• Title/Summary/Keyword: SEED 알고리즘

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A Study on the Hyperspectral Image Classification with the Iterative Self-Organizing Unsupervised Spectral Angle Classification (반복최적화 무감독 분광각 분류 기법을 이용한 하이퍼스펙트럴 영상 분류에 관한 연구)

  • Jo Hyun-Gee;Kim Dae-Sung;Yu Ki-Yun;Kim Yong-Il
    • Korean Journal of Remote Sensing
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    • v.22 no.2
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    • pp.111-121
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    • 2006
  • The classification using spectral angle is a new approach based on the fact that the spectra of the same type of surface objects in RS data are approximately linearly scaled variations of one another due to atmospheric and topographic effects. There are many researches on the unsupervised classification using spectral angle recently. Nevertheless, there are only a few which consider the characteristics of Hyperspectral data. On this study, we propose the ISOMUSAC(Iterative Self-Organizing Modified Unsupervised Spectral Angle Classification) which can supplement the defects of previous unsupervised spectral angle classification. ISOMUSAC uses the Angle Division for the selection of seed points and calculates the center of clusters using spectral angle. In addition, ISOMUSAC perform the iterative merging and splitting clusters. As a result, the proposed algorithm can reduce the time of processing and generate better classification result than previous unsupervised classification algorithms by visual and quantitative analysis. For the comparison with previous unsupervised spectral angle classification by quantitative analysis, we propose Validity Index using spectral angle.

Extraction and Revision of Building Information from Single High Resolution Image and Digital Map (단일 고해상도 위성영상과 수치지도로부터 건물 정보 추출 및 갱신)

  • Byun, Young-Gi;Kim, Hye-Jin;Choi, Jae-Wan;Han, You-Kyung;Kim, Yong-Il
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.26 no.2
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    • pp.149-156
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    • 2008
  • In this paper, we propose a method aiming at updating the building information of the digital maps using single high resolution satellite image and digital map. Firstly we produced a digital orthoimage through the automatic co-registration of QuickBird image and 1:1,000 digital map. Secondly we extracted building height information through the template matching of digital map's building vector data and the image's edges obtained by Canny operator. Finally we refined the shape of some buildings by using the result from template matching as the seed polygon of the greedy snake algorithm. In order to evaluate the proposed method's effectiveness, we estimated accuracy of the extracted building information using LiDAR DSM and 1:1,000 digital map. The evaluation results showed the proposed method has a good potential for extraction and revision of building information.

Bulk Insertion Method for R-tree using Seeded Clustering (R-tree에서 Seeded 클러스터링을 이용한 다량 삽입)

  • 이태원;문봉기;이석호
    • Journal of KIISE:Databases
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    • v.31 no.1
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    • pp.30-38
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    • 2004
  • In many scientific and commercial applications such as Earth Observation System (EOSDIS) and mobile Phone services tracking a large number of clients, it is a daunting task to archive and index ever increasing volume of complex data that are continuously added to databases. To efficiently manage multidimensional data in scientific and data warehousing environments, R-tree based index structures have been widely used. In this paper, we propose a scalable technique called seeded clustering that allows us to maintain R-tree indexes by bulk insertion while keeping pace with high data arrival rates. Our approach uses a seed tree, which is copied from the top k levels of a target R-tree, to classify input data objects into clusters. We then build an R-tree for each of the clusters and insert the input R-trees into the target R-tree in bulk one at a time. We present detailed algorithms for the seeded clustering and bulk insertion as well as the results from our extensive experimental study. The experimental results show that the bulk insertion by seeded clustering outperforms the previously known methods in terms of insertion cost and the quality of target R-trees measured by their query performance.

