• Title/Summary/Keyword: spatial and spatiotemporal data

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Visualizing the distributions and spatiotemporal changes of metabolites in Panax notoginseng by MALDI mass spectrometry imaging

  • Sun, Chenglong;Ma, Shuangshuang;Li, Lili;Wang, Daijie;Liu, Wei;Liu, Feng;Guo, Lanping;Wang, Xiao
    • Journal of Ginseng Research
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    • v.45 no.6
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    • pp.726-733
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    • 2021
  • Background: Panax notoginseng is a highly valued medicinal herb used widely in China and many Asian countries. Its root and rhizome have long been used for the treatment of cardiovascular and hematological diseases. Imaging the spatial distributions and dynamics of metabolites in heterogeneous plant tissues is significant for characterizing the metabolic networks of Panax notoginseng, and this will also provide a highly informative approach to understand the complex molecular changes in the processing of Panax notoginseng. Methods: Here, a high-sensitive MALDI-MS imaging method was developed and adopted to visualize the spatial distributions and spatiotemporal changes of metabolites in different botanical parts of Panax notoginseng. Results: A wide spectrum of metabolites including notoginsenosides, ginsenosides, amino acids, dencichine, gluconic acid, and low-molecular-weight organic acids were imaged in Panax notoginseng rhizome and root tissues for the first time. Moreover, the spatiotemporal alterations of metabolites during the steaming of Panax notoginseng root were also characterized in this study. And, a series of metabolites such as dencichine, arginine and glutamine that changed with the steaming of Panax notoginseng were successfully screened out and imaged. Conclusion: These spatially-resolved metabolite data not only enhance our understanding of the Panax notoginseng metabolic networks, but also provide direct evidence that a serious of metabolic alterations occurred during the steaming of Panax notoginseng.

Spatiotemporal Removal of Text in Image Sequences (비디오 영상에서 시공간적 문자영역 제거방법)

  • Lee, Chang-Woo;Kang, Hyun;Jung, Kee-Chul;Kim, Hang-Joon
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.41 no.2
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    • pp.113-130
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    • 2004
  • Most multimedia data contain text to emphasize the meaning of the data, to present additional explanations about the situation, or to translate different languages. But, the left makes it difficult to reuse the images, and distorts not only the original images but also their meanings. Accordingly, this paper proposes a support vector machines (SVMs) and spatiotemporal restoration-based approach for automatic text detection and removal in video sequences. Given two consecutive frames, first, text regions in the current frame are detected by an SVM-based texture classifier Second, two stages are performed for the restoration of the regions occluded by the detected text regions: temporal restoration in consecutive frames and spatial restoration in the current frame. Utilizing text motion and background difference, an input video sequence is classified and a different temporal restoration scheme is applied to the sequence. Such a combination of temporal restoration and spatial restoration shows great potential for automatic detection and removal of objects of interest in various kinds of video sequences, and is applicable to many applications such as translation of captions and replacement of indirect advertisements in videos.

Spatial Characteristics and Driving Forces of Cultivated Land Changes by Coupling Spatial Autocorrelation Model and Spatial-temporal Big Data

  • Hua, Wang;Yuxin, Zhu;Mengyu, Wang;Jiqiang, Niu;Xueye, Chen;Yang, Zhang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.2
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    • pp.767-785
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    • 2021
  • With the rapid development of information technology, it is now possible to analyze the spatial patterns of cultivated land and its evolution by combining GIS, geostatistical analysis models and spatiotemporal big data for the dynamic monitoring and management of cultivated land resources. The spatial pattern of cultivated land and its evolutionary patterns in Luoyang City, China from 2009 to 2019 were analyzed using spatial autocorrelation and spatial autoregressive models on the basis of GIS technology. It was found that: (1) the area of cultivated land in Luoyang decreased then increased between 2009 and 2019, with an overall increase of 0.43% in 2019 compared to 2009, with cultivated land being dominant in the overall landscape of Luoyang; (2) cultivated land holdings in Luoyang are highly spatially autocorrelated, with the 'high-high'-type area being concentrated in the border area directly north and northeast of Luoyang, while the 'low-low'-type area is concentrated in the south and in the municipal area of Luoyang, and being heavily influenced by topography and urbanization. The expansion determined during the study period mainly took place in the Luoyang City, with most of it being transferred from the 'high-low'-type area; (3) elevation, slope and industrial output values from analysis of the bivariate spatial autocorrelation and spatial autoregressive models of the drivers all had significant effects on the amount of cultivated land holdings, with elevation having a positive effect, and slope and industrial output having a negative effect.

