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An Approach for the Cross Modality Content-Based Image Retrieval between Different Image Modalities

  • Jeong, Inseong;Kim, Gihong
    • 한국측량학회지
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    • 제31권6_2호
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    • pp.585-592
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    • 2013
  • CBIR is an effective tool to search and extract image contents in a large remote sensing image database queried by an operator or end user. However, as imaging principles are different by sensors, their visual representation thus varies among image modality type. Considering images of various modalities archived in the database, image modality difference has to be tackled for the successful CBIR implementation. However, this topic has been seldom dealt with and thus still poses a practical challenge. This study suggests a cross modality CBIR (termed as the CM-CBIR) method that transforms given query feature vector by a supervised procedure in order to link between modalities. This procedure leverages the skill of analyst in training steps after which the transformed query vector is created for the use of searching in target images with different modalities. Current initial results show the potential of the proposed CM-CBIR method by delivering the image content of interest from different modality images. Despite its retrieval capability is outperformed by that of same modality CBIR (abbreviated as the SM-CBIR), the lack of retrieval performance can be compensated by employing the user's relevancy feedback, a conventional technique for retrieval enhancement.

DESIGN AND IMPLEMENTATION OF FEATURE-BASED 3D GEO-SPATIAL RENDERING SYSTEM USING OPENGL API

  • Kim Seung-Yeb;Lee Kiwon
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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    • pp.321-324
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    • 2005
  • In these days, the management and visualization of 3D geo-spatial information is regarded as one of an important issue in GiS and remote sensing fields. 3D GIS is considered with the database issues such as handling and managing of 3D geometry/topology attributes, whereas 3D visualization is basically concerned with 3D computer graphics. This study focused on the design and implementation for the OpenGL API-based rendering system for the complex types of 3D geo-spatial features. In this approach 3D features can be separately processed with the functions of authoring and manipulation of terrain segments, building segments, road segments, and other geo-based things with texture mapping. Using this implementation, it is possible to the generation of an integrated scene with these complex types of 3D features. This integrated rendering system based on the feature-based 3D-GIS model can be extended and effectively applied to urban environment analysis, 3D virtual simulation and fly-by navigation in urban planning. Furthermore, we expect that 3D-GIS visualization application based on OpenGL API can be easily extended into a real-time mobile 3D-GIS system, soon after the release of OpenGLIES which stands for OpenGL for embedded system, though this topic is beyond the scope of this implementation.

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감정 자질을 이용한 한국어 문장 및 문서 감정 분류 시스템 (A Korean Sentence and Document Sentiment Classification System Using Sentiment Features)

  • 황재원;고영중
    • 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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    • 제14권3호
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    • pp.336-340
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    • 2008
  • 최근 감정 분류에 대한 관심이 높아져 연구가 활발히 진행되고 있다. 문서 전체에 관한 감정의 분류도 중요하지만, 문서를 이루고 있는 문장에 관한 분류도 점차 그 필요성이 높아지고 있다. 본 논문에서는 한국어 감정 분류 시스템 구축을 위해서 추출된 한국어 감정 자질을 이용한 한국어 문장 및 문서 감정 분류에 관해 연구한다. 한국어 감정 분류의 시작은 감정을 내포한 대표적인 어휘로부터 시작하며, 이와 같은 감정 자질들은 문장 및 문서의 감정을 분류하는데 결정적인 관여를 한다. 한국어 감정 자질의 추출을 위하여 영어 단어 시소러스 정보를 이용하여 자질들을 확장하고, 영한사전을 통해 확장된 자질들을 번역함으로써 감정 자질들을 추출하였다. 추출된 감정 자질들을 사용하여, 단어 벡터로 표현된 입력문서를 이진 분류기인 지지벡터 기계(SVM: Support Vector Machine)를 이용하여 문장과 문서에 내포된 감정을 판단하고 평가하였다.

