nils-herrmann/clean_scirepeval huggingface dataset:
Improved Bounds for the Nyström Method With Application to Kernel Classification

We develop two approaches for analyzing the approximation error bound for the Nyström method that approximates a positive semidefinite (PSD) matrix by sampling a small set of columns, one based on a concentration inequality for integral operators, and one based on random matrix theory. We show that the approximation error, measured in the spectral norm, can be improved from O(N/√m) to O(N/m1-ρ) in the case of large eigengap, where N is the total number of data points, m is the number of sampled data points, and ρ ∈ (0, 1/2) is a positive constant that characterizes the eigengap. When the eigenvalues of the kernel matrix follow a p-power law, our analysis based on random matrix theory further improves the bound to O(N/mp-1) under an incoherence assumption. We present a kernel classification approach based on the Nyström method and derive its generalization performance using the improved bound. We show that when the eigenvalues of the kernel matrix follow a p-power law, we can reduce the number of support vectors to N2p/(p2 - 1), which is sublinear in N when p > 1+√2, without seriously sacrificing its generalization performance.
A Virtual MCQA Information System Based on Flexsim

To predict and provide the "confidence" that whether all the quality requirements needed can be satisfied in Mass Customization, a virtual Mass Customization quality assurance (MCQA) system was built in the Flexsim environment. Then the Flexsim based system was extended in several ways. First, use FlexScript/C++ to implement the quality assurance simulation, the quality monitoring and quality control. Second, use Excel commands combined with macro-commands to extend its quality management function. Third, use Socket and ODBC respectively for the real-time data communication and nonreal-time database sharing. Finally, build a self-defined GUI to integrate all the functional modules. Some pivotal source codes of the system were also given.
Sources localization via multi-dimesional scaling based on subspace method

There is no doubt that the issue of estimate locations for unknown sources has been mattering a lot of debate in recent years, in the field of communication, Radar, Navigation, wireless sensor networks, ...etc. In this paper, the multidimensional scaling (MDS) based on subspace method was applied to solve the addressed issue in the presence of distance information that acquired from TOA measurements. The Simulation results show the significant consequences compared with Cramer-Rao lower bound (CRLB) as well as the modified version of classical Multi-dimensional scaling, it became close to the lower bound of variance when the signal to noise ratio increased.
Adaptive micro base station selection algorithm with limited feedback for user — Centric distributed millimeter-wave cell

In order to ensure the quality of service of the communication link, the user equipment(UE) can connect with one or more micro base stations(MBSs) in the user-centric millimeter-wave distributed cell. How to select the optimal MBSs to communicate with UE is a problem according to the channel environment. Based on the limited feedback beamforming technique of random vector quantization (RVQ) codebook this paper derives the expression that maximizes the average effective signal-to-noise ratio (ESNR), proposing an adaptive micro base station selection algorithm (AMBSS) and verifying its validity. The algorithm can adaptively select MBSs to communicate with UE based on the user's location, maximizing ESNR. The simulation results show that the performance of the algorithm is better than that of the fixed number of MBSs with obtaining more than 2dB in gain, reaching the optimal performance in the case of a fixed number of feedback bits.
Research on interference alignment based on dynamic power allocation in multi-cell

Interference alignment (IA) improves the system performance because it makes maximally overlap the interference in multi-user MIMO system. However, the current study was based on a given power; it does not take full advantage of the system's total power. How to allocate power among the users based on interference alignment is the key to this paper. Firstly, a framework of MIMO interference channel was developed and subspace interference alignment was analyzed. Secondly, a novel interference alignment scheme based on dynamic power allocation that can fully use of system power was proposed. Finally, a performance simulation in LTE system was present. The result shows that the average BER and interference power have a significant improvement at the expense of only a tiny system capacity.
Heuristic simulated annealing approach for diffusion scheduling in a semiconductor Fab

