nils-herrmann/clean_scirepeval huggingface dataset:
Dictionary Integration Using 3D Morphable Face Models for Pose-Invariant Collaborative-Representation-Based Classification

The paper presents a dictionary integration algorithm using 3D morphable face models (3DMM) for pose-invariant collaborative-representation-based face classification. To this end, we first fit a 3DMM to the 2D face images of a dictionary to reconstruct the 3D shape and texture of each image. The 3D faces are used to render a number of virtual 2D face images with arbitrary pose variations to augment the training data, by merging the original and rendered virtual samples to create an extended dictionary. Second, to reduce the information redundancy of the extended dictionary and improve the sparsity of reconstruction coefficient vectors using collaborative-representation-based classification (CRC), we exploit an on-line class elimination scheme to optimise the extended dictionary by identifying the training samples of the most representative classes for a given query. The final goal is to perform pose-invariant face classification using the proposed dictionary integration method and the on-line pruning strategy under the CRC framework. Experimental results obtained for a set of well-known face data sets demonstrate the merits of the proposed method, especially its robustness to pose variations.
Motor imagery classification based on the optimized SVM and BPNN by GA

Brain-computer interface (BCI) is a specific Human-Computer interface in which the brain wave is employed as the carrier of control information. The ultimate goal of BCI is to build a direct communication pathway between human brain and external environment that does not depend on the limb mobility and language. In this paper, we carry out the experiment about the left or right hand motor imagery, and support vector machine with genetic algorithm(GA-SVM) and back propagation neural network with genetic algorithm (GA-BP) are employed to classify the μ rhythm evoked by movement imagination. The experiment results prove that GA-SVM can easily find out the appropriate parameters of SVM and GA-BP can avoid getting into local minimization to great extend. So higher accuracy of classification is achieved.
Design and performance of a microstrip reflectarray antenna

Microstrip reflectarray antennas present an alternative to conventional directive antennas in that they are flat, inexpensive, easy to install and manufacture, conformal to the mounting surface, easy to package, and they possess high power and beam steering capabilities. For the first time, a comprehensive, experimentally verified design procedure for the microstrip reflectarray is presented. In this design procedure, the microstrip reflectarray has been shown to be an effective linear array capable of beam switching and dual polarization. The design procedure also allows the array to be fed from a feed-horn offset at any given angle to the plane of the array. The design procedure is well suited for CAD programs.
Automatic Detection and Tracking of Maneuverable Birds in Videos

In this paper, we try to detect and track maneuverable birds in captured videos for further automatic research. To avoid abrupt scene change, videos are captured by pointing the camera upwards and making the image against the sky. Two levels (pixel level and frame level) background update algorithm is used to get the foreground in real time. In frame level, three thresholds are used to update the background to achieve fast background update under abrupt scene changing. Targets are detected from the binary foreground after retrieving contours, size filter and margin measure. The tracking of maneuverable birds is achieved by using a Markov chain Monte Carlo (MCMC) filter with no move types. The experiment results show that multiple maneuverable birds are detected and tracked accurately in real time, and the size of the tracking box adjust fast to cover the true area of birds.
Comparison of Photovoltaic Performance Enhancement in BiFeO3 by Using Graphene and Carbon Nanotubes as Transparent Electrode

Enhanced photovoltaic performance of BiFeO3 (BFO) material by utilizing graphene and carbon nanotubes (CNT) as transparent electrodes is compared for the first time. The short circuit current density and open circuit voltage are measured to be 34μA/cm2, 2.4μA/cm2, 0.27V and 0.31V by utilizing graphene and carbon nanotubes (CNT), respectively, much higher than the value reported in polycrystalline BFO. A theoretical model considering ferroelectric polarization, interface state, and energy band bending are constructed to investigate the carrier transportation behavior of the BFO solar cell. A Photochromic film is also proposed as an interesting application by using graphene/BFO/Pt solar cell as a photo detector.
Design and Verification of Heterogeneous Streaming Parallel Mechanisms on Kepler CUDA

In many-core based parallel computing field, how to optimally allocate and schedule computing core resources according to characteristics of parallel applications is one typical and fundamental problem, which touches closely to computing performances. After analyzing features and mechanisms of Kepler CUDA architecture, three heterogeneous streaming parallel computing modes and corresponding constraints, and mechanisms are studied and described in detail. Considering the performance differences between different processing steps of one parallel task, a novel mechanism for balancing resource and performance of one whole task is further studied. Finally, we present typical implementation methods on Kepler CUDA processor, and implement typical matrix-processing algorithms and complicated target-detecting algorithms with these three different computing modes. Experiments show that these modes can adapt different types of applications, and the performance of pipelining parallel computing mode is usually better.
The limitation for the growth of step of DPTA method

