SVM for English semantic classification in parallel environment

Semantic analysis is very important and very helpful for many researches and many applications for a long time. SVM is a famous algorithm which is used in the researches and applications in many different fields. In this study, we propose a new model using a SVM algorithm with Hadoop Map (M)/Reduce (R) for English document-level emotional classification in the Cloudera parallel network environment. Cloudera is also a distributed system. Our English testing data set has 25,000 English documents, including 12,500 English positive reviews and 12,500 English negative reviews. Our English training data set has 90,000 English sentences, including 45,000 English positive sentences and 45,000 English negative sentences. Our new model is tested on the English testing data set and we achieve 63.7% accuracy of sentiment classification on this English testing data set.     

A decision tree using ID3 algorithm for English semantic analysis

Natural language processing has been studied for many years, and it has been applied to many researches and commercial applications. A new model is proposed in this paper, and is used in the English document-level emotional classification. In this survey, we proposed a new model by using an ID3 algorithm of a decision tree to classify semantics (positive, negative, and neutral) for the English documents. The semantic classification of our model is based on many rules which are generated by applying the ID3 algorithm to 115,000 English sentences of our English training data set. We test our new model on the English testing data set including 25,000 English documents, and achieve 63.6% accuracy of sentiment classification results.     

Modeling of axis-symmetric steam plasma flow in a non-transferred torch

This paper discusses the numerical modeling of steam plasma in a DC non-transferred torch equipped with well-type cathode, where the non-trivial azimuthal velocity component and turbulent effect are both taken into account. In order to investigate the complicated flow characteristics of thermal plasma due to the interaction between steam and electric arc, the flow filed inside the plasma torch is modeled by the magnetic–hydrodynamic (MHD) equations. The governing equations are then solved numerically using a non-staggered finite volume discretization based on Cartesian grid system. The anode location and maximum current density at cathode are fixed by the corresponding experimental measurement at a given flow rate. The predicted result suggests that the steam plasma can be accelerated to a mean velocity of 1500 m/s at torch outlet with the mass flow rate of 5 g/s and the system current of 180 A. A strong vortex flow structure is found inside the torch due to the introduction of azimuthal velocity at the gas inlet, which should help to stabilize the rotating arc during the torch operation.     

Morphology and intersections of crazes in polystyrene films

Craze network with interconnecting crazes was produced in thin (~60nm) polystyrene films by using a spherical stretching method. For 30% and 45% radial strain, the average mesh size, defined as the square root of average non-crazed areas enclosed by crazes, decreased from about 28m to 4.6 and 2.7m, respectively, as the molecular weight increased from 46 900 to 1 350 000. At a molecular weight of about 10⁶, the interactions between crazes became evident by the split and change of directions at the end of their propagation. Two types of intersection appeared to exist in parallel. The first type showed void formation at the intersections with no apparent fibril displacement effect. The second type showed that the fibrils at the intersection of two perpendicular crazes reoriented to a new direction which seemed to be determined by the relative displacements of the two crazes at the intersections. This observation suggests that the craze fibrils can be displaced and further stretched by a second crazing process.     

Benchmarking nanotechnology for high-performance and low-power logic transistor applications

Recently there has been tremendous progress made in the research of novel nanotechnology for future nanoelectronic applications. In particular, several emerging nanoelectronic devices such as carbon-nanotube field-effect transistors (FETs), Si nanowire FETs, and planar III-V compound semiconductor (e.g., InSb, InAs) FETs, all hold promise as potential device candidates to be integrated onto the silicon platform for enhancing circuit functionality and also for extending Moore's Law. For high-performance and low-power logic transistor applications, it is important that these research devices are frequently benchmarked against the existing Si logic transistor data in order to gauge the progress of research. In this paper, we use four key device metrics to compare these emerging nanoelectronic devices to the state-of-the-art planar and nonplanar Si logic transistors. These four metrics include: 1) CV/I or intrinsic gate delay versus physical gate length L/sub g/; 2) energy-delay product versus L/sub g/; 3) subthreshold slope versus L/sub g/; and 4) CV/I versus on-to-off-state current ratio I/sub ON//I/sub OFF/. The results of this benchmarking exercise indicate that while these novel nanoelectronic devices show promise and opportunities for future logic applications, there still remain shortcomings in the device characteristics and electrostatics that need to be overcome. We believe that benchmarking is a key element in accelerating the progress of nanotechnology research for logic transistor applications.     

A reinforcement discrete neuro-adaptive control for unknown piezoelectric actuator systems with dominant hysteresis

The theoretical and experimental studies of a reinforcement discrete neuro-adaptive control for unknown piezoelectric actuator systems with dominant hysteresis are presented. Two separate nonlinear gains, together with an unknown linear dynamical system, construct the nonlinear model (NM) of the piezoelectric actuator systems. A nonlinear inverse control (NIC) according to the learned NM is then designed to compensate the hysteretic phenomenon and to track the reference input without the risk of discontinuous response. Because the uncertainties are dynamic, a recurrent neural network (RNN) with residue compensation is employed to model them in a compact subset. Then, a discrete neuro-adaptive sliding-mode control (DNASMC) is designed to enhance the system performance. The stability of the overall system is verified by Lyapunov stability theory. Comparative experiments for various control schemes are also given to confirm the validity of the proposed control.     

A new design method and half-step operation for ultrasonic stepping motors

In this paper, a systematic design method and a new half-step operation are proposed for ultrasonic stepping motors (USMs) which are based on the principle of spatially shifted standing vibrations. With emphasis on the combination of the order of vibration mode, the number of spatial phase shifts, the number of electrodes, and the number of simultaneously excited electrodes, the design equations and constraints are newly derived, hence, proposing the design procedure. The finite-element method and impedance measurement are also employed to investigate the vibration of the stator. By borrowing the control idea of electromagnetic stepping motors, the half-step operation is newly applied to this USM so that the step size can be further halved. An 80-step USM is prototyped. The proposed design method and half-step operation are well supported by experimentation.     

Micromechanical digital-to-analog converter for out-of-plane motion

This paper describes a novel micromechanical digital-to-analog converter (MDAC) for out-of-plane motion using electrostatic parallel-plate actuators. The proposed mechanism converts an N-bit digital signal to a mechanical out-of-plane displacement that is proportional to the analog value represented by the N-bit binary word. The mechanism is analogous to that of an electrical binary-weighted-input digital-to-analog converter (DAC). It consists of a movable platform, an array of parallel-plate microactuators each operating in an ON/OFF mode and a set of connection springs that connect the actuators to the platform. The spring constants of the connection springs are weighted so that the stiffness of successive springs is related by a factor of 2. A 4-bit mechanism has been fabricated using the Poly-MUMPS process, achieving a total stroke of 675 nm (full-scale output) and step size (LSB) of 45 nm in a highly repeatable and stable manner. The linearity error (LE) of the device is within /spl plusmn/0.28 LSB, and the differential linearity error (DLE) is within /spl plusmn/0.25 LSB. This mechanism can be configured for many promising applications, particularly in optical devices and systems such as tunable external cavity diode laser, tunable VCSELs, adaptive micromirror array and tunable wavelength filter.