• Title/Summary/Keyword: 38-key model

Search Result 122, Processing Time 0.023 seconds

Designing and Evaluating Digital Video Storyboard Surrogates (디지털 영상 초록의 설계와 평가에 관한 연구)

  • Kim, Hyun-Hee;Kim, Yong-Ho;Ko, Su-Hyun
    • Journal of Korean Library and Information Science Society
    • /
    • v.38 no.4
    • /
    • pp.463-480
    • /
    • 2007
  • This study examines the design and utilization of video storyboard surrogates in the digital video libraries. To do this, first we constructed the arrangement model of key-frames for storyboard based on the FRBR model, image communication and PRECIS Indexing theories and evaluated the model using 6 sample videos and 26 participants. The study results show that the video storyboard surrogates based on the arrangement model has a higher accuracy value in terms of summary extraction than that of the sequential video storyboard. Moreover, watching both types of video storyboard one after another, especially browsing the sequential video storyboard first and then the arrangement model-based one, produces a remarkable increase in accuracy value of summary extraction. The study proposes two methods of utilizing the video storyboard surrogates in the digital video libraries: Designing a video browsing interface where users can use the sequential storyboard as a default and then the arrangement model-based one for re-watching; and utilizing the arrangement model-based storyboard as structured match sources of image-based queries.

  • PDF

CHAOTIC THRESHOLD ANALYSIS OF NONLINEAR VEHICLE SUSPENSION BY USING A NUMERICAL INTEGRAL METHOD

  • Zhuang, D.;Yu, F.;Lin, Y.
    • International Journal of Automotive Technology
    • /
    • v.8 no.1
    • /
    • pp.33-38
    • /
    • 2007
  • Since it is difficult to analytically express the Melnikov function when a dynamic system possesses multiple saddle fixed points with homoclinic and/or heteroclinic orbits, this paper investigates a vehicle model with nonlinear suspension spring and hysteretic damping element, which exhibits multiple heteroclinic orbits in the unperturbed system. First, an algorithm for Melnikov integrals is developed based on the Melnikov method. And then the amplitude threshold of road excitation at the onset of chaos is determined. By numerical simulation, the existence of chaos in the present system is verified via time history curves, phase portrait plots and $Poincar{\acute{e}}$ maps. Finally, in order to further identify the chaotic motion of the nonlinear system, the maximal Lyapunov exponent is also adopted. The results indicate that the numerical method of estimating chaotic threshold is an effective one to complicated vehicle systems.

A Preliminary Trophic Flow Model for Gwangyang Bay, Korea (광양만 예비 영양류 모형)

  • Kang, Yun-Ho
    • Korean Journal of Fisheries and Aquatic Sciences
    • /
    • v.38 no.3
    • /
    • pp.184-195
    • /
    • 2005
  • A preliminary quantitative model of the trophic structure in Gwangyang bay, Korea was obtained using ECOPATH and data from relevant studies to date in the region. The model integrates and analyzes biomass, food spectrum, trophic interactions and the key trophic pathways of the system. The bay model comprises 9 groups of benthic primary producer, phytoplankton, zooplankton, benthos, bivalve, pelagic fish, demersal fish and piscivorous fish. The total system throughput was estimated at $2.4\;kgWW/m^2/yr$, including a consumption of $41\%$, exports of $9\%$, respiratory flows of $24\%$ and flows into detritus of $26\%$. All of which originate from primary producers measured at $52\%$ and detritus of $48\%$. The total biomass was seen to be high compared to the levels of Somme, Delaware, Chesapeake Bays and Seine Estuary. This seems to be possibly due to artificial bivalve aquaculture and overestimation of benthos and benthic primary producer groups. The deviation can be calibrated by neglecting aquaculture and decreasing the habitat area for the groups. The trophic network of the bay shows a low level of recycling and organization as indicated by Finn's cycling index $3.3\%$, Ascendancy $3.1\;kgC/m^2/yr$ bits, Capacity $5.1\;kgC/m^2/yr$ bits and Redundancy $2.2\;kgC/m^2/yr$ bits. A high relative ascendancy of $62\%$ and a low internal relative ascendancy of $18\%$ indicate the system is not fully organized and stable towards disturbances, depending upon external connections. Although the model should be continuously provided with field data and calibrated further in depth, this study is the first trophic model applied to the region. The model can be a useful tool to understand the ecosystem in a quantitative manner.

