nils-herrmann/clean_scirepeval huggingface dataset:
Synthesis for Width Minimization in the Single-Electron Transistor Array

Power consumption has become one of the primary challenges to meetMoore's law. For reducing power consumption, single-electron transistor (SET) at room temperature has been demonstrated as a promising device for extending Moore's law due to its ultralow power consumption in operation. Previous works have proposed automated mapping approaches for SET arrays that focused on minimizing the number of hexagons in the SET arrays. However, the area of an SET array is the product of the bounded height and the bounded width, and the height usually equals the number of inputs in the Boolean function. Consequently, in this paper, we focus on the width minimization to reduce the overall area in the mapping of the SET arrays. Our approach consists of techniques of product term minimization, branch-then-share (BTS)-aware variable reordering, SET array architecture relaxation, and BTS-aware product term reordering. The experimental results on a set of MCNC and IWLS 2005 benchmarks show that the proposed approach saves 45% of width compared with the work by Chiang et al., which focused on hexagon count minimization, and also saves 13% of width compared with the work by Chen et al., which focused on width minimization.
An adaptive fuzzy control for robotic manipulators

In this paper, an adaptive fuzzy control strategy is developed for robotic manipulators to guarantee both global stability and performance. A controller output error method (COEM) is introduced and applied to the design of adaptive fuzzy control system. The proposed control strategy employs a gradient descent algorithm to minimize a cost function which is based on the error of the controller output and is minimized by tuning some or all of the parameters of fuzzy controller. The simulation results show that the proposed control is effective and yields superior tracking performance.
Design of Power System Harmonic Measurement System Based on LabVIEW

Harmonic measurement plays an important part in power systems. In this paper, a brief introduction on sources and harms of harmonics is given. A harmonic measurement method based on interpolating windowed FFT is proposed and analyzed. According to the analytic results, a multifunctional virtual instrument system for harmonic measurement of voltage and current signals is designed and implemented in LabVIEW environment. Furthermore, the function of remote transfer of measured results is implemented using the AppletVIEW Toolkit in LabVIEW adopting a B/S framework. Measurement results show the feasibility and validity of the system.
Layered wireless video multicast using omni-directional relays

Wireless video multicast enables delivery of popular events to many wireless users in a bandwidth efficient manner. However, providing good and stable video quality to a large number of users with varying channel conditions remains elusive. We propose to integrate layered video coding with cooperative communication to enable efficient and robust video multicast in infrastructure-based wireless networks. We determine the user partition and transmission time scheduling that can optimize a multicast performance criterion.
Perceptual video quality assessment on a mobile platform considering both spatial resolution and quantization artifacts

In this paper, we investigated the impact of spatial resolution and quantization on the perceptual quality of a compressed video coded from the SVC reference software - JSVM. Two subjective quality tests have been carried out on the TI Zoom2 mobile development platform (MDP). 5 different spatial resolutions (i.e., from QCIF to 4CIF) and 4 different quantization levels (i.e., QP 22, 28, 36, 44) are chosen to create the processed video sequences (PVS) from 7 different video sources. First test focuses on the effect of spatial resolution at fixed QP 22, while second test explores the impact of both spatial resolution and quantization artifacts. Videos coded at different spatial resolutions are displayed at the full screen size of the mobile platform. We report the test results in terms of how MOS reduces as the spatial resolution decreases at constant QP, and how MOS reduces as QP increases under the same spatial resolution. We found that the dropping rate of the MOS vs. spatial resolution increases as QP increases and the dropping rate of the MOS vs. QP increases as spatial resolution reduces. In addition, the dropping rate against spatial resolution is faster when the video is changing in a lower motion speed; while the dropping rate against QP is faster when the video has less texture details. Also, the dropping rate of MOS against spatial resolution can be captured by a one-parameter falling exponential function in most of cases.
Direct Torque Control for Permanent-Magnet Synchronous Machines Based on Duty Ratio Modulation

This paper proposes a novel duty ratio modulated direct torque control (DDTC) to concurrently reduce torque ripple and stator flux ripple that are typically associated with conventional direct torque control (DTC). Three different methods of duty ratio determination are presented to achieve various control objectives, namely DDTC-final, DDTC-mean and DDTC-rms. Additionally, adjustable error weight coefficients are introduced to balance the torque ripple reduction and stator flux ripple reduction. Experimental results are presented to validate the effectiveness of proposed DDTC. Furthermore, the comparative evaluation of proposed DDTC, conventional DDTC and DTC is conducted on the basis of several criteria to verify the superiority of proposed DDTC.
Cross Layer Adaptation for H.264 Video Multicasting Over Wireless Lan

