• Title/Summary/Keyword: homogeneous environment

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Preparation and Properties of Disc Type CuO Catalyst Impregnated Ceramic Filters (디스크형 산화구리 촉매담지 세라믹필터의 제조와 물성)

  • Hong Min-Sun;Moon Su-Ho;Lee Jae-Chun;Lee Dong-Sub;Lim Woo Taik
    • Journal of Korean Society for Atmospheric Environment
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    • v.20 no.2
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    • pp.185-193
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    • 2004
  • A catalyst with CuO ceramic filter for simultaneous treatment of dust and HAP was prepared and characterized. Catalytic ceramic filter can not only potentially achieve the substantial savings in energy but provide with effective optimization and integration of process for simultaneous removal of SO$_2$, NO$_{x}$ and particulates from flue gases. Catalytic ceramic filters remove simultaneously particulates on exterior surface of filters and reduce NO to $N_2$ and $H_2O$ by SCR (Selective Catalytic Reduction) process. Preparation of catalyst impregnated ceramic filter with disk shape (Ψ 50) follow the processing of alumino-silicate ceramic filter, support impregnation and catalyst impregnation (copper oxide). Preparation routes of alumino-silicate catalyst carrier suitable for production of catalytic filters practically were studied and developed using the sol-gel and colloidal processing, homogeneous precipitation and impregnation method. Characterization of the catalyst, catalyst carrier catalytic filter materials have been performed the using various techniques such as BET, XRD, TGA, SEM. Combination of the sol-gel and colloidal processing and impregnation method is recommended to prepare catalyst carriers economically for catalytic filter applications.s.

The Air Quality Analysis in Underground Shopping Centers Using Pattern Recognition (Pattern Recognition을 이용한 지하상가에서의 대기오염물질의 농도 분석에 관한 연구)

  • 김동술;김형석
    • Journal of Korean Society for Atmospheric Environment
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    • v.6 no.1
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    • pp.1-10
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    • 1990
  • The purpose of the study was to analyze air quality in underground shopping centers using pattern recognition methods. In order to perform this, the concentraion of air pollutants such as $CO, NO_2, NO_x, SO_2$, and particulate matters was measured at the 11 different shopping centers in Seoul metropolitan area and the total of 47 samples were obtained at random based on the size of shopping centers. To introduce a new concept of the "average concentration" for the indoor air quality analyses, the various multivariate statistical analyses have been studied. Thus, a cluster analysis was applied to separate the samples into pseudo-patterns and a disjoint principal component analysis was used to generate homogeneous patterns after removing outliers from the pseudo-patterns. The 6 homogeneous patterns were then obtained as follows:the first pattern was a group of clean sites;the second a group of sites having high dust concentration;the third a group of sites having high dust and $NO_x$ concentration;the fourth a group of sites having low dust and $SO_2$ concentraion and high CO concentration;the fifth a group of sites having high $NO_2 and SO_2$ concentration;and the final a group of miscellaneous sites. Thus, the average concentration could be estimated for each pattern.h pattern.

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Non-Homogeneous Haze Synthesis for Hazy Image Depth Estimation Using Deep Learning (불균일 안개 영상 합성을 이용한 딥러닝 기반 안개 영상 깊이 추정)

  • Choi, Yeongcheol;Paik, Jeehyun;Ju, Gwangjin;Lee, Donggun;Hwang, Gyeongha;Lee, Seungyong
    • Journal of the Korea Computer Graphics Society
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    • v.28 no.3
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    • pp.45-54
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    • 2022
  • Image depth estimation is a technology that is the basis of various image analysis. As analysis methods using deep learning models emerge, studies using deep learning in image depth estimation are being actively conducted. Currently, most deep learning-based depth estimation models are being trained with clean and ideal images. However, due to the lack of data on adverse conditions such as haze or fog, the depth estimation may not work well in such an environment. It is hard to sufficiently secure an image in these environments, and in particular, obtaining non-homogeneous haze data is a very difficult problem. In order to solve this problem, in this study, we propose a method of synthesizing non-homogeneous haze images and a learning method for a monocular depth estimation deep learning model using this method. Considering that haze mainly occurs outdoors, datasets mainly containing outdoor images are constructed. Experiment results show that the model with the proposed method is good at estimating depth in both synthesized and real haze data.

