Search results for: Human Arm model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8833

Search results for: Human Arm model

8533 Predictive Model of Sensor Readings for a Mobile Robot

Authors: Krzysztof Fujarewicz

Abstract:

This paper presents a predictive model of sensor readings for mobile robot. The model predicts sensor readings for given time horizon based on current sensor readings and velocities of wheels assumed for this horizon. Similar models for such anticipation have been proposed in the literature. The novelty of the model presented in the paper comes from the fact that its structure takes into account physical phenomena and is not just a black box, for example a neural network. From this point of view it may be regarded as a semi-phenomenological model. The model is developed for the Khepera robot, but after certain modifications, it may be applied for any robot with distance sensors such as infrared or ultrasonic sensors.

Keywords: Mobile robot, sensors, prediction, anticipation.

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8532 Statistical Models of Network Traffic

Authors: Barath Kumar, Oliver Niggemann, Juergen Jasperneite

Abstract:

Model-based approaches have been applied successfully to a wide range of tasks such as specification, simulation, testing, and diagnosis. But one bottleneck often prevents the introduction of these ideas: Manual modeling is a non-trivial, time-consuming task. Automatically deriving models by observing and analyzing running systems is one possible way to amend this bottleneck. To derive a model automatically, some a-priori knowledge about the model structure–i.e. about the system–must exist. Such a model formalism would be used as follows: (i) By observing the network traffic, a model of the long-term system behavior could be generated automatically, (ii) Test vectors can be generated from the model, (iii) While the system is running, the model could be used to diagnose non-normal system behavior. The main contribution of this paper is the introduction of a model formalism called 'probabilistic regression automaton' suitable for the tasks mentioned above.

Keywords: Model-based approach, Probabilistic regression automata, Statistical models and Timed automata.

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8531 Paremaeter Determination of a Vehicle 5-DOF Model to Simulate Occupant Deceleration in a Frontal Crash

Authors: Javad Marzbanrad, Mostafa Pahlavani

Abstract:

This study has investigated a vehicle Lumped Parameter Model (LPM) in frontal crash. There are several ways for determining spring and damper characteristics and type of problem shall be considered as system identification. This study use Genetic Algorithm (GA) procedure, being an effective procedure in case of optimization issues, for optimizing errors, between target data (experimental data) and calculated results (being obtained by analytical solving). In this study analyzed model in 5-DOF then compared our results with 5-DOF serial model. Finally, the response of model due to external excitement is investigated.

Keywords: Vehicle, Lumped-Parameter Model, GeneticAlgorithm, Optimization

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8530 Green Lean TQM Human Resource Management Practices in Malaysian Automotive Companies

Authors: Noor Azlina Mohd Salleh, Salmiah Kasolang, Ahmed Jaffar

Abstract:

Green Lean Total Quality Management (LTQM) Human Resource Management (HRM) System is a system comprises of HRM in Environmental Management System (EMS) practices which is integrated to TQM with Lean Manufacturing (LM) principles. HRM is essential especially in dealing with low motivation and less productive employees. The ultimate goal of this system is to focus on achieving total human resource development that is motivated and capable to optimize their creativity to be a part of Green and Lean TQM organization. A survey questionnaire was developed and distributed to 30 highly active automotive vendors in Malaysia and analyzed by Minitab v16 and SPSS v17. It was found out companies that are practicing Green LTQM HRM practices have generated more revenue and have RND capability. However, years of company establishment do not affect the openness of the company to adapt new initiatives that can help to improve the effectiveness of the operations. It was also found out the importance of training, communication and rewards for employees. The Green LTQM HRM practices framework model established in this study hopefully will give preliminary insight especially to companies that are still looking for system that can improve their productivity from managing human resource. This is preliminary study that combined 4 awards practices, ISO/TS16949, Toyota Production System SAEJ4000, MAJAICO Lean Production System and EMS focusing on highly active companies that have been involved in MAJAICO Program and Proton Vendor Development Program. Future study can be conducted to know the status at other industry as well as case study pertaining to this system.

