nils-herrmann/clean_scirepeval huggingface dataset:
Graphics Processing Unit-Based High Frame Rate Ultrasonic Tissue Motion Visualization

Ultrasonic tissue motion can be visualized in three steps: the gray scale motion detection, the Unsteady Flow Line Integral Convolution (UFLIC) algorithm to trace the velocity field, and display techniques for both the global motion and the local radial/tangential velocity components. Because of the large amount of data and high computational requirement in UFLIC, it was difficult to meet real-time requirement on CPU. In this paper a parallel algorithm based on the graphics processing unit (GPU) was proposed to implement ultrasonic tissue motion visualization, and it represented both the direction and amplitude of the motion by texture and color. Furthermore, a method was proposed to calculate the local radial/tangential velocity components. Finally, we got a frame rate of about more than 300 fps with the vector field size of 260×260.
Controlling strategy and implementation for synchronously closing 550 kV parallel capacitor

Synchronously closing can avoid surge current and overvoltage on the parallel capacitor. There will be more meaningful to 550 kV than lower voltage capacitor because the insulation requirements are relatively higher in 550 kV situations. Circuit breaker's synchronous operation and Synchronously Controlling Controller (SCC) can be a key part to the modern substation intellectualization and automation system in the future. The controlling strategy for synchronously closing 550 kV parallel capacitor has been discussed in-depth in this paper. The main influence factors, such as Rate of Decrease Dielectric Strength (RDDS), deviation of closing time of the circuit breaker, and residual voltage on the capacitor, have been considered. The optimized mechanical contact point for synchronously closing has been obtained. Based on embedded technology, a SCC for synchronously closing 550 kV parallel capacitor and fitting IEC 61850 standard has been developed and has passed the 4th rigorous level EMC test. The test results indicate that the SCC has enough accuracy, calculation and reaction speed, and reliability for real application.
Robustness design of uncertain discrete-time fuzzy descriptor systems with guaranteed admissibility

This paper considers the admissibility and robustness of uncertain discrete-time fuzzy descriptor systems. The general definition of admissibility for the nonlinear fuzzy descriptor systems given here includes the regularity, stability and causality together, it embodies the homologous relationship between the overall system and the subsystems. The robust admissibility of the uncertain discrete-time fuzzy descriptor systems is analyzed in terms of matrix norm. Furthermore, a relaxed criterion is derived to guarantee the admissibility of the closed-loop uncertain discrete-time fuzzy descriptor system, by this criterion the fuzzy controller can be designed systematically. An example is given to show the results presented in this paper.
Bytecode-based software monitoring and trusted evolution programming framework

Point to reliability of distributed software in open complex environment, this paper proposes a bytecode-based software monitoring and trusted evolution programming framework, which injects monitoring ability and evolution ability into the software in construction and running phase. The framework is comprised of three module, business-logic and monitor-requirement description module (BMDM), monitoring capability infusing module (MCIM), and online evolution module (OEM), BMDM provides monitoring requirement expression language MRL+, MCIM compiles monitoring requirements monitoring requirement into aspect code, insert aspect code into source system by bytecode-based AOP technology, generate the target system with monitoring ability, and send monitoring information to OEM by event. OEM compares the state event with predefined evolution rules, when the predefined rules are triggered, perform the evolution actions, achieve real-time system's monitoring and correction. Finally, actual cases are analyzed to show that the framework can construct reliability software with monitoring ability and evolution ability efficiently.
Neural Network with Adaptive Immune Genetic Algorithm for Eddy Current Nondestructive Testing

For eddy current nondestructive testing (ECNDT), an immune genetic algorithm (IGA) is presented, which can overcome the disadvantages of genetic algorithm (GA), such as possibility of being trapped on locally minimum value and prematurity convergence. Moreover, crossover and mutation operators are selected by adaptive algorithm to overcome prematurity. Compared with GA, the convergence precision and generalization of IGA are improved remarkably
Stability Analysis of a Class of Discrete Switched Fuzzy Systems

This paper introduces a innovated representation model, namely, a discrete-time switched fuzzy system, which differs from existing ones. In this model, a system is a switched system whose subsystems are all discrete-time T-S fuzzy systems. Using switching technique, the single Lyapunov function method and multiple Lyapunov functions method, the state feedback controllers are built to ensure that the relevant closed-loop system is quadratically stable in this paper. Moreover, switching laws of the state-dependent form achieving system quadratic stability of the switched fuzzy system are given. The main conditions are given in form of convex combination and LMI, which are more solvable. The elaborated illustrative examples and the respective simulation experiments demonstrate the effectiveness of the proposed method.
Optimization control of active distribution network based on Photovoltaic forecast information