Depth Images-based Human Detection, Tracking and Activity Recognition Using Spatiotemporal Features and Modified HMM

  • Kamal, Shaharyar;Jalal, Ahmad;Kim, Daijin
    • Journal of Electrical Engineering and Technology
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    • v.11 no.6
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    • pp.1857-1862
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    • 2016
  • Human activity recognition using depth information is an emerging and challenging technology in computer vision due to its considerable attention by many practical applications such as smart home/office system, personal health care and 3D video games. This paper presents a novel framework of 3D human body detection, tracking and recognition from depth video sequences using spatiotemporal features and modified HMM. To detect human silhouette, raw depth data is examined to extract human silhouette by considering spatial continuity and constraints of human motion information. While, frame differentiation is used to track human movements. Features extraction mechanism consists of spatial depth shape features and temporal joints features are used to improve classification performance. Both of these features are fused together to recognize different activities using the modified hidden Markov model (M-HMM). The proposed approach is evaluated on two challenging depth video datasets. Moreover, our system has significant abilities to handle subject's body parts rotation and body parts missing which provide major contributions in human activity recognition.

Query Operations for Fuzzy Spatiotemporal Databases (퍼지 시공간 데이터베이스를 위한 질의 연산)

  • Nhan Vu Thi Hong;Chi Jeong-Hee;Ryu Keun-Ho
    • 한국공간정보시스템학회:학술대회논문집
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    • 2004.12a
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    • pp.81-88
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    • 2004
  • GIS (geographic information system) applications increasingly require the representation of geospatial objects with fuzzy extent and querying of time-varying information. In this paper, we Introduce a FSTDB (fuzzy spatiotemporal database) to represent and manage states and events causing changes of dynamic fuzzy objects using fuzzy set theory. We also propose the algorithms for the operators to be included in a GIS to make it able to answer queries depending on fuzzy predicates during a time interval and a method to identify the development process of objects during a certain period based on the designed database. They can be used in application areas handling time-varying geospatial data, including global change (as in climate or land cover change) and social (demographic, health, ect.) application.

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Performance improvement of long-range underwater acoustic communication in deep water using spatiotemporal diversity (심해 장거리 환경에서 시공간 다이버시티를 이용한 수중음향통신성능 향상)

  • Park, Heejin;Kim, Donghyeon;Kim, J.S.;Hahn, Joo Young;Park, Joung-Soo
    • The Journal of the Acoustical Society of Korea
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    • v.38 no.5
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    • pp.587-592
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    • 2019
  • ISI (Inter Symbol Interference) reduces the performance of UAComm (Underwater Acoustic Communication). This paper shows that the performance of UAComm can be improved through the spatiotemporal diversity method that is the combination of spatial diversity and temporal diversity methods. By using spatiotemporal diversity, the array aperture was reduced to increase the efficiency of the UAComm system. It is also verified using the experimental data of BLAC18 (Biomimetic Long range Acoustic Communication 18) conducted in October 2018.

Visual Mapping from Spatiotemporal Table Information to 3-Dimensional Map (시-공간 도표정보의 3차원 지도 기반 가시화기법)

  • Lee, Seok-Jun;Jung, Soon-Ki
    • Journal of the HCI Society of Korea
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    • v.1 no.2
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    • pp.51-58
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    • 2006
  • Information visualization, generally speaking, consists of three steps: transform from raw data to data model, visual mapping from data model to visual structure, and transform from visual structure to information model. In this paper, we propose a visual mapping method from spatiotemporal table information, which is related to events in large-scale building, to 3D map metaphor. The process has also three steps as follows. First, after analyzing the table attributes, we carefully define a context to fully represent the table-information. Second, we choose meaningful attribute sets from the context. Third, each meaningful attribute set is mapped to one well defined visual structure. Our method has several advantages. First, users can intuitively achieve non-spatial information through the 3D map which is a powerful spatial metaphor. Second, this system shows various visual mapping method applicable to other data models in the form of table, especially GIS. After describing the whole concept of our visual mapping, we will show the results of implementation for several requests.