Target Detection probability simulation in the homogeneous ground clutter environment

  • Kim, In-Kyu;Moon, Sang-Man;Kim, Hyoun-Kyoung;Lee, Sang-Jong;Kim, Tae-Sik;Lee, Hae-Chang
    • International Journal of Aeronautical and Space Sciences
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    • v.6 no.1
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    • pp.8-16
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    • 2005
  • This paper describes target detection performance of millimeter wave radar that exits on non-stationary target detection schemes in the ground clutter conditions. The comparison of various CFAR process schemes such as CA(Cell-Average)-CFAR, GO(Greatest Of)/SO(Smallest Of)-CFAR, and OS(Order Statistics)-CFAR performance are applied. Using matlab software, we show the performance and loss between target detection probability and signal to noise ratio. This paper concludes the OS-CFAR process performance is better than any others and satisfies the optimal detection probability without loss of detection in the homogeneous clutter, When range bins increase.

Evolving swarm of UAVs

  • Chi, T.Z.;Cheng, Hayong;Page, J.R.;Ahmed, N.A.
    • Advances in aircraft and spacecraft science
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    • v.1 no.2
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    • pp.219-232
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    • 2014
  • This paper reports on an ongoing study investigating the feasibility of using an evolutionary method to develop the rules governing Self-Organised (SO) systems for use in swarms of unmanned aerial vehicles. In general, it is difficult to design swarm systems that follow explicit global behaviour. Unlike optimising a predefined objective function, the solution to the problem is the emergent behaviour in the SO systems which results from simultaneous interactions among agents and between agents and their environment. In this study, evolutionary algorithms are used to investigate their control and effectiveness in synthesising the weighting of different rules on SO emergent behaviour. Both homogeneous swarms and heterogeneous swarms were considered though the results provided are for a case study investigating the simplest problem a homogeneous swarm without mutation. Though simple this study does indicate the potential of the approach.

Does mudcake change the results of modeling gamma-gamma well-logging?

  • Rasouli, Fatemeh S.
    • Nuclear Engineering and Technology
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    • v.54 no.9
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    • pp.3390-3397
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    • 2022
  • Among the different techniques available, nuclear methods, including gamma-gamma logging tools, are of special importance. Though the real environment which surrounds the drilled borehole is a complex fractured medium which the fluid can flow through the porosities, simulation studies generally use the traditional model of a homogeneous mixture of formation and the liquid. Considering a previously published study, which shows that modeling of fluid flow in fractured reservoirs and simulating the formation as an inhomogeneous fractured medium leads to different results compared with those of homogeneous mixture, here we study the effect of the presence of drilling fluid (mudcake) on the response of the detectors in both the models. To study this effect, a typical gamma-gamma logging tool was modeled by using the MCNPX Monte Carlo code. The results show that the responses of the detectors in the mixture model in the presence of various thicknesses of mudcake are sensitive to the density of the formation material. However, this effect is not notable in the inhomogeneous fractured medium. These results emphasize the importance of the model employed for simulation of the medium in gamma-gamma well-logging.