With the cost declining of Photovoltaic (PV) power generation and the support of government, it can be expected that a large number of PV systems will be accessed to the distribution network in the future. The development of active distribution network provides a good solution to improve the intermittent energy consumptive ability of distribution network. Active distribution network is able to control the controllable units flexibly and effectively. Thus it can achieve optimal operation ensuring system stability and power quality. Based on the existing optimization strategies, this paper proposed two kind optimal strategies according to time scale, long-term comprehensive optimization (in 24 hours) and short-term real-time optimization (in 15 to 30 minutes), to achieve the most economical operation within one day with real-time error correction. Here considering PV power generation as one kind intermittent energy source accessed to the distribution network, long-term optimization needs daily loads and PV systems daily forecast information and short-term real-time optimization needs the ultra short-term forecast of the PV system. Considering the computing time and prediction accuracy, this paper applied PV system grey prediction methods (GM (1, 1)). At last, this paper verified the economical and effective characters of the optimization control strategy by a proper case.
Infrared face recognition method based on blood perfusion image and Curvelet transformation

In this paper, a fast infrared face recognition method using blood perfusion conversion and Curvelet transformation is proposed. Firstly, to get the good performance of infrared face recognition from the biological feature, thermal images are converted into blood perfusion domain by blood perfusion model. Secondly, Curvelet transform has better directional and edge representation abilities than widely used wavelet transformation and other classic transformations. Inspired by these attractive attributes of Curvelets in sparse representation of the images, we introduce the idea of decomposing images into their curvelet subbands to extract the principal representative feature, which saves the computational complexity and storage units. Finally, the nearest neighbor classifier is chosen to get the method recognition result. The experiments illustrate that compared with those traditional methods based on PCA, the proposed method has better performance and requires fewer computations and memory units.
Moving Horizon Estimation for Mobile Robots With Multirate Sampling

This paper investigates the multirate moving horizon estimation (MMHE) problem for mobile robots with inertial sensor and camera, where the sampling rates of the sensors are not identical. In the sense of the multirate systems, some sensors may have no measurements at certain sampling times, which can be regarded as measurement missing and may significantly degrade the estimation performance. A binary switching sequence is introduced to model the multirate sampling process, and an explicit mathematical description of this process is proposed where a prediction value activated by a prediction generator is used for the output of missing sampling for slow measurement. The prediction generator provides a set of predictions to make the estimation system achieve the desired performance. By choosing a cost function, the optimal estimator is obtained by solving a regularized least-squares problem with unconstraints. The constrained MMHE problem is studied by using the interior-point algorithm. The input-to-state stability is investigated for the optimal estimator in the presence of bounded disturbances and noises. Finally, a mobile robot tracking platform is designed, and both simulations and experiments are presented to demonstrate the effectiveness of the proposed method.
Iterative Image Coding with Overcomplete Curvelet Transform

This paper presents a new coding technique based on a overcomplete curvelet transform. Curvelets provide an essentially optimal representation for typical objects which are discontinuities along curves. However curvelets transform has high redundancy, the process of selecting the optimal set of coefficients to code is much more difficult because many different sets of transform coefficients can represent the same decoded image. The transform is optimized through an iterative projection process in the transform domain in order to minimize the quantization error in the image domain. So we select the optimal set of quantized coefficients based on iterative projection of signals between the image domain and transform domain with a non-linear process (a quantizer). The optimal set of quantized coefficients is coded by the simple entropy coder. The compression performance of the coding technique based on a overcomplete curvelet transform is compared with that of Wavelet Transform, both objectively and subjectively, and is found to offer advantages of up to about 0.7 dB for Lena image and to about 1.42 dB for Barbara image in PSNR and significant reduction in visibility of some types of coding artifacts.
Magnetic Field and Force Calculation in Linear Permanent-Magnet Synchronous Machines Accounting for Longitudinal End Effect

This paper presents an improved analytical method for predicting the magnetic field and forces in linear permanent-magnet synchronous machines (LPMSMs) accounting for both the primary end effect and secondary end effect. So far, the magnetic field calculation of LPMSM in most studies is conducted in Cartesian coordinate, whereas the end effect is neglected by applying periodic boundary. In this paper, to implement the analytical model, a polar presentation of the machine geometry is proposed and the subdomain method is applied to calculate the magnetic field. Then, according to the developed model, the tangential thrust and normal forces are calculated based on the Maxwell stress theory. Numerical results are subsequently obtained by finite-element method and employed to validate the analytical model. Finally, an LPMSM prototype is manufactured and experiments are conducted. The results show that the developed analytical model has high accuracy for predicting the magnetic field and forces.
On-Chip Thermal Management With Microchannel Heat Sinks and Integrated Micropumps

