• Title/Summary/Keyword: Multi database

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Cooperative Query Answering Using the Metricized Knowledge Abstraction Hierarchy (계량화된 지식 추상화 계층을 이용한 협력적 질의 처리)

  • Shin, Myung-Keun
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.3
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    • pp.87-96
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    • 2006
  • Most conventional database systems support specific queries that are concerned only with data that match a query qualification precisely. A cooperative query answering supports query analysis, query relaxation and provides approximate answers as well as exact answers. The key problem in the cooperative answering is how to provide an approximate functionality for alphanumeric as well as categorical queries. In this paper, we propose a metricized knowledge abstraction hierarchy that supports multi-level data abstraction hierarchy and distance metric among data values. In order to facilitate the query relaxation, a knowledge representation framework has been adopted, which accommodates semantic relationships or distance metrics to represent similarities among data values. The numeric domains also compatibly incorporated in the knowledge abstraction hierarchy by calculating the distance between target record and neighbor records.

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지구물리탐사자료의 지리정보시스템 해석

  • Han, Su-Hyeong;Kim, Ji-Su;Sin, Jae-U;Gwon, Il-Ryong
    • Journal of the Korean Geophysical Society
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    • v.5 no.1
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    • pp.29-39
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    • 2002
  • Geophysical data sets from the Chojeong area in the Chungbok-Do are compositely studied in terms of multi-attribute interpretations for the subsurface mappings of shallow fracture zones, associated with groundwater reservoir. Utilizing a GIS software, the attribute data were implemented to a database; a lineament from the satellite image, electrical resistivities and its standard deviation, radioactivity, seismic velocity, and bedrock depth. In an attempt to interpret 1-D electrical sounding data in 3-D views, 1-D data are firstly performed horizontal and vertical inter- and extrapolation. Reconstruction of a resistivity volume is found to be an effective scheme for subsurface mapping of shallow fracture zones. Shallow fracture zones are located in the southeastern part of the study area, which are commonly correlated with the various exploration data.

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Parenteral Nutrition in Hospitalized Adult Patients in South Korea (성인 입원환자의 정맥영양요법 사용 현황)

  • Ock, Miyoung;Lee, Sera;Kim, Hyunah
    • Journal of Clinical Nutrition
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    • v.10 no.2
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    • pp.38-44
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    • 2018
  • Purpose: Parenteral nutrition (PN) is known to provide therapeutic beneficial improvements in malnourished patients for whom enteral nutrition is not feasible. The objective of this study was to investigate the current clinical characteristics and utilization of PN in Korea. Methods: We analyzed the Health Insurance Review Agency National Inpatients Sample database from 2014 to 2016, which included 13% of all hospitalized patients in Korea. Adult patients aged 20 years or older and receiving premixed multi-chamber bag containing PN were included for this study. Patient characteristics, admission type, primary diagnosis, and hospital demographics were evaluated. SAS version 9.4 was used for data analysis. Results: From 2014 to 2016, 149,504 patients received premixed PN, with 226,281 PN prescriptions being written. The mean patient age was 65.0 years, and 81,876 patients (54.8%) were male. Premixed 3-chamber bag and 2-chamber bag PN solutions were utilized in 131,808 (88.2%) and 32,033 (21.4%) patients, respectively. The number of patients hospitalized through the emergency department were 70,693 (47.3%), whereas 43,125 patients (28.8%) were administered PN in intensive care units. In the adult PN patients, the highest primary diagnosis was malignant neoplasm of the stomach (8,911, 6.0%), followed by organism unspecified pneumonia (7,008, 4.7%), and gastroenteritis and colitis of unspecified origin (6,381, 4.3%). Overall, 34% of adult PN patients were diagnosed with malignancies, the most common being neoplasm of the stomach (17.7%), neoplasm of bronchus/lung (11.2%), neoplasm of colon (11.1%), and neoplasm of liver/intrahepatic bile ducts (10.0%). PN solutions were most frequently administered in the metropolitan area (55.0%) and in hospitals with more than 1,000 beds (23.6%). Conclusion: PN was commonly administered in older patients, with primary diagnosis of malignancy in a significant number of cases. This study is the first large-scale description of PN-prescribing patterns in real-world clinical practice in South Korea.

Development and Application of Arduino Based Multi-sensors System for Agricultural Environmental Information Collection - A Case of Hog Farm in Yeoju, Gyeonggi - (농업환경정보 수집을 위한 아두이노 기반 멀티 센서 시스템 개발 및 적용 - 경기 여주시 소재 양돈농가를 사례로 -)

  • Han, Jung-Heon;Park, Jong-Jun
    • Journal of Korean Society of Rural Planning
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    • v.25 no.2
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    • pp.15-21
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    • 2019
  • The agricultural environment is changing and becoming more advanced due to the influence of the 4th Industrial Revolution. From the basic plan of Rural Informatics to the current level of 2nd generation smart farms aimed at improving productivity using Big data, cloud network and more IoT technology. We are continuing to provide support and research and development. However, many problems remain to be solved in order to supply and settle smart farms in Korea. The purpose of this study is to provide a method of collecting and sharing data on farming environment and to help improve the income and productivity of farmers based on collected data. In the case of hog farm, the multiple sensors for environmental data like temperature, humidity and gases and the network environment for connecting the internet were established. The environment sensor was made using the ESP8266 Node MCU board as micro-controller, DHT22 sensor for temperature and humidity, and MQ series sensors for various gases in the hog pens. The network sensor was applied experimentally for one month and the environmental data of the hog farm was stored on a web database. This study is expected to raise the importance of collecting and managing the agricultural and environmental data, for the next generation farmers to understand the smart farm more easily and to try it by themselves.

