Earticle

Distributed mobility management (DMM) is currently being researched and standardized in academia and standardization development organizations for the purpose of overcoming the major issues of existing centralized mobility management. The most recent DMM protocols are being redesigned with regard to the control and data plane separation concept. However, at present, there is no solution for supporting IP multicast listeners in such new DMM environments. In this paper, we review ongoing academic research works, standardization activities and propose an IP multicast mobility design for the DMM environment using the control and data plane concept.

High-throughput genotyping and sequencing has revolutionized animal breeding by providing access to vast amounts of genomic data to facilitate precise selection for desirable traits. This shift from traditional methods to genomic selection provides dense marker information for predicting genetic variants. However, the success of genomic selection heavily depends on the accuracy and quality of the genomic data. Inaccurate or low-quality data can lead to flawed predictions, compromising breeding programs and reducing genetic gains. Therefore, stringent quality control (QC) measures are essential at every stage of data processing. QC in genomic data involves managing single nucleotide polymorphism (SNP) quality, assessing call rates, and filtering based on minor allele frequency (MAF) and Hardy-Weinberg equilibrium (HWE). High-quality SNP data is crucial because genotyping errors can bias the estimates of breeding values. Cost-effective low-density genotyping platforms often require imputation to deduce missing genotypes. QC is vital for genomic selection, genome-wide association studies (GWAS), and population genetics analyses because it ensures data accuracy and reliability. This paper reviews QC strategies for genomic data and emphasizes their applications in animal breeding programs. By examining various QC tools and methods, this review highlights the importance of data integrity in achieving successful outcomes in genomic selection, GWAS, and population analyses. Furthermore, this review covers the critical role of robust QC measures in enhancing the reliability of genomic predictions and advancing animal breeding practices.

As new applications of cloud data management system (CDMS) such as online games, cooperation edit, social network, and so on, are increasing, transaction processing capabilities for CDMS are required. Several transaction processing methods for cloud data management system (CDMS) have been proposed. However, existing transaction processing methods have some problems. Some of them provide limited transaction processing capabilities. Some of them are hard to be integrated with existing CDMSs. In this paper, we proposed a new concurrency control method to support transaction processing capability for CDMS to solve these problems. The proposed method was designed and implemented based on Spark, an in-memory distributed processing framework. It uses RDD (Resilient Distributed Dataset) model to provide fault tolerant to data in the main memory. In our proposed method, database stored in CDMS is loaded to main memory managed by Spark. The loaded data set is then transformed to RDD. In addition, we proposed a multi-version concurrency control method through immutable characteristics of RDD. Finally, we performed experiments to show the feasibility of the proposed method.

It is essential to guarantee a handoff dropping probability below a predetermined threshold for wireless mobile networks. Previous studies have proposed admission control policies for integrated voice/data traffic in wireless mobile networks. However, since QoS has been considered only in terms of CDP (Call Dropping Probability), the result has been a serious CBP (Call Blocking Probability) unfairness problem between voice and data traffic. In this paper, we suggest a new admission control policy that treats integrated voice and data traffic fairly while maintaining the CDP constraint. For underprivileged data traffic, which requires more bandwidth units than voice traffic, the packet is placed in a queue when there are no available resources in the base station, instead of being immediately rejected. Furthermore, we have adapted the biased coin method concept to adjust unfairness in terms of CBP. We analyzed the system model of a cell using both a two-dimensional continuous-time Markov chain and the Gauss-Seidel method. Numerical results demonstrate that our CAC (Call Admission Control) scheme successfully achieves CBP fairness for voice and data traffic.

In this study, climate data analysis was conducted at two Korean museums to demonstrate its benefits for developing customized climate control standards to preserve artifacts in a sustainable manner. Case studies were conducted at Taean National Maritime Museum and Jungwon National Research Institute of Cultural Heritage where monitoring data were collected over a 7-month period. The results showed that display cases greatly mitigated the risks associated with mold and mechanical deformation: they maintained a consistent relative humidity of 50%–60% while the galleries had a much wider variance of 35%–85%. At Taean National Maritime Museum, the microclimates within the display cases deviated from the climate control standards for the galleries despite artifacts remaining undamaged, which indicates that the standards may need to be reassessed for sustainable collection management. At Jungwon National Research Institute of Cultural Heritage, plastic bags were shown to be an effective strategy for preserving metal artifacts by maintaining the relative humidity below 20% and preventing corrosion. These findings emphasize the need for adopting climate control standards to match the specific context of each museum and demonstrate how a comprehensive climate data analysis can facilitate sustainable collection management for long-term preservation of artifacts.

