• Title/Summary/Keyword: mapping space

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MOLECULAR LINE STUDY OF L1014 WITH SRAO 6M TELESCOPE (L1014 분자운 핵에 대한 SRAO 6m 망원경을 이용한 분자선 관측연구)

  • Lee, Chang-Won
    • Publications of The Korean Astronomical Society
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    • v.20 no.1 s.24
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    • pp.1-5
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    • 2005
  • We report molecular line observations of CO(1-0), $^{13}CO(1-0)$, CS(2-1), and HCN(1-0) with SRAO 6m telescope toward L1014-IRS which is thought to be a very faint infrared source embedded in previously known 'starless' core L1014. The CO(1-0) observations find several components with different velocities along the line of sight of L1014, $4km\;s^{-1}$ and between $40{\sim}50km\;s^{-1}$. We find a parsec scale CO molecular outflow at the $4km\;s^{-1}$ component for the first time the direction of which is coincident with that of the small scale (${\sim}500pc$) outflow previously found. Although the observation is not covered for whole area of the outflow, the size of the molecular outflow seems not very inconsistent with the expected age of L1014-IRS. More accurate size and shape of the molecular outflow from L1014-IRS will be determined from the full coverage mapping in CO over the outflow region in very near future.

Adaptive Memory Controller for High-performance Multi-channel Memory

  • Kim, Jin-ku;Lim, Jong-bum;Cho, Woo-cheol;Shin, Kwang-Sik;Kim, Hoshik;Lee, Hyuk-Jun
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.16 no.6
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    • pp.808-816
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    • 2016
  • As the number of CPU/GPU cores and IPs in SOC increases and applications require explosive memory bandwidth, simultaneously achieving good throughput and fairness in the memory system among interfering applications is very challenging. Recent works proposed priority-based thread scheduling and channel partitioning to improve throughput and fairness. However, combining these different approaches leads to performance and fairness degradation. In this paper, we analyze the problems incurred when combining priority-based scheduling and channel partitioning and propose dynamic priority thread scheduling and adaptive channel partitioning method. In addition, we propose dynamic address mapping to further optimize the proposed scheme. Combining proposed methods could enhance weighted speedup and fairness for memory intensive applications by 4.2% and 10.2% over TCM or by 19.7% and 19.9% over FR-FCFS on average whereas the proposed scheme requires space less than TCM by 8%.

An Adaptive and Real-Time System for the Analysis and Design of Underground Constructions

  • Gutierrez, Marte
    • Geotechnical Engineering
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    • v.26 no.9
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    • pp.33-47
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    • 2010
  • Underground constructions continue to provide challenges to Geotechnical Engineers yet they pose the best opportunities for development and deployment of advance technologies for analysis, design and construction. The reason for this is that, by virtue of the nature of underground constructions, more data and information on ground characteristics and response become available as the construction progresses. However, due to several barriers, these data and information are rarely, if ever, utilized to modify and improve project design and construction during the construction stage. To enable the use of evolving realtime data and information, and adaptively modify and improve design and construction, the paper presents an analysis and design system, called AMADEUS, for underground projects. AMADEUS stands for Adaptive, real-time and geologic Mapping, Analysis and Design of Underground Space. AMADEUS relies on recent advances in IT (Information Technology), particularly in digital imaging, data management, visualization and computation to significantly improve analysis, design and construction of underground projects. Using IT and remote sensors, real-time data on geology and excavation response are gathered during the construction using non-intrusive techniques which do not require expensive and time-consuming monitoring. The real-time data are then used to update geological and geomechanical models of the excavation, and to determine the optimal, construction sequences and stages, and structural support. Virtual environment (VE) systems are employed to allow virtual walk-throughs inside an excavation, observe geologic conditions, perform virtual construction operations, and investigate stability of the excavation via computer simulation to steer the next stages of construction.

