• Title/Summary/Keyword: Computer Model

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Analysis and Usage of Computer Experiments Using Spatial Linear Models (공간선형모형을 이용한 전산실험의 분석과 활용)

  • Park, Jeong-Soo
    • Journal of Korean Society for Quality Management
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    • v.34 no.2
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    • pp.122-128
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    • 2006
  • One feature of a computer simulation experiment, different from a physical experiment, is that the output is often deterministic. Moreover the codes are computationally very expensive to run. This paper deals with the design and analysis of computer experiments(DACE) which is a relatively new statistical research area. We model the response of computer experiments as the realization of a stochastic process. This approach is basically the same as using a spatial linear model. Applications to the optimal mechanical designing and model calibration problems are illustrated. Algorithms for selecting the best spatial linear model are also proposed.

The Learning Effect of Teaching Materials Using Computer Animation of Particulate Model in Elementary School Science Classes (초등학교 과학 수업에 적용한 입자 모델의 컴퓨터 애니메이션 교수자료의 학습 효과)

  • 박재원;백성혜
    • Journal of Korean Elementary Science Education
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    • v.23 no.2
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    • pp.116-122
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    • 2004
  • The purpose of this study is to investigate effects of computer animations using particulate model in elementary science classes related to air pressure. To do those, four classes of 5th grade in an elementary school located in a city were selected. As an experiment group, two classes were applied the teaching materials of computer animations developed for this study based on particulate model. The other classes as a control group were not applied these materials in science classes. The total scores of experiment group in which computer animation using particulate model was applied in science classes are higher than those of the control group in the conception test. Only in one conception related to high and low atmospheric air pressure, the scores of the two groups are not significantly different at 0.05 significance level.

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A New Methodology for Software Reliability based on Statistical Modeling

  • Avinash S;Y.Srinivas;P.Annan naidu
    • International Journal of Computer Science & Network Security
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    • v.23 no.9
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    • pp.157-161
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    • 2023
  • Reliability is one of the computable quality features of the software. To assess the reliability the software reliability growth models(SRGMS) are used at different test times based on statistical learning models. In all situations, Tradational time-based SRGMS may not be enough, and such models cannot recognize errors in small and medium sized applications.Numerous traditional reliability measures are used to test software errors during application development and testing. In the software testing and maintenance phase, however, new errors are taken into consideration in real time in order to decide the reliability estimate. In this article, we suggest using the Weibull model as a computational approach to eradicate the problem of software reliability modeling. In the suggested model, a new distribution model is suggested to improve the reliability estimation method. We compute the model developed and stabilize its efficiency with other popular software reliability growth models from the research publication. Our assessment results show that the proposed Model is worthier to S-shaped Yamada, Generalized Poisson, NHPP.

Human Face Tracking and Modeling using Active Appearance Model with Motion Estimation

  • Tran, Hong Tai;Na, In Seop;Kim, Young Chul;Kim, Soo Hyung
    • Smart Media Journal
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    • v.6 no.3
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    • pp.49-56
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    • 2017
  • Images and Videos that include the human face contain a lot of information. Therefore, accurately extracting human face is a very important issue in the field of computer vision. However, in real life, human faces have various shapes and textures. To adapt to these variations, A model-based approach is one of the best ways in which unknown data can be represented by the model in which it is built. However, the model-based approach has its weaknesses when the motion between two frames is big, it can be either a sudden change of pose or moving with fast speed. In this paper, we propose an enhanced human face-tracking model. This approach included human face detection and motion estimation using Cascaded Convolutional Neural Networks, and continuous human face tracking and modeling correction steps using the Active Appearance Model. A proposed system detects human face in the first input frame and initializes the models. On later frames, Cascaded CNN face detection is used to estimate the target motion such as location or pose before applying the old model and fit new target.

A Formal Specification and Checking Technique of Feature model using Z language (휘처 모델의 Z 정형 명세와 검사 기법)

  • Song, Chee-Yang;Cho, Eun-Sook;Kim, Chul-Jin
    • Journal of the Korea Society of Computer and Information
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    • v.18 no.1
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    • pp.123-136
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    • 2013
  • The Feature model can not be guaranteed the syntactic accuracy of its model and be difficult the validation using automatic tool for its syntax, because this model is expressed by a graphical and informal structure in itself. Therefore, there is a need to formalize and check for the feature model, to precisely define syntax for construct of the model. This paper presents a Z formal specification and a model checking mechanism of the feature model to guarantee the correctness of the model. It first defines the translation rules between feature model and Z, and then converts the syntax of the feature model into the Z schema specification by applying these rules. Finally, the Z schema specification is checked syntax, type, and domain errors using the Z/Eves validation tool to assure the correctness of its specification, With the use of the proposed method, we may express more precisely the construct of the feature model. Moreover the domain analyst are able to usefully verify the errors of the generated feature model.

