• 제목/요약/키워드: Behavior pattern model

검색결과 427건 처리시간 0.022초

SFRC구조물의 휨거동에 관한 해석적 연구 (Analytical Study of Flexural Behavior on Steel Fiber Reinforced Concrete Structure)

  • 서성탁
    • 한국산업융합학회 논문집
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    • 제11권1호
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    • pp.35-40
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    • 2008
  • Various characters of the concrete are greatly improved as the effect of the steel fiber. As the improvement effect of the steel fiber, the increment in flexural strength, shear strength, toughness, and impact strength are remarkable, and tenacious concrete is obtained. This paper presents model which can predict mechanical behavior of the structure according to aspect ratio and volume fraction of steel fiber. Experiments on compressive strength, elastic modulus and tensile strength were performed with self-made cylindrical specimens of variable aspect ratios. This paper presents an analytical study on the behavior of a beam specimen with steel fiber reinforced concrete(SFRC). The effect of the SFRC on the crack pattern, failure mode and the flexural behavior of the structure were investigated. The analysis model based on the nonlinear layered finite element method was successfully able to find the necessary amount of steel fibers, tensile steels and beam section which can best approximate flexural strength and ductility of a given conventionally reinforced concrete beam.

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Conjoint Choice Model을 이용한 주제공원 이용자들의 선택행동 연구 (A Study on the Theme Park Users's Choice behavior: Application of Conjoint Choice Model)

  • 홍성권
    • 한국조경학회지
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    • 제28권1호
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    • pp.19-28
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    • 2000
  • The purposes of this study are two folds: a) to introduce conjoint choice model to research the choice behavior of theme park users, and b) to suggest the strategies to strengthen the competitiveness of theme parks. The major four theme parks in Seoul metropolitan areas were selected as study areas. A leading polling agency was employed to select 432 respondents by probability sampling and to conduct face-to-face interview. Both alternative generating and choice set generating fractional factorial design were conducted simultaneously to meet the necessary and sufficient conditions for calibration of the conjoint choice model. Dummy coding was used to represent the attribute levels, and the alternative-specific model was calibrated. The goodness-of-fit of the model was quite satisfactory($\rho$$^2$=0.47950), and most parameters values had to expected sign and magnitude. Car was preferred transport mode to shuttle bus for visiting theme parks ; however the most ideal attribute levels only were estimated significantly. Most attribute levels of shuttle bus were estimated significantly except the Dream Land, which is the least attractive park among study areas. Simulation results showed that the shuttle bus was a mode worth providing to switch the current car dominant visiting pattern of theme parks, which will be one the effective strategies to attract more patrons, especially for potential users adjacent to parks. Several ideals were suggested for future researches, in terms of utilization of more general utility function and new base alternative, and inclusion of more salient attributes such as constraints in the model.

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Real-world multimodal lifelog dataset for human behavior study

  • Chung, Seungeun;Jeong, Chi Yoon;Lim, Jeong Mook;Lim, Jiyoun;Noh, Kyoung Ju;Kim, Gague;Jeong, Hyuntae
    • ETRI Journal
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    • 제44권3호
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    • pp.426-437
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    • 2022
  • To understand the multilateral characteristics of human behavior and physiological markers related to physical, emotional, and environmental states, extensive lifelog data collection in a real-world environment is essential. Here, we propose a data collection method using multimodal mobile sensing and present a long-term dataset from 22 subjects and 616 days of experimental sessions. The dataset contains over 10 000 hours of data, including physiological, data such as photoplethysmography, electrodermal activity, and skin temperature in addition to the multivariate behavioral data. Furthermore, it consists of 10 372 user labels with emotional states and 590 days of sleep quality data. To demonstrate feasibility, human activity recognition was applied on the sensor data using a convolutional neural network-based deep learning model with 92.78% recognition accuracy. From the activity recognition result, we extracted the daily behavior pattern and discovered five representative models by applying spectral clustering. This demonstrates that the dataset contributed toward understanding human behavior using multimodal data accumulated throughout daily lives under natural conditions.

