• Title/Summary/Keyword: Generate Data

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Tree Removal Filtering using Aerial Photographs DTM to Analyze Producing Section of Forest Soil Sediment Disaster (산지토사재해 발생구간 분석을 위한 항공사진 DTM에서의 수목필터링)

  • Woo, Choong-Shik;Youn, Ho-Joong;Jeong, Yong-Ho
    • Journal of the Korean Association of Geographic Information Studies
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    • v.10 no.3
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    • pp.22-30
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    • 2007
  • It is difficult to generate DTM using aerial photographs because trees usually cover disaster occurred areas. So, this study proposed how to filter by moving window using digital aerial photographs and generate accurate DTM. The results were compared with those of adaptive filtering by commercial digital photogrammetry software (Socet set) to find out the effect of tree removal by window size in forest soil sediment disaster. And then they were compared with DTM generated from LiDAR data. As a result, it was showed that the accuracy of moving filtering DTM was lower than that of LiDAR DTM while it was higher by 6m than that of Adaptive filtering.

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A study on the characteristic of problem solving process in the architectural design process (건축디자인과정에서 문제해결의 특성에 관한 연구)

  • Kim, Yong-Il;Han, Jae-Su
    • Journal of The Korean Digital Architecture Interior Association
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    • v.11 no.3
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    • pp.53-59
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    • 2011
  • In creative design, it is necessary to understand the characteristic of architectural design. In the world of design problem, a distinction can be made between those that are well-defined and those that are ill-defined. Well-defined problems are those for which the ends or goal, are already prescribed and apparent, their solution requires the provision of appropriate means. For ill-defined problems, on the other hand, both the ends and the means of solution are unknown at the outset of the problem solving exercise, at least in their entirety. Most of design problems is ill-defined, which is unknown at the beginning of the problem solving exercise. In order to solve the design problem, Designers take advantage of the search methods of problem space, such as global-search-methods(depth-first-methods, breath-first-methods), local-search-methods(generate and test, heuristics, hill-climbing, reasoning) and visual thinking, which is represented through sketching. Sketching is a real part of design reasoning and it does so through a special kind of visual imagery. Also in the design problem solving it have been an important means of problem exploration and solution generation. By sketching, they represent images held in the mind as well as makes graphic images which help generate mental images of entity that is being designed. The search methods of problem space and a visual thinking have been crucially considered in the architectural design. The purpose of this paper is to explore the property of design by means of the pre-existed-experiment data and literature research. The findings will help design the architectural design for more creative results.

Study on Classification Algorithm based on Weight of Support and Confidence Degree (지지도와 신뢰도의 가중치에 기반한 분류알고리즘에 관한 연구)

  • Kim, Keun-Hyung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.4
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    • pp.700-713
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    • 2009
  • Most of any existing classification algorithm in data mining area have focused on goals improving efficiency, which is to generate decision tree more rapidly by utilizing just less computing resources. In this paper, we focused on the efficiency as well as effectiveness that is able to generate more meaningful classification rules in application area, which might consist of the ontology automatic generation, business environment and so on. For this, we proposed not only novel function with the weight of support and confidence degree but also analyzed the characteristics of the weighted function in theoretical viewpoint. Furthermore, we proposed novel classification algorithm based on the weighted function and the characteristics. In the result of evaluating the proposed algorithm, we could perceive that the novel algorithm generates more classification rules with significance more rapidly.