This paper describes cross-layer optimization strategies and simulation results for H.264 video multicast over wireless LAN. The proposed scheme takes into account the varying channel conditions of multiple users, and dynamically allocates available bandwidth between source coding and channel coding. In particular, source coding parameters (intra update and quantization) and application-layer FEC code rate are chosen jointly to optimize a multicast performance criterion, based on feedbacks from all multicast receivers. Two performance criteria for video multicast are investigated and compared
Research on community discovery of CSLN

CSLN is the citation semantic link network that combines the citation network and the semantic network. CSLN model not only makes the citation network to have semantics, but also make the citation network to have reasoning ability. This paper firstly gives the theory foundation of the community discovery research of CSLN. Then the paper gives the overall design of the community discovery of CSLN that construct SCLN, calculate the semantic similarity between citations and reveal the semantic community of CSLN. Finally, the experiment verifies the effectiveness and feasibility of the community discovery method of the CSLN. The community discovery research of CSLN not only can find the cutting-edge issues in different research fields, but also has very important significance to forecast the future development direction and research hotspot of research field.
Modeling and simulation of MPEG-2 video transport over ATM networks considering the jitter effect

In this paper, the operation of MPEG-2 systems is modeled and simulated when an MPEG-2 transport stream is delivered through a ATM network with jitter. A novel approach to analyzing the decoder buffer behavior in the presence of network jitter is presented. The probability density function of the interarrival time of the ATM adaptation layer 5 (AAL5) Protocol Data Unit (PDU) is derived from a MPEG-2 video source model and an ATM network jitter model. Based on a real-time decoding requirement of the MPEG-2 transport stream (TS) system target decoder (T-STD), the decoder buffer behavior is simulated. The modeling; and simulation results show that jitter affects decoder buffer size and packet loss ratio in a significant way.
Improved Mach Zehnder Optical Modulators with Modified Ridge Structure

Mach Zehnder type optical modulators with modified ridge structure on a coplanar waveguide traveling wave electrode are investigated by the use of finite element method and BPM CAD waveguide software. The two ends of conventional ridge structure added taped ridge structures is considered, the transmission loss is obviously reduced. It is shown that the device increased modified ridge structure can efficiently reduce the transmission loss and the extinction ratio at the same output waveguide. In other words, the optical properties of Mach Zehnder type optical modulator with modified ridge structure on a coplanar waveguide traveling-wave electrode are obviously enhanced
Multi-moving targets detecting and tracking in a surveillance system

Aiming at the selection and refreshment of background, moving objects detecting, sequence matching, research on multi-moving targets detecting and tracking based on single fixed camera was performed. Firstly, a recursive filter in temporal domain to form the reference image for adaptive background updating was highlighted. Then foreground was separated from background based on difference between reference image and current image. Secondly, moving regions in foreground were extracted through analysis on connected binary foreground image. Detected binary regions were then grouped into moving targets based on fuzzy clustering analysis. Thirdly, an extended Kalman filter and C-constant velocity Kalman tracking algorithm were presented for the matching and tracking multi-moving targets represented by region. Finally, experiments on outdoors video streams have demonstrated the significant performance of proposed strategies.
A Limited-Client-Capability Broadcasting Scheme for VoD Applications

Data broadcasting is independent of client arrival rate, and thus it is very suitable to transmit popular videos that interest many clients at a particular period of time. One broadcasting method (called periodic broadcasting) is to partition a video into segments, which are then simultaneously broadcast on several data channels. Once clients want to watch the video, they download the segments from these channels. Specially, the skyscraper broadcasting (SkB), client-centric approach (CCA), greedy disk-conserving broadcasting (GDB) schemes were proposed to support a client with a small bandwidth. This paper presents a limited-client-capability broadcasting (LCCB) scheme, which achieves small waiting time, bandwidth consumption, and buffer demand on the client side. In comparison with SkB, CCA, and GDB, LCCB gains smaller waiting time. Extensive simulation results indicate that LCCB also requires lower client buffer spaces than SkB, CCA, and GDB.
A bottle finish inspect method based on fuzzy support vector machines and wavelet transform

Bottle finish chinks are regarded as the most critical defects of bottles adopted in food and beverage production. This paper presents a bottle finish inspecting methods. An algorithm based on probability and statistic is applied for determination of region of interest. For extracting feature, the circular law is used to carry on the scanning, and then the 1D wavelet transform is performed. The fuzzy support vector machines are used as classifiers, which synthesize the fuzzy theory and SVMs. At the same time an optimization algorithm based on genetic algorithm is proposed to confirm the parameters of the fuzzy support vector machines in this paper, and it ensure that the fuzzy SVMs have good classification ability. The proposed algorithms are proved to be efficient in automatic finish inspection.
A novel nested graph cuts method for segmenting human lymph nodes in 3D high frequency ultrasound images