A cohesive model for concrete mesostructure considering friction effect between cracks

  • Huang, Yi-qun;Hu, Shao-wei
    • Computers and Concrete
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    • 제24권1호
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    • pp.51-61
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    • 2019
  • Compressive ability is one of the most important mechanical properties of concrete material. The compressive failure process of concrete is pretty complex with internal tension, shear damage and friction between cracks. To simulate the complex fracture process of concrete at meso level, methodology for meso-structural analysis of concrete specimens is developed; the zero thickness cohesive elements are pre-inserted to simulate the crack initiation and propagation; the constitutive applied in cohesive element is established to describe the mechanism of crack separation, closure and friction behavior between the fracture surfaces. A series of simulations were carried out based on the model proposed in this paper. The results reproduced the main fracture and mechanical feature of concrete under compression condition. The effect of key material parameters, structure size, and aggregate content on the concrete fracture pattern and loading carrying capacities was investigated. It is found that the inner friction coefficient has a significant influence on the compression character of concrete, the compression strength raises linearly with the increase of the inner friction coefficient, and the fracture pattern is sensitive to the mesostructure of concrete.

Gene Expression Pattern Analysis via Latent Variable Models Coupled with Topographic Clustering

  • Chang, Jeong-Ho;Chi, Sung Wook;Zhang, Byoung Tak
    • Genomics & Informatics
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    • 제1권1호
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    • pp.32-39
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    • 2003
  • We present a latent variable model-based approach to the analysis of gene expression patterns, coupled with topographic clustering. Aspect model, a latent variable model for dyadic data, is applied to extract latent patterns underlying complex variations of gene expression levels. Then a topographic clustering is performed to find coherent groups of genes, based on the extracted latent patterns as well as individual gene expression behaviors. Applied to cell cycle­regulated genes of the yeast Saccharomyces cerevisiae, the proposed method could discover biologically meaningful patterns related with characteristic expression behavior in particular cell cycle phases. In addition, the display of the variation in the composition of these latent patterns on the cluster map provided more facilitated interpretation of the resulting cluster structure. From this, we argue that latent variable models, coupled with topographic clustering, are a promising tool for explorative analysis of gene expression data.

교통카드 자료를 활용한 지하철 혼잡도 개선 연구 : Early Bird 정책대안을 중심으로 (A Study on Improving Subway Crowding Based on Smart Card Data : a Focus on Early Bird Policy Alternative)

  • 이상준;신성일
    • 한국IT서비스학회지
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    • 제19권2호
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    • pp.125-138
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    • 2020
  • Currently, subway crowding is estimated by observing a specific point at specific hours once or twice every 1 or 2 years. Given the extensive subway network in Seoul Metropolitan Area covering 588 stations, 11 lines and 80 transfer stations as of 2017, implementing crowding mitigation policy may have its limitations due to data uncertainty. A proposal has recently been made to effectively use smart card data, which generates big data on the overall subway traffic related to an estimated 8 million passengers per day. To mitigate subway crowding, this study proposes two viable options based on data related to smart card used in Seoul Metropolitan Area. One is to create a subway passenger pattern model to accurately estimate subway crowding, while the other is to prove effectiveness of early bird policy to distribute subway demand that is concentrated at certain stations and certain time. A subway passenger pattern model was created to estimate the passenger routes based on subway terminal ID at the entrance and exit and data by hours. To that end, we propose assigning passengers at the routes similar to the shortest routes based on an assumption that passengers choose the fastest routes. In the model, passenger flow is simulated every minute, and subway crowding level by station and line at every hour is analyzed while station usage pattern is identified by depending on passenger paths. For early bird policy, highly crowded stations will be categorized based on congestion level extracted from subway passenger pattern model and viability of a policy which transfers certain traveling demands to early commuting hours in those stations will be reviewed. In particular, review will be conducted on the impact of policy implemented at certain stations on other stations and lines from subway network as a whole. Lastly, we proposed that smart card based subway passenger pattern model established through this study used in decision making process to ensure effective implementation of public transport policy.

Evolution of pullout behavior of geocell embedded in sandy soil

  • Yang Zhao;Zheng Lu;Jie Liu;Jingbo Zhang;Chuxuan Tang;Hailin Yao
    • Geomechanics and Engineering
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    • 제38권3호
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    • pp.275-284
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    • 2024
  • This paper aims to explore the evolution of the pullout behavior of geocell reinforcement insights from three-dimensional numerical studies. Initially, a developed model was validated with the model test results. The horizontal displacement of geocells and infill sand and the passive resistance transmission in the geocell layer were analyzed deeply to explore the evolution of geocell pullout behavior. The results reveal that the pullout behavior of geocell reinforcement is the pattern of progressive deformation. The geocell pockets are gradually mobilized to resist the pullout force. The vertical walls provide passive pressure, which is the main contributor to the pullout force. Hence, even if the frontal displacement (FD) is up to 90m mm, only half of the pockets are mobilized. Furthermore, the parametric studies, orthogonal analysis, and the building of the predicted model were also carried out to quantitative the geocell pullout behavior. The weights of influencing factors were ranked. Ones can calculate the pullout force accurately by inputting the aspect ratio, geocell modulus, embedded length, frontal displacement, and normal stress.

