities based on pure open source stack. It is expected that this implemented system can expand with further image processing algorithms using public and open data sets.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제16권8호
• /
• pp.2772-2786
• /
• 2022

We had researched an automatic authentication-supported medical information platform[6]. The proposed automatic authentication consists of user authentication and mobile terminal authentication, and the authentications are performed simultaneously in patients' emergency conditions. In this paper, we studied on finding emergency conditions for the automatic authentication by applying big data processing and AI mechanism on the extended medical information platform with an added edge computing system. We used big data processing, SVM, and 1-Dimension CNN of AI mechanism to find emergency conditions as authentication means considering patients' underlying diseases such as hypertension, diabetes mellitus, and arrhythmia. To quickly determine a patient's emergency conditions, we placed edge computing at the end of the platform. The medical information server derives patients' emergency conditions decision values using big data processing and AI mechanism and transmits the values to an edge node. If the edge node determines the patient emergency conditions, the edge node notifies the emergency conditions to the medical information server. The medical server transmits an emergency message to the patient's charge medical staff. The medical staff performs the automatic authentication using a mobile terminal. After the automatic authentication is completed, the medical staff can access the patient's upper medical information that was not seen in the normal condition.