• Title/Summary/Keyword: sparse sampling

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Analysis of Manganese Nodule Abundance in KODOS Area (KODOS 지역의 망간단괴 부존률 분포해석)

  • Jung, Moon Young;Kim, In Kee;Sung, Won Mo;Kang, Jung Keuk
    • Economic and Environmental Geology
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    • v.28 no.3
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    • pp.199-211
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    • 1995
  • The deep sea camera system could render it possible to obtain the detailed information of the nodule distribution, but difficult to estimate nodule abundance quantitatively. In order to estimate nodule abundance quantitatively from deep seabed photographs, the nodule abundance equation was derived from the box core data obtained in KODOS area(long.: $154^{\circ}{\sim}151^{\circ}W$, lat.: $9^{\circ}{\sim}12^{\circ}N$) during two survey cruises carried out in 1989 and 1990. The regression equation derived by considering extent of burial of nodule to Handa's equation compensates for the abundance error attributable to partial burial of some nodules by sediments. An average long axis and average extent of burial of nodules in photographed area are determined according to the surface textures of nodules, and nodule coverage is calculated by the image analysis method. Average nodule abundance estimated from seabed photographs by using the equation is approximately 92% of the actual average abundance in KODOS area. The measured sampling points by box core or free fall grab are in general very sparse and hence nodule abundance distribution should be interpolated and extrapolated from measured data to uncharacterized areas. The another goal of this study is to depict continuous distribution of nodule abundance in KODOS area by using PC-version of geostatistical model in which several stages are systematically proceeded. Geostatistics was used to analyse spatial structure and distribution of regionalized variable(nodule abundance) within sets of real data. In order to investigate the spatial structure of nodule abundance in KODOS area, experimental variograms were calculated and fitted to a spherical models in isotropy and anisotropy, respectively. The spherical structure models were used to map out distribution of the nodule abundance for isotropic and anisotropic models by using the kriging method. The result from anisotropic model is much more reliable than one of isotropic model. Distribution map of nodule abundance produced by PC-version of geostatistical model indicates that approximately 40% of KODOS area is considered to be promising area(nodule abundance > $5kg/m^2$) for mining in case of anisotropy.

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Application of Indicator Geostatistics for Probabilistic Uncertainty and Risk Analyses of Geochemical Data (지화학 자료의 확률론적 불확실성 및 위험성 분석을 위한 지시자 지구통계학의 응용)

  • Park, No-Wook
    • Journal of the Korean earth science society
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    • v.31 no.4
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    • pp.301-312
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    • 2010
  • Geochemical data have been regarded as one of the important environmental variables in the environmental management. Since they are often sampled at sparse locations, it is important not only to predict attribute values at unsampled locations, but also to assess the uncertainty attached to the prediction for further analysis. The main objective of this paper is to exemplify how indicator geostatistics can be effectively applied to geochemical data processing for providing decision-supporting information as well as spatial distribution of the geochemical data. A whole geostatistical analysis framework, which includes probabilistic uncertainty modeling, classification and risk analysis, was illustrated through a case study of cadmium mapping. A conditional cumulative distribution function (ccdf) was first modeled by indicator kriging, and then e-type estimates and conditional variance were computed for spatial distribution of cadmium and quantitative uncertainty measures, respectively. Two different classification criteria such as a probability thresholding and an attribute thresholding were applied to delineate contaminated and safe areas. Finally, additional sampling locations were extracted from the coefficient of variation that accounts for both the conditional variance and the difference between attribute values and thresholding values. It is suggested that the indicator geostatistical framework illustrated in this study be a useful tool for analyzing any environmental variables including geochemical data for decision-making in the presence of uncertainty.

Knowledge, Attitude, and Practice Regarding Cervical Cancer among Rural Community Women in Northeast Thailand

  • Mongsawaeng, Cholticha;Kokorn, Nawaporn;Kujapun, Jirawoot;Norkaew, Jun;Kootanavanichpong, Nusorn;Chavenkun, Wasugree;Ponphimai, Sukanya;Kaewpitoon, Soraya J;Tongtawee, Taweesak;Padchasuwan, Natnapa;Pengsaa, Prasit;Kompor, Pontip;Kaewpitoon, Natthawut
    • Asian Pacific Journal of Cancer Prevention
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    • v.17 no.1
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    • pp.85-88
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    • 2016
  • Background: Cervical cancer is the second most common malignancy among women worldwide, and women of reproductive age in Thailand. However, information on the behavior regarding cervical cancer in rural community Thailand is sparse. Objective: To assess the knowledge, attitude, and practice regarding cervical cancer (CC) among rural community women in Nakhon Ratchasima, Thailand, using predesigned structured questionnaires. Materials and Methods: A cross-sectional survey was conducted in 8 villages of Non Sung district, Nakhon Ratchasima province, Thailand, during January to April 2015. Bloom's taxonomy was used as a framework for the study. 265 women aged between 30-60 years old were selected by simple random sampling. All participants completed predesigned questionnaires with 4 parts: demographic data, knowledge, attitude, and practice regarding cervical cancer. Descriptive statistics were used for analysis in this study. Results: The majority of participants were in the age group of 41-50 years old (42.6%) with senior secondary school level of education (32.1%), marriage status (85.0%), agricultural employment (59.6%), and family income between 6,000-10,000 baht per month (54.3%). Some 63.4% and 68.7% participants had high knowledge and moderate level of attitudes regarding CC, while 41.1%, 48.7%, and 10.2% had neem regularly, irregularly or never screened for CC, respectively. The main reasons for not screening were were shyness (44.4%) and no time (55.6%). Vaginal discharge and itching were the common signs and symptoms of participants who were screened at a health promotion hospital of sub-district. Conclusions: CC is still a health problem in the rural community. Therefore, health education is required, particularly for those who have never undergone screening.