게임플레이 가능성을 위한 감정요소 분석 프레임워크 (Analytic Framework of Emotion Factors for Gameplay Capability)

  • 김미진;김재호
    • 한국콘텐츠학회논문지
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    • 제10권6호
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    • pp.188-196
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    • 2010
  • 본 논문은 MMORPG 게임플레이 경험에서 사용자의 행동패턴(Behavior Pattern)과 감정요소(Emotion Factors)간의 관계를 규명하여 사용자의 플레이 가능성(Play Capability)을 실증적으로 설계하기 위한 방법에 관한 것이다. 게임플레이 프로세스와 감정요소 도출을 모델링하기 위해 인지심리학적 측면(Process of Ruled-Based Systems on Cognitive Science Approach)에서 선행를 고찰하였다. 퀘스트(Quest)기반의 RPG게임내 특정상황에서 유저의 인지적 감정상태를 도출하기 위해 게임플레이 과정에서 생성되는 유저의 감정반응을 게임 설계과정에서 적용할 수 있는 프로세스를 정립하였다. 이러한 방법은 게임플레이 설계시 유저의 주류행동에 대한 통제 뿐만 아니라 비주류행동에 대한 감정상태의 실시간적 대응이 가능할 것으로 본다. 따라서 본 논문의 결과는 게임플레이 설계시 게임플레이 가능성을 향상시키기 위한 감정 분석 구조(Analytic Framework)를 제시함에 있어 의의를 갖는다.

핵연료 파손 예측을 위한 경험적 자료와 결정론적 모델의 접합 방법 (A Study on the Method of Combining Empirical Data and Deterministic Model for Fuel Failure Prediction)

  • Cho, Byeong-Ho;Yoon, Young-Ku;Chang, Soon-Heung
    • Nuclear Engineering and Technology
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    • 제19권4호
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    • pp.233-241
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    • 1987
  • 본 연구는 제한된 수의 핵연료의 경험적 파손자료로부터 핵연료 파손 확률을 현실적으로 예측하기 위해 결정론적 모델로부터의 파손화률 예측치와 실제 경험적 자료로부터의 파손 확률 예측치를 접합하는 방법을 시도하였다. 이 접합 방법에 의한 파손 화률 예측치는 결정론적 모델 또는 경험적 파손 자료로부터의 독립적인 예측치보다 신뢰도가 높다. 본 연구에서는 핵연료 성능 예측코드인 SPEAR의 방법론을 응용한 핵연료 파손 패턴의 체계적 발견법 (hierarchical pattern discovery)이 접합 모델에서의 결정론적 모델로부터의 예측치에 대한 가중치와 패턴 경계를 체계적으로 찾기 위해 고안되었다. 이 연구에서 개발된 접합 방법을 PROFIT모델과 경험적 파손자료를 이용하여 CANDU형 핵연료 재장전중 출력 상승에 의해 수반되는 핵연료파손 예측에 적응시켜 보았다.

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삼각형 네트워크를 갖는 단층 및 복층 구형 스페이스 프레임 구조물의 좌굴특성에 관한 비교 연구 (A Comparative Study on the Buckling Characteristics of Single-layer and Double-layer Spherical Space Frame Structure with Triangular Network Pattern)

  • 이호상;정환목;권영환
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 1998년도 가을 학술발표회 논문집
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    • pp.251-257
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    • 1998
  • Spherical space frame structure with triangular network pattern, which has the various characteristics for the mechanic property, a funtional property, an aesthetic property and so on, has often been used as one of the most efficient space structures. It is expected that this type will be used widely in large-span structural roofs. But because this structure is made of network by combination of line elements there me many nodes therefore, the structure behavior is very complicated and there can be an overall collapse of structure by buckling phenomenon if the external force reaches a limitation. This kind of buckling is due to geometric shape, network pattern, the number of layer and so on, of structure. Therefore spherical space frame with triangle network pattern have attracted many designers and researchers attention all over the world. The number of layer of space frame is divided in to the simgle, double, multi layer. That is important element which is considered deeply in the beginning of structural design. The buckling characteristics of single-layer model and double-layer model for the spherical space frame structure with triangular network pattern are evaluated and the buckling loads of these types are compared with investigation their structural efficiency in this study.

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