• Title/Summary/Keyword: 표준데이터

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Factors Affecting Falls of Demented Inpatients (치매 입원환자의 낙상 영향 요인)

  • Kim, Sang-Mi;Lee, Seong-A
    • 한국노년학
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    • v.39 no.2
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    • pp.231-240
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    • 2019
  • The study aimed to identify risk factors for falls as well as hospitalization status according to disease and demographic characteristics of demented inpatients by investigating the in-depth Injury Patient Surveillance System data collected by Korea Centers for Disease Control and Prevention(KCDC). Older adults over 60 years old who were diagnosed with dementia were included(n=1,732). Their data were analyzed after being assigned to either a fall group or a non-fall group. STATA was used for statistical analyses, such as frequency analysis, chi-square (χ2) test, and logistics regression. It was found that 8.0% of the demented inpatients experienced falls. According to the analysis on category of fall and non-fall group were statistically significant difference in age and Charlson Comorbidity Index(CCI) and bone density deficiency. Based on the logistic regression analysis of factors affecting falls, older adults over 80 are 2.386 times more likely to fall and based on a target with a CCI of 0, the risk of falls is 0.421 times lower, finally based on those without bone density disorder, the fall risk for those with bone density disorder was 3.581 times higher. Therefore, we expect that the important about the factors relating to falls identified in this can not only be found valuable for educating inpatients with dementia and care-givers, but also be used as reference that supports clinical professionals to make decisions on falls management for patients with dementia.

International Case Study and Strategy Proposal for IUCN Red List of Ecosystem(RLE) Assessment in South Korea (국내 IUCN Red List of Ecosystem(생태계 적색목록) 평가를 위한 국제 사례 연구와 전략 제시)

  • Sang-Hak Han;Sung-Ryong Kang
    • Journal of Wetlands Research
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    • v.25 no.4
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    • pp.408-416
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    • 2023
  • The IUCN Red List of Ecosystems serves as a global standard for assessing and identifying ecosystems at high risk of biodiversity loss, providing scientific evidence necessary for effective ecosystem management and conservation policy formulation. The IUCN Red List of Ecosystems has been designated as a key indicator (A.1) for Goal A of the Kunming-Montreal Global Biodiversity Framework. The assessment of the Red List of Ecosystems discerns signs of ecosystem collapse through specific criteria: reduction in distribution (Criterion A), restricted distribution (Criterion B), environmental degradation (Criterion C), changes in biological interaction (Criterion D), and quantitative estimation of the risk of ecosystem collapse (Criterion E). Since 2014, the IUCN Red List of Ecosystems has been evaluated in over 110 countries, with more than 80% of the assessments conducted in terrestrial and inland water ecosystems, among which tropical and subtropical forests are distributed ecosystems under threat. The assessment criteria are concentrated on spatial signs (Criteria A and B), accounting for 68.8%. There are three main considerations for applying the Red List of Ecosystems assessment domestically: First, it is necessary to compile applicable terrestrial ecosystem types within the country. Second, it must be determined whether the spatial sign assessment among the Red List of Ecosystems categories can be applied to the various small-scale ecosystems found domestically. Lastly, the collection of usable time series data (50 years) for assessment must be considered. Based on these considerations, applying the IUCN Red List of Ecosystems assessment domestically would enable an accurate understanding of the current state of the country's unique ecosystem types, contributing to global efforts in ecosystem conservation and restoration.

A Study on the Performance Analysis of AIoT High-Efficiency Streetlamp for Carbon Emissions (탄소배출권용 AIoT 고효율 가로등 성능분석 연구)

  • Seung-Ho Park;Seong-Uk Shin;Kyung-Sunl Yoo
    • Journal of Advanced Technology Convergence
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    • v.2 no.4
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    • pp.13-19
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    • 2023
  • Following the signing of the Paris Agreement on Climate Change (UNFCCC, 2015), the world is expanding greenhouse gas reduction activities through comprehensive participation that includes not only developed countries but also developing countries. Major countries around the world are placing high expectations on the effectiveness of total carbon emissions regulation through the carbon emissions market. However, in order to obtain carbon credits, third-party verification is required based on quantitative carbon reduction data. Accordingly, in this paper, we developed an AIoT high-efficiency street light for carbon emissions and conducted a performance analysis study to measure the luminous efficiency of the lighting fixture. To obtain carbon emissions rights, we used high-efficiency LED PKG, developed our own high-voltage PFC, and developed high-efficiency lighting fixtures capable of communication. For communication, the 2.4GHz LoRa method was adopted between the lighting fixture and the gateway. Lens design was conducted through simulation of Korea Expressway Corporation's standard streetlight types A, B, and C. The performance of the streetlight was verified as being more efficient than other existing products through the measurement of luminous efficiency by an accredited rating agency, and it is expected that carbon emissions rights will be obtained by reducing electrical energy through this.