Three-dimensional (3D) quantitative-ultrasound (QUS) methods were recently developed and successfully applied to detect cancerous regions in freshly-dissected lymph nodes (LNs). The 3D high frequency ultrasound (HFU) images obtained from these LNs contain three different parts: LN-parenchyma (LNP), fat, and phosphate-buffered saline (PBS). To apply QUS estimates inside the LNP region, an automatic and accurate algorithm for LNP segmentation is needed. In this paper, we describe a novel, nested-graph-cut (NGC) method that effectively exploits the nested structure of the LN images. To overcome the large variability of the intensity distribution of LNP pixels due to acoustic attenuation and focusing, we further describe an iterative self-updating framework combining NGC and spline-based robust intensity fitting. Dice similarity coefficients of 89.56±8.44% were achieved when the proposed automatic segmentation algorithm was compared to expert manual segmentation on a dataset consisting of 115 LNs.
Screen content image segmentation using least absolute deviation fitting

We propose an algorithm for separating the foreground (mainly text and line graphics) from the smoothly varying background in screen content images. The proposed method is designed based on the assumption that the background part of the image is smoothly varying and can be represented by a linear combination of a few smoothly varying basis functions, while the foreground text and graphics create sharp discontinuity and cannot be modeled by this smooth representation. The algorithm separates the background and foreground using a least absolute deviation method to fit the smooth model to the image pixels. This algorithm has been tested on several images from HEVC standard test sequences for screen content coding, and is shown to have superior performance over other popular methods, such as k-means clustering based segmentation in DjVu and shape primitive extraction and coding (SPEC) algorithm. Such background/foreground segmentation are important pre-processing steps for text extraction and separate coding of background and foreground for compression of screen content images.
The intelligent multimodal pressure control of diamond synthesis process for cubic hinge press

In order to improve the quality and yield of synthetic diamond using Y-500 cubic hinge press, a novel intelligent control in synthesis process was studied deeply in this paper. After both classical and new technical automatic synthesis processes were analyzed, the characteristics and current situation of control of pressure plant were discussed. Then an intelligent multimodal pressure control method is proposed. The proposed method divides the precise control process of rising and holding pressure into three phases according to the characteristics of dynamic information, and the compound control is used. Further more, the switch control, the fuzzy control and the proportional plus intermittent intelligent integral control are applied to different phase respectively, and the rules of online expert segmentation identification and switching are established, thus, the control mode can change with the segment and perform smoothly. Finally the proposed method is applied to control system of Y-500 cubic hinge press, and excellent pressure tracking performance is achieved, thus its feasibility is proved too.
Perturbations of Compressed Data Separation With Redundant Tight Frames

In the era of big data, the multi-modal data can be seen everywhere. Research on such data has attracted extensive attention in the past few years. In this paper, we investigate the perturbations of compressed data separation with redundant tight frames via <inline-formula> <tex-math notation="LaTeX">$\tilde {\boldsymbol {\Phi }}\text {-}{\ell _{q}}$ </tex-math></inline-formula>-minimization. By exploiting the properties of the redundant tight frame and the perturbation matrix, i.e., mutual coherence, null space property, and restricted isometry property, the condition on reconstruction of sparse signal with redundant tight frames is established, and the error estimation between the local optimal solution and the original signal is also provided. Numerical experiments are carried out to show that <inline-formula> <tex-math notation="LaTeX">$\tilde {\boldsymbol {\Phi }}\text {-}{\ell _{q}}$ </tex-math></inline-formula>-minimization is robust and stable for the reconstruction of sparse signal with redundant tight frames. To our knowledge, our works may be the first study concerning the perturbations of the measurement matrix and the redundant tight frame for compressed data separation.
Improving SNR of MFL Signal in Flaw Detection of Coal Mine Wire Ropes

Magnetic flux leakage detection (MFL) is widely used as an effective method in detection of broken wires of ropes. In order to improve the accuracy of flaw detection using MFL signal, the effect of the distance between a sensor and the surface of a wire rope (i.e. lift-off) is investigated. The main principles for the choice of lift-off are analyzed, and a method is proposed from the point of view of the magnetic circuit design to restrain the impact of fluctuations of sensor lift-off and improve the signal-to- noise ratio (SNR) of MFL signal. The method is validated through computer simulation and laboratory experiment. The results show that the SNR of MFL signal in flaws detection of wire ropes can be increased by over 25%.
Majority logic circuits optimisation by node merging

