• Title/Summary/Keyword: hotspots

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Detection of Hotspots for Geospatial Lattice Data

  • Moon, Sung-Ho;Kim, Jong-Duk
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.1
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    • pp.131-139
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    • 2006
  • Statistical analyses for spatial data are important features for various types of fields. Spatial data are taken at specific locations or within specific regions and their relative positions are recorded. Lattice data are synoptic observation covering an entire spatial region, like cancer rates corresponding to each county in a state. The main purpose of this paper is to detect hotspots for the region with significantly high or low rates. Kulldorff(1997) detected hotspots based on circular spatial scan statistics. We propose a new method to find any shapes of hotspots by use of echelon analysis with spatial scan statistics.

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Detection of Hotspots on Multivariate Spatial Data

  • Moon, Sung-Ho
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.4
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    • pp.1181-1190
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    • 2006
  • Statistical analyses for spatial data are important features for various types of fields. Spatial data are taken at specific locations or within specific regions and their relative positions are recorded. Lattice data are synoptic observation covering an entire spatial region, like cancer rates corresponding to each county in a state. Until now, the echelon analysis has been applied only to univariate spatial data. As a result, it is impossible to detect the hotspots on the multivariate spatial data In this paper, we expand the spatial data to time series structure. And then we analyze them on the time space and detect the hotspots. Echelon dendrogram has been made by piling up each multivariate spatial data to bring time spatial data. We perform the structural analysis of temporal spatial data.

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Categorical Data Analysis by Means of Echelon Analysis with Spatial Scan Statistics

  • Moon, Sung-Ho
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.1
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    • pp.83-94
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    • 2004
  • In this study we analyze categorical data by means of spatial statistics and echelon analysis. To do this, we first determine the hierarchical structure of a given contingency table by using echelon dendrogram then, we detect candidates of hotspots given as the top echelon in the dendrogram. Next, we evaluate spatial scan statistics for the zones of significantly high or low rates based on the likelihood ratio. Finally, we detect hotspots of any size and shape based on spatial scan statistics.

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A nationwide analysis of mammalian biodiversity hotspots in South Korea (전국단위의 포유류 생물다양성우수지역 분석 연구)

  • Kim, Jiyeon;Kwon, Hyuksoo;Seo, Changwan;Kim, Myungjin
    • Journal of Environmental Impact Assessment
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    • v.23 no.6
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    • pp.453-465
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    • 2014
  • Hotspots are top sites in terms of species diversity as the most threatened and most diverse sites which have been used to select priority areas for reserves. The purpose of this paper is to identify biodiversity hotspots through analyzing nationwide spatial patterns of species richness and rarity of Korean mammals. Four endangered mammals and eleven common mammals were selected as target species. Environmental variables as model input data were consisted of topography, distance, and vegetation structure etc. and Maxent was used to develop species distribution models for target species. Species richness and rarity were used as index of biodiversity. The results of this study were as follows. Firstly, hotspots of species richness for endangered mammals were in high elevation and steep mountain areas. However, species richness for whole mammals were high in low elevation of mountains. Secondly, distribution pattern of species rarity for endangered mammals were similar as richness. However, hotspots of species rarity for whole mammals were a little different from species richness. Species rarity was high in both low and high elevation of mountain areas. This study will provide the useful information for a biodiversity assessment, a habitat conservation, a national ecological network plan, and the management of protected areas.

Analysis on Ecosystem Service Hotspots Based on Regional Environmental Stakeholders' Perception - A case study of Ansan - (지역 환경분야 이해당사자 인식을 반영한 생태계서비스 우수지역 분석 - 안산시를 대상으로 -)

  • Kim, Ilkwon;Kim, Sunghoon;Lee, Jae-Hyuck;Kwon, Hyuksoo
    • Journal of Environmental Impact Assessment
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    • v.27 no.5
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    • pp.417-430
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    • 2018
  • Identification and mangement of ecosystem service hotspots are necessary to set environmental policies that include concepts of ecosystem service. Assessment and mapping of ecosystem service hotspot referring areas with high amount of ecosystem services provide essential information to manage ecosystem services effectively. Assessment of hotspots based on regional environmental stakeholders' perception is an useful approach to identify priority areas where management practices are required. This study estimated weights on regulating ecosystem services from regional environmental stakeholders' surveys in Ansan, and then, identified regulating service hotspots with weights. The result indicated that regulating services are, in order of importance, water quality, air quality, erosion, and climate control. The north-eastern forest of Ansan was mainly revealed as an ecosystem service hotspot. Ecosystem service hotspots were spatially distributed similarly regardless of environmental stakeholders' weights. Identification of ecosystem service hotspot with environmental stakeholders' perception can be applied in decision-support tools for ecosystem service management.