The Homogeneous Regions and Functional Regions in the Internal Structure of Seoul (서울시 등질지역과 기능지역의 구조 분석)

  • Son Seung-ho
    • Journal of the Korean Geographical Society
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    • v.39 no.4
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    • pp.562-584
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    • 2004
  • This paper intends to identify the structure of homogeneous regions and functional regions in Seoul based on B.J.L. Berry's ‘general field theory of spatial behavior’. The structure of homogeneous regions by using socio-economic variables can explain how the structural elements of the city are arranged. It can be ssid that Seoul has shifted towards more complicated and differentiated features in terms of homogeneous regions. The different patterns are found between the northern part to Han River where old torn areas are located and the southern part to Han River where newly urbanized areas are located. Usually, the concentric pattern and the sectoral pattern coexist, which is enhanced moving from CBD to the outskirt area. The distribution of different social classes shows irregular pattern similar to the variation of living environment. The social gap is expected to be more widening between new towns and old towns. The analysis of spatial movement pattern shows no clear hierarchical order because of current shifts towards both multi-nuclear pattern and spatial dispersion. The functional regions show duplicated structure overlapping their boundaries each other. The ‘general field theory of spatial behavior’ strongly suggests that spatial interactions among sub-areas in the city are differentiated from the basic characteristics and function of each sub-area. The attributes of homogeneous regions and functional regions are interrelated in the characteristics of isomorphic nature.

Study On Lagrangian Heat Source Tracking Method for Urban Thermal Environment Simulations (도시 열환경 시뮬레이션을 위한 라그랑지안 열원 역추적 기법의 연구)

  • Kim, Seogcheol;Lee, Joosung;Yun, Jeongim;Kang, Jonghwa;Kim, Wansoo
    • Journal of Korean Society for Atmospheric Environment
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    • v.33 no.6
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    • pp.583-592
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    • 2017
  • A method is proposed for locating the heat sources from temperature observations, and its applicability is investigated for urban thermal environment simulations. A Lagrangian particle dispersion model, which is originally built for simulating the pollutants spread in the air, is exploited to identify the heat sources by transporting the Lagrangian heat particles backwards in time. The urban wind fields are estimated using a diagnostic meteorological model incorporating the morphological model for the urban canopy. The proposed method is tested for the horizontally homogeneous urban boundary layer problems. The effects of the turbulence levels and the computational time on the simulation are investigated.

Performance Improvement of a Variability-index CFAR Detector for Heterogeneous Environment (비균질 환경에 강인한 검출기를 위한 변동 지수 CFAR의 성능 향상)

  • Shin, Jong-Woo;Kim, Wan-Jin;Do, Dae-Won;Lee, Dong-Hun;Kim, Hyoung-Nam
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.49 no.3
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    • pp.37-46
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    • 2012
  • In RADAR and SONAR detection systems, noise environment can be classified into homogeneous and heterogeneous environment. Especially heterogeneous environments are modelled as target masking and clutter edge. Since the variability-index (VI) CFAR, a composed CFAR algorithm, dynamically selects one of the mean-level algorithms based on the VI and the MR (mean ratio) test, it is robust to various environments. However, the VI CFAR still suffers from lowered detection probabilities in heterogeneous environments. To overcome these problems, we propose an improved VI CFAR processor where TM (trimmed mean) CFAR and a sub-windowing technique are introduced to minimize the degradation of the detection probabilities appeared in heterogeneous environments. Computer simulation results show that the proposed method has the better performance in terms of detection probability and false alarm probability compared to the VI CFAR and single CFAR algorithms.

An Adaptive Goal-Based Model for Autonomous Multi-Robot Using HARMS and NuSMV

  • Kim, Yongho;Jung, Jin-Woo;Gallagher, John C.;Matson, Eric T.
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.16 no.2
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    • pp.95-103
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    • 2016
  • In a dynamic environment autonomous robots often encounter unexpected situations that the robots have to deal with in order to continue proceeding their mission. We propose an adaptive goal-based model that allows cyber-physical systems (CPS) to update their environmental model and helps them analyze for attainment of their goals from current state using the updated environmental model and its capabilities. Information exchange approach utilizes Human-Agent-Robot-Machine-Sensor (HARMS) model to exchange messages between CPS. Model validation method uses NuSMV, which is one of Model Checking tools, to check whether the system can continue its mission toward the goal in the given environment. We explain a practical set up of the model in a situation in which homogeneous robots that has the same capability work in the same environment.