• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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• pp.150-152
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• 2006

The DISCOVER Project (${\underline{D}}istributed$ ${\underline{I}}nformation$ ${\underline{S}}ervices$ for ${\underline{C}}limate$ and ${\underline{O}}cean$ products and ${\underline{V}}isualizations$ for ${\underline{E}}arth$ ${\underline{R}}esearch$) is a NASA funded Earth Science REASoN project that strives to provide highly accurate, carefully calibrated, long-term climate data records and near-real-time ocean products suitable for the most demanding Earth research applications via easy-to-use display and data access tools. A key element of DISCOVER is the merging of data from the multiple sensors on multiple platforms into geophysical data sets consistent in both time and space. The project is a follow-on to the SSM/I Pathfinder and Passive Microwave ESIP projects which pioneered the simultaneous retrieval of sea surface temperature, surface wind speed, columnar water vapor, cloud liquid water content, and rain rate from SSM/I and TMI observations. The ocean products available through DISCOVER are derived from multi-sensor observations combined into daily products and a consistent multi-decadal climate time series. The DISCOVER team has a strong track record in identifying and removing unexpected sources of systematic error in radiometric measurements, including misspecification of SSM/I pointing geometry, the slightly emissive TMI antenna, and problems with the hot calibration source on AMSR-E. This in-depth experience with inter-calibration is absolutely essential for achieving our objective of merging multi-sensor observations into consistent data sets. Extreme care in satellite inter-calibration and commonality of geophysical algorithms is applied to all sensors. This presentation will introduce the DISCOVER products currently available from the web site, http://www.discover-earth.org and provide examples of the scientific application of both the diurnally corrected optimally interpolated global sea surface temperature product and the 4x-daily global microwave water vapor product.

• 전산구조공학
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• 제10권3호
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• pp.241-250
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• 1997

콘크리트에 발생하는 변형률 국소화는 연화거동에 수반하여 변형이 국부적으로 집중되는 현상으로 이를 유한요소해석 할 수 있는 일관된 알고리즘을 개발하는 것이 본 연구의 목적이다. 변형률 국소화현상이 발생한 콘크리트는 변형률이 집중되는 국소화영역과 그외의 영역인 비국소화영역으로 크게 구분할 수 있으며 국소화영역에서는 연화현상을 포함하는 탄소성거동을 하게 되며 비국소화영역은 손상제하거동을 수반하게 된다. 변형률 국소화현상이 진행중인 콘크리트의 국소화영역을 모델링하기 위하여 열역학적으로 정식화된 전형적인 소성모델에 콘크리트의 극한응력 이후에 비선형 연화로 표현되는 소성거동을 고려할 수 있는 일반화된 Drucker-Prager모델을 도입하였으며 소성이론식의 적분을 위해 return-mapping 알고리즘을 사용하고 일관된 알고리즘을 전개하였다. 또한, 콘크리트의 비국소화영역의 모델링을 위하여 열역학적 자유에너지함수를 수정하여 비선형 탄성 및 손상의 일관된 알고리즘을 전개하였다. 개발된 알고리즘에 의한 유한요소해석을 통해 압축을 받는 콘크리트 부재의 변형률 국소화 현상을 해석하였다.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 1994년도 가을 학술발표회 논문집
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• pp.267-272
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• 1994

This work presents a method of optimum design for reinforced concrete building frames with rectangular cross sections. The optimization techniques used is based on the principle of divided parameters. The design variable parameters are divided into two groups, external and internal, and the optimization is also divided into external and internal procedure. This principle overcomes difficulties arising from the presence of two materials in one element, the property peculiar to reinforced concrete. Several search algorithms are tested to verify their accuracy for the external optimization. Among them pattern search algorithms has been found consistent. This work proposes a new method, modified pattern search, and a number of sample problems prove its accuracy and usefulness. Exhaustive search for all local minima in the design spaces for two sample problems has been carried out to understand the nature of the problem. The number of local minima identified is quite more than expected and it has become understood that the researcher's task in this field is to find a better local minimum if not global. The designs produced by the method preposed have been found better than those from other method, and they are in full accord with ACI Building Code Requirments(ACI 318-89).

