• 제목/요약/키워드: Multi-air classification

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Korea Emissions Inventory Processing Using the US EPA's SMOKE System

  • Kim, Soon-Tae;Moon, Nan-Kyoung;Byun, Dae-Won W.
    • Asian Journal of Atmospheric Environment
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    • 제2권1호
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    • pp.34-46
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    • 2008
  • Emissions inputs for use in air quality modeling of Korea were generated with the emissions inventory data from the National Institute of Environmental Research (NIER), maintained under the Clean Air Policy Support System (CAPSS) database. Source Classification Codes (SCC) in the Korea emissions inventory were adapted to use with the U.S. EPA's Sparse Matrix Operator Kernel Emissions (SMOKE) by finding the best-matching SMOKE default SCCs for the chemical speciation and temporal allocation. A set of 19 surrogate spatial allocation factors for South Korea were developed utilizing the Multi-scale Integrated Modeling System (MIMS) Spatial Allocator and Korean GIS databases. The mobile and area source emissions data, after temporal allocation, show typical sinusoidal diurnal variations with high peaks during daytime, while point source emissions show weak diurnal variations. The model-ready emissions are speciated for the carbon bond version 4 (CB-4) chemical mechanism. Volatile organic carbon (VOC) emissions from painting related industries in area source category significantly contribute to TOL (Toluene) and XYL (Xylene) emissions. ETH (Ethylene) emissions are largely contributed from point industrial incineration facilities and various mobile sources. On the other hand, a large portion of OLE (Olefin) emissions are speciated from mobile sources in addition to those contributed by the polypropylene industry in point source. It was found that FORM (Formaldehyde) is mostly emitted from petroleum industry and heavy duty diesel vehicles. Chemical speciation of PM2.5 emissions shows that PEC (primary fine elemental carbon) and POA (primary fine organic aerosol) are the most abundant species from diesel and gasoline vehicles. To reduce uncertainties in processing the Korea emission inventory due to the mapping of Korean SCCs to those of U.S., it would be practical to develop and use domestic source profiles for the top 10 SCCs for area and point sources and top 5 SCCs for on-road mobile sources when VOC emissions from the sources are more than 90% of the total.

군집화 기반 정상상태 식별을 활용한 시스템 에어컨의 냉매 충전량 분류 모델 개발 (Development of Classification Model on SAC Refrigerant Charge Level Using Clustering-based Steady-state Identification)

  • 김재희;노유정;정종환;최봉수;장석훈
    • 한국전산구조공학회논문집
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    • 제35권6호
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    • pp.357-365
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    • 2022
  • 냉매 오충전은 에어컨에서 빈번하게 발생하는 고장 모드 중 하나로, 적정 충전량 대비 부족 및 과충전 모두 냉방 성능의 저하를 유발하므로 충전된 냉매량을 정확하게 판단하는 것이 중요하다. 본 연구에서는 퍼지 군집화 기법을 통한 정상상태 식별을 통해 냉매 오충전량을 다중 분류하는 모델을 개발하였다. 정상상태 식별을 위해 에어컨 운전 데이터에 대해 이동 평균 간의 차이를 활용한 퍼지 군집화 알고리즘을 적용하였으며, IFDR를 통해 기존 연구된 정상상태 판단 기법들과 식별 결과를 비교하였다. 이후, 시스템 내 상관성을 고려한 mRMR을 이용해 특징을 선택하였으며, 도출된 특징을 이용해 SVM 기반의 다중 분류 모델이 생성되었다. 제안된 방법은 시험 데이터를 통해 만족할 만한 분류 정확도와 강건성을 도출하였다.

국방분야 비인가 이미지 파일 탐지를 위한 다중 레벨 컨볼루션 신경망 알고리즘의 구현 및 검증 (Implementation and Verification of Multi-level Convolutional Neural Network Algorithm for Identifying Unauthorized Image Files in the Military)

  • 김영수
    • 한국멀티미디어학회논문지
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    • 제21권8호
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    • pp.858-863
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    • 2018
  • In this paper, we propose and implement a multi-level convolutional neural network (CNN) algorithm to identify the sexually explicit and lewdness of various image files, and verify its effectiveness by using unauthorized image files generated in the actual military. The proposed algorithm increases the accuracy by applying the convolutional artificial neural network step by step to minimize classification error between similar categories. Experimental data have categorized 20,005 images in the real field into 6 authorization categories and 11 non-authorization categories. Experimental results show that the overall detection rate is 99.51% for the image files. In particular, the excellence of the proposed algorithm is verified through reducing the identification error rate between similar categories by 64.87% compared with the general CNN algorithm.

