• 제목/요약/키워드: Challenge Model

검색결과 868건 처리시간 0.027초

Generic Multidimensional Model of Complex Data: Design and Implementation

  • Khrouf, Kais;Turki, Hela
    • International Journal of Computer Science & Network Security
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    • 제21권12spc호
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    • pp.643-647
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    • 2021
  • The use of data analysis on large volumes of data constitutes a challenge for deducting knowledge and new information. Data can be heterogeneous and complex: Semi-structured data (Example: XML), Data from social networks (Example: Tweets) and Factual data (Example: Spreading of Covid-19). In this paper, we propose a generic multidimensional model in order to analyze complex data, according to several dimensions.

상시진동 계측자료를 이용한 Nanjing TV탑의 강성계수 추정 (Identification of Stiffness Parameters of Nanjing TV Tower Using Ambient Vibration Records)

  • Kim Jae Min;Feng. M. Q.
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 1998년도 봄 학술발표회 논문집
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    • pp.291-300
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    • 1998
  • This paper demonstrates how ambient vibration measurements at a limited number of locations can be effectively utilized to estimate parameters of a finite element model of a large-scale structural system involving a large number of elements. System identification using ambient vibration measurements presents a challenge requiring the use of special identification techniques, which ran deal with very small magnitudes of ambient vibration contaminated by noise without the knowledge of input farces. In the present study, the modal parameters such as natural frequencies, damping ratios, and mode shapes of the structural system were estimated by means of appropriate system identification techniques including the random decrement method. Moreover, estimation of parameters such as the stiffness matrix of the finite element model from the system response measured by a limited number of sensors is another challenge. In this study, the system stiffness matrix was estimated by using the quadratic optimization involving the computed and measured modal strain energy of the system, with the aid of a sensitivity relationship between each element stiffness and the modal parameters established by the second order inverse modal perturbation theory. The finite element models thus identified represent the actual structural system very well, as their calculated dynamic characteristics satisfactorily matched the observed ones from the ambient vibration test performed on a large-scale structural system subjected primarily to ambient wind excitations. The dynamic models identified by this study will be used for design of an active mass damper system to be installed on this structure fer suppressing its wind vibration.

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The Route of Leishmania tropica Infection Determines Disease Outcome and Protection against Leishmania major in BALB/c Mice

  • Mahmoudzadeh-Niknam, Hamid;Khalili, Ghader;Abrishami, Firoozeh;Najafy, Ali;Khaze, Vahid
    • Parasites, Hosts and Diseases
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    • 제51권1호
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    • pp.69-74
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    • 2013
  • Leishmania tropica is one of the causative agents of leishmaniasis in humans. Routes of infection have been reported to be an important variable for some species of Leishmania parasites. The role of this variable is not clear for L. tropica infection. The aim of this study was to explore the effects of route of L. tropica infection on the disease outcome and immunologic parameters in BALB/c mice. Two routes were used; subcutaneous in the footpad and intradermal in the ear. Mice were challenged by Leishmani major, after establishment of the L. tropica infection, to evaluate the level of protective immunity. Immune responses were assayed at week 1 and week 4 after challenge. The subcutaneous route in the footpad in comparison to the intradermal route in the ear induced significantly more protective immunity against L. major challenge, including higher delayed-type hypersensitivity responses, more rapid lesion resolution, lower parasite loads, and lower levels of IL-10. Our data showed that the route of infection in BALB/c model of L. tropica infection is an important variable and should be considered in developing an appropriate experimental model for L. tropica infections.

인체에서 식품의 기능성 확인을 위한 최신의 분석 방법 (New paradigm for human intervention study in functional food development)

  • 김지연;김민서;정세원;권오란
    • 식품과학과 산업
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    • 제51권1호
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    • pp.8-15
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    • 2018
  • Functional food research has been struggling to demonstrate their beneficial effects in human, however, the physiological changes in humans who are in the target for functional food are very subtle and long term. In addition, it is difficult to obtain significant beneficial effect because of the necessity of using relatively healthy subjects. Relatively healthy subjects are homeostatic, and most of the biomarkers maintain a certain level under the "normal" or "resting" state. Moreover, due to wide inter-individual variation, it is difficult to detect significant changes. To address this problem, research has been actively conducted to identify the efficacy of natural products using 'omics' and 'bioinformatics' technology. In this review, we would like to introduce the human intervention studies applied homeostatic challenge model.

망막 영상 분석을 위한 두 갈래 분류기 (Two-Branch Classifier for Retinal Imaging Analysis)

  • 오영택;박현진
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2021년도 춘계학술대회
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    • pp.614-616
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    • 2021
  • 세계는 안구 질병 치료, 시력 회복 서비스, 훈련된 안과 전문의의 부족 등 안과 측면에서 어려움에 직면해 있다. 안구 병리를 조기에 발견하고 진단하면 시각 장애를 예방할 수 있다. 하지만 기존의 망막 영상 공개 데이터 세트는 임상에서 발견되는 다양한 질병으로 구성되어 있지 않기 때문에 다양한 안구 질환을 분류하는 방법을 개발하기가 어렵다. 본 연구는 2021 ISBI challenge에서 공개된 데이터 세트인 Retinal Fundus Multi-disease Image Dataset (RFMiD) 을 이용하여 안구 질환을 분류하는 방법을 제안한다. 본 연구의 목표는 망막 이미지를 정상, 비정상 범주로 선별하기 위한 강력하고 일반화 가능한 모델을 개발하는 것이다. 제안된 모델의 성능은 수신자 조작 특성 곡선 아래 면적 점수로 비공개 테스트 데이터 세트에 대해 0.9782의 값을 보여준다.