Ardupilot, PX4는 드론에 탑재되는 대표적인 오픈소스 프로젝트이며 개발비용 절감, 소스코드의 안정성, 신속한 개발 피드백 등의 이유로 드론 제어 오픈소스들은 국내·외에서 드론 개발에 널리 사용되고 있다. 하지만 이와 같은 장점 이면에는 치명적인 단점 또한 존재한다. 여러 기관에서 사용되고 있는 드론에 탑재된 오픈소스들이 데이터 보안에 대한 취약점이 존재할 경우, 해당 기관에서 사용되는 드론은 모두 잠재적으로 보안 공격의 대상이 되며 이는 환경의 특성에 따라 연쇄적인 경제적, 인명적 손실을 불러올 수 있다. 본 논문에서는 Ardupilot, PX4에서 사용하고 있는 MAVLink v1.0, MAVLink v2.0의 데이터 보안 취약점을 설명하고 이에 대응할 수 있는 양자 기반 난수 발생기를 활용한 개체 인증, 데이터 보안을 제안하며 제안된 데이터 보안의 성능 측정을 통해 가용성 분석을 수행한다.

Ardupilot and PX4 are representative open source projects for drones, and drone-controlled open sources are widely used for drone development at home and abroad due to reduced development costs, stability of source code, and rapid development feedback. However there are also fatal drawbacks behind such advantages. Open-source on drones used by various agencies If there are vulnerabilities in data security, all drones used by those agencies are potentially subject to security attacks, this could lead to a series of economic and human losses, depending on the nature of the environment. In this paper, we explain the data security vulnerabilities of MAVLink v1.0, MAVLink v2.0 used in Ardupilot, PX4, and propose object authentication using quantum entropy-based random number generator to respond to them, propose data security, and conduct availability analysis through performance measurement of proposed data security.

Agricultural reservoirs are important facilities for storing or managing water for the purpose of securing agricultural water, creating and expanding agricultural production bases, and using them to increase agricultural production. In particular, the Korea Rural Community Corporation (KRC) manages agricultural reservoirs scattered across the country, and officially recognizes and distributes hydrological data to increase their public utilization and aims to improve the value of water resources. Data on the water level of agricultural reservoirs are important. However, errors such as missing values and outliners limit utilization of the data in various fields of research and industry. Therefore, water quality data measures should be devised to increase reliability. this study categorized different error types and looked at automatic correction methods to enhance the reliability of the vast hydrological data. In addition, the water level data corrected from errors were compared to the reference hydrologic data through expert judgment in accordance with the quality control procedure, and the most appropriate measures were verified. As KRC manages more agricultural reservoirs than any other institution, the proposed method of efficient and automatic water level data correction in this study is expected to increase the availability and reliability of the hydrological data.

해양 탄성파탐사 자료취득시스템은 항측시스템, 기록시스템, 스트리머 케이블, 음원 등으로 구성된다. 항측시스템은 계획된 측선에 따라 탐사선을 계산된 위치로 이동시키며, 탐사선과 수중에서 예인되는 탐사장비의위치를 측정 및 계산하는 중요한 역할을 수행한다. 본 기술보고에서는 동해 울릉분지에서 심해 유가스전 탐사기술 개발을 위해 석유물리탐사선 탐해2호로 수행된 항측 자료취득 및 품질관리 등의 과정과 항측 자료취득및 품질관리의 중요성에 대해서 소개하고자 한다.

Marine seismic data acquisition system consists of navigation system, recording system, streamer cable and seismic source. Navigation system performs the important role steering the vessel along the pre-plot survey line and measuring and calculating the position between survey vessel and deployed equipments. To develop the deepwater hydrocarbon exploration technology in the Ulleung Basin, in this technical report, we introduce the processes of navigation data acquisition and quality control conducted by navigation system of R/V Tamhae II and report those importance.