An analysis on enhancement of customer satisfaction for conversion farm with $2^{nd}$ and $3^{rd}$ industry (2.3차 산업 융합 농장의 고객 만족 요인 분석)

  • Jang, Hyun-Dong;Kim, Soung-Hun
    • Korean Journal of Agricultural Science
    • /
    • v.38 no.4
    • /
    • pp.769-774
    • /
    • 2011
  • This study aimed at finding the factors impacting customer satisfaction (CS) for conversion farm with $2^{nd}$ and $3^{rd}$ industry, because the most important thing in the conversion farm is enhancing customer satisfaction. The data on CS from 173 pumpkin farm's customers by on-line survey were gathered. The analysis using structural equation model with Amos was carried out. Product, service and purchasing were determined as 3 factors impacting to CS. The result showed that purchasing is the biggiest contributor to CS. It means the customers using on-ine market are very sensitive to farm's brand and logistics. It is also found that conversion with processing and farm experience activity is definitely affecting to building customer's trust. In conclusion, making efforts on enhancing CS in conversion farm is the key to success.

First-Order Logic Generation and Weight Learning Method in Markov Logic Network Using Association Analysis (연관분석을 이용한 마코프 논리네트워크의 1차 논리 공식 생성과 가중치 학습방법)

  • Ahn, Gil-Seung;Hur, Sun
    • Journal of Korean Society of Industrial and Systems Engineering
    • /
    • v.38 no.1
    • /
    • pp.74-82
    • /
    • 2015
  • Two key challenges in statistical relational learning are uncertainty and complexity. Standard frameworks for handling uncertainty are probability and first-order logic respectively. A Markov logic network (MLN) is a first-order knowledge base with weights attached to each formula and is suitable for classification of dataset which have variables correlated with each other. But we need domain knowledge to construct first-order logics and a computational complexity problem arises when calculating weights of first-order logics. To overcome these problems we suggest a method to generate first-order logics and learn weights using association analysis in this study.

Location Selection of Distribution Centers by Using Grey Relational Analysis (GRA를 이용한 물류센터 입지선정문제)

  • Woo, Taehee;Bach, Seung
    • Journal of Korean Society of Industrial and Systems Engineering
    • /
    • v.38 no.2
    • /
    • pp.82-90
    • /
    • 2015
  • Location selection of distribution centers is a crucial task for logistics operators and key decision makers of an organization. This is a multi-criteria decision making (MCDM) process which includes both quantitative and qualitative criteria. In order to propose an optimized location selection model, this research suggests a hierarchical group of evaluation criteria : 5 major criteria with 15 sub-criteria. The MCDM approach presented in this research, by integrating Grey Relational Analysis (GRA) with Analytic Hierarchy Process (AHP), tends to rectify the overall quality and uncertainty of the values of evaluation criteria. An example of a location selection case in Korea is illustrated in this study to show the effectiveness of this method.

Modeling of RGB mass-loss to predict the HB mass distribution in globular clusters

  • Pasquato, Mario
    • The Bulletin of The Korean Astronomical Society
    • /
    • v.38 no.2
    • /
    • pp.79.2-79.2
    • /
    • 2013
  • The distributions of Horizontal Branch (HB) star color, temperature, and mass encode a great deal of information on the stellar evolutionary and (possibly) dynamical processes taking place in Globular Clusters (GCs). An accurate physical modeling of the Red Giant Branch (RGB) mass-loss process is key to solving the so-called second parameter problem. In my poster I will present the most recent advancements of an analytical model for mass-loss along the RGB. The model predicts the HB mass distribution with remarkable accuracy over a sample of 4 GCs. These results were submitted as a paper to ApJ (Pasquato et al. 2013, ApJ submitted), but here I expand on them presenting refinements to the model and a comparison with HB masses obtained from Galex ultraviolet observations.