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Determining the Location of Urban Planning Measures for Preventing Debris-Flow Risks: Based on the MCDM Method (MCDM 기법을 이용한 도심지 토사재해 예방을 위한 도시계획적 대책 위치 결정방법 제안)

  • Moon, Yonghee;Lee, Sangeun;Kim, Soyoon;Kim, Myoungsoo
    • Journal of the Korean Society of Safety
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    • v.32 no.5
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    • pp.103-114
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    • 2017
  • The landslide disaster damage has been increased by mountain development, leading to construction of educational facilities, medical facilities, petty industrial facilities, and large housing complexes. Therefore, effective regulation is required as an effort in urban planning solutions. For suggesting specific mitigation strategies on urban landslide, this study aims to define evaluation criteria for urban planning management of debris-flow disaster. AHP (Analytic Hierarchy Process), one of the multiple criterion decision making methods, was utilized in this study. This study makes use of 16 sub-criteria under the framework of hazard, exposure, and vulnerability, and well-planned expert survey measures their weights. The weights are also applied to evaluate each grid in urban space (min $10{\times}10m$) and classify it with red, orange, yellow, or green grade so that areas at higher risk are clearly identified. This study concludes that the suggested method is useful to support a strategies for urban planning management of debris-flow disaster, particularly in a GIS base.

Stability Analysis and Proposal of a Simple Form of a Fuzzy PID Controller

  • Lee, Byung-Kyul;Kim, In-Hwan;Kim, Jong-Hwa
    • Journal of Advanced Marine Engineering and Technology
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    • v.28 no.8
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    • pp.1299-1312
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    • 2004
  • This paper suggests the simple form of a fuzzy PID controller and describes the design principle, tracking performance, stability analysis and changes of parameters of a suggested fuzzy PID controller. A fuzzy PID controller is derived from the design procedure of fuzzy control. It is well known that a fuzzy PID controller has a simple structure of the conventional PID controller but posses its self-tuning control capability and the gains of a fuzzy PID controller become nonlinear functions of the inputs. Nonlinear calculation during fuzzification, defuzzification and the fuzzy inference require more time in computation. To increase the applicability of a fuzzy PID controller to digital computer, a simple form of a fuzzy PID controller is introduced by the backward difference mapping and the analysis of the fuzzy input space. To guarantee the BIBO stability of a suggested fuzzy PID controller, ‘small gain theorem’ which proves the BIBO stability of a fuzzy PI and a fuzzy PD controller is used. After a detailed stability analysis using ‘small gain theorem’, from which a simple and practical method to decide the parameters of a fuzzy PID controller is derived. Through the computer simulations for the linear and nonlinear plants, the performance of a suggested fuzzy PID controller will be assured and the variation of the gains of a fuzzy PID controller will be investigated.

A Syudy on Applications of Convex Hull Algorithm in the SPH (SPH에서의 Convex Hull 알고리즘 적용연구)

  • Lee, Jin-Sung;Lee, Young-Shin
    • Journal of the Korea Institute of Military Science and Technology
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    • v.14 no.2
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    • pp.313-320
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    • 2011
  • SPH(Smoothed Particle Hydrodynamics) is a gridless Lagrangian technique that is useful as an alternative numerical analysis method used to analyze high deformation problems as well as astrophysical and cosmological problems. In SPH, all points within the support of the kernel are taken as neighbours. The accuracy of the SHP is highly influenced by the method for choosing neighbours from all particle points considered. Typically a linked-list method or tree search method has been used as an effective tool because of its conceptual simplicity, but these methods have some liability in anisotropy situations. In this study, convex hull algorithm is presented as an improved method to eliminate this artifact. A convex hull is the smallest convex set that contains a certain set of points or a polygon. The selected candidate neighbours set are mapped into the new space by an inverse square mapping, and extract a convex hull. The neighbours are selected from the shell of the convex hull. These algorithms are proved by Fortran programs. The programs are expected to use as a searching algorithm in the future SPH program.

Prediction of Protein Interactions using the Associative Feature Concept Space Mapping (연관속성개념공간으로의 사상을 이용한 단백질 상호작용 예측)

