• Title/Summary/Keyword: artificial structure

Search Result 1,496, Processing Time 0.032 seconds

Characteristics of Oceanographic Environment in a Building with a Sea Area for the Artificial Upwelling Structure. (인공용승구조물 설치해역의 해양환경 특성)

  • Kim Dong-Sun;Hwang Suk-Bum
    • Proceedings of KOSOMES biannual meeting
    • /
    • 2005.11a
    • /
    • pp.133-137
    • /
    • 2005
  • To investigated the variation of marine environments due to set up of artificial structure, we carried out field observations. High temperature and salinity waters were distributed clearly in the southeastern part of study area during summer season. The variation of current structure was also occurred around study area where artificial structure set up. In 2005 after set up of artificial structure, the nutrient concentration increased greater than that in 2002 before set up artificial structures. To illustrate the characteristics of marine environment due to set up of artificial structure, quantitative analyses on the effect of artificial structure are important.

  • PDF

Calculating Data and Artificial Neural Network Capability (데이터와 인공신경망 능력 계산)

  • Yi, Dokkyun;Park, Jieun
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.26 no.1
    • /
    • pp.49-57
    • /
    • 2022
  • Recently, various uses of artificial intelligence have been made possible through the deep artificial neural network structure of machine learning, demonstrating human-like capabilities. Unfortunately, the deep structure of the artificial neural network has not yet been accurately interpreted. This part is acting as anxiety and rejection of artificial intelligence. Among these problems, we solve the capability part of artificial neural networks. Calculate the size of the artificial neural network structure and calculate the size of data that the artificial neural network can process. The calculation method uses the group method used in mathematics to calculate the size of data and artificial neural networks using an order that can know the structure and size of the group. Through this, it is possible to know the capabilities of artificial neural networks, and to relieve anxiety about artificial intelligence. The size of the data and the deep artificial neural network are calculated and verified through numerical experiments.

The Intertidal Macrobenthic Community along an Artificial Structure (인공구조물에 따른 조간대 대형저서동물 군집변화)

  • Yu Ok-Hwan;Lee Hyung-Gon;Lee Jae-Hac
    • Korean Journal of Fisheries and Aquatic Sciences
    • /
    • v.39 no.spc1
    • /
    • pp.132-141
    • /
    • 2006
  • Artificial structures have been designed as pilot structures to promote the creation and restoration of tidal flats. However, little information is available as to whether such artificial construction affects the macrobenthic community structure. We monitored the variation of the macrobenthic community structure and species composition near natural and artificial structures (seaweed and a timber fence) on the tidal flats near the Iwon Dike, Korea. In total, 137 macrobenthic species were recorded during this study, predominantly crustaceans (47%), polychaetes (18%), and molluscs (27%). Polychaetes comprised over 50% of the total density, followed by gastropods (38%) and crustaceans (11%). Macrobenthic species composition in the artificial and natural areas, was initially similar, but it differed after 7 months. The gastropod Umbonium thomasi, the most dominant species, was present at both sites in the first month after the start of the experiment, but disappeared at the artificial sites within 7 months, suggesting disturbance by the environmental factors. The number of species and diversity (H') varied significantly within sites at the beginning of the experiment, but no difference was observed after 7 months. Multivariate analysis (multidimensional scaling) revealed significant differences in community structure between the artificial and the natural areas from 7 months after the start of the experiment, except from 18 to 21 months. The community structures were mainly influenced by U. thomasi. Community structure at the artificial sites was affected by environmental variables, such as carbon, COD/IL sulfide, loss of ignition, kurtosis and silt, which changed over time. We observed no significant correlations between environmental variables and the dominant species, except in the case of Spio sp. and Macrophthalmus dilatatus, suggesting that the biological interactions and temporary disturbances such as typhoon, as well as the effects of artificial structures may also be important regulating factors in this system.

Characteristics of Oceanographic Environment in a Sea Area for the Building of Artificial Upwelling Structure (인공용승구조물 설치해역의 해양환경 특성)

  • Kim Dong-Sun;Hwang Suk-Bum
    • Journal of the Korean Society of Marine Environment & Safety
    • /
    • v.12 no.1 s.24
    • /
    • pp.1-8
    • /
    • 2006
  • To investigate the variation of marine environments due to set up of artificial structure, we carried out field observations. High temperature and salinity waters near the south frontal area were distributed clearly in the southeastern part of study area during summer season The variation of current structure was also occurred around study area where artificial structure set up. In 2005 after set up of artificial structure, the nutrient concentration increased greater than that in 2002 before set up artificial structures. To illustrate the characteristics of marine environment due to set up of artificial structure, quantitative analyses on the effect of artificial structure are important.

  • PDF

A Study on the Artificial Recognition System on Visual Environment of Architecture (건축의 시각적 환경에 대한 지능형 인지 시스템에 관한 연구)

  • Seo, Dong-Yeon;Lee, Hyun-Soo
    • KIEAE Journal
    • /
    • v.3 no.2
    • /
    • pp.25-32
    • /
    • 2003
  • This study deals with the investigation of recognition structure on architectural environment and reconstruction of it by artificial intelligence. To test the possibility of the reconstruction, recognition structure on architectural environment is analysed and each steps of the structure are matched with computational methods. Edge Detection and Neural Network were selected as matching methods to each steps of recognition process. Visual perception system established by selected methods is trained and tested, and the result of the system is compared with that of experiment of human. Assuming that the artificial system resembles the process of human recognition on architectural environment, does the system give similar response of human? The result shows that it is possible to establish artificial visual perception system giving similar response with that of human when it models after the recognition structure and process of human.