유럽 집합주택을 대상으로 한 환경친화적 외피의 특성 분석 - 외피의 구축적 특성에 따른 유형별 분석을 중심으로 - (A Study on the Characteristics of Environment-friendly Skins of European Housing - Focused on the Structural Characteristics of the skins -)

  • 원현성;김진우;오세규
    • KIEAE Journal
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    • 제8권1호
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    • pp.11-18
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    • 2008
  • The purpose of this study is to analyze application methods and structural characteristics of each element of environment-friendly European housing through classification of skin types. The results of the study are following. 1) The skins are classified by three types; single skin with multi layers, double skin with single layer and double skin with multi layers. 2) Most single skins with multi-layer are composed with wooden louvers, sun blinds and insulating windows. There are introduction of atrium and balcony, and variation sectional space composition according to cases. 3) There are two types of double skins; to put cavity between inner skin and outer skin and more extensional spaces such as balconies, corridors and stair halls. Solar walls and mechanical ventilators are often introduced to double skins with multi-layer. 4) The functions of the latest environment-friendly skins are vary from controllers and buffers of indoor environmental elements such as temperature, light, air and sound to equipments to perform essential functions to efficiently operate HVAC systems.

AN ASSESSMENT OF LAND COVER CHANGES AND ASSOCIATED URBANIZATION IMPACTS ON AIR QUALITY IN NAWABSHAH, PAKISTAN: A REMOTE SENSING PERSPECTIVE

  • Shaikh, Asif Ahmed;Gotoh, Keinosuke
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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    • pp.555-558
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    • 2006
  • In recent years, urban development has expanded rapidly in Nawabshah City of Pakistan. A major effect associated with this population trend is transformation of the landscape from natural cover types to increasingly impervious urban land. The core objective of this study are to provide time-series information to define and measure the urban land cover changes of Nawabshah, Pakistan between the years 1992 and 2002, and to examine related urbanization impacts on air quality of the study area. Two multi-temporal Landsat images acquired in 1992 and 2002 together with standard topographical maps to measure land cover changes were used in this study. The image processing and data manipulation were conducted using algorithms supplied with the ERDAS Imagine software. An unsupervised classification approach, which uses a minimum spectral distance to assign pixels to clusters, was used with the overall accuracy ranging from 84 percent to 92 percent. Land cover statistics demonstrate that during the study period (1992-2002) extensive transformation of barren and vegetated lands into urban land have taken place in Nawabshah City. Results revealed that land cover changes due to urbanization has not only contaminated the air quality of the study area but also raised the health concerns for the local residents.

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이동표적에 적용 가능한 공대지 유도폭탄의 투하 가능 영역 (Computation of Launch Acceptability Region of Air-to-Surface Guided Bomb for Moving Target)

  • 강예준
    • 한국항공우주학회지
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    • 제49권7호
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    • pp.601-608
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    • 2021
  • 공대지 유도폭탄의 투하 가능 영역(LAR)은 플랫폼이 목표하는 지점에 장착물이 성공적으로 명중하기 위해 진입해야 하는 영역을 의미한다. 목표물의 기동 종류에 따라 크게 고정표적, 이동표적으로 나누며, 본 논문에서는 고정표적 및 이동표적에도 적용 가능한 투하 가능 영역의 산출 알고리즘에 대해 연구하였다. 이는 플랫폼과 표적, 대기환경을 매개변수로 하여 입력변수를 변화시키며 다중 시뮬레이션을 수행 후 회귀 및 분류 알고리즘을 이용하여 적절한 투하 가능 영역을 시현하기 위한 함수를 개발하였다. 운용 적합성을 위한 시현 알고리즘을 적용하여 적절한 투하 가능 영역이 도출되며, 결과적으로 이동표적에도 적용할 수 있는 공대지 유도폭탄의 투하 가능 영역 알고리즘의 적용 가능성을 확인하였다.

냉동시스템 고장 진단 및 고장유형 분석을 위한 3단계 분류 알고리즘에 관한 연구 (A study on the 3-step classification algorithm for the diagnosis and classification of refrigeration system failures and their types)