  • Eom Jae-Hong;Zhang Byoung-Tak
    • Proceedings of the Korean Information Science Society Conference
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    • 2006.06a
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    • pp.73-75
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    • 2006
  • 생물체 내에서 중요 생물학적 기능을 수행하는 기본 단위인 단백질 및 이들의 상호작용 대한 많은 연구가 이루어져 다양한 생물체에 대한 단백질 상호작용 데이터베이스가 구축되었다. 본 논문에서는 효모에 대해 공개되어있는 단백질 상호작용 데이터를 이용하여 새로운 단백질 상호작용을 예측하는 방법을 제안한다. 논문에서는 문헌에서 연관 정보를 효율적으로 찾아내기 위하여 제안된 연관개념공간 탐색 방법을 확장하여 단백질 상호작용 예측에 사용한다. 단백질들은 각각이 가지는 다양한 속성들의 벡터로 간주되며, 상호작용은 해당 단백질들의 연관성을 통해 이루어지는 것으로 표현된다. 상호작용하는 두 단백질들의 속성은 단어의 공동 출현과 같이 고려되어 단백질 상호작용은 두 단백질 벡터의 요소로 표현되고 벡터의 요소 속성들 간의 연관성을 표현하기 위해 연관속성개념공간으로 사상되어 공간상의 거리 기반으로 연관속성을 추출한다. 추출된 연관속성을 최대로 포함하는 단백질들 간의 상호작용을 예측하는 방식으로 단백질 상호작용을 예측한다. 논문에서 제안한 방법은 효모의 단백질 상호작용 예측에 대해 평균 약 91.8%의 예측 정확도를 보여, 연관속성개념공간을 이용한 방법이 단백질 상호작용을 예측하는 또 다른 대안으로 사용 될 수 있음을 확인하였다.

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A Hashing Method Using PCA-based Clustering (PCA 기반 군집화를 이용한 해슁 기법)

  • Park, Cheong Hee
    • KIPS Transactions on Software and Data Engineering
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    • v.3 no.6
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    • pp.215-218
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    • 2014
  • In hashing-based methods for approximate nearest neighbors(ANN) search, by mapping data points to k-bit binary codes, nearest neighbors are searched in a binary embedding space. In this paper, we present a hashing method using a PCA-based clustering method, Principal Direction Divisive Partitioning(PDDP). PDDP is a clustering method which repeatedly partitions the cluster with the largest variance into two clusters by using the first principal direction. The proposed hashing method utilizes the first principal direction as a projective direction for binary coding. Experimental results demonstrate that the proposed method is competitive compared with other hashing methods.

Development of the Calibration Algorithm of 3 Axis Vector Sensor Using Ellipsoid (타원체를 이용한 3축 센서의 실시간 보정 알고리듬 개발)

  • Hwang, Jung Moon;Kim, Jung Han
    • Journal of the Korean Society for Precision Engineering
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    • v.32 no.7
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    • pp.643-651
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    • 2015
  • Multi-axis magnetic and accelerometer sensor are widely used in consumer product such as smart phones. The vector output of multi-axis sensors have errors on each axis such as offset error, scale error, non-orthogonality. These errors cause many problems on the performance of the applications. In this paper, we designed the effective inline compensation algorithm for calibrating of 3 axis sensors using ellipsoid for mass production of multi-axis sensors. The outputs with those kinds of errors can be modeled by ellipsoid, and the proposed algorithm makes sequential mappings of the virtual ellipsoid to perfect sphere which is calibrated function of the sensor on three-dimensional space. The proposed calibrating process composed of four main stages and is very straightforward and effective. In addition, another imperfection of the sensor such as the drift from temperature can be easily inserted in each mapping stage. Numerical simulation and experimental results shows great performance of the proposed compensation algorithm.

Stream Data Analysis of the Weather on the Location using Principal Component Analysis (주성분 분석을 이용한 지역기반의 날씨의 스트림 데이터 분석)

  • Kim, Sang-Yeob;Kim, Kwang-Deuk;Bae, Kyoung-Ho;Ryu, Keun-Ho
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.28 no.2
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    • pp.233-237
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    • 2010
  • The recent advance of sensor networks and ubiquitous techniques allow collecting and analyzing of the data which overcome the limitation imposed by time and space in real-time for making decisions. Also, analysis and prediction of collected data can support useful and necessary information to users. The collected data in sensor networks environment is the stream data which has continuous, unlimited and sequential properties. Because of the continuous, unlimited and large volume properties of stream data, managing stream data is difficult. And the stream data needs dynamic processing method because of the memory constraint and access limitation. Accordingly, we analyze correlation stream data using principal component analysis. And using result of analysis, it helps users for making decisions.