nils-herrmann/clean_scirepeval huggingface dataset:
AB network adjust the step and the hidden-layer neurons algorithm based on BP network

For the classical BP algorithm has some deficiencies, such as the accuracy is insufficient, the rate of convergence does not descend, weight value closes to zero. This paper proposes the AB neural network to adjust the step and the hidden-layer neurons algorithm based on BP network. Network A with learning ability configures and adjusts the structure of Network B and trains it, by adjusting the step and the hidden-layer neurons of Network B, obviously enlarge the modification of weight to escape from flat region. The introduction of “prior knowledge” made training of Network B intelligently and automatically. The simulation results of Sin Function shows that the proposed method can effectively speed up the multilayer feed-forward neural network training process.
A study on CT sinogram statistical distribution by information divergence theory

In low-dose X-ray computed tomography (CT) image reconstruction, accurate modeling of the statistical properties of the measured data (i.e., both the transmission data and the sinogram data after linearity calibration) is essential to achieve high diagnostic image quality. By current X-ray CT systems, the acquired transmission data can be described by a compound Poisson distribution upon an electronic noise background. Such a statistical distribution is numerically intractable for image reconstruction. On the other hand, the sinogram data can be easily manipulated for image reconstruction, but lack a statistical description for optimal reconstruction in low-dose applications. In this paper, we propose the use of information divergence theory to describe the statistical distribution of the sinogram data. Specifically, the αdivergence, as a typical example, is adapted to fit the low-dose CT sinogram data. To minimize the associated cost function for frequency curve fitting, the exponential functional family was chosen and the Minka's fixed-point numerical calculation scheme was employed. By repeatedly scans from an anthropomorphic torso phantom at several mAs levels from normal- to low-dose imaging, the corresponding α values were fitted. As the mAs level increased toward normaldose imaging, the corresponding α value approached to favor a normal distribution, as expected. As the mAs level decreased toward low-dose imaging, the corresponding a value approached to deviate away from a normal distribution. These experimental observations indicated that the αdivergence measure can describe the statistical distributions of the sinogram data and, therefore, has the potential to be a cost function for statistical reconstruction of low-dose CT images.
Characterizations of double-gate SBTT studying by a 2-D full-band Monte Carlo device simulator

A double-gate Schottky barrier tunneling transistor (DGSBTT) structure is investigated by a 2-D full-band Monte Carlo device simulator. A Schottky barrier contact model including tunneling effect and Schottky effect has been implemented in this simulator. The result shows that DGSBTF has a big performance improvement compare to single gate SBTT, its Ion/Ioff is more than 10/sup 5/ at Vds= 1.0 V.
A Motion Retargeting Method for Topologically Different Characters

In this paper, we present a real-time method for motion retargeting between topologically different characters. An intermediate skeleton is used for setting correspondence between nodes of the source skeleton and the target skeleton. When animal-to-human motion retargeting is performed, segment lengths of the intermediate skeleton are adjusted to address the problem such as upper limbs unable to reach the ground. To get a satisfactory motion, an improved adaptation principle based on end effector constraints is introduced for eliminating undesirable phenomena.
A cloud service architecture for analyzing big monitoring data

Cloud monitoring is of a source of big data that are constantly produced from traces of infrastructures, platforms, and applications. Analysis of monitoring data delivers insights of the system's workload and usage pattern and ensures workloads are operating at optimum levels. The analysis process involves data query and extraction, data analysis, and result visualization. Since the volume of monitoring data is big, these operations require a scalable and reliable architecture to extract, aggregate, and analyze data in an arbitrary range of granularity. Ultimately, the results of analysis become the knowledge of the system and should be shared and communicated. This paper presents our cloud service architecture that explores a search cluster for data indexing and query. We develop REST APIs that the data can be accessed by different analysis modules. This architecture enables extensions to integrate with software frameworks of both batch processing (such as Hadoop) and stream processing (such as Spark) of big data. The analysis results are structured in Semantic Media Wiki pages in the context of the monitoring data source and the analysis process. This cloud architecture is empirically assessed to evaluate its responsiveness when processing a large set of data records under node failures.
A novel procedure of TOA estimation in IR UWB ranging in the presence of NBI

Narrowband interference (NBI) is a serious problem in time based ultra wideband (UWB) precise ranging. To suppress it, notch filtering is a practical method. However, the notch filter will distort the desired signal, especially when there are multiple interferences. So when using the matched filter (MF) at the receiver, if we still use the transmitted pulse to match the received signal preprocessed by notch filters, there exist mismatch between the received signal and the template, thus degrading ranging performance. In this study, we use a new template. We pass the transmitted signal through the already designed notch filters and then the output will be the new template. Simulation results verify the effectiveness of NBI suppression by notch filters and the improvement of ranging with the new template.
Comparative Research of Portfolio Model Using Fuzzy Theory