Comparative analysis of informationattributes inchemical accident response systems through Unstructured Data: Spotlighting on the OECD Guidelines for Chemical Accident Prevention, Preparedness, and Response (비정형 데이터를 이용한 화학물질 사고 대응 체계 정보속성 비교 분석 : 화학사고 예방, 대비 및 대응을 위한 OECD 지침서를 중심으로)

  • YongJin Kim;Chunghyun Do
    • Journal of Intelligence and Information Systems
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    • v.29 no.4
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    • pp.91-110
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    • 2023
  • The importance of manuals is emphasized because chemical accidents require swift response and recovery, and often result in environmental pollution and casualties. In this regard, the OECD revised OECD Guidelines for the Prevention, Preparedness, and Response to Chemical Accidents (referred to as the OECD Guidelines), in June 2023. Moreover, while existing research primarily raises awareness about chemical accidents, highlighting the need for a system-wide response including laws, regulations, and manuals, it was difficult to find comparative research on the attributes of manuals. So, this paper aims to compare and analyze the second and third editions of the OECD Guidelines, in order to uncover the information attributes and implications of the revised version. Specifically, TF-IDF (Term Frequency-Inverse Document Frequency) was applied to understand which keywords have become more important, and Word2Vec was applied to identify keywords that were used similarly and those that were differentiated. Lastly, a 2×2 matrix was proposed, identifying the topics within each quadrant to provide a deeper comparison of the information attributes of the OECD Guidelines. This study offers a framework to help researchers understand information attributes. From a practical perspective, it appears valuable for the revision of standard manuals by domestic government agencies and corporations related to chemistry.

The Measurement Algorithm for Microphone's Frequency Character Response Using OATSP (OATSP를 이용한 마이크로폰의 주파수 특성 응답 측정 알고리즘)

  • Park, Byoung-Uk;Kim, Hack-Yoon
    • The Journal of the Acoustical Society of Korea
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    • v.26 no.2
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    • pp.61-68
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    • 2007
  • The frequency response of a microphone, which indicates the frequency range that a microphone can output within the approved level, is one of the most significant standards used to measure the characteristics of a microphone. At present, conventional methods of measuring the frequency response are complicated and involve the use of expensive equipment. To complement the disadvantages, this paper suggests a new algorithm that can measure the frequency response of a microphone in a simple manner. The algorithm suggested in this paper generates the Optimized Aoshima's Time Stretched Pulse(OATSP) signal from a computer via a standard speaker and measures the impulse response of a microphone by convolution the inverse OATSP signal and the received by the microphone to be measured. Then, the frequency response of the microphone to be measured is calculated using the signals. The performance test for the algorithm suggested in the study was conducted through a comparative analysis of the frequency response data and the measures of frequency response of the microphone measured by the algorithm. It proved that the algorithm is suitable for measuring the frequency response of a microphone, and that despite a few errors they are all within the error tolerance.

Technique to Reduce Container Restart for Improving Execution Time of Container Workflow in Kubernetes Environments (쿠버네티스 환경에서 컨테이너 워크플로의 실행 시간 개선을 위한 컨테이너 재시작 감소 기법)

  • Taeshin Kang;Heonchang Yu
    • The Transactions of the Korea Information Processing Society
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    • v.13 no.3
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    • pp.91-101
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    • 2024
  • The utilization of container virtualization technology ensures the consistency and portability of data-intensive and memory volatile workflows. Kubernetes serves as the de facto standard for orchestrating these container applications. Cloud users often overprovision container applications to avoid container restarts caused by resource shortages. However, overprovisioning results in decreased CPU and memory resource utilization. To address this issue, oversubscription of container resources is commonly employed, although excessive oversubscription of memory resources can lead to a cascade of container restarts due to node memory scarcity. Container restarts can reset operations and impose substantial overhead on containers with high memory volatility that include numerous stateful applications. This paper proposes a technique to mitigate container restarts in a memory oversubscription environment based on Kubernetes. The proposed technique involves identifying containers that are likely to request memory allocation on nodes experiencing high memory usage and temporarily pausing these containers. By significantly reducing the CPU usage of containers, an effect similar to a paused state is achieved. The suspension of the identified containers is released once it is determined that the corresponding node's memory usage has been reduced. The average number of container restarts was reduced by an average of 40% and a maximum of 58% when executing a high memory volatile workflow in a Kubernetes environment with the proposed method compared to its absence. Furthermore, the total execution time of a container workflow is decreased by an average of 7% and a maximum of 13% due to the reduced frequency of container restarts.