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권1호
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• pp.109-134
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• 2018

Collaborative Filtering (CF) is widely used in recommendation field, which can be divided into rating-based CF and learning-to-rank based CF. Although many methods have been proposed based on these two kinds of CF, there still be room for improvement. Firstly, the data sparsity problem still remains a big challenge for CF algorithms. Secondly, the malicious rating given by some illegal users may affect the recommendation accuracy. Existing CF algorithms seldom took both of the two observations into consideration. In this paper, we propose a recommendation method based on listwise learning-to-rank by incorporating users' social information. By taking both ratings and order of items into consideration, the Plackett-Luce model is presented to find more accurate similar users. In order to alleviate the data sparsity problem, the improved matrix factorization model by integrating the influence of similar users is proposed to predict the rating. On the basis of exploring the trust relationship between users according to their social information, a listwise learning-to-rank algorithm is proposed to learn an optimal ranking model, which can output the recommendation list more consistent with the user preference. Comprehensive experiments conducted on two public real-world datasets show that our approach not only achieves high recommendation accuracy in relatively short runtime, but also is able to reduce the impact of malicious ratings.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권7호
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• pp.3414-3434
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• 2016

Classical key generation is complicated to update and key distribution generally requires fixed infrastructures. In order to eliminate these restrictions researchers have focused much attention on physical-layer (PHY-layer) based key generation methods. In this paper, we present a PHY-layer fingerprints based fuzzy key generation scheme, which works to prevent primary user emulation (PUE) attacks and spectrum sensing data falsification (SSDF) attacks, with multi-node collaborative defense strategies. We also propose two algorithms, the EA algorithm and the TA algorithm, to defend against eavesdropping attacks and tampering attacks in mobile cognitive radio networks (CRNs). We give security analyses of these algorithms in both the spatial and temporal domains, and prove the upper bound of the entropy loss in theory. We present a simulation result based on a MIMO-OFDM communication system which shows that the channel response characteristics received by legitimates tend to be consistent and phase characteristics are much more robust for key generation in mobile CRNs. In addition, NIST statistical tests show that the generated key in our proposed approach is secure and reliable.

• 한국염색가공학회지
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• 제20권1호
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• pp.48-56
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• 2008

A real-time inspection system has been developed by combining CCD based image processing algorithm and a standard lighting equipment. The system was tested for defective fabrics showing nozzle contact scratch marks, which are one of the frequently occurring defects. Two algorithms used were compared according to both their processing time and detection rate. First algorithm (algorithm A) was based on morphological image processing such as dilation and opening for effective treatment of defective printing areas while second one (algorithm B) mainly employs well-defined edge detection technique based on canny detector and Zermike moment. It was concluded' that although both algorithms were quite successful, algorithm B showed relatively consistent performance than algorithm A in detecting complex patterns.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2008년도 학술대회 3부
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• pp.224-224
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• 2008

Recent advances in model acquisition, computer-aided design, and simulation technologies have resulted in massive databases of complex geometric data occupying multiple gigabytes and even terabytes. In various graphics/geometric applications, the major performance bottleneck is typically in accessing these massive geometric data due to the high complexity of such massive geometric data sets. However, there has been a consistent lower growth rate of data access speed compared to that of computational processing speed. Moreover, recent multi-core architectures aggravate this phenomenon. Therefore, it is expected that the current architecture improvement does not offer the solution to the problem of dealing with ever growing massive geometric data, especially in the case of using commodity hardware. In this tutorial, I will focus on two orthogonal approaches--multi-resolution and cache-coherent layout techniques--to design scalable graphics/geometric algorithms. First, I will discuss multi-resolution techniques that reduce the amount of data necessary for performing geometric methods within an error bound. Second, I will explain cache-coherent layouts that improve the cache utilization of runtime geometric applications. I have applied these two techniques into rendering, collision detection, and iso-surface extractions and, thereby, have been able to achieve significant performance improvement. I will show live demonstrations of view-dependent rendering and collision detection between massive models consisting of tens of millions of triangles on a laptop during the talk.

