We present a microfluidic-chip-based concept for continuous fractionation of magnetic microspheres (MMS) having a broad size distribution. Fractionation is achieved through a combination of shear-induced inertial lift...
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ISBN:
(纸本)9781618395955
We present a microfluidic-chip-based concept for continuous fractionation of magnetic microspheres (MMS) having a broad size distribution. Fractionation is achieved through a combination of shear-induced inertial lift forces that act on particles flowing through a curvilinear channel (i.e., Dean Flow) and magnetostatic forces produced by an octupolar arrangement of magnets mounted below the chip. The chip was designed, built, and tested using different MMS mixtures. The novel device enables the complete recovery of MMS from highly diluted suspensions, the separation of MMS mixtures, and size dependent fractionation of MMS.
The unsupervised classification of hyperspectral images containing mixed pixels is addressed in this paper. Hyperspectral images are characterized by a trade-off between the spectral and the spatial resolution, this l...
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The unsupervised classification of hyperspectral images containing mixed pixels is addressed in this paper. Hyperspectral images are characterized by a trade-off between the spectral and the spatial resolution, this leading to data sets containing mixed pixels, e.g. pixels jointly occupied by more than a single land cover class. In [1], a preliminary research based on spectral unmixing concepts was conducted, in order to handle mixed pixels and to obtain thematic maps at a finer spatial resolution. In this work, we extend the investigation by proposing a new methodology based on image clustering. Experiments conducted on real data show the comparative effectiveness of the proposed method, which provides good results in terms of accuracy and is less sensitive to pixels with extreme values of reflectance.
Graphite fibers with high structural perfection and small diameters (∼1 μm) provide a sensitive medium to study the effect of ion implantation on the transport properties of graphite and to observe the defect struct...
Graphite fibers with high structural perfection and small diameters (∼1 μm) provide a sensitive medium to study the effect of ion implantation on the transport properties of graphite and to observe the defect structure associated with the implantation process. Graphite fibers prepared from the thermal decomposition of benzene and subsequent heat treatment to high temperatures (∼2900°C) have been shown to achieve the high structural perfection necessary to carry out such experiments. Implantation-induced changes in the fiber resistivity are reported and are found to be larger at low temperature, as expected on the basis of residual resistance arguments. Using the lattice fringe imaging technique of high resolution electron microscopy, the implantation-induced defect structure can be observed directly. The results show local expansion of the interlayer graphite planes, with an interlayer separation ranging up to 3.9 Å in the implanted region, compared with ∼3.4 Å for the well-ordered layers beyond the ion penetration depth.
Abstract In this paper we address the pursuing or target tracking problem where an autonomous robotic vehicle is required to move towards a maneuvering target using range-only measurements. A new switched based contro...
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Abstract In this paper we address the pursuing or target tracking problem where an autonomous robotic vehicle is required to move towards a maneuvering target using range-only measurements. A new switched based control strategy is proposed to solve the pursuing problem that can be described as comprising a continuous cycle of two distinct phases: i) the determination of the bearing, and ii) following the direction computed in the previous step while the range is decreasing. We provide conditions under which the switched closed-loop system achieves convergence of the relative distance error to a small neighborhood around zero. Simulation results are presented and discussed.
In this paper we propose a new technique for designing feedback control of a DC motor speed using fractional order proportional-integral-derivative (FOPID controller). DC motor is often used in robotics and other fiel...
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In this paper we propose a new technique for designing feedback control of a DC motor speed using fractional order proportional-integral-derivative (FOPID controller). DC motor is often used in robotics and other fields of control and therefore speed control is very important. FOPID controller's parameters are composed of the proportionality constant, integral constant, derivative constant, derivative order and integral order, and its design is more complex than that of conventional integer-order proportional-integral-derivative (PID) controllers. Here the controller synthesis is formulated as a single objective optimization problem and based on Integral Time Absolute Error (ITAE) criterion. A modified Artificial Bee Colony Algorithm is been used to tune the FOPID controller parameters.
Artificial Bee Colony (ABC) algorithm is one of the most recent swarm intelligence based algorithms which simulates the foraging behavior of honey bee colonies. In the present study we propose a simple modification in...
