To help physicians and their assistants plan, rehearse and follow up a surgical therapy with a computer device, people may carry out a three-dimensional (3-D) cardiac modeling by digital imageprocessingalgorithms an...
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Modern experimental setups generate prolonged and intense data streams. For example, non-contact measurement techniques PIV (Particle image Velocimetry), based on continuous imageprocessing, are widely used in the ex...
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Modern experimental setups generate prolonged and intense data streams. For example, non-contact measurement techniques PIV (Particle image Velocimetry), based on continuous imageprocessing, are widely used in the experimental aerodynamics and hydrodynamics. These experimental stereo or volumetric velocimetry 3D PIV setups are able to generate long-lasting and intensive flows of images by using two or more cameras. High computational complexity of the imageprocessingalgorithms is the main limiting factor in the conditions of the low computational performance of PIV setups itself. Removal of these limitations by moving imageprocessing tasks on a remote supercomputer by using our proposed technology "Distributed PIV", which will allow users to apply their new high-precision parallel algorithms in a real-time and implement feedback to the experimental setup. This paper describes the innovative technology for high-performance processing of the intensive flows of the structured data generated by an experimental setup and delivered through a high-speed DWDM backbone directly into computing nodes of a remote supercomputer. A high BDP (Bandwidth-Delay Product) problem case in the design of protocols such as TCP in respect of performance tuning to achieve maximum network throughput is solved by designed middleware. (C) 2016 Elsevier Inc. All rights reserved.
Thousands of years ago written language was introduced as a way of enhancing and facilitating communication. Fast forward to the twenty first century much has changed, especially the flow of data incrementing at fast ...
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This article describes the problem of segmentation of the spine for lateral C spine radiographs. In this case, the most frequently used approach is the Active Shape Model. The use of the Active Appearance Model is con...
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ISBN:
(纸本)9783319669052
This article describes the problem of segmentation of the spine for lateral C spine radiographs. In this case, the most frequently used approach is the Active Shape Model. The use of the Active Appearance Model is considered in this paper. Segmentation quality of sample data is tested for selected preprocessing and predetecting edge algorithms: Sobel filter, Canny edge detection algorithm, and Statistical Dominance Algorithm. The particularly important issue of precise description of contours is considered and partially tested. The aim is to deliver a good quality preliminary step to syntactic analysis of vertebrae using the generalized shape language.
In this paper, several optimizations are proposed to enhance the quality of lane detection algorithms in automotive applications. Considering the diagonal directions of lanes, the proposed limited Hough transform newl...
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In this paper, several optimizations are proposed to enhance the quality of lane detection algorithms in automotive applications. Considering the diagonal directions of lanes, the proposed limited Hough transform newly introduces image-splitting and angle-limiting schemes that relax the number of possible angles at the line voting process. In addition, unnecessary edges along the horizontal and vertical directions are pre-defined and removed during the edge detection procedures, increasing the detecting accuracy remarkably. Simulation results shows that the proposed lane recognition algorithm achieves an accuracy of more than 90% and a computing speed of 92 frame/sec, which are superior to the results from the previous algorithms.
The proceedings contain 21 papers. The special focus in this conference is on Informatics in Control, Automation and Robotics. The topics include: Parameter identification and model-based control of redundantly actuat...
ISBN:
(纸本)9783319550107
The proceedings contain 21 papers. The special focus in this conference is on Informatics in Control, Automation and Robotics. The topics include: Parameter identification and model-based control of redundantly actuated, non-holonomic, omnidirectional vehicles;passivity-based control design and experiments for a rolling-balancing system;time-optimal paths for a robotic batting task;an adaptive terminal sliding mode guidance law for head pursuit interception with impact angle considered;kinematic and dynamic approaches in gait optimization for humanoid robot locomotion;identification and control of the waelz process using infrared imageprocessing;modeling and calibrating triangulation lidars for indoor applications;a comparison of discretization methods for parameter estimation of nonlinear mechanical systems using extended kalman filter: Symplectic versus classical approaches;dynamics calibration and real-time state estimation of a redundant flexible joint robot based on encoders and gyroscopes;visual servoing path-planning with elliptical projections;Mathematical model for the output signal’s energy of an ideal DAC in the presence of clock jitter;stochastic integration filter with improved state estimate mean-square error computation;fractional models of lithium-ion batteries with application to state of charge and ageing estimation;co-operation of biology related algorithms for solving opinion mining problems by using different term weighting schemes;bifurcation analysis and active control of surge and rotating stall in axial flow compressors via passivity;task controller for performing remote centre of motion;toward an automatic fongbe speech recognition system: Hierarchical mixtures of algorithms for phoneme recognition;spatial fusion of different imaging technologies using a virtual multimodal camera.