This paper presents an efficient algorithm for diffusion scheduling in a semiconductor fab. The diffusion area commonly creates long queue time in the entire process flow. Due to the complex constraints, such as parallel batching and time windows, and large solution space, it is difficult to find a feasible schedule in a timely manner. A greedy randomized procedure forms the batches. A heuristic method is introduced to handle the time window constraints. Two important properties of the problem are identified and applied to improve the quality of the solution. Simulated annealing is used as a local search procedure. Compared with the real schedule in the fab, the proposed algorithm can increase the effective moves significantly without violating queue time constraints.
Cost-sensitive face recognition

Traditional face recognition systems attempt to achieve a high recognition accuracy, which implicitly assumes that the losses of all misclassifications are the same. However, in many real-world tasks this assumption is not always reasonable. For example, it will be troublesome if a face-recognition-based door-locker misclassifies a family member as a stranger such that s/he were not allowed to enter the house; but it will be a much more serious disaster if a stranger were misclassified as a family member and allowed to enter the house. In this paper, we propose a framework which formulates the problem as a multi-class cost-sensitive learning task, and propose a theoretically sound method based on Bayes decision theory to solve this problem. Experimental results demonstrate the effectiveness and efficiency of the proposed method.
Quality fusion based multimodal eye recognition

Multimodal eye recognition can improve the biometric systems recognition accuracy by combining iris and sclera recognition. However, poor quality images can significantly affect the system performance. In this paper, we proposed a quality fusion based multimodal eye recognition. Our quality measure evaluated the entire eye image quality, iris area quality, and sclera area quality. The experimental results show that our overall iris and sclera quality scores are highly correlated to recognition accuracy, and our quality fusion based eye recognition can improve and predict the performance of eye recognition systems.
Multiresolution feature extraction in target detection of UWB SAR

This paper firstly analyzes the difference between high-frequency synthetic aperture radar (SAR) and low-frequency ultra-wide band synthetic aperture radar (UWB SAR) in extraction of multiresolution feature. And then we establish the equivalent models of target and trunk clutter in UWB SAR images and analyze the differences of multiresolution characteristic between target and trunk clutter as image resolution is varied from fine to course. Two forms of first-order autoregression (AR) model are introduced to model multiresolution sequences, and a two-dimensional (2-D) definition of generalized likelihood ratio (GLR) is presented to improve the robustness of multiresolution feature extraction. At last a feature extraction experiment of multiresolution based on region of interest (ROT) is accomplished. The results of experiment testify that the multiresolution feature is effective to improve the performance of UWB SAR target detection.
Fault diagnosis method research of the automobile power train impacting durability test-bed based on data and model method

The safety and reliability of the automobile power train impacting durability test-bed are key technical indexes of the test-bed. Fault diagnosis frequently, accurately and timely is one of the important ways of increasing the safety and reliability of the test-bed. To ensure the reliability service of the test-bed and the testing personnel security, this paper deeply analysed the mechanical failure mechanism of the test-bed, and pointed at the fault characteristics of the test-bed, we diagnosed the fault of the test-bed based on data and model method. In the data based method, Wavelet theory was used to diagnose the fault of the test-bed rotor. To make up the lack of the data based method, the Kalman filter was used to diagnose and simulate the drop of inertia disc based on the model. The results showed that it could meet the demand of diagnosis of mechanical fault of the test-bed based on the data and model method as well as improve the safety and reliability of the test-bed, moreover provide a foothold for diagnosing the complete machine fault of the test-bed.
Research of indemnificatory housing object divided based on cluster analysis

Within the government vigorously promoting, indemnificatory housing achieved the positive results, but the division of the object of indemnificatory housing is still the difficulty of the policy-making. This article starts from the characteristic elements of the object of indemnificatory housing, using the theory of cluster analysis and SPSS software to classify the objects, and analysis of interview data. The results show that cluster analysis can divide the object of indemnificatory housing clearly. And the research is the innovative exploration of method on objects of housing security.
The research of opportunity recognition strategy under different types of entrepreneurial environment — Based on two dimensions of entrepreneurs characteristics and market environment