Development of a Framework for Semi-automatic Building Test Collection Specialized in Evaluating Relation Extraction between Technical Terminologies (기술용어 간 관계추출의 성능평가를 위한 반자동 테스트 컬렉션 구축 프레임워크 개발)

  • Jeong, Chang-Hoo;Choi, Sung-Pil;Lee, Min-Ho;Choi, Yun-Soo
    • The Journal of the Korea Contents Association
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    • v.10 no.2
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    • pp.481-489
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    • 2010
  • Due to the increase of the attention on relation extraction systems, the construction of test collections for assessing their performance has emerged as an important task. In this paper, we propose semi-automatic framework capable of constructing test collections for relation extraction on a large scale. Based on this framework, we develop a test collection which can assess the performance of various approaches to extracting relations between technical terminologies in scientific literatures. This framework can minimize the cost of constructing this kind of collections and reduce the intrinsic fluctuations which may come from the diversity in characteristics of collection developers. Furthermore, we can construct balanced and objective collections by means of controlling the selection process of seed documents and terminologies using the proposed framework.

A Study on Security Consideration and Utilization of Domestic Encryption Algorithm for Developing Secure Smartphone Applications (안전한 스마트폰 애플리케이션 개발을 위한 보안 고려사항 및 국산암호알고리즘 적용 방안 연구)

  • Kim, Jee Yeon;Jeon, Woong Ryul;Lee, Young Sook;Kim, Mi Joo;Jung, Hyun Chul;Won, Dong Ho
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.7 no.1
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    • pp.51-61
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    • 2011
  • A smartphone is a mobile phone that offers more advanced computing ability and connectivity than a contemporary basic feature phone. Unlike feature phone, a smartphone allows the user to install and run more advanced applications based on a specific platform. Smartphones run complete operating system software providing a platform for application developers. A smartphone will become the default computing method for many point activities in the not-too-distant future, such as e-mail, online shopping, gaming, and even video entertainment. For smartphone that contains sensitive information and access the Internet, security is a major issue. In the 1980s, security issues were hardly noticed; however, security is a major issue for users today, which includes smart phones. Because security is much more difficult to address once deployment and implementation are underway, it should be considered from the beginning. Recently our government recognized the importance of smartphone security and published several safety tips for using the smartphone. However, theses tips are user-oriented measures. Maintaining the security of a smartphone involves the active participation of the user. Although it is a important users understand and take full advantage of the facilities afforded by smarphone, it is more important developers distribute the secure smartphone application through the market. In this paper we describe some scenarios in which user is invaded his/her privacy by smartphone stolen, lost, misplaced or infected with virus. Then we suggest the security considerations for securing smartphone applications in respect with developers. We also suggest the methods applying domestic encryption algorithms such as SEED, HIGHT and ARIA in developing secure applications. This suggested security considerations may be used by developers as well as users (especially organizations) interested in enhancing security to related security incidents for current and future use of smartphones.

A Study on the Automatic Detection of Railroad Power Lines Using LiDAR Data and RANSAC Algorithm (LiDAR 데이터와 RANSAC 알고리즘을 이용한 철도 전력선 자동탐지에 관한 연구)

  • Jeon, Wang Gyu;Choi, Byoung Gil
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.31 no.4
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    • pp.331-339
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    • 2013
  • LiDAR has been one of the widely used and important technologies for 3D modeling of ground surface and objects because of its ability to provide dense and accurate range measurement. The objective of this research is to develop a method for automatic detection and modeling of railroad power lines using high density LiDAR data and RANSAC algorithms. For detecting railroad power lines, multi-echoes properties of laser data and shape knowledge of railroad power lines were employed. Cuboid analysis for detecting seed line segments, tracking lines, connecting and labeling are the main processes. For modeling railroad power lines, iterative RANSAC and least square adjustment were carried out to estimate the lines parameters. The validation of the result is very challenging due to the difficulties in determining the actual references on the ground surface. Standard deviations of 8cm and 5cm for x-y and z coordinates, respectively are satisfactory outcomes. In case of completeness, the result of visual inspection shows that all the lines are detected and modeled well as compare with the original point clouds. The overall processes are fully automated and the methods manage any state of railroad wires efficiently.