This paper presents a new piecewise linear modeling method for the planning of polyvinyl chloride (PVC) plants. In our previous study (hid. Eng. Chem. Res., 2016, SS, 12430-12443, DOI: 10.1021/***.6b02825), a multiper...
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This paper presents a new piecewise linear modeling method for the planning of polyvinyl chloride (PVC) plants. In our previous study (hid. Eng. Chem. Res., 2016, SS, 12430-12443, DOI: 10.1021/***.6b02825), a multiperiod mixed-integer nonlinear programming (MINLP) model was developed to demonstrate the importance of integrating both the material processing and the utility systems. However, the optimization problem is really difficult to solve due to the process intrinsic nonlinearities, i.e., the operating cost or energy-consuming characteristics of calcium carbide furnaces, electrolytic cells, and CHP units. The present paper intends to address this challenge by using the piecewise linear modeling approach that provides good approximation of the global nonlinearity with locally linear models. Specifically, a hinging hyperplanes (HH) model is introduced to approximate the nonlinear items in the original MINLP model. HH model is a kind of continuous piecewise linear (CPWL) model, which is proven to be effective for any continuous linear functions with arbitrary dimensions on compact sets in any given precision, and is the basis for the linearization MINLP model. As a result, with the help of auxiliary variables, the original MINLP can be transformed into a mixed-integer linear program (MILP) model, which then can be solved by many established efficient and mature algorithms. Computational results show that the proposed model can reduce the solving time by up to 97% or more and the planning results are close to or even better than those obtained by the MINLP approach.
A wearable electroencephalogram (EEG) is a small mobile device used for long-term brain monitoring systems. Applications of these systems include fatigue monitoring, mental/emotional monitoring, and brain-computer int...
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A wearable electroencephalogram (EEG) is a small mobile device used for long-term brain monitoring systems. Applications of these systems include fatigue monitoring, mental/emotional monitoring, and brain-computer interfaces. However, the usage of wireless wearable EEG systems is limited due to the risks posed by the wireless RF communication radiation in a long-term exposure to the human brain. A novel microwave radiation-free system was developed by integrating visible light communication technology into a wearable EEG device. In this work, we investigated the system's performance in transmitting EEG data at different illuminance level and proposed an algorithm that functions at low illuminance levels for increased transmission distance. Using a 30 Hz smartphone camera, the proposed system was able to transmit 2.4 kbps of error-free EEG data up to 4 meter, which is equal to similar to 300 lux using an aspheric focus lens. (C) 2017 Optical Society of America
Hadoop has become a widely used open source framework for large scale data processing. MapReduce is the core component of Hadoop. It is this programming paradigm that allows for massive scalability across hundreds or ...
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ISBN:
(纸本)9783319483085;9783319483078
Hadoop has become a widely used open source framework for large scale data processing. MapReduce is the core component of Hadoop. It is this programming paradigm that allows for massive scalability across hundreds or thousands of servers in a Hadoop cluster. It allows processing of extremely large video files or image files on data nodes. This can be used for implementing Content Based image Retrieval (CBIR) algorithms on Hadoop to compare and match query images to the previously stored terabytes of an image descriptors databases. This work presents the implementation for one of the well-known CBIR algorithms called Scale Invariant Feature Transformation (SIFT) for image features extraction and matching using Hadoop platform. It gives focus on utilizing the parallelization capabilities of Hadoop MapReduce to enhance the CBIR performance and decrease data input\output operations through leveraging Partitioners and Combiners. Additionally, imageprocessing and computer vision tools such as Hadoop imageprocessing (HIPI) and Open Computer Vision (OpenCV) are integration is shown.
In present scenario, agriculture forms a vital part in India's economy. More than 50 % of India's population is dependent (directly or indirectly) on agriculture for their livelihood. In India many crops are c...
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ISBN:
(纸本)9789811016752;9789811016745
In present scenario, agriculture forms a vital part in India's economy. More than 50 % of India's population is dependent (directly or indirectly) on agriculture for their livelihood. In India many crops are cultivated, out of which wheat being one of the most important food grain that this country cultivates and exports. Thus it can be seen that wheat forms a major part of the Indian agricultural system and India's economy. Hence, maintenance of the steady production of above stated crop is very important. The main idea of this project is to provide a system for detecting wheat leaf diseases. The given system will study the leaf image of a wheat plant through imageprocessing and pattern recognition algorithms. Former algorithms are used for extracting vital information from the leaf and the latter is used for detecting the disease that it is infected with. For imageprocessing and segmentation usage of k-means algorithm and canny filter has been suggested. Pattern recognition is achieved through PCA or GLCM and classification through SVM or ANN.
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