By discussing both linear and nonlinear fuzzy situations, we give the relevant model and the solution method. First of all, regarding the target level of investment return and investment risk as the half trapezoidal fuzzy number, we give the fuzzy portfolio selection model of linear satisfaction degree. Then, to describe the investor satisfaction degree of investment return and investment risk better, a logarithmic membership function has been imported. Following, we give the fuzzy portfolio selection model of nonlinear satisfaction degree. Nonlinear optimize model can be transferred to linear programming model, so that model calculation has been simplified significantly. Finally, according to the actual data of Chinese securities market, both of models have been compared by using genetic algorithm. Result indicates that portfolio selection model based on linear and nonlinear membership function includes not only historical data, but also investors' expectation. That accords with human psychology and fact. However, by adopting the nonlinear membership function and adjusting its parameter, it can furthest get portfolio that accords with investor's expectation. Therefore, nonlinear membership function is better than linear membership function.
Dynamic Policy Based Network Management Scheme in Mobile Environment

A dynamic policy based network management scheme is presented for the problem that traditional policies can¿t preferably adapt to change of network state. It defined dynamic policy form and appended new module PMA to IETF policy frame to improves the adaptability of policie. Then the application of dynamic policy to allocate resource is presented. By experiment and analysis, it is shown that this scheme insures new call blocking probability, reduces handoff call dropping probability and increases network resource utilizing rate effectively.
Benchmark Generation Using Domain Specific Modeling

Performance benchmarks are domain specific applications that are specialized to a certain set of technologies and platforms. The development of a benchmark application requires mapping the performance specific domain concepts to an implementation and producing complex technology and platform specific code. Domain specific modeling (DSM) promises to bridge the gap between application domains and implementations by allowing designers to specify solutions in domain-specific abstractions and semantics through domain specific languages (DSL). This allows generation of a final implementation automatically from high level models. The modeling and task automation benefits obtained from this approach usually justify the upfront cost involved. This paper employs a DSM based approach to invent a new DSL, DSLBench, for benchmark generation. DSLBench and its associated code generation facilities allow the design and generation of a completely deployable benchmark application for performance testing from a high level model. DSLBench is implemented using Microsoft domain specific language toolkit. It is integrated with the Visual Studio 2005 Team Suite as a plug-in to provide extra modeling capabilities for performance testing. We illustrate the approach using a case study based on .Net and C#.
A testbed implementation for Service Based Bearer Control in 3GPP2

The policy and charging control function is defined as PCC (Policy and Charging Control) by 3GPP and SBBC (Service Based Bearer Control) by 3GPP2. It is valuable to establish an experimental testbed for PCC and SBBC to improve and verify the related performance. At present, we can make use of Open Source IMS (OSIMS) and UCT PCF to simulate 3GPP PCC, but there is no testbed for the policy control function of SBBC architecture. In this paper, we implement a new SBBC testbed based on 3GPP PCC Testbed, whose features show that it is closely in line with the specifications of 3GPP2. Several tests are designed to verify various performances of SBBC. The test results show that our SBBC testbed is effective to be used for researches on QoS controlling in future converged networks.
Comparison of continuous and discontinuous Current Source Drivers for high frequency applications

Comprehensive comparison of continuous and discontinuous Current Source Drivers (CSDs) are presented in terms of switching loss reduction, gate energy recovery, range of duty cycle and fast dynamic response. The advantages and disadvantages of the continuous and discontinuous CSDs are summarized. Overall, the discontinuous CSDs achieve better performance over the continuous CSDs. A 12V input, 1.3V/30A output and 1MHz buck converter was built to verify the difference between these two types of the CSDs.
A new discontinuous Current Source Driver for high frequency power MOSFETs

This paper proposes a new Current Source Driver (CSD) with discontinuous inductor current. Compared to other CSDs proposed in the previous work, the most important advantage of the proposed CSD is the small inductance (typically, 20nH at 1MHz switching frequency). This translates into the footprint reduction of as much as 90%. Other features of the proposed CSD includes: 1) fast switching speed and reduced switching loss; 2) discontinuous inductor current with low circulating loss; 3) gate energy recovery; 4) wide range of duty cycle and switching frequency. The experimental results verified the functionality of the proposed CSD. At 1.3V output, the new CSD improves the efficiency from 80.7% using a conventional driver to 85.7% at 25A output, and at 30A output, from 77.9% to 84.4%.
A novel One-cycle control strategy for three-phase power converter