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거리 기반 적응형 임계값을 활용한 강건한 3차원 물체 탐지 (Robust 3D Object Detection through Distance based Adaptive Thresholding)

  • 이은호;정민우;김종호;이경수;김아영
    • 로봇학회논문지
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    • 제19권1호
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    • pp.106-116
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    • 2024
  • Ensuring robust 3D object detection is a core challenge for autonomous driving systems operating in urban environments. To tackle this issue, various 3D representation, including point cloud, voxels, and pillars, have been widely adopted, making use of LiDAR, Camera, and Radar sensors. These representations improved 3D object detection performance, but real-world urban scenarios with unexpected situations can still lead to numerous false positives, posing a challenge for robust 3D models. This paper presents a post-processing algorithm that dynamically adjusts object detection thresholds based on the distance from the ego-vehicle. While conventional perception algorithms typically employ a single threshold in post-processing, 3D models perform well in detecting nearby objects but may exhibit suboptimal performance for distant ones. The proposed algorithm tackles this issue by employing adaptive thresholds based on the distance from the ego-vehicle, minimizing false negatives and reducing false positives in the 3D model. The results show performance enhancements in the 3D model across a range of scenarios, encompassing not only typical urban road conditions but also scenarios involving adverse weather conditions.

Time Limits in Challenging a Tribunal's Jurisdiction

  • Chan, Leng-Sun;Han, Ye-Won
    • 한국중재학회지:중재연구
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    • 제23권3호
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    • pp.81-99
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    • 2013
  • One of the most defining characteristics of arbitration is that an arbitral tribunal's jurisdiction is established by parties' mutual agreement. If a party to the arbitral proceedings believes that a tribunal constituted lacks jurisdiction to conduct the arbitral proceedings, it may challenge the jurisdiction of the tribunal in different ways. Although the concept of kompetenz-kompetenz and the grounds to challenge the Tribunal's jurisdiction are readily accepted in the arbitration community, what parties often fail to observe is the time limit imposed by the relevant laws in bringing such objections. This article aims to examine several main ways of challenging the tribunal's jurisdiction and the applicable time limits in each scenario. The article will then focus on the consequences of a party's failure to adhere to the strict time limits and its effect at the post-award stage. These issues will be considered in the light of case law from different Model law jurisdictions with particular illustrations from the arbitration law of Singapore.

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DRC 휴보의 4족 보행 제어 (Quadruped Walking Control of DRC-HUBO)

  • 김정엽
    • 한국생산제조학회지
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    • 제24권5호
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    • pp.548-552
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    • 2015
  • In this paper, we describe the quadruped walking-control algorithm of the complete full-size humanoid DARPA Robotics Challenge-HUBO (DRC-HUBO) robot. Although DRC-HUBO is a biped robot, we require a quadruped walking function using two legs and two arms to overcome uneven terrains in the DRC. We design a wave-type quadruped walking pattern as a feedforward control using several walking parameters, and we design zero moment point (ZMP) controllers to maintain stable walking using an inverted pendulum model and an observed-state feedback control scheme. In particular, we propose a switching algorithm for ZMP controllers using supporting value and weighting factors in order to maintain the ZMP control performance during foot switching. Finally, we verify the proposed algorithm by performing quadruped walking experiments using DRC-HUBO.

TETRA 인증 프로토콜 분석 (The Analysis of the TETRA Authentication Protocol)

  • 박용석;안재환;정창호;안정철
    • 한국정보통신학회:학술대회논문집
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    • 한국해양정보통신학회 2006년도 춘계종합학술대회
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    • pp.187-190
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    • 2006
  • TETRA 시스템에서는 인가된 단말기만이 망에 접속하도록 하기 위해 단말기 인증 서비스를 제공한다. 단말기 인증이란 Challenge-response 프로토콜에 의해 단말기와 인증센터에 사전에 공유된 인증키가 일치하는지를 확인하는 과정이다. 본 논문에서는 TETRA 인증 시스템에서 인증키 생성/분배/주입 모델을 분석하고, 인증키의 노출로 인한 복제단말기의 위협을 분석한다.

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Pattern mining for large distributed dataset: A parallel approach (PMLDD)

  • Pal, Amrit;Kumar, Manish
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권11호
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    • pp.5287-5303
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    • 2018
  • Handling vast amount of data found in large transactional datasets is an obvious challenge for the conventional data mining algorithms. Addressing this challenge, our paper proposes a parallel approach for proper decomposition of mining problem into sub-problems in order to find frequent patterns from these datasets. The proposed, Pattern Mining for Large Distributed Dataset (PMLDD) approach, ensures minimum dependencies as well as minimum communications among sub-problems. It establishes a linear aggregation of the intermediate results so that it can be adapted to large-scale programming models like MapReduce. In this context, an algorithmic structure for MapReduce programming model is presented. PMLDD guarantees an efficient load balancing among the sub-problems by a specific selection criterion. Further, it optimizes the number of required iterations over the dataset for mining frequent patterns as compared to the existing approaches. Finally, we believe that our approach is scalable enough to handle larger datasets in terms of performance evaluation, and the result analysis justifies all these mentioned concerns.