With the world economy and technology progress, entrepreneurial activity plays a more and more important role in the economic growth, science and technology progress and international competitiveness improve. Although entrepreneurial activities is increasing, it is little and little which really can identify and grasp the opportunity, and succeed in entrepreneurial and make the enterprise continue forever, because it mainly depends on entrepreneur's personal characteristics and market environment. Therefore, based on entrepreneur's characteristic dimension and market environment dimension, this paper constructs a entrepreneurial environment type matrix, and puts forward the corresponding strategies that how to identify opportunities under the different types of entrepreneurial environment.
Fault Diagnosis Based on Belief Rule Base With Considering Attribute Correlation

With the growing demand for high safety in industrial system, fault diagnosis has attracted more and more attention. Currently, belief rule base (BRB) has shown an excellent performance in modeling complex system, where the expert knowledge is used effectively. Existing BRB models are assumed that the inputs of the attributes are independent and the attribute correlation is not taken into account. However, in some engineering system, there is an obvious correlation among these attributes. The correlated attributes may produce redundant information which limits the abilities of attributes to express the accurate information of system. In this paper, a new BRB model with considering attribute correlation (BRB-c) is proposed. Moreover, a decoupling matrix is introduced to eliminate the redundant information from the attributes. The initial parameters of the decoupling matrix are given according to the expert knowledge. And then, when the inputs of the attributes are available, the parameters in the decoupling matrix are trained by an optimization model. The projection covariance matrix adaption evolution strategy is chosen as an optimization algorithm. A practical case study about fault diagnosis of oil pipeline is conducted and the results show that the BRB-c model can diagnose the leak size and leak time of oil pipeline accurately, which can demonstrate that the proposed model can be widely applied in engineering for fault diagnosis.
A Batch Dyeing Machine's Controller Based on Embedded System

Traditional controllers for dyeing batch machines, which are mainly implemented on the obsolete 8-bit or16-bit MCU or PLC platform, have some disadvantages in network communication, input and output ports, human-machine interaction, dyeing-program edition, control functions and so on. This paper proposes a new batch dyeing machine’s controller based on the 32-bit embedded platform. It is realized on the ARM7 hardware platform with embedded operating system eCos whose source codes are open and free. The design and implementation of the embedded controller are described in detail after analyzing the function requirements of a typical batch dyeing process. Finally, the migration of the embedded software is done and an experimental controller with powerful functions and high performance is produced.
SAR images matching based on local shape descriptors

For SAR Images Navigation images matching according to keypoints and feature descriptors is a key technology. Firstly, the novel algorithm detects local extrema in Zoser Pyramid and assigns their orientations. Secondly, it extracts edges by Canny Detector and for each keypoint tests its feature vectors with 49 dimensions by statistic histograms method according to relative distances and orientations between the keypoint and other surrounding points on edges. Lastly, it gets corresponding pixels of two images by matching between two Descriptors. The algorithm has matching in variance to image displacement, scale and rotation, and is shown to provide robust matching across a substantial range of affine distortion, change in 3D viewpoint, addition of noise, and change in illumination. Because SAR images are often blurred and lack of stable details, the algorithm can achieve more reliable recognition and process 3 times quicker than SIFT.
Cache and consistency in NOSQL

In recent years a new type of database (NOSQL) has emerged in the field of persistence. June 2009, a global gathering of NOSQL Movement triggered the fuse of “database revolution”, Non-relational database has now become an extremely popular new areas, NOSQL aims to solve the needs of high concurrent read-write, efficient mass data storage and access, database scalability and high availability. In these large-scale concurrent systems, cluster cache and data consistency become the focus of attention. This article proposes a fast and effective approach to estimate the solution of the data consistency. We use node split and consistent hashing techniques to reduce the servers load by analyzing the request from the client. Each server node can be divided into a set of virtual nodes, which located in a ring. The complexity caused by the size of the set is determined by the target system. Through physical node split, we can reduce the cache miss rate. In order to reduce the complexity of the algorithm of consistency hashing, we will introduce a football game example.
Study on continuous detection of vibro-roller compactness

