• Title/Summary/Keyword: Data visualization

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Machine Learning based Prediction of The Value of Buildings

  • Lee, Woosik;Kim, Namgi;Choi, Yoon-Ho;Kim, Yong Soo;Lee, Byoung-Dai
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.8
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    • pp.3966-3991
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    • 2018
  • Due to the lack of visualization services and organic combinations between public and private buildings data, the usability of the basic map has remained low. To address this issue, this paper reports on a solution that organically combines public and private data while providing visualization services to general users. For this purpose, factors that can affect building prices first were examined in order to define the related data attributes. To extract the relevant data attributes, this paper presents a method of acquiring public information data and real estate-related information, as provided by private real estate portal sites. The paper also proposes a pretreatment process required for intelligent machine learning. This report goes on to suggest an intelligent machine learning algorithm that predicts buildings' value pricing and future value by using big data regarding buildings' spatial information, as acquired from a database containing building value attributes. The algorithm's availability was tested by establishing a prototype targeting pilot areas, including Suwon, Anyang, and Gunpo in South Korea. Finally, a prototype visualization solution was developed in order to allow general users to effectively use buildings' value ranking and value pricing, as predicted by intelligent machine learning.

Recognition and Visualization of Crack on Concrete Wall using Deep Learning and Transfer Learning (딥러닝과 전이학습을 이용한 콘크리트 균열 인식 및 시각화)

  • Lee, Sang-Ik;Yang, Gyeong-Mo;Lee, Jemyung;Lee, Jong-Hyuk;Jeong, Yeong-Joon;Lee, Jun-Gu;Choi, Won
    • Journal of The Korean Society of Agricultural Engineers
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    • v.61 no.3
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    • pp.55-65
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    • 2019
  • Although crack on concrete exists from its early formation, crack requires attention as it affects stiffness of structure and can lead demolition of structure as it grows. Detecting cracks on concrete is needed to take action prior to performance degradation of structure, and deep learning can be utilized for it. In this study, transfer learning, one of the deep learning techniques, was used to detect the crack, as the amount of crack's image data was limited. Pre-trained Inception-v3 was applied as a base model for the transfer learning. Web scrapping was utilized to fetch images of concrete wall with or without crack from web. In the recognition of crack, image post-process including changing size or removing color were applied. In the visualization of crack, source images divided into 30px, 50px or 100px size were used as input data, and different numbers of input data per category were applied for each case. With the results of visualized crack image, false positive and false negative errors were examined. Highest accuracy for the recognizing crack was achieved when the source images were adjusted into 224px size under gray-scale. In visualization, the result using 50 data per category under 100px interval size showed the smallest error. With regard to the false positive error, the best result was obtained using 400 data per category, and regarding to the false negative error, the case using 50 data per category showed the best result.

Saliency Score-Based Visualization for Data Quality Evaluation

  • Kim, Yong Ki;Lee, Keon Myung
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.15 no.4
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    • pp.289-294
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    • 2015
  • Data analysts explore collections of data to search for valuable information using various techniques and tricks. Garbage in, garbage out is a well-recognized idiom that emphasizes the importance of the quality of data in data analysis. It is therefore crucial to validate the data quality in the early stage of data analysis, and an effective method of evaluating the quality of data is hence required. In this paper, a method to visually characterize the quality of data using the notion of a saliency score is introduced. The saliency score is a measure comprising five indexes that captures certain aspects of data quality. Some experiment results are presented to show the applicability of proposed method.

Social graph visualization techniques for public data (공공데이터에 적합한 다양한 소셜 그래프 비주얼라이제이션 알고리즘 제안)

  • Lee, Manjai;On, Byung-Won
    • Journal of the HCI Society of Korea
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    • v.10 no.1
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    • pp.5-17
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    • 2015
  • Nowadays various public data have been serviced to the public. Through the opening of public data, the transparency and effectiveness of public policy developed by governments are increased and users can lead to the growth of industry related to public data. Since end-users of using public data are citizens, it is very important for everyone to figure out the meaning of public data using proper visualization techniques. In this work, to indicate the significance of widespread public data, we consider UN voting record as public data in which many people may be interested. In general, it has high utilization value by diplomatic and educational purposes, and is available in public. If we use proper data mining and visualization algorithms, we can get an insight regarding the voting patterns of UN members. To visualize, it is necessary to measure the voting similarity values among UN members and then a social graph is created by the similarity values. Next, using a graph layout algorithm, the social graph is rendered on the screen. If we use the existing method for visualizing the social graph, it is hard to understand the meaning of the social graph because the graph is usually dense. To improve the weak point of the existing social graph visualization, we propose Friend-Matching, Friend-Rival Matching, and Bubble Heap algorithms in this paper. We also validate that our proposed algorithms can improve the quality of visualizing social graphs displayed by the existing method. Finally, our prototype system has been released in http://datalab.kunsan.ac.kr/politiz/un/. Please, see if it is useful in the aspect of public data utilization.

