An approach for a leak detection and localization scheme is presented. With respect to developing methods for diagnosis in commercial vehicles, applicability of existing approaches for leak diagnosis in pipelines has ...
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ISBN:
(纸本)9781467318716
An approach for a leak detection and localization scheme is presented. With respect to developing methods for diagnosis in commercial vehicles, applicability of existing approaches for leak diagnosis in pipelines has been evaluated. A leakage localization strategy using an Extended Kalman Filter (EKF) in combination withthe Method of Characteristics (MOC) is adapted to pneumatic systems and implemented in Matlab/Simulink. To deal with boundary limitations due to possible sections for leak localization along the pipe, a methodical extension based on the idea of virtual pipes is proposed and integrated into the overall method. Verifications, resulting from a simulation model as well as from measurements at a real test bench, are presented. the promising results are discussed and suggestions for possible steps of further development are given.
Recommender systems have become an important research area both in industry and academia over the last decade. Memory-based collaborative filtering methods include user-based and item-based methods have been explored ...
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Recommender systems have become an important research area both in industry and academia over the last decade. Memory-based collaborative filtering methods include user-based and item-based methods have been explored in many product domains for their simplicity. Memory-based collaborative filtering methods compute the average ratings between similar users or items to predict unrated entries. As a consequence, it is difficult to find similar users or items when the rating data is sparse. the recommendation quality can be poor. this paper proposed an efficient Rating-Based Recommender Algorithm named RBRA. With a new model based on user behavior and item features, RBRA can achieve results that are more accurate even when the rating data is sparse. In the prediction phase, RBRA takes an adaptively weighted prediction, which utilizes both ratings of the same item by different users and different items by the same user. the final ratings are evaluated from two sources, user-based and item-based approaches. Experimental results show that RBRA achieves 400% faster recommendation speed with better accuracy.
In this paper, the path planning method with two different obstacle avoiding models are proposed to solve the target pursuit and obstacle avoid problem (TPOA). Both of the models are originated from linear programming...
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In this paper, the path planning method with two different obstacle avoiding models are proposed to solve the target pursuit and obstacle avoid problem (TPOA). Both of the models are originated from linear programming (LP). One model introduced integer variable to describe the relative position of robot and obstacles, then MILP based obstacle-avoided model is built;the other used a tangent line to define the feasible and infeasible region of robot in obstacle area, thus LP based obstacle-avoided constraints are given. Simulations are demonstrated comparatively to show the effectiveness of the proposed methods.
the analysis of the quality of a virgin olive oil involves the determination of a series of chemical indexes and organoleptic characteristics. In this work we propose an online prediction model for three chemical inde...
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the analysis of the quality of a virgin olive oil involves the determination of a series of chemical indexes and organoleptic characteristics. In this work we propose an online prediction model for three chemical indexes: acidity, peroxide index and humidity content, based on an hyperspectral artificial vision system. Two methods have been developed for the construction of the model: (1) partial least squares regression (PLS) using all the captured spectral components, and (2) partial least squares regression over a subset of the components obtained applying a genetic algorithm (GA-PLS). the design and validation was carried out using olive oil samples from different seasons analysed by a renowned laboratory.
Active Appearance models (AAMs) are widely used to estimate the shape of the face together with its orientation, but AAM approaches tend to fail when the face is under wide angular variations. Although it is feasible ...
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Active Appearance models (AAMs) are widely used to estimate the shape of the face together with its orientation, but AAM approaches tend to fail when the face is under wide angular variations. Although it is feasible to capture the overall 3D face structure using 3D data from range cameras, the locations of facial features are often estimated imprecisely or incorrectly due to depth measurement uncertainty. Face alignment using 2D and 3D images suffer from different issues and have varying reliability in different situations. the existing approaches introduce a weighting function to balance 2D and 3D alignments in which the weighting function is tuned manually and the sensor characteristics are not taken into account. In this paper, we propose to balance 3D face alignment using 2D and 3D data based on the observed data and the sensors characteristics. the feasibility of wide-angle face alignment is demonstrated using two different sets of depth and conventional cameras. the experimental results show that a stable alignment is achieved with a maximum improvement of 26% compared to 3D AAM using 2D image and 30% improvement over the state-of-the-art 3DMM methods in terms of 3D head pose estimation.
Contact mode Atomic Force Microscopy (AFM) is popularly used by the biophysics community to study mechanical properties of cells and tissue due to its ability to quantify biological processes like disease proliferatio...