Keywords: Automotive Industry, Lean Manufacturing, Operational Engineering Management, Total Quality Management. Environmental Management System.

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8529 The Establishment of RELAP5/SNAP Model for Kuosheng Nuclear Power Plant

Authors: C. Shih, J. R. Wang, H. C. Chang, S. W. Chen, S. C. Chiang, T. Y. Yu

Abstract:

After the measurement uncertainty recapture (MUR) power uprates, Kuosheng nuclear power plant (NPP) was uprated the power from 2894 MWt to 2943 MWt. For power upgrade, several codes (e.g., TRACE, RELAP5, etc.) were applied to assess the safety of Kuosheng NPP. Hence, the main work of this research is to establish a RELAP5/MOD3.3 model of Kuosheng NPP with SNAP interface. The establishment of RELAP5/SNAP model was referred to the FSAR, training documents, and TRACE model which has been developed and verified before. After completing the model establishment, the startup test scenarios would be applied to the RELAP5/SNAP model. With comparing the startup test data and TRACE analysis results, the applicability of RELAP5/SNAP model would be assessed.

Keywords: RELAP5, TRACE, SNAP, BWR.

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8528 Comprehensive Risk Assessment Model in Agile Construction Environment

Authors: Jolanta Tamošaitienė

Abstract:

The article focuses on a developed comprehensive model to be used in an agile environment for the risk assessment and selection based on multi-attribute methods. The model is based on a multi-attribute evaluation of risk in construction, and the determination of their optimality criterion values are calculated using complex Multiple Criteria Decision-Making methods. The model may be further applied to risk assessment in an agile construction environment. The attributes of risk in a construction project are selected by applying the risk assessment condition to the construction sector, and the construction process efficiency in the construction industry accounts for the agile environment. The paper presents the comprehensive risk assessment model in an agile construction environment. It provides a background and a description of the proposed model and the developed analysis of the comprehensive risk assessment model in an agile construction environment with the criteria.

Keywords: Assessment, environment, agile, model, risk.

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8527 Finite Element and Subspace Identification Approaches to Model Development of a Smart Acoustic Box with Experimental Verification

Authors: Tamara Nestorović, Jean Lefèvre, Stefan Ringwelski, Ulrich Gabbert

Abstract:

Two approaches for model development of a smart acoustic box are suggested in this paper: the finite element (FE) approach and the subspace identification. Both approaches result in a state-space model, which can be used for obtaining the frequency responses and for the controller design. In order to validate the developed FE model and to perform the subspace identification, an experimental set-up with the acoustic box and dSPACE system was used. Experimentally obtained frequency responses show good agreement with the frequency responses obtained from the FE model and from the identified model.

Keywords: Acoustic box, experimental verification, finite element model, subspace identification.

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8526 Using Ontology Search in the Design of Class Diagram from Business Process Model

Authors: Wararat Rungworawut, Twittie Senivongse

Abstract:

Business process model describes process flow of a business and can be seen as the requirement for developing a software application. This paper discusses a BPM2CD guideline which complements the Model Driven Architecture concept by suggesting how to create a platform-independent software model in the form of a UML class diagram from a business process model. An important step is the identification of UML classes from the business process model. A technique for object-oriented analysis called domain analysis is borrowed and key concepts in the business process model will be discovered and proposed as candidate classes for the class diagram. The paper enhances this step by using ontology search to help identify important classes for the business domain. As ontology is a source of knowledge for a particular domain which itself can link to ontologies of related domains, the search can give a refined set of candidate classes for the resulting class diagram.

Keywords: Business Process Model, Model DrivenArchitecture, Ontology, UML Class Diagram.