An Efficient Morphological Segmentation Using a Connected Operator Based on Size and Contrast (크기 및 대조 기반의 Connected Operator를 이용한 효과적인 수리형태학적 영상분할)

  • Kim, Tae-Hyeon;Moon, Young-Shik
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.6
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    • pp.33-42
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    • 2005
  • In this paper, we propose an efficient segmentation algerian using morphological grayscale reconstruction for region-based coding. Each segmentation stage consists of simplification, marker extraction and decision. The simplification removes unnecessary components to make an easier segmentation. The marker extraction finds the flat zones which are the seed points from the simplified image. The decision is to locate the contours of regions detected by the marker extraction. For the simplification, we use a new connected operator based on the size and contrast. In the marker extraction stage, the regions reconstructed to original values we excluded from the candidate marker. For the other regions, the regions which are larger than structuring elements or have higher contrast than a threshold value are selected as markers. For the initial segmentation, the conventional hierarchical watershed algorithm and the extracted markers are used. Finally in the region merging stage, we propose an efficient region merging algorithm which preserves a high quality in terms of the number of regions. At the same time, the pairs which have higher contrast than a threshold are excluded from the region merging stage. Experimental results show that the proposed marker extraction method produces a small number of markers, while maintaining high quality and that the proposed region merging algorithm achieves a good performance in terms of the image quality and the number of regions.

Cataloguing of Anther Expressed Genes through Differential Slot Blot in Oriental Lily (Lilium Oriental Hybrid 'Acapulco') (아카풀코나리에서 Differential Slot Blot을 이용한 약발현 유전자 목록작성)

  • Suh, Eun-Jung;Yu, Hee Ju;Han, Bong Hee;Lim, Yong Pyo;Jeong, Mi-Jeong;Lee, Seong-Kon;Kim, Dong-Hern;Chang, An-Cheol;Yae, Byeong Woo
    • Horticultural Science & Technology
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    • v.31 no.5
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    • pp.598-606
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    • 2013
  • Anther is the major organ of flower in responsible to reproduction and outward appearance. From anther-specific cDNA library of Lilium Oriental Hybrid 'Acapulco', 2000 expressed sequence tags were selected randomly. Differential slot blot analysis with cDNA probes from the anther and leaf was used to get anther-expressed clone and 570 non-redundant ESTs were obtained and sequenced. Compared to the GenBank database using BLASTX algorithm, 191 clones showed significant similarity but others (66.5%) did not measured to known sequence. Functional categories according to gene ontology (GO) annotation included sequence representing a significant portion of protein in cell and cell part respectively. A transcriptional analysis at 7 different organs and developmental stage was performed using northern blot with thirty ESTs as putative anther specific gene. This report suggest that selection of anther expressed clone using differential slot blot was considered as very effective tool and our current study can provide fundamental information on the lily anther including pollen furthermore.

Financial Fraud Detection using Text Mining Analysis against Municipal Cybercriminality (지자체 사이버 공간 안전을 위한 금융사기 탐지 텍스트 마이닝 방법)