마이데이터는 개인데이터 활용 체계의 새로운 패러다임으로, 데이터 주체가 자신의 데이터를 어떻게 사용하고 어디에 제공할 것인지 결정할 수 있다. 데이터 주체의 동의 하에 서비스 제공자는 여러 서비스에 걸쳐 흩어져있는 고객의 데이터를 수집하고 이를 바탕으로 고객 맞춤화된 서비스를 제공한다. 기존의 마이데이터 서비스 모델들에서, 데이터 주체는 데이터 스토리지에 저장된 자신의 개인 정보를 서비스 제공자 또는 제3자의 데이터 프로세서에게 판매할 수 있다. 하지만 개인정보가 한 번 제3자의 프로세서에게 판매되어 그들의 프로세서에 의해 처리될 경우 그 순간부터 데이터를 추적하고 통제할 수 없다는 문제가 발생한다. 따라서 본 논문에서는 기존 마이데이터 운영 모델들의 문제점들을 개선하여 데이터 주체에게 더 높은 통제권을 부여하는 클라우드 모델을 제시한다. 동시에, 클라우드 모델과 같이 데이터 스토리지, 컨트롤러, 프로세서가 모두 한 곳에 모여있는 경우 클라우드가 침해될 시 모든 데이터가 한 번에 침해될 수 있다는 점을 고려하여, 이러한 위험을 줄일 수 있도록 클라우드-디바이스 간 협력적 암호화와 클라우드 컴포넌트들 간 격리 기술을 적용한 클라우드 모델 아키텍쳐를 함께 제시한다.

MyData is an approach of personal data management, which grants data subjects the right to decide how to use and where to provide their data. With the explicit consent of the subjects, service providers can collect scattered data from data sources and offer personalized services based on the collected data. In existing service models, personal data saved in data storage can be shared with data processors of service providers or third parties. However, once personal data are transferred to third-party processors, it is difficult for data subjects to trace and control their personal data. Therefore, in this paper, we propose a cloud model where both data storage and processor are located within a single cloud, ensuring that data do not leave the cloud.

본 연구에서는 수재해 정보 플랫폼 내 자료처리 시스템 설계를 위해 자료처리 과정의 복잡도를 분석하고 이에 따른 설계 방안을제시하였다. 일반적으로 자료를 수집하고 분석하는 시스템은 자료와 알고리즘의 자료처리 과정이 고정된 고정 자료-알고리즘 자료처리 방식을 사용한다. 하지만 시스템의 복잡도가 증가하면 자료처리 시스템에서 관리해야 하는 자료처리 과정의 수가 급증하는문제가 발생한다. 이를 해결하기 위해 자료와 알고리즘 사이에 인터페이스가 존재하는 동적 자료-알고리즘 자료처리 방식을 적용할수 있다. 각 방식의 장단점을 분석한 뒤, 수재해 정보 플랫폼에 최적화된 자료처리 시스템의 설계안을 제시할 수 있었다.

In this study, we present the architecture design of data control system in water hazard information platform with analyzing the complexity of the data processing. Generally, data control systems in data collection and analysis platforms base on the constant data-algorithm data processing meaning that data processing between data and algorithm is fixed. But the number of data processing in data control system is rapidly increasing because of increasing of complexity of system. To hold down the number of data processing, dynamic data-algorithm data processing is able to be applied to data control system. After comparison each data-algorithm data processing method, we suggest design method of the data control system optimizing water hazard information platform.

비 보안영역의 외부인터넷과 보안영역의 내부업무망간에 적용된 기존의 망간 자료전송기술을 빌딩시설관리 SCADA시스템 제어망에 그대로 적용할 경우에 다양한 문제들이 도출된다. 기존의 망간 자료전송기술은 모든 데이터를 대상으로 블랙리스트 기반의 보안기법이 적용되기 때문에 고 복잡성 및 고 비용이 수반된다. 하지만, 빌딩시설관리 SCADA제어시스템에서 유통되는 데이터의 특성은 소수의 정형적인 제어 데이터가 반복성과 주기성을 갖기 때문에 이를 대상으로 화이트리스트 기반의 보안기법 적용이 가능하다. 이를 통해서 망간 자료전송에 적용된 보안기술이 단순화되어 저 비용으로 빌딩시설관리 SCADA시스템 제어망 구축이 가능하다. 본 논문에서는 이러한 문제점들을 정리하고 이를 해결하는 방안을 제시하여 빌딩시설관리 SCADA제어시스템에 특화된 빌딩 제어망 구축방안을 제안하였다.