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Contact mode Atomic Force Microscopy (AFM) is popularly used by the biophysics community to study mechanical properties of cells and tissue due to its ability to quantify biological processes like disease proliferation and stem cell differentiation. While AFM indentation experiments are relatively straightforward, interpretation of the AFM data is subject to some debate. three factors make the AFM force data prone to incorrect interpretation, namely, the appropriate contact model to use to fit the post-contact AFM data, identifying the point when the AFM probe contacts the cell, and variability in the stiffness of the probe used to estimate material properties of cells. A lot of research has been directed towards developing constitutive models based on sample material property assumptions, however, variability in the AFM probe stiffness and contact point uncertainty has received limited attention. this suggests the need to have an integrated probabilistic model to estimate mechanical properties from the AFM force data which can account for errors contributed from these two sources. In this work, we have developed an Error-In-Variables (EIV) based Bayesian Changepoint model to estimate the contact point and the Young's Modulus from AFM force curves on fixed mouse Embryonic Stem cells (mESC) in the indentation range of 1-1.5 μm. Our results indicate that the EIV-based Bayesian Approach can be used to obtain robust estimates of material properties of biomaterials.
Generation of grasps for automated object manipulation in cluttered scenarios presents major challenges for various modules of the pipeline such as 2D/3D visual processing, 3D modeling, grasp hypothesis generation, gr...
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ISBN:
(纸本)9781467317375
Generation of grasps for automated object manipulation in cluttered scenarios presents major challenges for various modules of the pipeline such as 2D/3D visual processing, 3D modeling, grasp hypothesis generation, grasp planning and path planning. In this paper, we present a solution framework for solving a complex instance of the problem - represented by a heap of unknown and unstructured objects in a bounded environment - in our case, a box;withthe goal being removing all objects in the box using an attention driven object modeling approach to cognitive grasp planning. the focus of the algorithm delves on Grasping by Components (GBC), with a prioritization scheme derived from scene based attention and attention driven segmentation. In order to overcome the traditional challenge of segmentation performing poorly in cluttered scenes, we employ a novel active segmentation approach suited to our scenario. While the attention module helps prioritize objects in the heap and salient regions, the GBC scheme segments out parts and generates grasp hypotheses for each part. GBC is a very important component of any scalable and holistic grasping system since it abstracts point cloud object data with parametric shapes and no apriori knowledge (such as 3D models) is required. Earlier work in 3D model building (such as CAD based, simple geometries, bounding boxes, Superquadrics etc.) have depended on precise shape and pose recognition as well as exhaustive training to learn or exhaustive searching in grasp space to generate good grasp hypotheses. these methods are not scalable for real-time scenarios, complex shapes and unknown environments - key challenges in robotic grasping. In order to alleviate this concern, we present a novel parametric algorithm to estimate grasp points and approach vectors from the 3D parametric shape model, along with innovative schemes to optimize the computation of the parametric models as well as to refine the generated grasp hypotheses based on th
the proceedings contain 78 papers. the topics discussed include: composite control of periodic-review just-in-time inventory systems with asymmetric costs;sensitivity-based feedforward and feedback control using algor...
ISBN:
(纸本)9781424478279
the proceedings contain 78 papers. the topics discussed include: composite control of periodic-review just-in-time inventory systems with asymmetric costs;sensitivity-based feedforward and feedback control using algorithmic differentiation;robust polynomial eigenstructure assignment control of a class of nonlinear systems;constrained robot motion planning: imbalanced Jacobian algorithm vs. optimal control approach;control of nonholonomic autonomous vehicles and their formations;energy saving control in low cost pneumatic positioning systems;autonomous navigation of transport robot in the urban environment;application of adaptive neural network to dishwasher operation control;Takagi-Sugeno-Kang type fuzzy models with fuzzy equations in the consequence part;numerical method for drag minimization in compressible flows;adaptive tracking-control synthesis for functionally uncertain systems via modified backstepping;and sensitivity analysis of infinite order hyperbolic optimal control problems.
this paper presents a robotics framework intended to be used for rowing simulation. It provides kinematic and inverse dynamic models for the system composed of boat, rowers and oars. the inverse dynamic model is based...
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ISBN:
(纸本)9781457709142
this paper presents a robotics framework intended to be used for rowing simulation. It provides kinematic and inverse dynamic models for the system composed of boat, rowers and oars. the inverse dynamic model is based on the Recursive Newton-Euler Algorithm with free-floating base dealing with tree-structured systems with kinematic loops. Examples of simulations of a rowing-like model are given along with external force models. It is composed of a total of 6 links for the rower and the oars, the floating boat, and 7 joints. It presents a branched structure with one loop enabling to test the ability of the framework regarding its goals.
the positive switched 2D linear systems described by the Roesser models are addressed. Necessary and sufficient conditions for the asymptotic stability of the positive switched 2D linear systems described by the Roess...
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ISBN:
(纸本)9781457709142
the positive switched 2D linear systems described by the Roesser models are addressed. Necessary and sufficient conditions for the asymptotic stability of the positive switched 2D linear systems described by the Roesser models for any switching are established. the considerations are illustrated by numerical examples.
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