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A Study on the Spatiotemporal Characteristics of Chemical Discharges and Quantified Hazard-Based Result Scores Using Pollutant Release and Transfer Register Data (화학물질배출이동량 자료를 활용한 화학물질배출량 및 유해기반지수 정량화와 시공간 특성 연구)

  • Lim, Yu-Ra;Gan, Sun-Yeong;Bae, Hyun-Joo
    • Journal of Environmental Health Sciences
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    • v.48 no.5
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    • pp.272-281
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    • 2022
  • Background: The constant consumption of chemical products owing to expanding industrialization has led to an increase in public interest in chemical substances. As the production and disposal processes for these chemical products cause environmental problems, regional information on the hazard level of chemical substances is required considering their effects on humans and in order to ensure environmental safety. Objectives: This study aimed to identify hazard contribution and spatiotemporal characteristics by region and chemical by calculating a hazard-based result score using pollutant release and transfer register (PRTR) data. Methods: This study calculated the chemical discharge and hazard-based result score from the Risk-Screening Environmental Indicators (RSEI) model, analyzed their spatiotemporal patterns, and identified hotspot areas where chemical discharges and high hazard-based scores were concentrated. The amount of chemical discharge and hazard-based risk scores for 250 cities and counties across South Korea were calculated using PRTR data from 2011 to 2018. Results: The chemical discharge (high densities in Incheon, Daegu, and Busan) and hazard-based result scores (high densities in Incheon, Chungcheongnam-do, and some areas of Gyeongsangnam-do Province) showed varying spatial patterns. The chemical discharge (A, B) and hazard-based result score (C, D) hotspots were identified. Additionally, identification of the hazard-based result scores revealed differences in the type of chemicals contributing to the discharge. Ethylbenzene accounted for ≥80% of the discharged chemicals in the discharge hotspots, while chromium accounted for >90% of the discharged chemicals in the hazard-based result score hotspots. Conclusions: The RSEI hazard-based result score is a quantitative indicator that considers the degree of impact on human health as a toxicity-weighted value. It can be used for the management of industries discharging chemical substances as well as local environmental health management.

Discovery of Frequent Sequence Pattern in Moving Object Databases (이동 객체 데이터베이스에서 빈발 시퀀스 패턴 탐색)

  • Vu, Thi Hong Nhan;Lee, Bum-Ju;Ryu, Keun-Ho
    • The KIPS Transactions:PartD
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    • v.15D no.2
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    • pp.179-186
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    • 2008
  • The converge of location-aware devices, GIS functionalities and the increasing accuracy and availability of positioning technologies pave the way to a range of new types of location-based services. The field of spatiotemporal data mining where relationships are defined by spatial and temporal aspect of data is encountering big challenges since the increased search space of knowledge. Therefore, we aim to propose algorithms for mining spatiotemporal patterns in mobile environment in this paper. Moving patterns are generated utilizing two algorithms called All_MOP and Max_MOP. The first one mines all frequent patterns and the other discovers only maximal frequent patterns. Our proposed approach is able to reduce consuming time through comparison with DFS_MINE algorithm. In addition, our approach is applicable to location-based services such as tourist service, traffic service, and so on.

Spatiotemporal Distribution of Gastrointestinal Tract Cancer through GIS over 2007-2012 in Kermanshah-Iran

  • Reshadat, Sohyla;Saeidi, Shahram;Zangeneh, Ali Reza;Khademi, Nahid;Khasi, Keyvan;Ghasemi, SayedRamin;Gilan, Nader Rajabi
    • Asian Pacific Journal of Cancer Prevention
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    • v.16 no.17
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    • pp.7737-7742
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    • 2015
  • Background: Cancer is one of the common causes of disability and mortality in the world. The present study aimed to define the spatiotemporal distribution of gastrointestinal tract cancers using a geographic information system (GIS) over the time period of 2007-2012 in Kermanshah-Iran. Materials and Methods: The method of studying was descriptive-analytical as well as comparative with gastrointestinal tract cancer patients based in the City of Kermanshah over the time period covered. For data analysis, the GIS and SPSS 16.0 were applied. Results: According to the pathological reports within the space of 5 years, 283 cases of gastrointestinal tract cancer (157 in males, 156 in females) were reported. The performed tests in terms of spatial distribution in the environment of GIS indicated that the disease demonstrated a clustered pattern in the City of Kermanshah. More to the point, some loci of this disease have emerged in the City of Kermanshah that in the first level, 6 neighborhoods with 29-59 cases of this disease per square kilometer and in the second level, 15-29 cases. Conclusions: Gastrointestinal tract cancer demonstrated an ascending trend within the space of 5 years of research and the spatiotemporal distribution of cancer featured a concentrated and clustered pattern in the City of Kermanshah.