Case Analysis of Bible Visualization based on Text Data Traits -Focused on Content, Structure, Quotation of Text- (텍스트 데이터의 특성에 따른 성경 시각화 사례 분석 -텍스트의 내용적, 구조적 특성 및 인용 정보를 중심으로-)

  • Kim, Hyoyoung;Park, Jin Wan
    • The Journal of the Korea Contents Association
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    • v.13 no.8
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    • pp.83-92
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    • 2013
  • Text visualization begins with understanding text itself which is material of visual expression. To visualize any text data, sufficient understanding about characteristics of the text first and the expressive approaches can be decided depending on the derived unique characteristics of the text. In this research we aimed to establish theoretical foundation about the approaches for text visualization by diverse examples of text visualization which are derived through the various characteristics of the text. To do this, we chose the 'Bible' text which is well known globally and digital data of it can be accessed easily and thus diverse text visualization examples exist and analyzed the examples of the bible text visualization. We derived the unique characteristics of text-content, structure, quotation- as criteria for analyzing and supported validity of analysis by adopting at least 2-3 examples for each criterion. In the result, we can comprehend that the goals and expressive approaches are decided depending on the unique characteristics of the Bible text. We expect to build theoretical method for choosing the materials and approaches by analyzing more diverse examples with various point of views on the basis of this research.

Visualization of three-dimensional data with virtual reality (가상현실을 이용한 3차원 데이터 시각화)

  • Lee, Jae Eun;Ahn, Sojin;Jang, Dae-Heung
    • The Korean Journal of Applied Statistics
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    • v.30 no.3
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    • pp.345-362
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    • 2017
  • Various data visualization methods are utilized to analyze a huge amount of data. Among various methods, a three-dimensional image requires the rotation of the image to show a stereo image on a two-dimensional screen. This study discusses two methods of batch method and real-time method, which make it possible to construct of stereo images to improve the restriction of the three-dimensional image display with virtual reality. This investigation can be useful to better explore a three-dimensional data structure.

Flight data analysis and visualization program development (비행시험 자료 분석 및 가시화 프로그램 개발)

  • Park, Young-Keun;Lee, Sung-Jin;Lee, Gi-Doo;Lim, Sang-Soo;Lee, In-Won
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.42 no.3
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    • pp.263-269
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    • 2014
  • Flight test data visualization functions can improve an understanding of flight test results, test procedures, and the performance of a flight vehicle after flight tests. FlyingView was developed for researchers to analyse flight test data in a 3D virtual environment. It also can display X-Y plots using flight test data. It was developed and applied to flight tests of an air-to-ground weapon system of ADD. This paper describes the capabilities of FlyingView.

3D Visualization for Situational Awareness of Air Force Operations (공중작전 상황인식을 위한 3차원 가시화)

  • Kim Seong-Nam;Choi Jong-ln;Kim Chang-Hun;Lim Cheol-Su
    • Journal of KIISE:Computer Systems and Theory
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    • v.32 no.6
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    • pp.314-323
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    • 2005
  • This paper proposes a real-time 3D visualization system for situational awareness of Air force operations. This 3D system of situational awareness supports a high-level commander of Air force during the war game operations. These situation aware supporting data such as the aircraft track data of radar, aircraft schedule database, map and satellite image data are integrated into one structured data and those are visualized as 3D structure. By using an Out-of-Core method, we can visualize a 3D huge data in real-time in mobile notebook environment. The experiment shows several examples of 3D visualization supporting situation awareness for Air force operation.

Protein Interaction Network Visualization System Combined with Gene Ontology (유전자 온톨로지와 연계한 단백질 상호작용 네트워크 시각화 시스템)

  • Choi, Yun-Kyu;Kim, Seok;Yi, Gwan-Su;Park, Jin-Ah
    • Journal of KIISE:Computer Systems and Theory
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    • v.36 no.2
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    • pp.60-67
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    • 2009
  • Analyzing protein-protein interactions(PPI) is an important task in bioinformatics as it can help in new drugs' discovery process. However, due to vast amount of PPI data and their complexity, efficient visualization of the data is still remained as a challenging problem. We have developed efficient and effective visualization system that integrates Gene Ontology(GO) and PPI network to provide better insights to scientists. To provide efficient data visualization, we have employed dynamic interactive graph drawing methods and context-based browsing strategy. In addition, quick and flexible cross-reference system between GO and PPI; LCA(Least Common Ancestor) finding for GO; and etc are supported as special features. In terms of interface, our visualization system provides two separate graphical windows side-by-side for GO graphs and PPI network, and also provides cross-reference functions between them.

Web Service for Traffic Information Using Focus+Context Visualization Technique (Focus + Context 시각화 기법을 사용한 교통정보 웹 서비스)

  • Kim, Kwangseob;Nam, Doohee
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.14 no.2
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    • pp.101-106
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    • 2014
  • Information and Communication Technology environment has been developing rapidly and variety of services are in service. As data becomes increasingly sophisticated. These data was applied techniques of visualization in order to visualize efficiently. Various agencies are providing the map based data in real-time. However, traffic information is getting more complex and users are having a difficulty to understand with convential visualization techniques. This study was designed and implemented in the web service of traffic information using Focus+Context. Web service implemented HTML5(Hyper Text Markup Language 5), and it runs on browser of either desktop or mobile devices. This study sets an example as web application from a user perspective by combining information visualization and traffic information.