Perception and Help-Seeking Behavior among Older Persons: Six Hypothetical Elder Mistreatment Scenarios (노인학대 인식과 도움요청 태도에 관한 연구: 여섯 가지 노인학대 시나리오를 중심으로)

  • Yoon, Hyun Sook;Lee, Hee Yun;Kwon, Jong Hee;Yoon, Ji Young;Park, Eun Soo;Nam, Ryun;Kang, Sung Bo;Park, Keum Hwa
    • 한국노년학
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    • v.30 no.1
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    • pp.221-240
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    • 2010
  • Despite a growing trend in elder mistreatment, research about the problem and its effects on the victims has been sparse. Notably missing are the perspectives of older adults themselves, whose perceptions and responses to elder mistreatment are greatly affected by social and cultural context. The purpose of this study is to examine factors associated with older persons' perceptions of elder mistreatment and subsequent help-seeking behaviors. Six hypothetical scenarios featuring elders were the basis of interviews with 124 older persons, drawn by a quota sampling strategy. Findings indicated that older persons perceived situations of physical abuse (87.9%), financial abuse (86.3%), and psychological abuse (66.1%) to be elder mistreatment, yet respondents showed less sensitivity to elder mistreatment that took the form of physical mistreatment within a couple (47.6%), neglect (40.3%), and self-neglect (16.9%). Certain scenarios yielded less intention to seek help: namely, physical mistreatment within a couple, neglect, and self-neglect. Older persons' personal characteristics, social factors, and cultural factors exerted significant influence on both perception and help-seeking behavior. Perception was identified as a key factor that significantly influenced help-seeking behavior. Findings point to awareness of cultural and social context for success in elder mistreatment prevention, intervention, and policy design for this population.

A TBM data-based ground prediction using deep neural network (심층 신경망을 이용한 TBM 데이터 기반의 굴착 지반 예측 연구)

  • Kim, Tae-Hwan;Kwak, No-Sang;Kim, Taek Kon;Jung, Sabum;Ko, Tae Young
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.23 no.1
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    • pp.13-24
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    • 2021
  • Tunnel boring machine (TBM) is widely used for tunnel excavation in hard rock and soft ground. In the perspective of TBM-based tunneling, one of the main challenges is to drive the machine optimally according to varying geological conditions, which could significantly lead to saving highly expensive costs by reducing the total operation time. Generally, drilling investigations are conducted to survey the geological ground before the TBM tunneling. However, it is difficult to provide the precise ground information over the whole tunnel path to operators because it acquires insufficient samples around the path sparsely and irregularly. To overcome this issue, in this study, we proposed a geological type classification system using the TBM operating data recorded in a 5 s sampling rate. We first categorized the various geological conditions (here, we limit to granite) as three geological types (i.e., rock, soil, and mixed type). Then, we applied the preprocessing methods including outlier rejection, normalization, and extracting input features, etc. We adopted a deep neural network (DNN), which has 6 hidden layers, to classify the geological types based on TBM operating data. We evaluated the classification system using the 10-fold cross-validation. Average classification accuracy presents the 75.4% (here, the total number of data were 388,639 samples). Our experimental results still need to improve accuracy but show that geology information classification technique based on TBM operating data could be utilized in the real environment to complement the sparse ground information.

Studies on the Occurrence of Upland Weeds and the Competition with Soybeans (전지(田地)와 콩밭에 있어서 잡초(雜草)의 발생(發生) 및 경합(競合)에 관한 조사(調査) 연구(硏究))

  • Lee, Key-Hong;Lee, Eun-Woong
    • Korean Journal of Weed Science
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    • v.2 no.2
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    • pp.75-113
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    • 1982
  • Studies were carried out 1) to define the shape and size of sampling quadrat and its number of observations for weed experiments, 2) to characterize the growth and community of major summer weeds under upland condition and 3) to investigate the factors influencing competition between weeds and soybeans under weed-free and weedy conditions in early and late season cultures. No significant difference was noted among different shapes of quadrat (regular, rectangular, band, and circular) in the sampling efficiency of weeds. The results also suggested that the minimum size of quadrat was 0.25$m^2$ and the minimum number of replication was 2 times per plot. The major dominant weeds were about 10 species in the experimental field and the total number of weeds was in the range of 70 - 1,600 plants per $m^2$. Among the weeds Digitaria sanguinalis and Portulaca oleracea were the most dominant species. Growth amount and reproduction capability were also measured by weed species. Five different weed communities were identified in the field. The degree of dispersion by weed species and association among weeds were investigated. Intra-(within soybeans) and inter-specific (between soybeans and weeds) competition were studied in early and late season cultures of soybeans. The average yield of soybeans per plant was significantly decreased in both season cultures due to intra-specific competition as the planting density of soybeans increased, On the other hand, the average yield of soybeans per l0a was proportionally increased to the increase of planting density and the rate of its increase was more significant under weedy than weed-free condition. Most of the agronomic characteristics of soybeans were affected by weeds and its degree was greater in sparse planting than in dense planting and in early season than in late-season culture. Digitaria sanguinalis was the most competitive to soybeans in early season and both of Digitaria sanguinalis and Portulaca oleracea affected primarily the growth of soybeans in late season with about the same competitiveness. The occurrence of weeds was significantly decreased in early season and slightly decreased in late-season by dense planting of soybeans. The total growth amount of weeds was also considerably decreased by increase of soybean planting density both in early- and late-season cultures. The occurrence of Digitaria sanguinalis which was the most dominant in both seasons, and its growth amount was significantly decreased as the planting density of soybean was increased. On the other hand, the occurrence of Portulaca oleracea which was only dominant in late-season culture did not show significant response to the planting density of soybeans.

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