• 한국통신학회논문지
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• 제33권8A호
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• pp.805-814
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• 2008

Both EPCglobal Generation-2 (Gen2) for passive RFID systems and Intelleflex for semi-passive RFID systems use probabilistic slotted ALOHA with Q algorithm, which is a kind of dynamic framed slotted ALOHA (DFSA), as the tag anti-collision algorithm. A better tag anti-collision algorithm can reduce collisions so as to increase the efficiency of tag identification. In this paper, we introduce and analyze the estimation methods of the number of slots and tags for DFSA. To increase the efficiency of tag identification, we propose two new tag anti-collision algorithms, which are Chebyshev's inequality (CHI) algorithm and hybrid Q algorithm, and compare them with the conventional Q algorithm and adaptive adjustable framed Q (AAFQ) algorithm, which is mentioned in Part I. The simulation results show that AAFQ performs the best in Gen2 scenario. However, in Intelleflex scenario the proposed hybrid Q algorithm is the best. That is, hybrid Q provides the minimum identification time, shows the more consistent collision ratio, and maximizes throughput and system efficiency in Intelleflex scenario.

• 대한전자공학회논문지TC
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• 제42권1호`
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• pp.9-15
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• 2005

현재 위치결정기술에 주로 사용되고 있는 매체는 RF이다. 그러나 RF를 사용한 위치결정기술은 GPS나 실외의 LOS 상황에서 주로 이용되고 있다. 왜냐하면 실내에서는 다중경로 해상도가 좋지 않아 정확한 위치 값을 계산해 내기가 힘들기 때문이다. UWB는 다중경로 해상도가 높고 장애물 투과율이 좋은 실내 측위에 적합한 매체이며 현재 UWB 통신 및 위치측정에 사용하고자 하는 표준화가 IEEE 802.15 위원회에서 진행 중이다. 그러나 UWB를 이용한 실내 측위 알고리즘의 연구나 개발은 아직 미비하다. 본 논문에서는 실내 측위에서 UWB의 장점을 극대화 할 수 있는 TDOA 알고리즘 중 대표적인 두 가지 알고리즘을 분석하고 이를 UWB 실내 측위에 이용할 때 얼마나 정확한 위치를 추정할 수 있는지를 시뮬레이션을 통해 분석한다. 또한 UWB 채널모델을 분석하고 오차요소를 시뮬레이션에 적용하여 그 결과를 비교분석하며, 시뮬레이션 결과를 바탕으로 실내 측위를 위한 UWB의 가능성 및 적합한 알고리즘을 제안한다.

• 한국통신학회논문지
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• 제37권7C호
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• pp.527-537
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• 2012

본 논문은 다수의 자율무인차량 (Autonomous Unmanned Ground Vehicle) 들이 서로 협력하여 그룹 이동하는 타겟을 추적하고 지속적인 커버리지를 제공하는 무인차량 기반의 추적 네트워크 (UVTN: Unmanned Vehicle based Tracking Network) 구조와 알고리즘을 제안한다. UVTN은 움직이는 사람 또는 사물을 추적 감시하거나 이동하는 구조팀 또는 병사들에게 지속적인 네트워크 Access를 제공해 주기 위하여 커버리지를 최대화 하는 것을 목적으로 한다. 이러한 목적을 달성하기 위하여 UVTN은 주기적인 네트워크 확장과 수축 과정을 통한 무인차량 노드 재배치 및 네트워크 토폴로지 최적화를 수행한다. 또한 본 논문에서는 평균 커버리지비율과 이동거리 관점에서의 성능향상을 위한 개선 알고리즘들이 제안된다. 시뮬레이션을 통해 UVTN과 개선 알고리즘들이 그룹이 동성을 갖는 대상을 효율적으로 추적하여 지속적인 커버리지를 제공할 수 있음을 보인다.