• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.221-222
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• 2006

Today, Web Services is very well-known as a middle-ware that can inter-communicate between many different program languages. This paper test web services by implementing two different web services platforms which are MS .NET based server and Apache AXIS based client. Those platforms have different data structure/process, and they could not give the developer seamless data compatibility through web services. However we confirmed that handling data, by some data transforming rules, web services can successfully inter-communicate between MS .NET based server and Apache AXIS based client.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1265-1267
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• 2015

최근 IoT 기술의 등장으로 저전력 소형 컴퓨터인 라즈베리파이 클러스터가 IoT 데이터 처리를 위해 사용되고 있다. IoT 기술이 발전하면서 다양한 데이터가 생성되고 있으며 IoT 환경에서도 빅데이터 처리가 요구되고 있다. 빅데이터 처리 프레임워크에는 일반적으로 하둡이 사용되고 있으며 이를 대체하는 솔루션으로 Apache Spark가 등장했다. 본 논문에서는 PC와 라즈베리파이 클러스터에서의 성능을 Apache Spark를 통해 비교하였다. 본 실험을 위해 Yelp 데이터를 사용하며 데이터 로드 시간과 Spark SQL을 이용한 데이터 처리 시간을 통해 성능을 비교하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.543-544
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• 2020

최근 급증하는 클라우드 도입 정책에 비해 클라우드 취약점 진단 및 관리 기술은 상대적으로 미비하여 오픈소스로 사용되고 있는 클라우드 기술의 신규 취약점이 발생하고 있다. 본 논문에서는 Apache Spark를 활용한 쿠버네티스 클라우드 취악점 진단 시스템을 제안한다. 제안하는 시스템은 Apache Spark를 활용하여 쿠버네티스 클라우드를 구성할 때 작성되는 Object Spec의 데이터 중 취약점을 유발하는 값을 진단 및 분석, 대응이 가능하도록 설계하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.33-34
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• 2023

성장하는 빅 데이터 시장과 빅 데이터 수의 기하급수적인 증가는 기존 컴퓨팅 환경에서 데이터 처리의 어려움을 야기한다. 특히 이미지 데이터 처리 속도는 데이터양이 많을수록 현저하게 느려진다. 이에 본 논문에서는 Apache Spark와 OpenCV를 활용한 분산 클러스터 컴퓨팅 환경의 대용량 이미지 머신러닝 시스템을 제안한다. 제안하는 시스템은 Apache Spark를 통해 분산 클러스터를 구성하며, OpenCV의 이미지 처리 알고리즘과 Spark MLlib의 머신러닝 알고리즘을 활용하여 작업을 수행한다. 제안하는 시스템을 통해 본 논문은 대용량 이미지 데이터 처리 및 머신러닝 작업 속도 향상 방법을 제시한다.

• The KIPS Transactions:PartC
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• v.11C no.4
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• pp.545-554
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• 2004

WebDAV is a protocol to support collaboration among the workers in geographically distant locations through the Internet. WebDAV extends the web communication protocol HTTP/1.1 to provide a standard infrastructure for supporting asynchronous collaboration for various contents across the Internet. To provide the WebDAV functionality in legacy applications such as web-based collaborative systems or document management systems, those systems need to be implemented additionally to handle the WebDAV methods and headers information. In this paper, we developed an Apache-based WebDAV server, named DAVinci(WebDAV Is New Collaborative web-authoring Innovation)which supports the WebDAV specification. DAVinci was implemented as a form of service provider on a mod_dav Apache module. Mod_day, which is an Apache module, is an open source module to provide WebDAV capabilities in an Apache web server. We used a file system for storing resources and the PostgreSQL database for their properties. In addition, the system provides a consistency manager to guarantee that both resources and properties are maintained without inconsistency between resources and their properties.

• Journal of The Korean Society of Clinical Toxicology
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• v.6 no.1
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• pp.32-36
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• 2008

Purpose: The major complication of acute organophosphate (OP) poisoning is respiratory failure as a result of cholinergic toxicity. Many clinicians find it difficult to predict the optimal time to initiate mechanical ventilation (MV) weaning, and as a result have tended to provide a prolonged ventilator support period. The purpose of this study is to determine any clinical predictors based on patients characteristics and laboratory findings to assist in the optimal timing of mechanical ventilator weaning. Methods: We reviewed medical and intensive care records of 44 patients with acute OP poisoning who required mechanical ventilation admitted to medical intensive care unit between July 1998 and June 2007. Patient information regarding the poisoning, clinical data and demographic features, APACHE II score, laboratory data, and serial cholinesterase (chE) levels were collected. Base on the time period of MV, the patients were divided into two groups: early group (wean time < 7 days, n = 28) and delayed group (${\geq}$ 7 days, n = 16). Patients were assessed for any clinical characteristics and predictors associated with the MV weaning period. Results: During the study period, 44 patients were enrolled in this study. We obtained the sensitivity and specificity values of predictors in the late weaning group. APACHE II score and a reciprocal convert of hypoxic index but specificity (83.8%) is only APACHE II score. Also, the chE concentration (rho = -0.517, p = 0.026) and APACHE II score (rho = 0.827, p < 0.001) correlated with a longer mechanical ventilation duration. Conclusion: In patients with acute OP poisoning who required mechanical ventilation, the APACHE II scoring system on a point scale of less than 17 and decrements in cholinesterase levels on 1-3 days were good predictors of delayed MV weaning.