The existing data transmission technology applied between the non-secure external internet and the secure internal business network has various problems when applied to the building facility management SCADA system control network. Traditional inter-network data transfer technologies involve high complexity and high costs because blacklist-based security techniques are applied to all data. However, whitelist-based security techniques can be applied to data distributed in Building Facility Management SCADA control systems because a small number of structured control data are repeatable and periodic. This simplifies the security technology applied to inter-network data transmission, enabling building facility management SCADA system control network deployment at low cost. In this paper, we proposed building control networks specialized in building facility management SCADA control systems by providing solutions to address and address these problems.

최근 수년간 IoT (internet of things) 기술은 급격히 발달하였고 많은 분야에 적용되고 있다. IoT 디바이스는 다양한 환경에서 정보를 수집하고 분석하여 사용자에게 유용한 정보를 제공하는 역할을 수행한다. 최근에 IoT 디바이스 증가로 인하여, 가격이 저렴하고 사용하기 쉬운 하드웨어와 소프트웨어 기반의 오픈소스 플랫폼들이 많이 개발되어 제공되고 있다. 본 논문에서는 블루투스 무선 데이터를 스마트 폰과 실시간으로 통신할 수 있는 아두이노 기반의 IoT 시스템을 연구하였다. 그리고 안드로이드 스마트 폰과의 통신을 위하여 앱 인번터 2 기반의 무선 시스템 제어 앱을 개발하였다. 또한, 디바이스를 제어할 수 있는 아두이노 기반의 IoT 시스템을 제작하여 디바이스 사이의 연결성 측면의 기능을 구현하고자 한다.

In recent years, internet of things (IoT) technology has developed rapidly and has been applied in many fields. IoT devices collect and analyze information in various environments and provide useful information to users. Due to the recent increase in IoT devices, many open source platforms based on hardware and software that are cheap and easy to use have been developed and provided. In this paper, we have studied the IoT system based on Arduino which can communicate Bluetooth wireless data with smart phone in real time. And we have developed a wireless system control app based on App Invertor 2 for communication with Android smart phone. Also, we propose an IoT system based on Arduino which can control the devices and implement the function of connectivity between devices.

수자원 설계 및 홍수 예 경보 등을 위한 수문분석 시, 강우자료는 필수요소이다. 현재 수문분석 시 비교적 장기간의 자료를 보유하고 있는 기상청, 국토교통부 등의 지상기상관측지점(SSS, Surface Synoptic Stations)에 시 강우자료를 이용하고 있으나, 집중호우가 빈번히 발생하는 현실정과 집중호우의 발생빈도가 증가할 것으로 예상되는 향후에는 더욱 조밀한 관측망을 구성하고 있는 방재기상관측지점(AWS, Automatic Weather Stations)의 분 단위 강우자료를 이용한 분석이 필요하다. 그러나 방재기상관측지점의 분 단위 강우자료는 자동으로 관측되고 있어, 자료품질에 대한 문제점이 매번 지적되고 있다. 본 연구에서는 서울지역을 중심으로 기상청 방재기상관측지점의 분 단위 강우자료의 품질개선 방안에 관한 연구를 실시하였다. 분 단위 강우자료의 품질관리방안은 크게 3단계로 결측치 품질관리, 이상치 품질관리 그리고 강우 보완 품질관리로 구분하여 품질관리 방안을 제시하고 분석을 수행하였다. 마지막으로 서울지점의 분 단위 강우자료와 시 단위 강우자료의 비교분석을 통해 강우 품질관리에 대한 평가를 실시하였다. 이는 향후 분 단위 강우자료를 이용한 수문분석 시, 강우자료 품질관리 방안으로 활용될 것으로 판단된다.

Rainfall data is necessary component for water resources design and flood warning system. Most analysis are used long-term hourly data of surface synoptic stations from the Meteorological Administration, Ministry of land, Infrastructure and Transport and others. However, It will be used minutely data of more high density automatic weather stations than surface synoptic stations expecting to increase the frequency of heavy precipitation. But minutely data has a problem about quality of rainfall data by auto observation. This study analyzed about quality control method using automatic weather station's minutely rainfall data of meteorological administration. It was performed assessment of the quality control that was classified quality control of miss Data, outlier data and rainfall interpolation. This method will be utilized when hydrological analysis uses minute rainfall data.