  • Choi, Sukjae;Lee, Jungwon;Kwon, Ohbyung
    • Journal of Intelligence and Information Systems
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    • v.23 no.3
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    • pp.119-138
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    • 2017
  • Recently, SNS has become an important channel for marketing as well as personal communication. However, cybercrime has also evolved with the development of information and communication technology, and illegal advertising is distributed to SNS in large quantity. As a result, personal information is lost and even monetary damages occur more frequently. In this study, we propose a method to analyze which sentences and documents, which have been sent to the SNS, are related to financial fraud. First of all, as a conceptual framework, we developed a matrix of conceptual characteristics of cybercriminality on SNS and emergency management. We also suggested emergency management process which consists of Pre-Cybercriminality (e.g. risk identification) and Post-Cybercriminality steps. Among those we focused on risk identification in this paper. The main process consists of data collection, preprocessing and analysis. First, we selected two words 'daechul(loan)' and 'sachae(private loan)' as seed words and collected data with this word from SNS such as twitter. The collected data are given to the two researchers to decide whether they are related to the cybercriminality, particularly financial fraud, or not. Then we selected some of them as keywords if the vocabularies are related to the nominals and symbols. With the selected keywords, we searched and collected data from web materials such as twitter, news, blog, and more than 820,000 articles collected. The collected articles were refined through preprocessing and made into learning data. The preprocessing process is divided into performing morphological analysis step, removing stop words step, and selecting valid part-of-speech step. In the morphological analysis step, a complex sentence is transformed into some morpheme units to enable mechanical analysis. In the removing stop words step, non-lexical elements such as numbers, punctuation marks, and double spaces are removed from the text. In the step of selecting valid part-of-speech, only two kinds of nouns and symbols are considered. Since nouns could refer to things, the intent of message is expressed better than the other part-of-speech. Moreover, the more illegal the text is, the more frequently symbols are used. The selected data is given 'legal' or 'illegal'. To make the selected data as learning data through the preprocessing process, it is necessary to classify whether each data is legitimate or not. The processed data is then converted into Corpus type and Document-Term Matrix. Finally, the two types of 'legal' and 'illegal' files were mixed and randomly divided into learning data set and test data set. In this study, we set the learning data as 70% and the test data as 30%. SVM was used as the discrimination algorithm. Since SVM requires gamma and cost values as the main parameters, we set gamma as 0.5 and cost as 10, based on the optimal value function. The cost is set higher than general cases. To show the feasibility of the idea proposed in this paper, we compared the proposed method with MLE (Maximum Likelihood Estimation), Term Frequency, and Collective Intelligence method. Overall accuracy and was used as the metric. As a result, the overall accuracy of the proposed method was 92.41% of illegal loan advertisement and 77.75% of illegal visit sales, which is apparently superior to that of the Term Frequency, MLE, etc. Hence, the result suggests that the proposed method is valid and usable practically. In this paper, we propose a framework for crisis management caused by abnormalities of unstructured data sources such as SNS. We hope this study will contribute to the academia by identifying what to consider when applying the SVM-like discrimination algorithm to text analysis. Moreover, the study will also contribute to the practitioners in the field of brand management and opinion mining.

Current status and future of insect smart factory farm using ICT technology (ICT기술을 활용한 곤충스마트팩토리팜의 현황과 미래)

  • Seok, Young-Seek
    • Food Science and Industry
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    • v.55 no.2
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    • pp.188-202
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    • 2022
  • In the insect industry, as the scope of application of insects is expanded from pet insects and natural enemies to feed, edible and medicinal insects, the demand for quality control of insect raw materials is increasing, and interest in securing the safety of insect products is increasing. In the process of expanding the industrial scale, controlling the temperature and humidity and air quality in the insect breeding room and preventing the spread of pathogens and other pollutants are important success factors. It requires a controlled environment under the operating system. European commercial insect breeding facilities have attracted considerable investor interest, and insect companies are building large-scale production facilities, which became possible after the EU approved the use of insect protein as feedstock for fish farming in July 2017. Other fields, such as food and medicine, have also accelerated the application of cutting-edge technology. In the future, the global insect industry will purchase eggs or small larvae from suppliers and a system that focuses on the larval fattening, i.e., production raw material, until the insects mature, and a system that handles the entire production process from egg laying, harvesting, and initial pre-treatment of larvae., increasingly subdivided into large-scale production systems that cover all stages of insect larvae production and further processing steps such as milling, fat removal and protein or fat fractionation. In Korea, research and development of insect smart factory farms using artificial intelligence and ICT is accelerating, so insects can be used as carbon-free materials in secondary industries such as natural plastics or natural molding materials as well as existing feed and food. A Korean-style customized breeding system for shortening the breeding period or enhancing functionality is expected to be developed soon.