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8525 3D Face Modeling based on 3D Dense Morphable Face Shape Model

Authors: Yongsuk Jang Kim, Sun-Tae Chung, Boogyun Kim, Seongwon Cho

Abstract:

Realistic 3D face model is more precise in representing pose, illumination, and expression of face than 2D face model so that it can be utilized usefully in various applications such as face recognition, games, avatars, animations, and etc. In this paper, we propose a 3D face modeling method based on 3D dense morphable shape model. The proposed 3D modeling method first constructs a 3D dense morphable shape model from 3D face scan data obtained using a 3D scanner. Next, the proposed method extracts and matches facial landmarks from 2D image sequence containing a face to be modeled, and then reconstructs 3D vertices coordinates of the landmarks using a factorization-based SfM technique. Then, the proposed method obtains a 3D dense shape model of the face to be modeled by fitting the constructed 3D dense morphable shape model into the reconstructed 3D vertices. Also, the proposed method makes a cylindrical texture map using 2D face image sequence. Finally, the proposed method generates a 3D face model by rendering the 3D dense face shape model using the cylindrical texture map. Through building processes of 3D face model by the proposed method, it is shown that the proposed method is relatively easy, fast and precise.

Keywords: 3D Face Modeling, 3D Morphable Shape Model, 3DReconstruction, 3D Correspondence.

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8524 Domin-Specific Language for Enabling End- Users Model-Driven Information System Engineering

Authors: Ahmad F. Subahi, Anthony J. H. Simons

Abstract:

This Paper presents an on-going research in the area of Model-Driven Engineering (MDE). The premise is that UML is too unwieldy to serve as the basis for model-driven engineering. We need a smaller, simpler notation with a cleaner semantics. We propose some ideas for a simpler notation with a clean semantics. The result is known as μML, or the Micro-Modelling Language.

Keywords: Model-driven engineering, model transformations, domain-specific languages, end-user development.

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8523 Analytical Model Based Evaluation of Human Machine Interfaces Using Cognitive Modeling

Authors: Belkacem Chikhaoui, Helene Pigot

Abstract:

Cognitive models allow predicting some aspects of utility and usability of human machine interfaces (HMI), and simulating the interaction with these interfaces. The action of predicting is based on a task analysis, which investigates what a user is required to do in terms of actions and cognitive processes to achieve a task. Task analysis facilitates the understanding of the system-s functionalities. Cognitive models are part of the analytical approaches, that do not associate the users during the development process of the interface. This article presents a study about the evaluation of a human machine interaction with a contextual assistant-s interface using ACTR and GOMS cognitive models. The present work shows how these techniques may be applied in the evaluation of HMI, design and research by emphasizing firstly the task analysis and secondly the time execution of the task. In order to validate and support our results, an experimental study of user performance is conducted at the DOMUS laboratory, during the interaction with the contextual assistant-s interface. The results of our models show that the GOMS and ACT-R models give good and excellent predictions respectively of users performance at the task level, as well as the object level. Therefore, the simulated results are very close to the results obtained in the experimental study.

Keywords: HMI, interface evaluation, Analytical evaluation, cognitivemodeling, user modeling, user performance.

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8522 Input Data Balancing in a Neural Network PM-10 Forecasting System

Authors: Suk-Hyun Yu, Heeyong Kwon

Abstract:

Recently PM-10 has become a social and global issue. It is one of major air pollutants which affect human health. Therefore, it needs to be forecasted rapidly and precisely. However, PM-10 comes from various emission sources, and its level of concentration is largely dependent on meteorological and geographical factors of local and global region, so the forecasting of PM-10 concentration is very difficult. Neural network model can be used in the case. But, there are few cases of high concentration PM-10. It makes the learning of the neural network model difficult. In this paper, we suggest a simple input balancing method when the data distribution is uneven. It is based on the probability of appearance of the data. Experimental results show that the input balancing makes the neural networks’ learning easy and improves the forecasting rates.

Keywords: AI, air quality prediction, neural networks, pattern recognition, PM-10.