Assisted Magnetic Resonance Imaging Diagnosis for Alzheimer's Disease Based on Kernel Principal Component Analysis and Supervised Classification Schemes

  • Wang, Yu;Zhou, Wen;Yu, Chongchong;Su, Weijun
    • Journal of Information Processing Systems
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    • 제17권1호
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    • pp.178-190
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    • 2021
  • Alzheimer's disease (AD) is an insidious and degenerative neurological disease. It is a new topic for AD patients to use magnetic resonance imaging (MRI) and computer technology and is gradually explored at present. Preprocessing and correlation analysis on MRI data are firstly made in this paper. Then kernel principal component analysis (KPCA) is used to extract features of brain gray matter images. Finally supervised classification schemes such as AdaBoost algorithm and support vector machine algorithm are used to classify the above features. Experimental results by means of AD program Alzheimer's Disease Neuroimaging Initiative (ADNI) database which contains brain structural MRI (sMRI) of 116 AD patients, 116 patients with mild cognitive impairment, and 117 normal controls show that the proposed method can effectively assist the diagnosis and analysis of AD. Compared with principal component analysis (PCA) method, all classification results on KPCA are improved by 2%-6% among which the best result can reach 84%. It indicates that KPCA algorithm for feature extraction is more abundant and complete than PCA.

Human Activity Recognition with LSTM Using the Egocentric Coordinate System Key Points

  • Wesonga, Sheilla;Park, Jang-Sik
    • 한국산업융합학회 논문집
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    • 제24권6_1호
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    • pp.693-698
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    • 2021
  • As technology advances, there is increasing need for research in different fields where this technology is applied. On of the most researched topic in computer vision is Human activity recognition (HAR), which has widely been implemented in various fields which include healthcare, video surveillance and education. We therefore present in this paper a human activity recognition system based on scale and rotation while employing the Kinect depth sensors to obtain the human skeleton joints. In contrast to previous approaches that use joint angles, in this paper we propose that each limb has an angle with the X, Y, Z axes which we employ as feature vectors. The use of the joint angles makes our system scale invariant. We further calculate the body relative direction in the egocentric coordinates in order to provide the rotation invariance. For the system parameters, we employ 8 limbs with their corresponding angles each having the X, Y, Z axes from the coordinate system as feature vectors. The extracted features are finally trained and tested with the Long short term memory (LSTM) Network which gives us an average accuracy of 98.3%.

빅데이터 분석을 통한 전기차 파워트레인 도메인 전기전자 아키텍처 연구 (A Study on the Electrical and Electronic Architecture of Electric Vehicle Powertrain Domain through Big Data Analysis)

  • 김도곤;김우주
    • 한국정보시스템학회지:정보시스템연구
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    • 제31권4호
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    • pp.47-73
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    • 2022
  • Purpose The purpose of this study is to select the electronic architecture concept of the powertrain domain of the electronic platform to be applied to electric vehicles after 2025. Previously, the automotive electrical and electronic architecture was determined only by trend analysis, but the purpose was to determine the scenario based on the data and select it with clear evaluation indicators. Design/methodology/approach This study identified the function to be applied to the powertrain domain of next-generation electric vehicle, estimated the controller, defined the function feature list, organized the scenario candidates with the controller list and function feature list, and selected the final architecture scenario. Findings According to the research results, the powertrain domain of electric vehicles was selected as the architectural concept to apply the DCU (Domain Control Unit) and VCU (Vehicle Control Unit) integrated architecture to next-generation electric vehicles. Although it is disadvantageous or equivalent in terms of cost, it was found to be excellent in most indicators such as stability, security, and hardware demand.

A Close Contact Tracing Method Based on Bluetooth Signals Applicable to Ship Environments

  • Qianfeng Lin;Jooyoung Son
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권2호
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    • pp.644-662
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    • 2023
  • There are still outbreaks of COVID-19 across the world. Ships increase the risk of worldwide transmission of the virus. Close contact tracing remains as an effective method of reducing the risk of virus transmission. Therefore, close contact tracing in ship environments becomes a research topic. Exposure Notifications API (Application Programming Interface) can be used to determine the encountered location points of close contacts on ships. Location points of close contact are estimated by the encountered location points. Risky areas in ships can be calculated based on the encountered location points. The tracking of close contacts is possible with Bluetooth technology without the Internet. The Bluetooth signal can be used to judge the proximity among detecting devices by using the feature that Bluetooth has a strong signal at close range. This Bluetooth feature makes it possible to trace close contacts in ship environments. In this paper, we propose a method for close contact tracing and showing the risky area in a ship environment by combining beacon and Exposure Notification API using Bluetooth technology. This method does not require an Internet connection for tracing close contacts and can protect the personal information of close contacts.