  • PDF

Hybrid Approach-Based Sparse Gaussian Kernel Model for Vehicle State Determination during Outage-Free and Complete-Outage GPS Periods

  • Havyarimana, Vincent;Xiao, Zhu;Wang, Dong
    • ETRI Journal
    • /
    • v.38 no.3
    • /
    • pp.579-588
    • /
    • 2016
  • To improve the ability to determine a vehicle's movement information even in a challenging environment, a hybrid approach called non-Gaussian square rootunscented particle filtering (nGSR-UPF) is presented. This approach combines a square root-unscented Kalman filter (SR-UKF) and a particle filter (PF) to determinate the vehicle state where measurement noises are taken as a finite Gaussian kernel mixture and are approximated using a sparse Gaussian kernel density estimation method. During an outage-free GPS period, the updated mean and covariance, computed using SR-UKF, are estimated based on a GPS observation update. During a complete GPS outage, nGSR-UPF operates in prediction mode. Indeed, because the inertial sensors used suffer from a large drift in this case, SR-UKF-based importance density is then responsible for shifting the weighted particles toward the high-likelihood regions to improve the accuracy of the vehicle state. The proposed method is compared with some existing estimation methods and the experiment results prove that nGSR-UPF is the most accurate during both outage-free and complete-outage GPS periods.

Lack of Association Between the Matrix Metalloproteinase-2 -1306C>T Polymorphism and Breast Cancer Susceptibility: a Meta-analysis

  • Yang, Lu;Li, Ning;Wang, Siyu;Kong, Yanan;Tang, Hailin;Xie, Xinhua;Xie, Xiaoming
    • Asian Pacific Journal of Cancer Prevention
    • /
    • v.15 no.12
    • /
    • pp.4823-4827
    • /
    • 2014
  • Background: Since inconsistent results have been reported regarding the relation between the matrix metalloproteinase-2 (MMP-2) -1306C>T polymorphism and susceptibility for breast cancer, we performed a meta-analysis to investigate the issue. Materials and Methods: An internet search of PubMed and EMBASE was performed to identify eligible studies. Pooled odds ratios (ORs) with their corresponding confidence intervals (CIs) were calculated to evaluate any association between MMP-2 -1306C>T polymorphism and breast cancer susceptibility. Results: Nine case-control studies were included in the meta-analysis, involving 9,858 cases and 10,871 controls. Overall, there was no evidence of any association between the MMP-2 -1306C>T polymorphism and breast cancer susceptibility in different genetic models (T-allele vs C-allele: OR=0.95, 95%CI, 0.82-1.10, p=0.49; TT vs CC: OR=1.03, 95%CI, 0.90-1.19, p=0.66; TT+TC vs CC: OR=0.93, 95%CI, 0.78-1.10, p=0.38; TT vs TC+CC: OR=1.02, 95%CI, 0.89-1.17, p=0.77). In the subgroup analysis by ethnicity, CC was associated with a significant increase in breast susceptibility among Latin-Americans in the dominant model (OR=0.61, 95%CI, 0.40-0.93, p=0.02), but the association disappeared in other models. No significant association was observed among Europeans, East Asians and others in different genetic models. In the subgroup analysis by their source of controls, no significant association between MMP-2 -1306C>T polymorphism and breast cancer susceptibility was noted among population-based studies and hospital-based studies in different genetic models. Conclusions: The results of this meta-analysis suggest that MMP-2 -1306C>T polymorphism is not associated with breast cancer susceptibility, although the association among Latin-Americans in the dominant model was significant.

Inhibition of Citrate Synthase Thermal Aggregation In Vitro by Recombinant Small Heat Shock Proteins

  • Gong, Weina;Yue, Ming;Xie, Bingyan;Wan, Fanghao;Guo, Jianying
    • Journal of Microbiology and Biotechnology
    • /
    • v.19 no.12
    • /
    • pp.1628-1634
    • /
    • 2009
  • Small heat shock proteins (sHSPs) function as molecular chaperones that protect cells against environmental stresses. In the present study, the genes of hsp17.6 and hsp17.7, cytosolic class I sHSPs, were cloned from a tropical plant, Ageratina adenophorum. Their C-terminal domains were highly conserved with those of sHSPs from other plants, indicating the importance of the C-terminal domains for the structure and activity of sHSPs. The recombinant HSP17.6 and HSP17.7 were applied to determine their chaperone function. In vitro, HSP17.6 and HSP17.7 actively participated in the refolding of the model substrate citrate synthase (CS) and effectively prevented the thermal aggregation of CS at $45^{\circ}C$ and the irreversible inactivation of CS at $38^{\circ}C$ at stoichiometric levels. The prior presence of HSP17.7 was assumed to suppress the thermal aggregation of the model substrate CS. Therefore, this report confirms the chaperone activity of HSP17.6 and HSP17.7 and their potential as a protectant for active proteins.