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8521 Differentiation Capacity of Mouse L929 Fibroblastic Cell Line Compare With Human Dermal Fibroblast

Authors: Kasem Theerakittayakorn, Tanom Bunprasert

Abstract:

Mouse L929 fibroblastic cell line, which is widely used in many experiment aspects, was tested for their differentiation potency in osteogenic differentiation and adipogenic differentiation. Human dermal fibroblasts, which their differentiation potency are still be in confliction, also be taken in the experiment. The differentiations were conducted by using the inducing medium ingredients which is generally used to induce differentiation of stem cells. By the inducing media used, L929 mouse fibroblasts successfully underwent osteogenic differentiation and adipogenic differentiation while human dermal fibroblasts underwent only osteogenic differentiation but not for adipogenic differentiation. Human dermal fibroblasts are hard to be differentiated in adipogenic lineage and need specific proper condition for induction.

Keywords: Adipogenic differentiation, Fibroblast, Inducingmedium, Osteogenic differentiation

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8520 Measurement and Analysis of Human Hand Kinematics

Authors: Tamara Grujic, Mirjana Bonkovic

Abstract:

Measurements and quantitative analysis of kinematic parameters of human hand movements have an important role in different areas such as hand function rehabilitation, modeling of multi-digits robotic hands, and the development of machine-man interfaces. In this paper the assessment and evaluation of the reachto- grasp movement by using computerized and robot-assisted method is described. Experiment involved the measurements of hand positions of seven healthy subjects during grasping three objects of different shapes and sizes. Results showed that three dominant phases of reach-to-grasp movements could be clearly identified.

Keywords: Human hand, kinematics, reach-to-grasp movement.

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8519 Lean Impact Analysis Assessment Models: Development of a Lean Measurement Structural Model

Authors: Catherine Maware, Olufemi Adetunji

Abstract:

The paper is aimed at developing a model to measure the impact of Lean manufacturing deployment on organizational performance. The model will help industry practitioners to assess the impact of implementing Lean constructs on organizational performance. It will also harmonize the measurement models of Lean performance with the house of Lean that seems to have become the industry standard. The sheer number of measurement models for impact assessment of Lean implementation makes it difficult for new adopters to select an appropriate assessment model or deployment methodology. A literature review is conducted to classify the Lean performance model. Pareto analysis is used to select the Lean constructs for the development of the model. The model is further formalized through the use of Structural Equation Modeling (SEM) in defining the underlying latent structure of a Lean system. An impact assessment measurement model developed can be used to measure Lean performance and can be adopted by different industries.

Keywords: Impact measurement model, lean bundles, lean manufacturing, organizational performance.

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8518 An Implicit Region-Based Deformable Model with Local Segmentation Applied to Weld Defects Extraction

Authors: Y. Boutiche, N. Ramou, M. Ben Gharsallah

Abstract:

This paper is devoted to present and discuss a model that allows a local segmentation by using statistical information of a given image. It is based on Chan-Vese model, curve evolution, partial differential equations and binary level sets method. The proposed model uses the piecewise constant approximation of Chan-Vese model to compute Signed Pressure Force (SPF) function, this one attracts the curve to the true object(s)-s boundaries. The implemented model is used to extract weld defects from weld radiographic images in the aim to calculate the perimeter and surfaces of those weld defects; encouraged resultants are obtained on synthetic and real radiographic images.

Keywords: Active contour, Chan-Vese Model, local segmentation, weld radiographic images.

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8517 Model of Optimal Centroids Approach for Multivariate Data Classification

Authors: Pham Van Nha, Le Cam Binh

Abstract:

Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: Analysis of optimization, artificial intelligence-based optimization, optimization for learning and data analysis, global optimization.

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8516 Formal Verification of Cache System Using a Novel Cache Memory Model

Authors: Guowei Hou, Lixin Yu, Wei Zhuang, Hui Qin, Xue Yang

Abstract:

Formal verification is proposed to ensure the correctness of the design and make functional verification more efficient. As cache plays a vital role in the design of System on Chip (SoC), and cache with Memory Management Unit (MMU) and cache memory unit makes the state space too large for simulation to verify, then a formal verification is presented for such system design. In the paper, a formal model checking verification flow is suggested and a new cache memory model which is called “exhaustive search model” is proposed. Instead of using large size ram to denote the whole cache memory, exhaustive search model employs just two cache blocks. For cache system contains data cache (Dcache) and instruction cache (Icache), Dcache memory model and Icache memory model are established separately using the same mechanism. At last, the novel model is employed to the verification of a cache which is module of a custom-built SoC system that has been applied in practical, and the result shows that the cache system is verified correctly using the exhaustive search model, and it makes the verification much more manageable and flexible.