The damped pseudo-transient analysis (DPTA) method, of step 1 up to 3 are described as they are applied to a nonlinear circuit. The DPTA method with an effective implementation based on SPICE3 is compared to the pure pseudo-transient analysis and compound element pseudo-transient analysis (CEPTA) methods, and is shown to be more efficient. The first order multi-step linear integration algorithms, k step damped differentiation formulas (DDF-k), are applied to the DPTA method. For timestep Δt fixed, the damping effect of DPTA methods is enlarged as k increases. In this paper, we analyze the features for different step k. Also the limitation and how to choose suitable value for the step k are discussed.
Application of 3D Finite Element Software in Web Cracking Analysis of Concrete Box-Girder Bridge

For a curved rigid bridge found vertical cracks in web during the construction process, the finite element software (MIDAS) was used to analysis for the creaking reason for the cast-in-place concrete box bridge. From the analysis of the objectives, the credibility of the results, foundation for modeling, the factors choice for the model and relevant experience are introduced. Including low strength and low elastic modulus of concrete, low grade concretes when the prestressing tendons stretched, longitudinal and vertical tendons excess stretched than the Code permission, as well as the combined effects of these factors results are described in detail, conclude that the poor quality of construction should be the cause of the cracks. By the web of concrete core drilling inspection found that there are more honeycomb holes in the web which is the direct cause of cracks and verified the finite element analysis results.
Complex wavelet based image deconvolution

For image deconvolution, there are more methods, such as the CLEAN algorithm, maximum entropy deconvolution and iterative reconstruction. When the image contains sharp edges, these methods are less appropriate. Recently, we attempt to improve the performance near edges. In this paper we advance a new method PRECGDT-CWT, using the standard DT-CWT(Dual Tree- Complex Wavelet Transform) filters of the (13-19) taps near orthogonal filters at level 1 together with the 14-tap Q-shift filters at levels not less than 2.We chose ten iterations of the PRECG(the Conjugate Gradient algorithm used with the Preconditioned system) search direction starting from a WaRD estimate. We also compare the results with alternative deconvolution algorithms. The method of PRECGDT-CWT performs better than all the other methods tested and the published results on similar deconvolution experiments.
Array characteristic of the strong-coupling based on even-odd mode technology

The paper presents the even-odd mode (EOM) analysis technique for array electrical characteristics of strong-coupling in the fired state, and decompose the array port S-parameter within the emission-coupling antenna framework, resulting in odd-mode radiation power and odd-mode impedance. Its significance lies in two kinds of active impedance separation in the strong-coupling array port, and provides a theoretical support for the unit-port matches. Finally, the 180-degree hybrid balun is presents for the realization of the two modes of decomposition, and gives 2×2 array of the experimental and calculated results from the project implementation and application views.
Laser induced vapor bubbles in cryogenic liquids

in the large K region is due to the smoothing out of ripple by the diffraction. If the atomic density is nonuniform along the radial direction of laser beam, such an effect must be added in the analysis. The effects on the ionization efficiency of target atoms due to the abovementioned analyses will also be presented. *Department of Electric and Electronics Engineering, Ryukyu University 2-Senbaru, Nishihara, Okinawa 903-02, Japan *'Institute for Laser Technology 2-6, Yamadaoka, Suita, Osaka 565, Japan
On Comparison Of Pilot-Aided OFDM channel estimation algorithms

Orthogonal Frequency Division Multiplexing (OFDM) is an attractive modulation technique for communication between unmanned underwater vehicles (UUV) and a distant mother platform. The objective of this study is improving channel estimation accuracy in OFDM system because channel state information is required for signal detection at the receiver and its accuracy affects the overall performance of the system and it is essential to improve the channel estimation for more reliable communications. In this paper, the pilot signal estimation based on Least Square (LS), together with channel interpolation based on the discrete cosine transform, namely DCT-based LS estimator, is compared with LS channel estimation approaches and discussed. Two well known performance criteria: Mean Square Error (MSE) and Bit Error Rate (BER) are used for comparison by using Monte Carlo Simulations for 16 quartered amplitude modulation (16QAM). The results verify that the DCT-based LS estimator has a better performance for OFDM systems. Moreover, the effect of power limitation in terms of SNR and the number of pilots for a wireless channel is determined to compare the DCT-based LS estimator. The result indicates that the estimator with large number of pilots has better performance, but increases the computational complexity.
2D simulation of a SiGe HBT based on energy balance model

An implementation of the energy balance (EB) model is presented to describe energy transport in heterostructure transistors in this paper. As an application, a 2D simulation of a SiGe heterostructure bipolar transistor (HBT) is carried out. Some typical numerical results are presented, such as the I-V curve, distribution of electron density, current density and electron temperature, etc. Compared with the classical drift diffusion (DD) model, the EB model gives more accurate results at the cost of time and space complexity.
A Phase Increment-Based Frequency Estimator for General PSAM in Burst Communications