Hotspot Analysis of Korean Twitter Sentiments (한국어 트위터 감정의 핫스팟 분석)

  • Lim, Joasang;Kim, Jinman
    • Journal of Korea Multimedia Society
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    • v.18 no.2
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    • pp.233-243
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    • 2015
  • A hotspot is a spatial pattern that properties or events of spaces are densely revealed in a particular area. Whereas location information is easily captured with increasing use of mobile devices, so is not our emotion unless asking directly through a survey. Tweet provides a good way of analyzing such spatial sentiment, but relevant research is hard to find. Therefore, we analyzed hotspots of emotion in the twitter using spatial autocorrelation. 10,142 tweets and related GPS data were extracted. Sentiment of tweets was classified into good or bad with a support vector machine algorithm. We used Moran's I and Getis-Ord $G_i^*$ for global and local spatial autocorrelation. Some hotspots were found significant and drawn on Seoul metropolitan area map. These results were found very similar to an earlier conducted official survey of happiness index.

WLAN-3GPP Integration Architectures for Packet Based Data Services

  • Raktale Swapnil K.;Kumar Ashok
    • Journal of The Institute of Information and Telecommunication Facilities Engineering
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    • v.2 no.3
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    • pp.48-60
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    • 2003
  • With the rapid successful deployment of WLANs worldwide in numerous hotspots for high data rate, wireless access for data services has created the need to integrate the Cellular Networks with WLAN Networks. The integrated wireless environment will provide the end user a much better service experience along with a single subscription and a single bill. In this paper we focus on inter-working approaches, which combine WLANs and Cellular Networks into an integrated wireless environment capable of ubiquitous access to data services and very high data rates in hotspots areas. We first list the key requirements which are currently being standardized within the 30PP for integration with WLANs networks. We discuss two inter-working architectures namely loosely coupled and tightly coupled This paper will detail the loosely coupled inter-working approach while briefly discussing the tightly coupled inter-working. Finally, we will conclude that the loosely coupled approach is evolutionary and less intrusive than the tightly coupled approach.

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Distribution and phytomedicinal aspects of Paris polyphylla Smith from the Eastern Himalayan Region: A review

  • Sharma, Angkita;Kalita, Pallabi;Tag, Hui
    • CELLMED
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    • v.5 no.3
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    • pp.15.1-15.12
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    • 2015
  • Comparative studies have established that the North-Eastern (NE) region of India which is a part of the Eastern Himalayan region is affluent in both traditional knowledge based phytomedicine and biodiversity. About 1953 ethno-medicinal plants are detailed from the NE region of India out of which 1400 species are employed both as food and ethnopharmacological resources. Nearly 70% of species diversity has been reported from the two Indian biodiversity hotspots-The Western Ghats and the Eastern Himalayas and these hotspots are protected by tribal communities and their ancient traditional knowledge system. Paris polyphylla Smith belongs to the family Melanthiaceae and is a traditional medicinal herb which is known to cure some major ailments such as different types of Cancer, Alzheimer's disease, abnormal uterine bleeding, leishmaniasis etc. The major phytoconstituents are dioscin, polyphyllin D, and balanitin 7. Phylogeny of Paris was inferred from nuclear ITS and plastid psbA-trnH and trnL-trnF DNA sequence data. Results indicated that Paris is monophyletic in all analyses. Rhizoma Paridis, which is the dried rhizome of Paris polyphylla is mainly used in Traditional Chinese Medicine and its mode of action is known for only a few cancer cell lines. The current review determines to sketch an extensive picture of the potency, diversity, distribution and efficacy of Paris polyphylla from the Eastern Himalayan region and the future validation of its phytotherapeutical and molecular attributes by recognizing the Intellectual Property Rights of the Traditional Knowledge holders.

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.

Analysis of Roadkill Hotspot According to the Spatial Clustering Methods (공간 군집지역 탐색방법에 따른 로드킬 다발구간 분석)

  • Song, Euigeun;Seo, Hyunjin;Kim, Kyungmin;Woo, Donggul;Park, Taejin;Choi, Taeyoung
    • Journal of Environmental Impact Assessment
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    • v.28 no.6
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    • pp.580-591
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    • 2019
  • This study analyzed roadkill hotspots in Yeongju, Mungyeong-si Andong-si and Cheongsong-gun to compare the method of searching the area of the spatial cluster for selecting the roadkill hotspots. The local spatial autocorrelation index Getis-Ord Gi* statistics were calculated by different units of analysis, drawing hotspot areas of 9% from 300 m and 14% from 1 km on the basis of the total road area. The rating of Z-score in the 1km hotspot area showed the highest Z-score in the 28th National Road section on the border between Yecheon-gun and Yeongj-si. The kernel density method performed general kernel density estimation and network kernel density estimation analysis, both of which made it easier to visualize roadkill hotspots than district unit analysis, but there were limitations that it was difficult to determine statistically significant priority. As a result, local hotspot areas were found to be different according to the cluster analysis method, and areas that are in common need of reduction measures were found to be the hotspot of 28th National Road through Yeongju-si and Yecheon-gun. It is deemed that the results of this study can be used as basic data when identifying roadkill hotspots and establishing measures to reduce roadkill.