Keywords: Cache system, formal verification, novel model, System on Chip (SoC).

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8515 Automatic Generation of Ontology from Data Source Directed by Meta Models

Authors: Widad Jakjoud, Mohamed Bahaj, Jamal Bakkas

Abstract:

Through this paper we present a method for automatic generation of ontological model from any data source using Model Driven Architecture (MDA), this generation is dedicated to the cooperation of the knowledge engineering and software engineering. Indeed, reverse engineering of a data source generates a software model (schema of data) that will undergo transformations to generate the ontological model. This method uses the meta-models to validate software and ontological models.

Keywords: Meta model, model, ontology, data source.

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8514 Zero Inflated Strict Arcsine Regression Model

Authors: Y. N. Phang, E. F. Loh

Abstract:

Zero inflated strict arcsine model is a newly developed model which is found to be appropriate in modeling overdispersed count data. In this study, we extend zero inflated strict arcsine model to zero inflated strict arcsine regression model by taking into consideration the extra variability caused by extra zeros and covariates in count data. Maximum likelihood estimation method is used in estimating the parameters for this zero inflated strict arcsine regression model.

Keywords: Overdispersed count data, maximum likelihood estimation, simulated annealing.

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8513 Optimization and GIS-Based Intelligent Decision Support System for Urban Transportation Systems Analysis

Authors: Mohamad K. Hasan, Hameed Al-Qaheri

Abstract:

Optimization plays an important role in most real world applications that support decision makers to take the right decision regarding the strategic directions and operations of the system they manage. Solutions for traffic management and traffic congestion problems are considered major problems that most decision making authorities for cities around the world are looking for. This review paper gives a full description of the traffic problem as part of the transportation planning process and present a view as a framework of urban transportation system analysis where the core of the system is a transportation network equilibrium model that is based on optimization techniques and that can also be used for evaluating an alternative solution or a combination of alternative solutions for the traffic congestion. Different transportation network equilibrium models are reviewed from the sequential approach to the multiclass combining trip generation, trip distribution, modal split, trip assignment and departure time model. A GIS-Based intelligent decision support system framework for urban transportation system analysis is suggested for implementation where the selection of optimized alternative solutions, single or packages, will be based on an intelligent agent rather than human being which would lead to reduction in time, cost and the elimination of the difficulty, by human being, for finding the best solution to the traffic congestion problem.

Keywords: Multiclass simultaneous transportation equilibrium models, transportation planning, urban transportation systems analysis, intelligent decision support system.

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8512 Image Ranking to Assist Object Labeling for Training Detection Models

Authors: Tonislav Ivanov, Oleksii Nedashkivskyi, Denis Babeshko, Vadim Pinskiy, Matthew Putman

Abstract:

Training a machine learning model for object detection that generalizes well is known to benefit from a training dataset with diverse examples. However, training datasets usually contain many repeats of common examples of a class and lack rarely seen examples. This is due to the process commonly used during human annotation where a person would proceed sequentially through a list of images labeling a sufficiently high total number of examples. Instead, the method presented involves an active process where, after the initial labeling of several images is completed, the next subset of images for labeling is selected by an algorithm. This process of algorithmic image selection and manual labeling continues in an iterative fashion. The algorithm used for the image selection is a deep learning algorithm, based on the U-shaped architecture, which quantifies the presence of unseen data in each image in order to find images that contain the most novel examples. Moreover, the location of the unseen data in each image is highlighted, aiding the labeler in spotting these examples. Experiments performed using semiconductor wafer data show that labeling a subset of the data, curated by this algorithm, resulted in a model with a better performance than a model produced from sequentially labeling the same amount of data. Also, similar performance is achieved compared to a model trained on exhaustive labeling of the whole dataset. Overall, the proposed approach results in a dataset that has a diverse set of examples per class as well as more balanced classes, which proves beneficial when training a deep learning model.