In this paper, a general control approach is presented to achieve power-factor correction (PFC) for three-phase boost rectifiers. By considering the three-phase four-wire topology, the three-phase diode rectifier can be decoupled as independent single phase circuits. Thus the design of the controller is simplified by using the single-phase One-Cycle Control (OCC) with the advantages, such as constant switching frequency, no multipliers, and simple circuitry. Moreover, the block diagram of the proposed OCC controller is derived with some key equations. A 6 kW PFC rectifier was built and tied together using the proposed approach. Experiments and simulation have demonstrated the simplicity and the effectiveness of this method.
Clockless continuous-time neural spike sorting: Method, implementation and evaluation

In this paper, we present a new method for neural spike sorting based on Continuous Time (CT) signal processing. A set of CT based features are proposed and extracted from CT sampled pulses, and a complete event-driven spike sorting algorithm that performs classification based on these features is developed. Compared to conventional methods for spike sorting, the hardware implementation of the proposed method does not require any synchronisation clock for logic circuits, and thus its power consumption depend solely on the spike activity. This has been implemented using a variable quantisation step CT analogue to digital converter (ADC) with custom digital logic that is driven by level crossing events. Simulation results using synthetic neural data shows a comparable accuracy compared to template matching (TM) and Principle Components Analysis (PCA) based discrete sampled classification.
A non-isolated ZVS self-driven current tripler topology for low voltage and high current applications

A new non-isolated ZVS self-driven current tripler topology for high current and low voltage applications is proposed in this paper. The most important advantage of the proposed topology is reduced current stress and conduction losses of the synchronous rectifier (SR) MOSFETs and transformer windings, which is beneficial for high current applications. Other features of the proposed topology are: 1) duty-cycle extension; 2) ZVS of all the control MOSFETs; 3) reduced voltage stress over the SRs and reduced reverse recovery loss; 4) gate energy recovery of SRs and no external drive IC with the dead time control needed. A 12 V input, 1.0 V/50 A output, 1 MHz prototype was built to verify the advantages of the proposed converter.
A static reactive power coordination control strategy of solar PV plant considering voltage and power factor

The operation of large-scale grid-connected solar photovoltaic (PV) plants may cause the voltage fluctuation issue, which will affect the stable operation of power system. In order to reduce the adverse effects and power network loss caused by PV plants, the reactive power control of PV plant is investigated and a novel coordination control strategy considering both voltage and power factor is proposed in this paper. First, the effect of active and reactive power on voltage of interconnection point is analysed. Second, an eleven-zone reactive power control strategy is proposed, while nine-zone reactive power control strategy is always used today, the proposed strategy adopts both voltage and power factor of interconnection point as criterion to conduct respective controlling. At last, based on performance verification platform of solar PV plant power control system developed by authors, the feasibility and correctness of proposed elevenzone reactive power control strategy are proved by practices in a real solar PV plant grid integration project.
Application of GPS technology in frame-signal synchronization system of wireless broadband access

On the basis of adoption precision PPS signal from GPS to synchronize RP subsystem, this article realizes RPC frame-signal synchronization far away by designing Specific GSG module and GPS receiver, which can Optimize the spectrum utilization efficiency. The non-synchronization of RP frame-signal from different RPC and synchronization interference from different low-power base station have been resolved. Reliable technical support can be provided for low-power non-blind-area. It is a feasible and effective method to resolve frame-signal synchronization of wireless broadband access System.
An Uneven Probabilistic Flooding Algorithm for Small-World Wireless Multi-Hop Networks

Concept of small-world is applied in the context of wireless multi-hop networks in this paper. We build a network model by selecting a small part of nodes and magnifying their communication distance. It is proved that this model behaves small-world character, mainly in average path length and clustering coefficient. Based on this model we put forward an uneven probabilistic flooding algorithm. Simulation results show that small-world model outperforms general multi-hop wireless network model greatly in both network coverage and hop count.
Calibration of a robot hand-eye system with a concentric circles target

An approach for a robot hand-eye system calibration is presented using concentric circles target with one pair of orthogonal diameters. The geometric features of vanishing points on the orthogonal diameters are exploited to estimate the camera intrinsic and extrinsic parameters. One diameter is used to estimate the coefficients of the structured light plane. The structured light stripe projected on the circle center and one endpoint of each diameter are used to calculate the target position in the robot workspace and finally the transformation formula is used to obtain the hand-eye relationship. The measurement experimental results verify the calibration method with the measurement average absolute error 0.33mm and the average relative error 0.21%.
A digital power factor correction (PFC) control strategy optimized for DSP