In this paper, a two-stage phase-increment-based frequency estimator with a general pilot-symbol-assisted- modulation (PSAM) structure is proposed for burst-mode communications. We derive the true Cramer-Rao bounds (CRBs) under the general PSAM structure for pure data-aided (DA) estimator. The proposed phase increment-based estimator is a pure DA estimator and implemented via two stages. In the first stage, a joint auto-correlation with one-symbol delay (AC-1) and simplified L&R (S-L&R) estimator is employed for the coarse estimation. In another stage, a two-step simplified cross-correlation algorithm with three disjoint pilot blocks is proposed for the fine estimation, where the problem of phase ambiguity is solved in the first stage such that wide estimation range as large as half of symbol rate can be guaranteed, and the fine estimation improves overall estimation accuracy. It is shown that the proposed estimator exhibits wide operating range while providing both high accuracy and moderate complexity, and efficient pilot utilization.
Dynamic Duopolistic Competition with Sticky Prices and Advertising in Product Differentiation Market: A Feedback Nash Equilibrium

This paper develops a differential duopolistic game model of optimal sticky prices and advertising in product differentiation market, and investigates the feedback Nash equilibrium of dynamic price and advertising interactions in a competitive setting. Specifically, we have made two contributions with respect to the available literature. First, we have proposed the new assumption of the price adjustment speed is decided by the goodwill levels that are composed of consumer preference structure, the levels of the product differentiation and advertising expenditures, which extend the assumptions in existing literature. Second, we investigate how good differentiation, advertising and price stickiness interact in shaping the feedback Nash equilibrium allocation, and obtain the following three conclusions. First, the feedback Nash equilibrium output is increasing in product differentiation, price stickiness, and promotional efficiency. Second, the feedback Nash equilibrium advertising efforts are also increasing in both product differentiation and the speed of price adjustment, while the feedback Nash equilibrium advertising efforts is decreasing in promotional efficiency.
Memory-Augmented Attribute Manipulation Networks for Interactive Fashion Search

We introduce a new fashion search protocol where attribute manipulation is allowed within the interaction between users and search engines, e.g. manipulating the color attribute of the clothing from red to blue. It is particularly useful for image-based search when the query image cannot perfectly match users expectation of the desired product. To build such a search engine, we propose a novel memory-augmented Attribute Manipulation Network (AMNet) which can manipulate image representation at the attribute level. Given a query image and some attributes that need to modify, AMNet can manipulate the intermediate representation encoding the unwanted attributes and change them to the desired ones through following four novel components: (1) a dual-path CNN architecture for discriminative deep attribute representation learning, (2) a memory block with an internal memory and a neural controller for prototype attribute representation learning and hosting, (3) an attribute manipulation network to modify the representation of the query image with the prototype feature retrieved from the memory block, (4) a loss layer which jointly optimizes the attribute classification loss and a triplet ranking loss over triplet images for facilitating precise attribute manipulation and image retrieving. Extensive experiments conducted on two large-scale fashion search datasets, i.e. DARN and DeepFashion, have demonstrated that AMNet is able to achieve remarkably good performance compared with well-designed baselines in terms of effectiveness of attribute manipulation and search accuracy.
Fast visual object tracking via correlation filter and binary descriptors

Visual object tracking is one of the basic units in the construction of smart cities, which focuses on establishing a dynamic appearance model to represent and recognize the target in complex scenarios. In this paper, we consider visual object tracking as multiple local patches matching problem and design an online tracker based on correlation filter and binary descriptors. We integrate binary descriptors into our tracking model, which provide reliable and robust local feature information. Further, a self-adaptive decision scheme is proposed to fuse the global correlation information and the local feature descriptors. Experimental results on benchmark videos dedicate the effectiveness and robustness of our tracker.
Shifting From Knowledge Exploitation to Knowledge Exploration in New Product Development: A Case Study on Haier Washing Machine

Balance of exploration and exploitation is an important decision making problem in recent literatures. However, the role of time and the change mechanisms are lack of research. This paper conducted in-depth interviews with two product project managers and one manager in R&D department of washing machine business unit in Haier group. After the analysis of the innovation stage, comparative analysis in innovation, strategy, organization, performance and time, we find 5 propositions: find 5 propositions: 1) from knowledge exploitation to exploration is a process across innovation cycle, which can generate continuous innovation; 2) from knowledge exploitation to exploration is a process from strategic defender to strategic analyzer; 3) SBU management and R&D collaboration will be introduced in the period from exploitation to exploration; 4) the business performance during period from exploitation to exploration will be an inverted U shape; 5) the time of product search across exploitation and exploration is much longer than the time of product search in one learning mode.
Noise Clustering Using aNewDistance