• Journal of the Korea Society of Computer and Information
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• v.16 no.1
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• pp.175-182
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• 2011

This study proposes CAOPI(Computer Aided Organ Prediction Index) system based on APACHE II(Acute Physiology And Chronic Health Evaluation) for classifying disease severity and predicting the conditions of patients' major organs. The existing ICU disease severity evaluation is mostly about calculating risk scores using patients' data at certain points, which has limitations on making precise treatments. CAOPI system is designed to provide personalized treatments by classifying accurate severity degrees of emergency patients, predicting patients' mortality rate and scoring the conditions of certain organs.

• Korean Journal of Adult Nursing
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• v.17 no.3
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• pp.464-473
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• 2005

Purpose: The purpose of this study was to evaluate and compare the predictive ability of three mortality scoring systems; Acute Physiology and Chronic Health Evaluation(APACHE) III, Simplified Acute Physiology Score(SAPS) II, and Mortality Probability Model(MPM) II in discriminating in-hospital mortality for intensive care unit(ICU) patients with spontaneous intracerebral hemorrhage. Methods: Eighty-nine patients admitted to the ICU at a university hospital in Daejeon Korea were recruited for this study. Medical records of the subject were reviewed by a researcher from January 1, 2003 to March 31, 2004, retrospectively. Data were analyzed using SAS 8.1. General characteristic of the subjects were analyzed for frequency and percentage. Results: The results of this study were summarized as follows. The values of the Hosmer-Lemeshow's goodness-of-fit test for the APACHE III, the SAPS II and the MPM II were chi-square H=4.3849 p=0.7345, chi-square H=15.4491 p=0.0307, and chi-square H=0.3356 p=0.8455, respectively. Thus, The calibration of the MPM II found to be the best scoring system, followed by APACHE III. For ROC curve analysis, the areas under the curves of APACHE III, SAPS II, and MPM II were 0.934, 0.918 and 0.813, respectively. Thus, the discrimination of three scoring systems were satisfactory. For two-by-two decision matrices with a decision criterion of 0.5, the correct classification of three scoring systems were good. Conclusion: Both the APACHE III and the MPM II had an excellent power of mortality prediction and discrimination for spontaneous intracerebral hemorrhage patients in ICU.

• Database Research
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• v.34 no.3
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• pp.58-68
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• 2018

Distributed computing helps to efficiently store and process large data on a cluster of multiple machines. The performance of distributed computing is greatly influenced depending on the state of the servers constituting the distributed system. In this paper, we propose a self-diagnosis system that collects log data in a distributed system, detects anomalies and visualizes the results in real time. First, we divide the self-diagnosis process into five stages: collecting, delivering, analyzing, storing, and visualizing stages. Next, we design a real-time self-diagnosis system that meets the goals of real-time, scalability, and high availability. The proposed system is based on Apache Flume, Apache Kafka, and Apache Storm, which are representative real-time distributed techniques. In addition, we use simple but effective moving average and 3-sigma based anomaly detection technique to minimize the delay of log data processing during the self-diagnosis process. Through the results of this paper, we can construct a distributed real-time self-diagnosis solution that can diagnose server status in real time in a complicated distributed system.

• Journal of The Korean Society of Clinical Toxicology
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• v.14 no.2
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• pp.107-114
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• 2016

Purpose: The incidence of glufosinate poisoning is gradually increasing, and it can be fatal if severe poisoning occurs. However, factors useful for predicting the post-discharge neurological prognosis of patients who have ingested glufosinate have yet to be identified. Our objective was to evaluate the utility of the acute physiology and chronic health evaluation (APACHE) II score measured in the emergency department for predicting the neurological prognosis. Methods: From April 2012 to August 2014, we conducted a retrospective study of patients who had ingested glufosinate. The outcome of the patients at discharge was defined by the Cerebral Performance Category Score (CPC). The patients were divided into a good prognosis group (CPC 1, 2) and a poor prognosis group (CPC 3, 4, 5), after which the APACHE II scores were compared. The Hosmer-Lemeshow test and the area under the receiver operating characteristic (ROC) curve from patients determined calibration and discrimination. Results: A total of 76 patients were enrolled (good prognosis group: 67 vs poor prognosis group: 9). The cut-off value for the APACHE II score was 12 and the area under the curve value was 0.891. The Hosmer and Lemeshow C statistic x2 was 7.414 (p=0.387), indicating good calibration for APACHE II. Conclusion: The APACHE II score is useful at predicting the neurological prognosis of patients who have ingested glufosinate.