A predictive algorithm for digital control power factor correction (PFC) is presented in this paper. Based on this algorithm, all of the duty cycles required to achieve unity power factor in one half line period are calculated in advance by digital signal processors (DSP). A boost converter controlled by these precalculated duty cycles can achieve sinusoidal current waveform. One main advantage is that the digital control PFC implementation based on this control strategy can operate at a high switching frequency which is not directly dependent on the processing speed of DSP. Input voltage feed-forward compensation makes the output voltage insensitive to the input voltage variation and guarantees sinusoidal input current even if the input voltage is distorted. A prototype of boost PFC controlled by a DSP evaluation board was set up to implement the proposed predictive control strategy. Both the simulation and experimental results show that the proposed predictive strategy for PFC achieves near unity power factor.
A new analysis and design method for fuzzy logic controllers used in power converter

This paper proposes a novel design procedure of fuzzy logic controller (FLC) for DC-to-DC converters that integrates linear control techniques with fuzzy logic. The design procedure allows the small signal model of power converters and linear control design techniques to be used in the initial stages of FLC design. This simplifies the small signal design and the stability assessment of the FLC. By exploiting the fuzzy logic structure of the controller, heuristic knowledge is incorporated into the design, resulting in a non-linear controller with improved large signal performance over linear PI controllers
Double integral sliding mode control of paralleled dc/dc converters

The use of dc-dc converters connected in parallel is a suitable way to solve the technological problems that arise in large-capability power supply systems. This paper presents a new approach to parallel converters using double integral sliding mode control. This approach could alleviating the steady-state regulation error and enhancing dynamic current-sharing property by increasing the order of the proportional integral sliding mode (ISM) controllers using an additional integral term. Theoretical analysis and simulation results are provided for verification.
Chaotic Time Series Analysis of Pressure Fluctuation Signals in a Fluidized Bed Evaporator of Natural Circulation

In this study, the fluidized bed evaporator of natural circulation with different the holdup of solid particle are experimental studied. The holdup of solid particle, pressure fluctuation signals and heat flux are measured. Analyses of chaotic time series on pressure fluctuation signals are conducted to determine the relationship between chaotic characterizations parameter. The values of Kolmogorov entropy are positive and finite, and the values of correlation dimension are from 1.0 to 2.2. The analysis results indicate that the physical parameter fluctuations of the system with the FBENC are chaotic. In the estimations of chaotic invariants including correlation dimension, Kolmogorov entropy and Lyapunov exponent at the same given operation condition, the multi-value phenomena are found. The phenomenon reflects the multi-scale behavior occurred in such multi-phase flow boiling systems.
Design of Interpolative Sigma Delta Modulators Via Semi-Infinite Programming

This correspondence considers the optimized design of interpolative sigma delta modulators (SDMs). The first optimization problem is to determine the denominator coefficients. The objective of the optimization problem is to minimize the passband energy of the denominator of the loop filter transfer function (excluding the dc poles) subject to the continuous constraint of this function defined in the frequency domain. The second optimization problem is to determine the numerator coefficients in which the cost function is to minimize the stopband ripple energy of the loop filter subject to the stability condition of the noise transfer function (NTF) and signal transfer function (STF). These two optimization problems are actually quadratic semi-infinite programming (SIP) problems. By employing the dual-parameterization method, global optimal solutions that satisfy the corresponding continuous constraints are guaranteed if the filter length is long enough. The advantages of this formulation are the guarantee of the stability of the transfer functions, applicability to design of rational infinite-impulse-response (IIR) filters without imposing specific filter structures, and the avoidance of iterative design of numerator and denominator coefficients. Our simulation results show that this design yields a significant improvement in the signal-to-noise ratio (SNR) and have a larger stability range, compared with the existing designs
A micro-pressure sensor with high sensitivity and overload resistance

Presented is a piezoresistive absolute micro-pressure sensor, which features relatively high sensitivity and overload resistance simultaneously. In this investigation, the design, fabrication and testing of the sensor are carried out. By analyzing the stress distribution on sensitive elements using the finite-element method (FEM), an improved structure through introduction of sensitive beams and islands is built up. The proposed configuration presents its advantages in terms of sensitivity and overload resistance compared with the bossed diaphragm and plane diaphragm structures. The sensor is fabricated based on silicon bulk micromachining technology, and the processing is discussed. Testing results demonstrate the sensor features a relatively high sensitivity of 16.544 μV/V/Pa in the operating range of 500 Pa at room temperature, and a proper overload resistance of 200 times overpressure. Due to the favorable characteristics, the sensor can be utilized in measuring absolute micro pressure.