Wireless Triggering Pulse Generation for Digital X-ray Imaging System (디지털 x-ray 영상시스템을 위한 무선 트리거 발생기)

  • Ko, Dae-Sik;Lee, Jae-Cheol;Lee, Joo-Shin
    • Journal of Advanced Navigation Technology
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    • v.11 no.2
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    • pp.163-169
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    • 2007
  • In this paper, we propose a method of trigger pulse generation to capture the image on time by making a synchronization between the x-ray generator and digital x-ray image acquisition system. we designed a wireless trigger pulse generation circuit to make a synchronization between x-ray generator and digital image acquisition system and analysis its performance. When it starts to detect a certain level of x-ray radiation or above from the air, this method starts to generate a ACQ_START signal to indicate the timing for image acquisition starting from digital image acquisition system. Hence, when it starts to detect under certain level of x-ray signal from the air, this method starts to generate a ACC_END signal to indicate the timing for image acquisition stop from digital image acquisition system. Image acquisition is activated only this time between ACQ_START and ACQ_END signal. By doing this wireless detecting of x-ray signal from remote, we can get more accurate timing for capturing the x-ray image and any type of x-ray generator can be connected to digital image acquisition system, regards of wired protocol. This makes easy installation. We could get 3.5 line pair / mm resolution at 20 mAs of x-ray level with resolution chart. This is same or better image comparing to conventional wired result.

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A GA-based Inductive Learning System for Extracting the PROSPECTOR`s Classification Rules (프러스펙터의 분류 규칙 습득을 위한 유전자 알고리즘 기반 귀납적 학습 시스템)

  • Kim, Yeong-Jun
    • Journal of KIISE:Software and Applications
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    • v.28 no.11
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    • pp.822-832
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    • 2001
  • We have implemented an inductive learning system that learns PROSPECTOR-rule-style classification rules from sets of examples. In our a approach, a genetic algorithm is used in which a population consists of rule-sets and rule-sets generate offspring through the exchange of rules relying on genetic operators such as crossover, mutation, and inversion operators. In this paper, we describe our learning environment centering on the syntactic structure and meaning of classification rules, the structure of a population, and the implementation of genetic operators. We also present a method to evaluate the performance of rules and a heuristic approach to generate rules, which are developed to implement mutation operators more efficiently. Moreover, a method to construct a classification system using multiple learned rule-sets to enhance the performance of a classification system is also explained. The performance of our learning system is compared with other learning algorithms, such as neural networks and decision tree algorithms, using various data sets.

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LSTM Language Model Based Korean Sentence Generation (LSTM 언어모델 기반 한국어 문장 생성)

  • Kim, Yang-hoon;Hwang, Yong-keun;Kang, Tae-gwan;Jung, Kyo-min
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.41 no.5
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    • pp.592-601
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    • 2016
  • The recurrent neural network (RNN) is a deep learning model which is suitable to sequential or length-variable data. The Long Short-Term Memory (LSTM) mitigates the vanishing gradient problem of RNNs so that LSTM can maintain the long-term dependency among the constituents of the given input sequence. In this paper, we propose a LSTM based language model which can predict following words of a given incomplete sentence to generate a complete sentence. To evaluate our method, we trained our model using multiple Korean corpora then generated the incomplete part of Korean sentences. The result shows that our language model was able to generate the fluent Korean sentences. We also show that the word based model generated better sentences compared to the other settings.

Generating a Korean Sentiment Lexicon Through Sentiment Score Propagation (감정점수의 전파를 통한 한국어 감정사전 생성)

  • Park, Ho-Min;Kim, Chang-Hyun;Kim, Jae-Hoon
    • KIPS Transactions on Software and Data Engineering
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    • v.9 no.2
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    • pp.53-60
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    • 2020
  • Sentiment analysis is the automated process of understanding attitudes and opinions about a given topic from written or spoken text. One of the sentiment analysis approaches is a dictionary-based approach, in which a sentiment dictionary plays an much important role. In this paper, we propose a method to automatically generate Korean sentiment lexicon from the well-known English sentiment lexicon called VADER (Valence Aware Dictionary and sEntiment Reasoner). The proposed method consists of three steps. The first step is to build a Korean-English bilingual lexicon using a Korean-English parallel corpus. The bilingual lexicon is a set of pairs between VADER sentiment words and Korean morphemes as candidates of Korean sentiment words. The second step is to construct a bilingual words graph using the bilingual lexicon. The third step is to run the label propagation algorithm throughout the bilingual graph. Finally a new Korean sentiment lexicon is generated by repeatedly applying the propagation algorithm until the values of all vertices converge. Empirically, the dictionary-based sentiment classifier using the Korean sentiment lexicon outperforms machine learning-based approaches on the KMU sentiment corpus and the Naver sentiment corpus. In the future, we will apply the proposed approach to generate multilingual sentiment lexica.