Keywords: Computer vision, deep learning, object detection, semiconductor.

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8511 Comparison of Two Interval Models for Interval-Valued Differential Evolution

Authors: Hidehiko Okada

Abstract:

The author previously proposed an extension of differential evolution. The proposed method extends the processes of DE to handle interval numbers as genotype values so that DE can be applied to interval-valued optimization problems. The interval DE can employ either of two interval models, the lower and upper model or the center and width model, for specifying genotype values. Ability of the interval DE in searching for solutions may depend on the model. In this paper, the author compares the two models to investigate which model contributes better for the interval DE to find better solutions. Application of the interval DE is evolutionary training of interval-valued neural networks. A result of preliminary study indicates that the CW model is better than the LU model: the interval DE with the CW model could evolve better neural networks. 

Keywords: Evolutionary algorithms, differential evolution, neural network, neuroevolution, interval arithmetic.

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8510 Cytotoxic Effects of Engineered Nanoparticles in Human Mesenchymal Stem Cells

Authors: Ali A. Alshatwi, Vaiyapuri S. Periasamy, Jegan Athinarayanan

Abstract:

Engineered nanoparticles’ usage rapidly increased in various applications in the last decade due to their unusual properties. However, there is an ever increasing concern to understand their toxicological effect in human health. Particularly, metal and metal oxide nanoparticles have been used in various sectors including biomedical, food and agriculture. But their impact on human health is yet to be fully understood. In this present investigation, we assessed the toxic effect of engineered nanoparticles (ENPs) including Ag, MgO and Co3O4 nanoparticles (NPs) on human mesenchymal stem cells (hMSC) adopting cell viability and cellular morphological changes as tools The results suggested that silver NPs are more toxic than MgO and Co3O4NPs. The ENPs induced cytotoxicity and nuclear morphological changes in hMSC depending on dose. The cell viability decreases with increase in concentration of ENPs. The cellular morphology studies revealed that ENPs damaged the cells. These preliminary findings have implications for the use of these nanoparticles in food industry with systematic regulations.

Keywords: Cobalt oxide, Human mesenchymal stem cells, MgO, Silver.

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8509 Toward Integrative Stormwater Design in Urban Spaces

Authors: Bruce K. Ferguson

Abstract:

The design requirements for successful human accommodation in urban spaces are well known; and the range of facilities available for meeting urban water quality and quantity requirements is also well established. Their competing requirements must be reconciled in order for urban spaces to be successful for both. This paper outlines the separate human and water imperatives and their interactions in urban spaces. Stormwater management facilities- relative potential contributions to urban spaces are contrasted, and design choices for achieving those potentials are described. This study uses human success of urban space as the evaluative criterion of stormwater amenity: human values call on stormwater facilities to contribute to successful human spaces. Placing water-s contribution under the overall idea of successful urban space is an evolution from previous subjective evaluations. The information is based on photographs and notes from approximately 1,000 stormwater facilities and urban sites collected during the last 35 years in North America and overseas, and the author-s experience on multi-disciplinary design teams. This conceptual study combines the disciplinary roles of engineering, landscape architecture, and sociology in effecting successful urban design.

Keywords: Stormwater, SUDS, Urban design, Values, Urban space.