머신러닝과 딥러닝의 기술이 보편화되면서 산업제어시스템의 이상(비정상) 탐지 연구에도 적용이 되기 시작하였다. 국내에서는 산업제어시스템의 이상 탐지를 위한 인공지능 연구를 활성화시키기 위하여 HAI 데이터셋을 개발하여 공개하였고, 산업제어시스템 보안위협 탐지 AI 경진대회를 시행하고 있다. 이상 탐지 연구들은 대개 기존의 딥러닝 학습 알고리즘을 변형하거나 다른 알고리즘과 함께 적용하는 앙상블 학습 모델의 방법을 통해 향상된 성능의 학습 모델을 만드는 연구가 대부분 이었다. 본 연구에서는 학습 모델과 데이터 전처리(pre-processing)의 개선을 통한 방법이 아니라, 비정상 데이터를 탐지하여 라벨링 한 결과를 보정하는 후처리(post-processing) 방법으로 이상 탐지의 성능을 개선시키는 연구를 진행하였고, 그 결과 기존 모델의 이상 탐지 성능 대비 약 10%이상의 향상된 결과를 확인하였다.

As the technology of machine learning and deep learning became common, it began to be applied to research on anomaly(abnormal) detection of industrial control systems. In Korea, the HAI dataset was developed and published to activate artificial intelligence research for abnormal detection of industrial control systems, and an AI contest for detecting industrial control system security threats is being conducted. Most of the anomaly detection studies have been to create a learning model with improved performance through the ensemble model method, which is applied either by modifying the existing deep learning algorithm or by applying it together with other algorithms. In this study, a study was conducted to improve the performance of anomaly detection with a post-processing method that detects abnormal data and corrects the labeling results, rather than the learning algorithm and data pre-processing process. Results It was confirmed that the results were improved by about 10% or more compared to the anomaly detection performance of the existing model.

과학기술데이터는 엄격한 평가기준에 의해 신뢰성과 정확성이 보장된 참조표준(standard reference data) 값을 지닐 수 있어야 한다. 참조표준은 측정표준을 바탕으로 구하여진 결과 값을 표준화시키는 작업으로서 데이터의 생산조건, 실험환경, 측정방법, 데이터 처리 등이 검토되어 참조데이터(reference data)와 구분된다. 참조표준은 “공인된 수치데이터”로 표현되고 이는 측정결과의 신뢰도를 정량적으로 나타내는 불확도(uncertainty)로 표기된다. 본 연구에서는 참조표준에 대한 의미를 이해하고, 평가되지 않은 과학기술 데이터가 어떤 평가 과정을 거쳐 참조표준으로 분류되는지를 알아보기 위해 소재물성분야를 예로 살펴보았다. 그리고 국가 참조표준을 본격적으로 운영하기 위한 방안으로 국가참조표준센터, 데이터센터, 위원회의 역할과 임무, 이를 뒷받침하기 위한 법적, 제도적 방안을 제시하였다.

Data produced during scientific and technical activities usually have value as standard reference data (SRD) which is a well-documented numeric value assessed for reliability and accuracy. The main criteria in the evaluation for SRD is how well their production is documented including a sample preparation, measurement method, data processing and so on, other than reference data. SRD is represented as a certified numeric value with uncertainty. In this study, the SRD in the area of material properties was introduced to provide understanding of SRD and its evaluation method. Also the national SRD system was studied. The national SRD system is composed of the center for the SRD, the data centers, and the committee. The role and task of those components were studied. The legislational and systematic supports for the system were proposed in this study.

본 연구에서는 기상청에서 수행하는 기존의 기상 관측에 대한 품질관리 절차 이외에 향후 스마트시티 등에서 활용될 수 있는 머신러닝 기반의 Internet of Things (IoT) 도시기상 관측 자료에 대한 품질검사 기준을 제안한다. 현재 기상청에서 종관기상관측(Automated Synoptic Observing System, ASOS)과 방재기상관측(Automatic Weather System, AWS) 기반으로 설정한 기준이 도시기상에 적합한지 확인하기 위하여 서울시에 설치된 SKT AWS 자료를 기반으로 사용성을 검증하였고, IoT 자체의 데이터가 가지는 특성을 고려하여 최종적으로 머신러닝 기반의 품질검사 알고리즘을 제안하였다. 품질검사 방법으로는 IoT 기기 자체에 대한 결측값 검사, 값 패턴 검사, 충분 데이터 검사, 통계적 범위 이상 검사, 시간값 이상 검사, 공간값 이상 검사를 먼저 수행하고, 기상청에서 제시하고 있는 기상 관측에 대한 품질검사인 물리한계검사, 단계검사, 지속성 검사, 기후범위 검사, 내적 일치성 검사를 5가지 기상요소에 대하여 각각 수행하였다. 제안한 알고리즘의 검증을 위하여 인천광역시 송도에 위치한 관측소에 실제 IoT 도시기상관측 데이터에 이를 적용하였다. 이를 통해 기존의 기상청 QC로는 확인할 수 없었던 IoT 기기가 가질 수 있는 결함을 확인할 수 있고, 알고리즘에 대한 검증을 진행하여 향후 스마트시티에 설치될 IoT 기상관측기기에 대한 품질검사 방법을 제안한다.