Confidence Map based Multi-view Image Generation Method from Stereoscopic Images (양안식 영상을 이용한 신뢰도 기반의 다시점 영상 생성 방법)

  • Kim, Do Young;Ho, Yo-Sung
    • Smart Media Journal
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    • v.2 no.4
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    • pp.27-33
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    • 2013
  • Multi-view video system provides both realistic 3D feelings and free-view navigation. But it is hard to transmit too huge data, so we send only two or three view images and generate intermediate view image using depth information. In this paper, we propose high quality multi-view image generation method from stereoscopic images. Since the stereo matching method does not provide accurate disparity values for all the pixels, especially at the occlusion area, we propose an occlusion handling method using the background pixels at first. We also apply a joint bilateral filtering to enhance the disparity map at the object boundary since it can affect the quality of synthesized images significantly. Finally, we can generate virtual view images at intermediate view positions using confidence map to reduce bad pixel and hole's error. Experimental results show the proposed method performs better than the conventional method.

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ISAR Imaging Using Rear View Radars of an Automobile (후방 감시 차량용 레이다를 이용한 ISAR 영상 형성)

  • Kang, Byung-Soo;Lee, Hyun-Seok;Lee, Seung-Jae;Kang, Min-Suk;Kim, Kyung-Tae
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.25 no.2
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    • pp.245-250
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    • 2014
  • This paper introduces the inverse synthetic aperture radar(ISAR) imaging technique for rear view target of an automobile, which uses both linear frequency modulation-frequency shift keying(LFM-FSK) waveform and monopulse tracking. LFM-FSK waveform consists of two sequential stepped frequency waveforms with some frequency offset, and thus, can be used to generate ISAR images of rear view target of an automobile. However, ISAR images can often be blurred due to non-uniform change rate of relative aspect angle between radar and target. In order to address this problem, one-dimensional(1-D) Lagrange interpolation technique in conjunction with angle information obtained from the monopulse tracking is applied to generate uniform data across the radar's aspect angle. Simulation results show that the proposed method can provide focused ISAR images.

Mapping Tool for Semantic Interoperability of Clinical Terms (임상용어의 의미적 상호운영성을 위한 매핑 도구)

  • Lee, In-Keun;Hong, Sung-Jung;Cho, Hune;Kim, Hwa-Sun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.60 no.1
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    • pp.167-173
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    • 2011
  • Most of the terminologies used in medical domain is not intended to be applied directly in clinical setting but is developed to integrate the terms by defining the reference terminology or concept relations between the terms. Therefore, it is needed to develop the subsets of the terminology which classify categories properly for the purpose of use and extract and organize terms with high utility based on the classified categories in order to utilize the clinical terms conveniently as well as efficiently. Moreover, it is also necessary to develop and upgrade the terminology constantly to meet user's new demand by changing or correcting the system. This study has developed a mapping tool that allows accurate expression and interpretation of clinical terms used for medical records in electronic medical records system and can furthermore secure semantic interoperability among the terms used in the medical information model and generate common terms as well. The system is designed to execute both 1:1 and N:M mapping between the concepts of terms at a time and search for and compare various terms at a time, too. Also, in order to enhance work consistency and work reliability between the task performers, it allows work in parallel and the observation of work processes. Since it is developed with Java, it adds new terms in the form of plug-in to be used. It also reinforce database access security with Remote Method Invocation (RMI). This research still has tasks to be done such as complementing and refining and also establishing management procedures for registered data. However, it will be effectively used to reduce the time and expenses to generate terms in each of the medical institutions and improve the quality of medicine by providing consistent concepts and representative terms for the terminologies used for medical records and inducing proper selection of the terms according to their meaning.