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Artificial Bee Colony (ABC) algorithm is one of the most recent swarm intelligence based algorithms which simulates the foraging behavior of honey bee colonies. In the present study we propose a simple modification in the basic structure of ABC to enhance the capabilities of virtual bees in locating the potential food sources (ones having sufficient amount of nectar in them). If the virtual bees are unable to locate a good food source even after a particular number of cycles then they are forced towards another food source with the help of a small perturbation. The corresponding algorithm is named as C-ABC, where C stands for Cauchy distribution which helps the bees in getting away from food sources which are not so good. Analysis of the proposed C-ABC on 5 standard benchmark problems and 7 non-traditional problems, suggested in the special session of CEC'2008, shows that the incorporation of the proposed scheme considerably improves the performance of basic ABC algorithm.
Now-a-days fractional order controllers are replacing integer order controllers in various applications due to their robust mechanism in enhancing the system performance. The only complexity using fractional order con...
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Now-a-days fractional order controllers are replacing integer order controllers in various applications due to their robust mechanism in enhancing the system performance. The only complexity using fractional order controllers is to determine the gain parameters, followed by integral and derivative constant. This article describes the design of Fractional-Order Proportional-Integral-Derivative (FOPID) controller using a newly developed variant of ABC known as Sobol Mutated Artificial Bee Colony (S-ABC). The mutation component of S-ABC is based on quasi random Sobol sequence. Controller synthesis is obtained by minimizing Integral Time Absolute Error (ITAE) criterion. In order to digitally realize the FOPID controller Tustin operator based continuous fraction approximation (CFE) method is used. Simulation results for some real life plants and comparison with other state of art optimization techniques over same problems demonstrate the superiority of proposed approach.
Hybrid excitation machines (HEMs) that consist of permanent magnet (PM) and field excitation coil (FEC) as their main flux sources has several attractive features compared to interior permanent magnet synchronous mach...
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Hybrid excitation machines (HEMs) that consist of permanent magnet (PM) and field excitation coil (FEC) as their main flux sources has several attractive features compared to interior permanent magnet synchronous machines (IPMSM) conventionally employed in hybrid electric vehicles (HEVs). Among various types of HEM, the machine with both permanent magnet and field excitation coil located on the stator has the advantage of robust rotor structure similar as switch reluctance machine (SRM). In addition, the variable flux control capabilities from field excitation coil make this machine becoming more attractive to be applied for high-speed motor drive systems, coupled with reduction gear. This HEM can be categorized as hybrid excitation flux switching synchronous machine (HEFSSM). In this paper, a novel 12Slot-10Pole HEFSSM where the field excitation coil is wounded in radial direction in the stator is proposed for traction drives in HEVs. The design target of the proposed machine is a maximum torque of 210Nm with reduction gear ratio of 4:1, a maximum power of 123kW, a maximum power density more than 3.5kW/kg, and a maximum speed of 20,000r/min with similar restrictions and specifications in IPMSM used for LEXUS RX400h. The deterministic design optimization method based on 2D-FEA is used to treat design parameters defined in rotor, armature coil slot and field excitation coil slot until the target performances are achieved, under maximum current density condition for both armature coil and field excitation coil. The final results show that the final design HEFSSM is able to keep the same torque density in existing IPMSM installed on a commercial SUV-HEV.
A kernel adapted to the spectral dimension of hyperspectral images is proposed in this paper. A distance based on a statistical cluster model is used to construct a radial kernel. This class specific kernel realizes a...
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A kernel adapted to the spectral dimension of hyperspectral images is proposed in this paper. A distance based on a statistical cluster model is used to construct a radial kernel. This class specific kernel realizes a compromise between a conventional Gaussian kernel and a Gaussian kernel on the first principal components of the considered class. An automatic gradient optimization is used to select the optimal hyperparameters. Experimental results on a real hyperspectral image show the kernel is effective compared to the conventional Gaussian kernel. Furthermoren the proposed kernel is less sensitive to one hyperparameter compared to the Gaussian kernel applied on the first principal components of the data.
Software testing is a process of verifying and validating that a software application or program works as per the users expectations. It is used to find out the important defects, flaws, or errors in the application c...
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Software testing is a process of verifying and validating that a software application or program works as per the users expectations. It is used to find out the important defects, flaws, or errors in the application code. In this paper we have developed a tool to generate different test cases automatically. To show the validity of the tool, we have considered the line equation problem and generated different test cases, and finally we conclude that Robustness Technique is better than Boundary Value Analysis, because the expected output (number of times) in case of Robustness Technique for intersecting lines, parallel lines and coincident lines are 12, 12 and 1 respectively while in case of Boundary Value Analysis it is 8, 8 and 1 respectively.
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