In addition to the current quality control procedures for the weather observation performed by the Korea Meteorological Administration (KMA), this study proposes quality inspection standards for Internet of Things (IoT) urban weather observed data based on machine learning that can be used in smart cities of the future. To this end, in order to confirm whether the standards currently set based on ASOS (Automated Synoptic Observing System) and AWS (Automatic Weather System) are suitable for urban weather, usability was verified based on SKT AWS data installed in Seoul, and a machine learning-based quality control algorithm was finally proposed in consideration of the IoT's own data's features. As for the quality control algorithm, missing value test, value pattern test, sufficient data test, statistical range abnormality test, time value abnormality test, spatial value abnormality test were performed first. After that, physical limit test, stage test, climate range test, and internal consistency test, which are QC for suggested by the KMA, were performed. To verify the proposed algorithm, it was applied to the actual IoT urban weather observed data to the weather station located in Songdo, Incheon. Through this, it is possible to identify defects that IoT devices can have that could not be identified by the existing KMA's QC and a quality control algorithm for IoT weather observation devices to be installed in smart cities of future is proposed.

Register control of roll-to-roll printing system for printed electronics requires accurate measurement of register errors. The register marks used for the recognition of patterns position between layers have inherently defects due to low printability of register marks themselves, which brings out inaccurate register accuracy and consequently low performance of printed electronics devices. In this study, the compensation methods for the unrecognized or missing register data are proposed to improve the recognition and consequently the control performance of register accuracy in roll-to-roll printing equipment. The compensation methods using the prior data and the linear interpolation are proposed and compared with the case without compensation for the simulation as well as experiment. Only the linear interpolation method could successfully compensate the missing data and consequently improve the register control performance. We should apply the compensation process of the register errors to improve the register control accuracy in the roll-to-roll printing equipment.

본 연구는 체중조절 방법이 휴식기 에너지 소비량(resting energy expenditure : REE)에 어떤 영향을 주는지를 알아보고, 특히 신체계측치의 변화가 체중조절 방법에 따른 체중변화의 내용을 예측하는지, 에너지 소비 지표중 하나인 REE와 호흡율(respiratory quotients: RQ)이 체중감소를 예측하는 지표로서의 의의가 있는지를 알아보기 위해 이루어졌다. 참여자는 서울시내 소재 여자대학에 재학중인 학생으로 본 연구목적에 동의한 여학생 중 신체질량지수가 23이상으로 과체중에 속하고 식사문제와 심리적 문제 및 기본적인 신체검사에서 이상소견이 없는 47명을 대상으로 하였다. 이들을 본인의 선호에 따라서 체중조절방법 가운데 식사조절 15명, 운동조절 18명, 약물투여 (일일 reductil 10mg) 14명을 할당하였다. 참여자 가운데 탈락된 9명(식사조절군 4명, 운동조절군 3명, 약물투여군 2명)을 제외한 38명의 자료를 최종 분석하였다. 식사조절군은 REE 검사를 근거로 현재 체중을 유지하는데 필요한 열량에서 일일 500kcal를 줄인 열량을 처방하였고 운동조절군은 운동부하검사를 실시하여 현재 체중을 유지하는데 필요한 열량에서 일일 500kcal를 소비할 수 있는 유산소 운동과 근력운동 처방하여 실시할 수 있도록 하였다. 약물투여군은 reductil 10mg을 투여하고 1개월 동안 약물을 복용하고 2kg이하로 변화가 온 경우에는 15mg을 투여하였다. 프로그램 시작 시, 1개월 후, 그리고 3개월 후 신체계측치와 REE, RQ를 측정한 결과,. 체중조절 방법에 따라 시간의 경과에 따른 REE의 변화와 RQ의 변화가 전체적으로는 유의한 차이를 보이지 않았으나 각 방법에 따라 시간에 따른 REE의 변화양상과 RQ의 변화양상은 다를 수 있는 가능성을 보여주었다. 그리고 체중조절 방법에 따라 시간의 경과에 따른 각종 신체계측자료는 각 군에서 유의한 차이를 보이지 않았으나 체중변화와 FFM, FM 및 WC의 변화 양상은 세군 간 다른 양상을 보였다. 초기 REE 값이나 RQ가 단기적이기는 하나 3개월간의 체중변화를 예측하는데 유의하지 않았다. 이런 결과는 효과적인 체중조절을 위해 체중조절 경과에 따라 체중조절 전략을 변화시키는 것이 유용할 수 있음을 시사한다. 마지막으로 본 연구의 제한점과 미래 연구에 대해서 논의하였다.