Analysis of the application of image quality assessment method for mobile tunnel scanning system (이동식 터널 스캐닝 시스템의 이미지 품질 평가 기법의 적용성 분석)

  • Chulhee Lee;Dongku Kim;Donggyou Kim
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.26 no.4
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    • pp.365-384
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    • 2024
  • The development of scanning technology is accelerating for safer and more efficient automated inspection than human-based inspection. Research on automatically detecting facility damage from images collected using computer vision technology is also increasing. The pixel size, quality, and quantity of an image can affect the performance of deep learning or image processing for automatic damage detection. This study is a basic to acquire high-quality raw image data and camera performance of a mobile tunnel scanning system for automatic detection of damage based on deep learning, and proposes a method to quantitatively evaluate image quality. A test chart was attached to a panel device capable of simulating a moving speed of 40 km/h, and an indoor test was performed using the international standard ISO 12233 method. Existing image quality evaluation methods were applied to evaluate the quality of images obtained in indoor experiments. It was determined that the shutter speed of the camera is closely related to the motion blur that occurs in the image. Modulation transfer function (MTF), one of the image quality evaluation method, can objectively evaluate image quality and was judged to be consistent with visual observation.

Impact of face masks on spectral and cepstral measures of speech: A case study of two Korean voice actors (한국어 스펙트럼과 캡스트럼 측정시 안면마스크의 영향: 남녀 성우 2인 사례 연구)

  • Wonyoung Yang;Miji Kwon
    • The Journal of the Acoustical Society of Korea
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    • v.43 no.4
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    • pp.422-435
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    • 2024
  • This study intended to verify the effects of face masks on the Korean language in terms of acoustic, aerodynamic, and formant parameters. We chose all types of face masks available in Korea based on filter performance and folding type. Two professional voice actors (a male and a female) with more than 20 years of experience who are native Koreans and speak standard Korean participated in this study as speakers of voice data. Face masks attenuated the high-frequency range, resulting in decreased Vowel Space Area (VSA) and Vowel Articulation Index (VAI)scores and an increased Low-to-High spectral ratio (L/H ratio) in all voice samples. This can result in lower speech intelligibility. However, the degree of increment and decrement was based on the voice characteristics. For female speakers, the Speech Level (SL) and Cepstral Peak Prominence (CPP) increased with increasing face mask thickness. In this study, the presence or filter performance of a face mask was found to affect speech acoustic parameters according to the speech characteristics. Face masks provoked vocal effort when the vocal intensity was not sufficiently strong, or the environment had less reverberance. Further research needs to be conducted on the vocal efforts induced by face masks to overcome acoustic modifications when wearing masks.

A Study on the Countmeasures of the Korean Pharmaceutical/Bio Industry to the EU Corporate Sustainability Due Diligence Directive, by using Text Mining (텍스트 마이닝을 활용한 국내 제약·바이오 업종의 EU 공급망 실사법 대응 방안 연구)

  • Sori Kim;Joonhak Ki
    • Information Systems Review
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    • v.26 no.1
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    • pp.93-117
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    • 2024
  • In February 2022, the EU announced a draft of the EU Corporate Sustainability Due Diligence Directive requiring due diligence and disclosure of information on environmental and human rights risks in corporate supply chains. This study evaluated the ability of 13 Korean pharmaceutical/bio companies to respond to the EU's demand for due diligence in the supply chain and compared it to 13 globally leading pharmaceutical/bio companies which are considered good in environmental and human rights risk management. For comparative analysis, text mining analysis was performed using R. Basic word frequency and concurrent words were analyzed and topic modeling was performed by applying Latent Dirichlet Allocation. As a result of the analysis, it was found that compared to advanced companies, domestic pharmaceutical and bio companies lack negative issue reporting and identification systems and supply chain due diligence implementation processes, and require advancement of data management for environmental and human rights information disclosure. Accordingly, domestic pharmaceutical and bio companies need to prepare differentiated support measures to systematically identify and reduce risks in the supply chain of small and medium-sized businesses beyond simply providing financial support. It is also desirable for the government to provide policy support by mandating Korea's own supply chain environment and human rights due diligence system, along with support for strengthening the ability to respond to due diligence of domestic pharmaceutical and bio companies, such as expert consulting and financial support.

Cost-aware Optimal Transmission Scheme for Shared Subscription in MQTT-based IoT Networks (MQTT 기반 IoT 네트워크에서 공유 구독을 위한 비용 관리 최적 전송 방식)

  • Seonbin Lee;Younghoon Kim;Youngeun Kim;Jaeyoon Choi;Yeunwoong Kyung
    • Journal of Internet of Things and Convergence
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    • v.10 no.4
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    • pp.1-8
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    • 2024
  • As technology advances, Internet of Things (IoT) technology is rapidly evolving as well. Various protocols, including Message Queuing Telemetry Transport (MQTT), are being used in IoT technology. MQTT, a lightweight messaging protocol, is considered a de-facto standard in the IoT field due to its efficiency in transmitting data even in environments with limited bandwidth and power. In this paper, we propose a method to improve the message transmission method in MQTT 5.0, specifically focusing on the shared subscription feature. The widely used round-robin method in shared subscriptions has the drawback of not considering the current state of the clients. To address this limitation, we propose a method to select the optimal transmission method by considering the current state. We model this problem based on Markov decision process (MDP) and utilize Q-Learning to select the optimal transmission method. Through simulation results, we compare our proposed method with existing methods in various environments and conduct performance analysis. We confirm that our proposed method outperforms existing methods in terms of performance and conclude by suggesting future research directions.