A Study on the Characteristics of the Manufacturing Method of Handbags by Brand

  • Youshin Park
    • 패션비즈니스
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    • 제27권6호
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    • pp.66-84
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    • 2023
  • Handbags are a part of fashion and while their significance and value are increasing, research on this topic is lacking. This study defines handbags and categorizes the materials used for making handbags, sewing methods, expression techniques, and terminologies related to accessories. A total of 1,743 handbags that were released from the Spring 2020 to Fall 2023, Ready-to-Wear collections by 8 selected brands (Hermes, Dior, Fendi, Chanel, Louis Vuitton, Prada, Gucci, and Alexander McQueen), were analyzed. Out of these, 732 unique designs, excluding those with only color variations, were studied. The most common sewing methods were 'Cut, sewing, and edge painting', 'Cylinder arm sewing', 'Cut, edge painting, and sewing', and 'Inverted seam', in that order. Slim strap designs primarily used the 'Cut, sewing, and edge painting' method, whereas the body, especially with narrow and hard leather, was best suited for the 'Cylinder arm sewing machine'. For expression techniques, the most frequently used methods were 'Quilting', 'Metal Eyelet', 'Embossing', 'Printing', 'Punching', and 'Weaving', respectively. The characteristics of each brand's production methods, expression techniques, and accessories were as follows: First, the exposure of logos and monograms is prominent. Unlike clothing, handbags often prominently feature the brand's logo or monogram. Second, signature quilting is a prominent feature. Quilting effectively conveys the brand's signature style, providing cushioning, volume, and pattern effects. Third, sustainable development is a growing trend. Brands are increasingly applying eco-friendly and socially responsible designs.

Effects of Preprocessing on Text Classification in Balanced and Imbalanced Datasets

  • Mehmet F. Karaca
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제18권3호
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    • pp.591-609
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    • 2024
  • In this study, preprocessings with all combinations were examined in terms of the effects on decreasing word number, shortening the duration of the process and the classification success in balanced and imbalanced datasets which were unbalanced in different ratios. The decreases in the word number and the processing time provided by preprocessings were interrelated. It was seen that more successful classifications were made with Turkish datasets and English datasets were affected more from the situation of whether the dataset is balanced or not. It was found out that the incorrect classifications, which are in the classes having few documents in highly imbalanced datasets, were made by assigning to the class close to the related class in terms of topic in Turkish datasets and to the class which have many documents in English datasets. In terms of average scores, the highest classification was obtained in Turkish datasets as follows: with not applying lowercase, applying stemming and removing stop words, and in English datasets as follows: with applying lowercase and stemming, removing stop words. Applying stemming was the most important preprocessing method which increases the success in Turkish datasets, whereas removing stop words in English datasets. The maximum scores revealed that feature selection, feature size and classifier are more effective than preprocessing in classification success. It was concluded that preprocessing is necessary for text classification because it shortens the processing time and can achieve high classification success, a preprocessing method does not have the same effect in all languages, and different preprocessing methods are more successful for different languages.

기능주도개발 Agile 방법을 사용할 때의 안전한 소프트웨어 개발에 관한 문헌연구 (A Systematic Literature Review on Secure Software Development using Feature Driven Development (FDD) Agile Model)

  • 아딜라 알바인;임란 가니;정승렬
    • 인터넷정보학회논문지
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    • 제15권1호
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    • pp.13-27
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    • 2014
  • Agile 방법론은 시간적 제약하에서도 효율적인 개발 프로세스로 빠르게 제품을 완성할 수 있는 방법으로 알려져 있다. 하지만 scrum, XP, DSDM 등과 같은 여타 Agile 방법들처럼 기능주도개발 (FDD) Agile 방법도 보안요소의 불가용성으로 인해 비판을 받고 있다. 이러한 이슈를 보다 자세히 살펴보기 위해 본 연구는 2001년부터 2012년사이에 나타난 연구들에 대한 체계적인 문헌연구를 수행하였다. 본 연구 결과, 현재 FDD 방법은 안전한 소프트웨어 개발을 부분적으로 지원하고 있는 것으로 나타났다. 하지만 안전한 소프트웨어 사용에 관한 상세한 정보가 문헌에 거의 나타나고 있지 않은 것으로 보아 이 분야에 대한 연구 노력은 거의 없어 보인다. 따라서 현재의 5단계 FDD 방법은 안전한 소프트웨어 개발에 충분하지 않음을 알 수 있고 결국, 본 연구는 FDD 방법에서 보안에 기반을 둔 새로운 수행 단계와 프랙티스가 제안될 필요가 있음을 보여준다.