Multi-tissue observation of the long non-coding RNA effects on sexually biased gene expression in cattle

  • Yoon, Joon;Kim, Heebal
    • Asian-Australasian Journal of Animal Sciences
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    • v.32 no.7
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    • pp.1044-1051
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    • 2019
  • Objective: Recent studies have implied that gene expression has high tissue-specificity, and therefore it is essential to investigate gene expression in a variety of tissues when performing the transcriptomic analysis. In addition, the gradual increase of long non-coding RNA (lncRNA) annotation database has increased the importance and proportion of mapped reads accordingly. Methods: We employed simple statistical models to detect the sexually biased/dimorphic genes and their conjugate lncRNAs in 40 RNA-seq samples across two factors: sex and tissue. We employed two quantification pipeline: mRNA annotation only and mRNA+lncRNA annotation. Results: As a result, the tissue-specific sexually dimorphic genes are affected by the addition of lncRNA annotation at a non-negligible level. In addition, many lncRNAs are expressed in a more tissue-specific fashion and with greater variation between tissues compared to protein-coding genes. Due to the genic region lncRNAs, the differentially expressed gene list changes, which results in certain sexually biased genes to become ambiguous across the tissues. Conclusion: In a past study, it has been reported that tissue-specific patterns can be seen throughout the differentially expressed genes between sexes in cattle. Using the same dataset, this study used a more recent reference, and the addition of conjugate lncRNA information, which revealed alterations of differentially expressed gene lists that result in an apparent distinction in the downstream analysis and interpretation. We firmly believe such misquantification of genic lncRNAs can be vital in both future and past studies.

A Review of the Literature Using the Korean National Environmental Health Survey (cycle 1-3) (국민환경보건기초조사 1~3기의 연구성과 검토)

  • Lee, Seungho;Kim, Jin Hee;Choi, Yoon-Hyeong;Kim, Sungkyoon;Lee, Kyung mu;Park, Jae Bum
    • Journal of Environmental Health Sciences
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    • v.47 no.3
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    • pp.227-244
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    • 2021
  • Objectives: The Korean National Environmental Health Survey provides representative biomonitoring data for environmental pollutants in South Korea. Over the last decade, there have been various studies published using this data. In this study, we aimed to provide information and implications by reviewing each study. Methods: We searched comprehensive electronic databases from PubMed, Google Scholar, and Naver Academic database using the key words 'Korean National Environmental Health Survey' and 'KoNEHS' through March 2021. A total of 57 studies were selected after reviewing the relevance of the data. Results: The most frequently studied pollutants were heavy metals (10), Cotinine (8), Bisphenol A (7), and Phthalates (6), in that order. In particular, Phthalates, Bisphenol A, and Parabens were often studied together (6). A decline in urinary cotinine and heavy metals in the body was shown over time among studies on exposure association. It was demonstrated that Phthalates and Bisphenol A were significantly related to obesity and diabetes from the studies of health impacts. Cross-section study design, spot urine, and insufficient health status information were mostly reported as limitations of the data. Conclusion: Since research has been focused on adults, further investigations of children and adolescents are required. In this regard, it is necessary to maintain the consistency of the data structure and provide integrated weights for all ages. In addition, it would allow the measurement of several environmental pollutants by considering subsample design. Lastly, integrated studies with multi-cycles and the health effects from co-exposure to multiple chemicals would be expected to provide important knowledge.

A computational estimation model for the subgrade reaction modulus of soil improved with DCM columns

  • Dehghanbanadaki, Ali;Rashid, Ahmad Safuan A.;Ahmad, Kamarudin;Yunus, Nor Zurairahetty Mohd;Said, Khairun Nissa Mat
    • Geomechanics and Engineering
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    • v.28 no.4
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    • pp.385-396
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    • 2022
  • The accurate determination of the subgrade reaction modulus (Ks) of soil is an important factor for geotechnical engineers. This study estimated the Ks of soft soil improved with floating deep cement mixing (DCM) columns. A novel prediction model was developed that emphasizes the accuracy of identifying the most significant parameters of Ks. Several multi-layer perceptron (MLP) models that were trained using the Levenberg Marquardt (LM) backpropagation method were developed to estimate Ks. The models were trained using a reliable database containing the results of 36 physical modelling tests. The input parameters were the undrained shear strength of the DCM columns, undrained shear strength of soft soil, area improvement ratio and length-to-diameter ratio of the DCM columns. Grey wolf optimization (GWO) was coupled with the MLPs to improve the performance indices of the MLPs. Sensitivity tests were carried out to determine the importance of the input parameters for prediction of Ks. The results showed that both the MLP-LM and MLP-GWO methods showed high ability to predict Ks. However, it was shown that MLP-GWO (R = 0.9917, MSE = 0.28 (MN/m2/m)) performed better than MLP-LM (R =0.9126, MSE =6.1916 (MN/m2/m)). This proves the greater reliability of the proposed hybrid model of MLP-GWO in approximating the subgrade reaction modulus of soft soil improved with floating DCM columns. The results revealed that the undrained shear strength of the soil was the most effective factor for estimation of Ks.