Liquid-cooled microchannel heat sinks are regarded as being amongst the most effective solutions for handling high levels of heat dissipation in space-constrained electronics. However, obstacles to their successful incorporation into products have included their high pumping requirements and the limits on available space which precludes the use of conventional pumps. Moreover, the transport characteristics of microchannels can be different from macroscale channels because of different scaling of various forces affecting flow and heat transfer. The inherent potential of microchannel heat sinks, coupled with the gaps in understanding of relevant transport phenomena and difficulties in implementation, have guided significant research efforts towards the investigation of flow and heat transfer in microchannels and the development of microscale pumping technologies and novel diagnostics. In this paper, the potential and capabilities of microchannel heat sinks and micropumps are discussed. Their working principle, the state of the art, and unresolved issues are reviewed. Novel approaches for flow field measurement and for integrated micropumping are presented. Future developments necessary for wider incorporation of microchannel heat sinks and integrated micropumps in practical cooling solutions are outlined
Confidential power supply and storage capacity calculation of the active distribution network planning

Confidential power supply and storage capacity (CPSSC) is the random variable of the power supply and storage capacity (PSSC). Its probability distribution is related to power and capacity of energy storage and probability distribution of uncontrollable DG and load in the autonomous regions. Its distribution function and density function can be derived by cumulant method and Gram-Charlier series expansion. CPSSC indicates the supply capacity and storage capacity range from a region to other regions. With CPSSC, network constraints and specific confidential level, both the rated and reserve power and capacity of energy storage can be confirmed in the active distribution network (ADN) by the proposed planning method. And the confidential level is variable according to the planning demand of different ADN autonomous regions. In the end a study case shows the effectiveness of the proposed method.
Active distribution network regional distributed energy resourceconsumption

The high penetration of distributed energy resources (DERs) causes huge pressure on the operation and management. In this paper, the distribution network is divided into regions based on the sectionalizing switch position. Each region receives the optimization goal from global optimal power flow (OPF) algorithm. Regional optimization algorithm is based on the indicator of feeder control error (FCE)[1] which offers the deviation between the aim of region exchange power and actual value. In region algorithm, local topology is only considered to eliminate the FCE quickly using DC power flow. When one region cannot reach the target, adjacent region will communicate with each other to reach the target of a larger region. This algorithm can make the most of renewable energy resource and realize the optimal regional economy. The effectiveness of regional DER consumption is verified by theoretical analysis and simulation.
Modeling of Product Development Management in Virtual Enterprise Based on Unified Modeling Language

Manufacturing enterprises are seeking more advanced and more effective manufacture method and management mode in order to meet the requirements of market. Virtual Enterprise as the important framework of agile manufacturing system has become the main evolvement goal of manufacturing enterprises. Virtual Enterprise comprises several member enterprises, so Virtual Enterprise can eliminate the restriction of technology and resources in the independent enterprise. Manufacture efficiency and quality of product can be enhanced. Obviously, the product development management is a very important task of Virtual Enterprise. Authors put forward applying the Unified Modeling Language to establishing the visual model of product development management in Virtual Enterprise. Moreover, authors set forth the detailed modeling methods and processes of Use Case Diagram, Activity Diagram, Sequence Diagram and Collaboration Diagram. Then the visual model can be integrated with the Diagrams. According to the visual model, the product development management in Virtual Enterprise can be arranged rationally, and then the manufacture efficiency can be enhanced markedly.
Formal modeling and verification of flexible load control for power grid CPS based on differential dynamic logic

In this paper, we proposed a formal modeling and verification method of CPS flexible load control strategy based on differential dynamic logic theory. HybridUML is used to construct the model for critical control process of flexible load in power grid. Based on the differential dynamic logic theory, the formalization protocol is created using the automatic hybrid reasoning tool KeYmaera, and the differential dynamic logic calculus rules are applied to formalize the system attributes. The effectiveness of the method is verified by instantiating the typical application scenario of flexible load.
Cast Shadow and Reflection Image Suppressing of Dynamic Object Segmentation with Edge Features Kernel Density Estimation