This study was tried to investigate that REE and RQ changes, and contents of weight loss might be different by weight control methods and to prove the prediction effects of REE and RQ for weight changes. For these purposes, 62 college women(BMI>23) were voluntarily recruited to response for advertizing. With the 2nd stepped selection procedures, 47 persons(15 diet group, 18 exercise group and 14 medication(Reductil 10mg-15mg/d) group) were finally selected. During the 3months course of study, 9 persons(4 for dieting group, 3 for exercise group and 2 for medication group) were dropped. Persons of diet group were forced to maintain 500kcal deficit per day of food intake on the basis of estimated daily requirements by REE at start point and present level of activity. Persons of exercise group also forced to maintain 500kcal deficit per day by exercise on the basis of estimated daily requirements by REE at start point and present level of food intake. Persons of medication group were maintained 10mg-15mg of Reductil per day and forced to maintain present level of food intake and activity. All persons should keep the write the daily eating diary and activity diary with pedometer and were monitored by specialists on weekly basis. Group LEARN program was done weekly for each group. At start, after 1month, and 3 months, anthrometric data(weight, BMI, FFM, FM, WC), REE and RQ were obtained. The results were as follows. First, There were no significant differences among three groups in the changing amounts of REE and RQ during 3 months. For each group, there was no significant change in the value of REE and RQ. However, changing patterns of REE and RQ according to time process were different by groups. Second, there were significant differences for each group in the changing amounts of weight, BMI, FFM, FM and WC during 3 months but there were no significant differences among three groups. However, changing patterns of FFM, FM and WC according to time process were different by groups. This might suggest that even weight loss was achieved, changing contents could be different by weight control methods. Third, REE and RQ value had no prediction effects for 3 months duration weight changes. Result that changing patterns of REE and RQ according to time process were different by groups even that there were no significant differences among three groups in the changing amounts of REE and RQ during 3 months may suggest that major weight control strategies can be arranged or mixed for effective weight control to keep the high REE and low RQ during the courses of weight control. Negative result for the prediction effects of REE and RQ may suggest the necessary to investigate it's relation with amounts of weight change or/and time lags after weight change.

Purpose: This study examines the factors influencing 30-day in-hospital mortality in elderly patients with community-acquired pneumonia(CAP) and compares them to those in adult patients. Methods: This secondary analysis used discharge data from the Korea Disease Control and Prevention Agency, covering the periodfrom January 1, 2020, to December 31, 2022. Statistical methods included χ² tests, t-tests, the Cox proportional hazards model for calculatingadjusted hazard ratios (HR), and Kaplan-Meier analysis. Results: The study found that older age (Adjusted HR=2.40, 95% CI=2.01-2.85, p<.001) and Emergency Room admissions (AdjustedHR=2.24, 95% CI=1.94-2.59, p<.001) are significantly associated with increased mortality in elderly patients. Other contributing factorsinclude residency area (Adjusted HR=1.73, 95% CI=1.04-2.87, p=.035), hospital setting (Adjusted HR=1.34, 95% CI=1.05-1.70,p=.017), and the number of hospital beds (Adjusted HR=1.27, 95% CI=1.11-1.46, p=.001). Conclusion: These findings underscore the importance of improving community health screenings and developing respiratory infectionprevention programs for elderly patients, especially those in high-risk areas.