Establishment of a BaTiO3-based Computational Science Platform to Predict Multi-component Properties (다성분계 물성을 예측하기 위한 BaTiO3기반 계산과학 플랫폼 구축)

  • Lee, Dong Geon;Lee, Han Uk;Im, Won Bin;Ko, Hyunseok;Cho, Sung Beom
    • Journal of Sensor Science and Technology
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    • v.31 no.5
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    • pp.318-323
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    • 2022
  • Barium titanate (BaTiO3) is considered to be a beneficial ceramic material for multilayer ceramic capacitor (MLCC) applications because of its high dielectric constant and low dielectric loss. Numerous attempts have been made to improve the physical properties of BaTiO3 in response to recent market trends by employing multicomponent alloying strategies. However, owing to its significant number of atomic combinations and unpredictable physical properties, finding a traditional experimental approach to develop multicomponent systems is difficult; the development of such systems is also time-consuming. In this study, 168 new structures were fabricated using special quasi-random structures (SQSs) of Ba1-xCaxTi1-yZryO3, and 1680 physical properties were extracted from first-principles calculations. In addition, we built an integrated database to manage the computational results, and will provide big data solutions by performing data analysis combined with AI modeling. We believe that our research will enable the global materials market to realize digital transformation through datalization and intelligence of the material development process.

Derivation of Surface Temperature from KOMPSAT-3A Mid-wave Infrared Data Using a Radiative Transfer Model

  • Kim, Yongseung
    • Korean Journal of Remote Sensing
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    • v.38 no.4
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    • pp.343-353
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    • 2022
  • An attempt to derive the surface temperature from the Korea Multi-purpose Satellite (KOMPSAT)-3A mid-wave infrared (MWIR) data acquired over the southern California on Nov. 14, 2015 has been made using the MODerate resolution atmospheric TRANsmission (MODTRAN) radiative transfer model. Since after the successful launch on March 25, 2015, the KOMPSAT-3A spacecraft and its two payload instruments - the high-resolution multispectral optical sensor and the scanner infrared imaging system (SIIS) - continue to operate properly. SIIS uses the MWIR spectral band of 3.3-5.2 ㎛ for data acquisition. As input data for the realistic simulation of the KOMPSAT-3A SIIS imaging conditions in the MODTRAN model, we used the National Centers for Environmental Prediction (NCEP) atmospheric profiles, the KOMPSAT-3Asensor response function, the solar and line-of-sight geometry, and the University of Wisconsin emissivity database. The land cover type of the study area includes water,sand, and agricultural (vegetated) land located in the southern California. Results of surface temperature showed the reasonable geographical pattern over water, sand, and agricultural land. It is however worthwhile to note that the surface temperature pattern does not resemble the top-of-atmosphere (TOA) radiance counterpart. This is because MWIR TOA radiances consist of both shortwave (0.2-5 ㎛) and longwave (5-50 ㎛) components and the surface temperature depends solely upon the surface emitted radiance of longwave components. We found in our case that the shortwave surface reflection primarily causes the difference of geographical pattern between surface temperature and TOA radiance. Validation of the surface temperature for this study is practically difficult to perform due to the lack of ground truth data. We therefore made simple comparisons with two datasets over Salton Sea: National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL) field data and Salton Sea data. The current estimate differs with these datasets by 2.2 K and 1.4 K, respectively, though it seems not possible to quantify factors causing such differences.

Customized AI Exercise Recommendation Service for the Balanced Physical Activity (균형적인 신체활동을 위한 맞춤형 AI 운동 추천 서비스)

  • Chang-Min Kim;Woo-Beom Lee
    • Journal of the Institute of Convergence Signal Processing
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    • v.23 no.4
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    • pp.234-240
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    • 2022
  • This paper proposes a customized AI exercise recommendation service for balancing the relative amount of exercise according to the working environment by each occupation. WISDM database is collected by using acceleration and gyro sensors, and is a dataset that classifies physical activities into 18 categories. Our system recommends a adaptive exercise using the analyzed activity type after classifying 18 physical activities into 3 physical activities types such as whole body, upper body and lower body. 1 Dimensional convolutional neural network is used for classifying a physical activity in this paper. Proposed model is composed of a convolution blocks in which 1D convolution layers with a various sized kernel are connected in parallel. Convolution blocks can extract a detailed local features of input pattern effectively that can be extracted from deep neural network models, as applying multi 1D convolution layers to input pattern. To evaluate performance of the proposed neural network model, as a result of comparing the previous recurrent neural network, our method showed a remarkable 98.4% accuracy.