In image analysis or vision understanding systems, the accuracy of segmentation results affects the quality of the systems seriously. The dynamic cast shadows and reflection images are ever-present fake objects in dynamic object segmentation, and they deteriorate the segmentation quality seriously. This paper presents a technique for cast shadow and reflection image suppressing of dynamic objects segmentation in videos. This technique is based on dynamic edge features and kernel density estimation. Unlike the classic kernel density estimation model which can only suppress cast shadows in color videos, this model can also suppress them in intensity videos, and with normal conditions it can suppress reflection images effectively. Although this technique introduces a little drawback of true object segmentation quality, its ability of fake objects suppressing is remarkable. Several experimental results with real videos are presented to demonstrate the effectiveness of this model.
A double phase-shift control strategy for a full-bridge three-level DC/DC converter

In this paper, a double phase-shift control strategy is proposed for the full-bridge three-level (FBTL) DC/DC converter applied into DC distribution systems with the medium DC bus voltage. By utilizing the proposed control strategy, the voltage change rate dv/dt and voltage stress of the transformer can be effectively reduced, which means that the reliability and EMC of the FBTL DC/DC converter can be improved. The operation principle and performances of the proposed control strategy is analyzed in detail. Finally, the simulation results are presented to verify the proposed control strategy.
Studies on the Measuring Method of Number Density of Ions in the High Speed Flow Field

At present, the method of using a parallel-plate probe to measure the number density of ions at atmosphere has some limitations such as big size of probe, low velocity of gas flow allowed to measure, and low accuracy. In this paper, a detector with a spherical probe is fabricated and is used to measure the number density of ions. The diameter of probe can be reduced to 6 mm. The highest velocity that can be measured is extended to 28 m/s, and the collecting rate is up to 100%. The spatial distribution diagram of ion number density is also given, with a cross section of 0.36 m2. Then, an effective method is provided to measure the number density of ions generated from the miniature ion source or in the gas flow with high velocity.
Analysis of reflection noise in RSOA based WDM PON

In reflective semiconductor optical amplifier (RSOA) based wavelength division multiplexing passive optical network (WDM-PON) system, reflection noise is a major factor impact on system performance. In this paper, a model experimental system is set up, in order to analyze various types of reflection noise in WDM-PON system, especially focus on the reflection noise and system performance of WDM-PON with 1.25Gb/s downstream line rate, 155Mb/s upstream line rate.
Attack behavioural analysis and secure access for wireless Access Point (AP) in open system authentication

With the rapid development of public service of wireless network, the quantities of free Access Points (APs) in open system authentication increase explosively. However, the security problems also raise prominent, especially, personal privacy disclosure brought by fake APs. We analyze the attack behaviors of the intruders. It is proved that open free AP can be attacked successfully by fake AP, compromised AP and spider AP. One type of fake AP attack (a software of airhack is developed) has been implemented to attack auto-reconnect method of legal AP and launched in real environment effectively. In order to ensure secure and trusted access, a new access method for AP in open system authentication is analyzed and improved to defense spider AP. This method is verified by the real typical instance of airhack.
Design of a Novel Acid-Sensing Biosensor Based on Taste Neurons and LAPS

A novel biosensor based on the platform of neuron- silicon interface was designed and characterized. Taste receptor cells cultured on light addressable potentiometric sensor (LAPS) can recognize sour stimuli as compared with non-acid solutions. A computational model of taste receptor cells was constructed to simulate the ionic currents and action potentials of taste receptor cells, to help decode extracellular signals recorded by LAPS. This study provides the prototype of a novel biosensor which deploys the sensory transduction and decoding mechanism from biology to realize chemosensing, potentially in a noninvasive and long- term manner.
Accelerating HMMer on FPGAs using systolic array based architecture

HMMer is a widely-used bioinformatics software package that uses profile HMMs (Hidden Markov Models) to model the primary structure consensus of a family of protein or nucleic acid sequences. However, with the rapid growth of both sequence and model databases, it is more and more time-consuming to run HMMer on traditional computer architecture. In this paper, the computation kernel of HMMer, P7Viterbi, is selected to be accelerated by FPGA. There is an infrequent feedback loop in P7Viterbi to update the value of beginning state (B state), which limits further parallelization. Previous work either ignored the feedback loop or serialized the process, leading to loss of either precision or efficiency. Our proposed syslolic array based architecture with a parallel data providing unit can exploit maximum parallelism of the full version of P7Viterbi. The proposed architecture speculatively runs with fully parallelism assuming that the feedback loop does not take place. If the rare feedback case actually occurs, a rollback mechanism is used to ensure correctness. Results show that by using Xilinx Virtex-5 110T FPGA, the proposed architecture with 20 PEs can achieve about a 56.8 times speedup compared with that of Intel Core2 Duo 2.33GHz CPU.