Quantum-dot Cellular Automata (QCA) has emerged as a new design paradigm for nanotechnologies. Since the operational logic in QCA is the majority logic, much research about the synthesis and optimisation of majority logic has been proposed recently. In this paper, we propose an optimisation method by merging nodes in the Majority-Inverter-Graph, which is the representation of majority logic circuits. Instead of using satisfiability solvers, our approach can identify the node mergers by using logic implications for circuit size reduction. The experimental results show that for a set of EPFL benchmarks, our approach can minimise the node count by 21% when integrated with the state-of-the-art on average.
Adaptive robust RBFNNs-based model estimator for a small quadrotor aircraft robot

This paper presents an on-line estimator that incorporates adaptive MIMO radical basis function neural networks (RBFNNs) for model identification of quadrotor unmanned aerial vehicles (UAVs). The inputs and outputs of quadrotor aircrafts can be obtained from dynamic models or real attitude and position sensors. The adaptive learning rate is employed in the gradient descent method for the update of the weights of RBFNNs, and Lyapunov approach guarantees the stability of the global convergence of the modeling errors. The Welsch functions are also employed as the error functions to get rid of the influence from the noise due to disturbances like wind gusts. Simulation results using Robotics Toolbox for Matlab verify the effectiveness and robustness of the proposed estimator compared with results of traditional RBFNNs. Experiment results from real aircraft platform show that RBFNNs combining adaptive learning rate and Welsch error functions can approximate the overall system with high accuracy and robustness to disturbances.
Multiobjective Optimization of HEV Fuel Economy and Emissions Using the Self-Adaptive Differential Evolution Algorithm

This paper describes the application of a novel multiobjective self-adaptive differential evolution (MOSADE) algorithm for the simultaneous optimization of component sizing and control strategy in parallel hybrid electric vehicles (HEVs). Based on an electric assist control strategy, the HEV optimal design problem is formulated as a nonlinear constrained multiobjective problem with competing and noncommensurable objectives of fuel consumption and emissions. The driving performance requirements are considered constraints. The proposed MOSADE approach adopts an external elitist archive to retain nondominated solutions that are found during the evolutionary process. To preserve the diversity of Pareto optimal solutions, a progressive comparison truncation operator based on the normalized nearest neighbor distance is proposed. Moreover, a fuzzy set theory is employed to extract the best compromise solution. Finally, the optimization is performed over the following three typical driving cycles that are currently used in the U.S. and European communities: 1) the file transfer protocol; 2) ECE+EUDC; and 3) Urban Dynamometer Driving Schedule. The results demonstrate the capability of the proposed approach to generate well-distributed Pareto optimal solutions of the HEV multiobjective optimization design problem. The comparison with the reported results of genetic-algorithm-based weighting sum approaches and Nondominated Sorting Genetic Algorithm II reveals the superiority of the proposed approach and confirms its potential for optimal HEV design.
Speaker Identification Using Discriminative Features and Sparse Representation

Speaker identification is an important topic with relevance to various disciplines. This paper proposes a novel speaker identification system, which consists of two major components—feature extraction and sparse representation classifier (SRC). Although SRC has been utilized for many classification purposes, few studies have provided insight into the link between the commonly used speaker identification feature, i-vector, and SRC. To combine i-vector and SRC sufficiently, we use probabilistic principal component analysis and Bartlett test to extract high-quality i-vector to construct a discriminative dictionary in SRC, supporting effective speaker identification. Besides improving dictionary from the i-vector aspect, we also utilize dictionary learning to further enhance the content of the dictionary. Two learning methods are proposed—robust principal component analysis dictionary and SVD-dictionary. Furthermore, we propose constructing a noise dictionary and combine it with the original dictionary to absorb and suppress noise when implementing the sparse coding. Various coding methods are utilized and analyzed. A comparison to the methods for speaker identification reveals that the proposed method outperforms the baselines and confirms its feasibility.
Notice of RetractionApplication of sketchup in the teaching of landscape design of undergraduate college

While a number of existing researches focus on the application of CAD, Potoshop and 3DMAX in the teaching of landscape design, this study probes into the application of sketchup software in the teaching, thus promoting the improvement of the teaching quality of landscape design. This study analyzed misunderstandings in the teaching of landscape design, and the application of sketchup in landscape design in the light of its specific use. The results showed that sketchup software is remarkable in six aspects, which are design concept, space design, global design, real-time rendering, usability, and data interchange. Sketchup has a bright prospect of application in the teaching of landscape design due to its focus on landscape design process and its good usability. Therefore, it is essential to offer sketchup courses in the major of landscape design and relevant majors in universities. The application of sketchup in landscape design courses can lead designers back to the traditional working style of coherent design and presentation, instead of merely focusing on design results, so as to effectively improve the efficiency of landscape design teaching.