Flow Characteristics of the Artificial Upwelling Structure by Porosity Change (공극률 변화에 따른 인공용승류 특성)

  • Lee, Hwang Ki;Kim, Young Min;Kim, Jong Kyu
    • Journal of the Korean Society for Marine Environment & Energy
    • /
    • v.20 no.2
    • /
    • pp.100-106
    • /
    • 2017
  • Artificial upwelling structure has been set up in sea mount. Bottom water can upwelling euphotic zone. Plentiful nutrient included in bottom water could not only enhance primary production but also expect food chain reaction and gathering fish. This study explain flowing features subject to porosity changes according to the material and shape of artificial upwelling structure. As a result, the upward flux is getting decreased while the porosity is increasing. And it figured out when the upward flux was decreased, the downward flux was also decreased. Futhermore, it was confirmed that the best efficiency of upwelling flux was shown up when the porosity was 10% according to the volume of artificial upwelling structure in case of 20% of porosity, it also has a good efficiency in comparison with impermeable artificial upwelling structure. Therefore, to build the artificial upwelling structure, It is encouraged to design it less than 20% of porosity for the best performance.

A Study on Function of Artificial Upwelling Structure of Material (재질에 따른 인공용승구조물의 기능성에 관한 연구)

  • Jeon, Yong-Ho;Kim, Hong-Jin;Ryu, Cheong-Ro
    • Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
    • /
    • 2002.10a
    • /
    • pp.277-282
    • /
    • 2002
  • This study was performed to find out basic function of artificial upwelling structures. Generation of artificial upwelling current was affected by size of structures, incident current and porosity. when stratification parameters was about 3.0, relative height(hs/h) of structures was $0.125{\sim}0.15$, stable artificial upwelling current was generated in the back-side of structures. when porosity is lower than 50%, the effect of artificial upwelling structure was to be better than little by little.

  • PDF

Characteristics of Wildbirds Habitat of Artificial Green Corridor in Gangseo-gu, Seoul (서울시 강서구 조성녹지축의 야생조류 서식처 특성 연구)

  • Choi, Jin-Woo;Lee, Kyong-Jae
    • Journal of Environmental Science International
    • /
    • v.19 no.1
    • /
    • pp.47-59
    • /
    • 2010
  • This study was to examine the characteristics of wirdbirds habitat for improvement plan in green corridor. The target site, Gangseo-gu artificial green corridor was set up with the structure in which small scale of core green space with Goongsan and Yeomchang neighborhood parks in urbanized city was connected with the artificial green space with Gongamnaru, Hwanggeumnae neighborhood parks with 28~42.5 m in width. Wild birds six~eleven species; Dendrocopos spp, Paradoxornis webbiana, Parus major, Phasianus colchicus, etc. were observed in core green, but wild birds of two~five species: Columba livuia, Passer montanus, Pica pica, Hypsipetes amaurotis, etc. were observed in artificial green space. Thus wild birds of artificial and generalist species only moved in artificial green space. The artificial green space where vegetation structure was consisted of single-layer with poorness chose target species laying stress on generalist species and edge species of Parus major, P. palustris, Paradoxornis webbiana etc. for short-term and interior species of Dendrocopos major, Picus canus, etc. for long-term. The result suggested enhancement methods for target species's habitat in green corridor: to secure at least a corridor 30 meters in artificial corridor, to secure ecological pond, to offer the various shelterer and environment of prey-resources through the multi-layer structure.

Bacterial Community Structure and the Dominant Species in Imported Pollens for Artificial Pollination

  • Kim, Su-Hyeon;Do, Heeil;Cho, Gyeongjun;Kim, Da-Ran;Kwak, Youn-Sig
    • The Plant Pathology Journal
    • /
    • v.37 no.3
    • /
    • pp.299-306
    • /
    • 2021
  • Pollination is an essential process for plants to carry on their generation. Pollination is carried out in various ways depending on the type of plant species. Among them, pollination by insect pollinator accounts for the most common. However, these pollinators have be decreasing in population density due to environmental factors. Therefore, use of artificial pollination is increasing. However, there is a lack of information on microorganisms present in the artificial pollens. We showed the composition of bacteria structure present in the artificial pollens of apple, kiwifruit, peach and pear, and contamination of high-risk pathogens was investigated. Acidovorax spp., Pantoea spp., Erwinia spp., Pseudomonas spp., and Xanthomonas spp., which are classified as potential high-risk pathogens, have been identified in imported pollens. This study presented the pollen-associated bacterial community structure, and the results are expected to be foundation for strengthening biosecurity in orchard industry.

Using artificial intelligence to solve a smart structure problem

  • Kaiwen, Liu;Jun, Gao;Ruizhe, Qiu
    • Structural Engineering and Mechanics
    • /
    • v.85 no.3
    • /
    • pp.393-406
    • /
    • 2023
  • Smart structures are those structure that could adopt some behavior to prevent instability in their responses. The recognition of stability deterioration has been performed through rigid mathematical formulations in control theory and unpredicted results could not be addressed in control systems since they are able to only work under their predefined condition. On the other hand, incorporating all affecting parameters could result in high computational cost and delay time in the response of the systems. Artificial intelligence (AI) method has shown to be a promising methodology not only in the computer science by at everyday life and in engineering problems. In the present study, we exploit the capabilities of artificial intelligence method to obtain frequency response of a smart structure. In this regard, a comprehensive development of equations is presented using Hamilton' principle and first order shear deformation theory. The equations were solved by numerical methods and the results are used to train an artificial neural network (ANN). It is demonstrated that ANN modeling could provide accurate results in comparison to the numerical solutions and it take less time than numerical solution.