DeepPTP: A Deep Pedestrian Trajectory Prediction Model for Traffic Intersection

  • Lv, Zhiqiang;Li, Jianbo;Dong, Chuanhao;Wang, Yue;Li, Haoran;Xu, Zhihao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.7
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    • pp.2321-2338
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    • 2021
  • Compared with vehicle trajectories, pedestrian trajectories have stronger degrees of freedom and complexity, which poses a higher challenge to trajectory prediction tasks. This paper designs a mode to divide the trajectory of pedestrians at a traffic intersection, which converts the trajectory regression problem into a trajectory classification problem. This paper builds a deep model for pedestrian trajectory prediction at intersections for the task of pedestrian short-term trajectory prediction. The model calculates the spatial correlation and temporal dependence of the trajectory. More importantly, it captures the interactive features among pedestrians through the Attention mechanism. In order to improve the training speed, the model is composed of pure convolutional networks. This design overcomes the single-step calculation mode of the traditional recurrent neural network. The experiment uses Vulnerable Road Users trajectory dataset for related modeling and evaluation work. Compared with the existing models of pedestrian trajectory prediction, the model proposed in this paper has advantages in terms of evaluation indicators, training speed and the number of model parameters.

Design of User Concentration Classification Model by EEG Analysis Based on Visual SCPT

  • Park, Jin Hyeok;Kang, Seok Hwan;Lee, Byung Mun;Kang, Un Gu;Lee, Young Ho
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.11
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    • pp.129-135
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    • 2018
  • In this study, we designed a model that can measure the level of user's concentration by measuring and analyzing EEG data of the subjects who are performing Continuous Performance Test based on visual stimulus. This study focused on alpha and beta waves, which are closely related to concentration in various brain waves. There are a lot of research and services to enhance not only concentration but also brain activity. However, there are formidable barriers to ordinary people for using routinely because of high cost and complex procedures. Therefore, this study designed the model using the portable EEG measurement device with reasonable cost and Visual Continuous Performance Test which we developed as a simplified version of the existing CPT. This study aims to measure the concentration level of the subject objectively through simple and affordable way, EEG analysis. Concentration is also closely related to various brain diseases such as dementia, depression, and ADHD. Therefore, we believe that our proposed model can be useful not only for improving concentration but also brain disease prediction and monitoring research. In addition, the combination of this model and the Brain Computer Interface technology can create greater synergy in various fields.

u-City service Model based on Implementation and Adaptability

  • Lee, Yeon-Ho;Ko, Seong-Sun;Lee, Nam-Yong;Kim, Jong-Bae
    • Journal of information and communication convergence engineering
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    • v.8 no.3
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    • pp.251-257
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    • 2010
  • The realization of u-City is coming near in some local governments by applying various city services, namely, u-City services to the city construction field to improve competitiveness of the city. But it is a reality that some local governments are experiencing many trial and errors in application of the u-City service in addition to the problem posing that the u-City service is not considering characteristics of development or application environment of an individual city. The present research proposes a service model for on-site application of the u-City service to solve this problem. The proposed model suggests a method for specifically conceptualizing and objectifying the on-site application that the existing concept-oriented model or an architecture-oriented model, etc. didn't provide. The verification system on effectiveness or effects of the u-City service model to remove ambiguity on the u-City service especially. The verification system of the u-City service model grasps the technology, function, procedure and target, etc. that the u-City service contains, evaluates whether the model satisfies conditions that the model should have, and secures objectivity and predictability of the u-City service model through confirmation on propriety, implementation and effectiveness, etc.

An Efficient Machine Learning Model for Clinical Support to Predict Heart Disease

  • Rao, B.Vara Prasada;Reddy, B.Satyanarayana;Padmaja, I. Naga;Kumar, K. Ashok
    • International Journal of Computer Science & Network Security
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    • v.22 no.6
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    • pp.223-229
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    • 2022
  • Early detection can help prevent heart disease, which is one of the most common reasons for death. This paper provides a clinical support model for predicting cardiac disease. The model is built using two publicly available data sets. The admissibility and application of the the model are justified by a sequence of tests. Implementation of the model and testing are also discussed

A Realistic Path Loss Model for Real-time Communication in the Urban Grid Environment for Vehicular Ad hoc Networks

  • Mostajeran, Ehsan;Noor, Rafidah Md;Anisi, Mohammad Hossein;Ahmedy, Ismail;Khan, Fawad Ali
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.10
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    • pp.4698-4716
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    • 2017
  • Wireless signal transmission is influenced by environmental effects. These effects have also been challenging for Vehicular Ad hoc Network (VANET) in real-time communication. More specifically, in an urban environment, with high mobility among vehicles, a vehicle's status from the transmitter can instantly trigger from line of sight to non-line of sight, which may cause loss of real-time communication. In order to overcome this, a deterministic signal propagation model is required, which has less complexity and more feasibility of implementation. Hence, we propose a realistic path loss model which adopts ray tracing technique for VANET in a grid urban environment with less computational complexity. To evaluate the model, it is applied to a vehicular simulation scenario. The results obtained are compared with different path loss models in the same scenario based on path loss value and application layer performance analysis. The proposed path loss model provides higher loss value in dB compared to other models. Nevertheless, the performance of vehicle-vehicle communication, which is evaluated by the packet delivery ratio with different vehicle transmitter density verifies improvement in real-time vehicle-vehicle communication. In conclusion, we present a realistic path loss model that improves vehicle-vehicle wireless real-time communication in the grid urban environment.