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8508 Face Detection in Color Images using Color Features of Skin

Authors: Fattah Alizadeh, Saeed Nalousi, Chiman Savari

Abstract:

Because of increasing demands for security in today-s society and also due to paying much more attention to machine vision, biometric researches, pattern recognition and data retrieval in color images, face detection has got more application. In this article we present a scientific approach for modeling human skin color, and also offer an algorithm that tries to detect faces within color images by combination of skin features and determined threshold in the model. Proposed model is based on statistical data in different color spaces. Offered algorithm, using some specified color threshold, first, divides image pixels into two groups: skin pixel group and non-skin pixel group and then based on some geometric features of face decides which area belongs to face. Two main results that we received from this research are as follow: first, proposed model can be applied easily on different databases and color spaces to establish proper threshold. Second, our algorithm can adapt itself with runtime condition and its results demonstrate desirable progress in comparison with similar cases.

Keywords: face detection, skin color modeling, color, colorfulimages, face recognition.

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8507 Usability Evaluation Framework for Computer Vision Based Interfaces

Authors: Muhammad Raza Ali, Tim Morris

Abstract:

Human computer interaction has progressed considerably from the traditional modes of interaction. Vision based interfaces are a revolutionary technology, allowing interaction through human actions, gestures. Researchers have developed numerous accurate techniques, however, with an exception to few these techniques are not evaluated using standard HCI techniques. In this paper we present a comprehensive framework to address this issue. Our evaluation of a computer vision application shows that in addition to the accuracy, it is vital to address human factors

Keywords: Usability evaluation, cognitive walkthrough, think aloud, gesture recognition.

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8506 Online Pose Estimation and Tracking Approach with Siamese Region Proposal Network

Authors: Cheng Fang, Lingwei Quan, Cunyue Lu

Abstract:

Human pose estimation and tracking are to accurately identify and locate the positions of human joints in the video. It is a computer vision task which is of great significance for human motion recognition, behavior understanding and scene analysis. There has been remarkable progress on human pose estimation in recent years. However, more researches are needed for human pose tracking especially for online tracking. In this paper, a framework, called PoseSRPN, is proposed for online single-person pose estimation and tracking. We use Siamese network attaching a pose estimation branch to incorporate Single-person Pose Tracking (SPT) and Visual Object Tracking (VOT) into one framework. The pose estimation branch has a simple network structure that replaces the complex upsampling and convolution network structure with deconvolution. By augmenting the loss of fully convolutional Siamese network with the pose estimation task, pose estimation and tracking can be trained in one stage. Once trained, PoseSRPN only relies on a single bounding box initialization and producing human joints location. The experimental results show that while maintaining the good accuracy of pose estimation on COCO and PoseTrack datasets, the proposed method achieves a speed of 59 frame/s, which is superior to other pose tracking frameworks.

Keywords: Computer vision, Siamese network, pose estimation, pose tracking.

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8505 CFD Simulation of Surge Wave Generated by Flow-Like Landslides

Authors: Liu-Chao Qiu

Abstract:

The damage caused by surge waves generated in water bodies by flow-like landslides can be very high in terms of human lives and economic losses. The complicated phenomena occurred in this highly unsteady process are difficult to model because three interacting phases: air, water and sediment are involved. The problem therefore is challenging since the effects of non-Newtonian fluid describing the rheology of the flow-like landslides, multi-phase flow and free surface have to be included in the simulation. In this work, the commercial computational fluid dynamics (CFD) package FLUENT is used to model the surge waves due to flow-like landslides. The comparison between the numerical results and experimental data reported in the literature confirms the accuracy of the method.

Keywords: Flow-like landslide, surge wave, VOF, non-Newtonian fluids, multi-phase flows, free surface flow.

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8504 Using Automatic Ontology Learning Methods in Human Plausible Reasoning Based Systems

Authors: A. R. Vazifedoost, M. Rahgozar, F. Oroumchian

Abstract:

Knowledge discovery from text and ontology learning are relatively new fields. However their usage is extended in many fields like Information Retrieval (IR) and its related domains. Human Plausible Reasoning based (HPR) IR systems for example need a knowledge base as their underlying system which is currently made by hand. In this paper we propose an architecture based on ontology learning methods to automatically generate the needed HPR knowledge base.

Keywords: Ontology Learning, Human Plausible Reasoning, knowledge extraction, knowledge representation.

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