Based onanewdistance, anovel noise-resistant fuzzy clustering algorithm called alternative noise clustering (ANC)algorithm isproposed. ANCisanextension ofthe noise clustering (NC)algorithm proposed byDave.By replacing theEuclidean distance usedintheobjective function ofNC algorithm, a new distance (nonEuclidean distance) isintroduced inNC algorithm. Basedonrobust statistical point ofviewandinfluence function, thenon-Euclidean distance ismorerobust than theEuclidean distance. SotheANC algorithm ismore robust thantheNC algorithm. Moreover, withthenew distance ANC candealwithnoises oroutliers better thanNC andfuzzyc-means(FCM).Thebetter performance oftheproposed algorithm isshownby performing experiments ondata sets.
Application of Butterworth Filter in Display of Radar Target Track

The noise in the radar data results in the flutter of the flight target in display screen, which may disturb observer. A rounding method for radar target track using Butterworth filter is proposed in this paper. With the spectrum characteristics of radar target track being analyzed, the filter’s parameters can be designed and figured out. Therefore, after the noise in radar signal is magnified by a transformation algorithm, it can be smoothed online. The results of MATLAB illustration show that the method has a reliable denoising performance.
High efficiency LED driver featuring auto output-voltage tuning

This paper presents a high efficiency LED driver that employs a current-mode buck regulator to energize four linear constant-current regulators. An auto-tuning procedure is introduced in to adjust the output voltage of buck regulator, which keeps the dropout voltage of the passive devices in linear regulators at a possible minimum level while maintaining high performance. Thus, the conversion efficiency of the linear regulator is maximized and so is the overall efficiency. A prototype of the high efficiency LED driver was designed with a standard 0.35µm CMOS process. The simulation results show that the expectant functions are well achieved.
Novel Compact Tri-Band Bandpass Filter With Controllable Bandwidths

Novel compact tri-band bandpass filter (BPF) with controllable bandwidths is presented in this letter. The tri-band performance is realized by using three sets of resonators, i.e., two sets of short-stub loaded dual-mode resonators, which are designed for the first and second passband, respectively, and half-wavelength resonators for the third passband. The three passband frequencies and bandwidths could be independently tuned and designed. The half-wavelength resonators are embedded between the two dual-mode resonators and serve as part of feed lines for the first and second passband, thus compact size is realized. The newly designed tri-band BPF is verified by circuit implementation and good agreement between the simulated and measured results can be observed.
Properties of solidified Dredged Sediment used as subgrade construction material

Three dredged sediment (DS) samples taken from Marine, Lake, and River were solidified with the Compound Dredged Sediment Solidification Additive, the physical and mechanical properties were tested after curing for 28 days. The water content of the solidified DS decreases with solidification additive content but still higher to fulfill the requirements for road subgrade filling material, the density and dry density increase with solidification additive content but lower than natural soil. The UCS strength, cohesion, and friction angle of solidified DS is suitable for base and embankment construction use, but the cost for base use is uneconomic, the cost for embankment use is acceptable.
Fractal dimension of Hadamard fractional integral of continuous functions with countable UV points

The present paper investigates fractal dimension of Hadamard fractional integral of continuous functions with countable UV points. Firstly, we prove that fractal dimension of Hadamard fractional integral of continuous functions with at most one UV point is 1. More generally, the conclusion still holds for continuous function containing finite UV points. Furthermore, we show that Hausdorff dimension of Hadamard fractional integral of continuous functions containing coutable UV points is 1. Finally, Box dimension of Hadamard fractional integral of continuous functions containing coutable UV points has been given.
Classification of imagery movement tasks for brain-computer interfaces based on energy

In order to extract the feature of electroencephalogram (EEG) quickly and efficiently, to improve the classification accuracy rate, band-pass filter and wavelet package were used to get mu and beta rhythms. In the time domain, energy feature was formed by the squared-amplitude of electroencephalogram (EEG) samples over the trials. The subtracted energy value of lead C3 and C4 was averaged by each trial. The polarity (positive or negative) of subtracted value for each trial indicates the kind of imagery movement and was used to classify. The method is simple and the classification accuracy rate is up to 87.857%.
Application of improved Taguchi method to the multiresponse optimization

Taguchi method is the most popular approach for multiresponse optimization. However, the weighting values of responses are ignored in this approach. Thus improved Taguchi method is presented, which applies the principal component analysis to evaluate the weights so that their relative importance can be properly described. The implementation and effectiveness of the proposed method are illustrated by an example from the literature. The results show that improved Taguchi method can optimize the multiresponses.