  • 이강배;박성호;이희원;이승재;이승현
    • 한국융합학회논문지
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    • 제12권8호
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    • pp.31-37
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    • 2021
  • 산업의 발전으로 도시화로 인해 건물의 규모가 커지면서, 건물의 공기 정화 및 쾌적한 실내 환경을 유지의 필요성 또한 증가하고 있다. 냉동 시스템의 모니터링 기술의 발전으로 건물 내에 발생하는 전력 소모량을 관리할 수 있게 되었다. 특히 상업용 건물에서 발생하는 전력 소모량 중 약 40%가 냉동 시스템에서 일어난다. 따라서 본 연구 냉동시스템 고장진단 알고리즘을 개발하기 위해서 냉동시스템의 구조를 이해하고, 냉동 시스템의 운영과정에서 발생하는 데이터를 수집 분석하여 다양한 유형과 심각도를 가지는 고장 상황을 조기에 신속하게 탐지 분류하고자 하였다. 특히 분류가 어려운 고장 유형들의 분류 정확도를 향상시키기 위하여 3단계 진단 및 분류 알고리즘을 개발하여 제안하였다. 다수의 실험과 초모수 (hyper parameter) 최적화 과정을 거쳐 각 단계에 적합한 분류 모형으로 SVM과 LGBM에 기반 한 모형을 제시하였다. 본 연구에서는 고장에 영향을 미치는 특성을 최대한 보존하면서, 선행연구에서 어려움을 겪었던 냉매 관련 고장을 포함한 모든 고장 유형을 우수한 결과로 도출하였다.

분산주성분 분석을 이용한 고등학교교실 내 오염패턴분류에 관한 연구 (Classification of Pollution Patterns in High School Classrooms using Disjoint Principal Component Analysis)

  • 장철순;이태정;김동술
    • 한국대기환경학회지
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    • 제22권6호
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    • pp.808-820
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    • 2006
  • In regard to indoor air quality patterns, the government introduced various polices that were about managing and monitoring quality of indoor air as a major assignment, and also executed 'Indoor Air Quality Management Act' which was presented in the May, 2004. However, among the multi-usage facilities controlled by the Act, the school was not included yet. This study goal was to investigate PM 10 pollution patterns of the high school classrooms using a pattern recognition method based on cluster analysis and disjoint principal component analysis, and further to survey levels of inorganic elements in May, June, and September, 2004. A hierarchical clustering method was examined to obtain possible objects in pseudo homogeneous sample classes by transformation raw data and by applying various distance. Following the analysis, the disjoint principal component analysis was used to define homogeneous sample class after deleting outliers. Then three homogeneous Patterns were obtained as follows: the first class had been separated and objects in the class were considered to be sampled under semi-open condition. This class had high concentration of Ca, Fe, Mg, K, Al, and Na which are related with a soil and a chalk compounds. The second class was obtained in which objects were sampled while working air-conditioners and was identified low concentration of PM 10 and elements. Objects in the last class were assigned during rainy day. A chalk, soil element and various types of anthropogenic sources including combustions and industrial influenced the third class. This methodology was thought to be helpful enough to classify indoor air quality patterns and indoor environmental categories when controlling an indoor air quality.

도시규모 중·장기 대기질영향평가를 위한 종관기상조건의 분류 (Classification of Synoptic Meteorological Conditions for the Medium or Long Term Atmospheric Environmental Assessment in Urban Scale)

  • 김철희;손혜영;김지아
    • 환경영향평가
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    • 제16권2호
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    • pp.157-168
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    • 2007
  • In case there is a need to run the multi-year urban scale air qulaity model, it is a difficult task due to the computational demand, requiring the statistical approach for the long time atmospheric environmental assessment. In an effort to approach toward long term urban assessment, the sixteen synoptic meteorological conditions are statistically classified from the estimated geostrophic wind speeds and directions of 850 hPa geopotential height field during 2000 ~ 2005. The geostrophic wind directions are subdivided into four even intervals (north, east, south, and west), geostrophic wind speeds into two classes(${\leq}5m/s$ and >5m/s), and daily mean cloud amount into 2 classes(${\leq}5/10$ and >5/10), which result into sixteen classes of the synoptic meteorological cases for each season. The frequency distributions for each 16 synoptic meteorological case are examined and some discussions on how these synoptic classifications can be used in the environmental assessment are presented.

고해상도 FMCW 레이더 영상 합성과 CW 신호 분석 실험을 통한 드론의 탐지 및 식별 연구 (Experimental Study of Drone Detection and Classification through FMCW ISAR and CW Micro-Doppler Analysis)

  • 송경민;문민정;이우경
    • 한국군사과학기술학회지
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    • 제21권2호
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    • pp.147-157
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    • 2018
  • There are increasing demands to provide early warning against intruding drones and cope with potential threats. Commercial anti-drone systems are mostly based on simple target detection by radar reflections. In real scenario, however, it becomes essential to obtain drone radar signatures so that hostile targets are recognized in advance. We present experimental test results that micro-Doppler radar signature delivers partial information on multi-rotor platforms and exhibits limited performance in drone recognition and classification. Afterward, we attempt to generate high resolution profile of flying drone targets. To this purpose, wide bands radar signals are employed to carry out inverse synthetic aperture radar(ISAR) imaging against moving drones. Following theoretical analysis, experimental field tests are carried out to acquire real target signals. Our preliminary tests demonstrate that high resolution ISAR imaging provides effective measures to detect and classify multiple drone targets in air.