The dynamics mathematical model of the driving wheel of vibro-roller-soil system is established, and the theoretical analysis and the simulation research of continuous detection for vibro-roller compactness are carried on. The relations of the vibrating wheel acceleration, the compact soil rigidity and damping are obtained; and then the method of measuring compactness indirectly through detecting vibrating wheel acceleration of the vibro-roller is proposed, and the continuous detection system of the vibro-roller compactness is developed based on above mentioned. The experiments indicate that the method and the developed system can realize the continuous detection of soil compactness, and can apply to engineering practice.
Constitutive relation of electric fatigue on the ferroelectric ceramics

Domain switching under an electric filed has been recognized as a fundamental origin causing deterioration and failure of the properties for ferroelectric ceramics. Based on the variations of the in-situ XRD and the macroscopic phenomenological constitutive formulation for PLZT, the present paper formulates the hysteresis loops and the strain loops of ferroelectric ceramics induced by electric fatigue. Considering the domain-wall pinning and depinning coexist during electric fatigue cycling, we simulate the remanent polarization, the ration of different domains and ration of switching domains. Furthermore we present numerically the hysteresis loops and the strain loops of poled and unpoled ferroelectric ceramics induced by electric fatigue. It is found the present results have the good quantitative agreement with experimental data of PLZT. The present model is applicable to describe electric fatigue of the ferroelectric thin film.
Multi-View Video Summarization

Previous video summarization studies focused on monocular videos, and the results would not be good if they were applied to multi-view videos directly, due to problems such as the redundancy in multiple views. In this paper, we present a method for summarizing multi-view videos. We construct a spatio-temporal shot graph and formulate the summarization problem as a graph labeling task. The spatio-temporal shot graph is derived from a hypergraph, which encodes the correlations with different attributes among multi-view video shots in hyperedges. We then partition the shot graph and identify clusters of event-centered shots with similar contents via random walks. The summarization result is generated through solving a multi-objective optimization problem based on shot importance evaluated using a Gaussian entropy fusion scheme. Different summarization objectives, such as minimum summary length and maximum information coverage, can be accomplished in the framework. Moreover, multi-level summarization can be achieved easily by configuring the optimization parameters. We also propose the multi-view storyboard and event board for presenting multi-view summaries. The storyboard naturally reflects correlations among multi-view summarized shots that describe the same important event. The event-board serially assembles event-centered multi-view shots in temporal order. Single video summary which facilitates quick browsing of the summarized multi-view video can be easily generated based on the event board representation.
Surface Smoothness Analysis of Tractor Modeling Based on CATIA

On the basis of introducing smoothing criteria of the surface, the principles and characteristics of the common surface smoothing analysis methods (surface curvature method, illumination model method) are studied. Taking a wheel cover of a tractor as an example, by using the surface smoothing analysis methods, surface smoothness of tractor modeling is analyzed and evaluated by shape analysis function of freestyle in CATIA. The result confirms that surface smoothing analysis methods can effectively analyze the quality of surface smoothing with displaying of a graphical terminal screen and meet consumers' visual sense requirement to product appearance.
Design of A Low Power High Entropy Chaos-Based Truly Random Number Generator

This paper presents a low power high entropy design of a truly random number generator based on a simple chaotic map of the Bernoulli shift, which is extended to keep robustness in practical implementation. The map is accurately realized by switched-current techniques, and a pipelined architecture post-processed by simple XOR circuits is used to improve the throughput and the entropy. The whole design is implemented in UMC 0.18 mum CMOS mixed signal process, and the statistical properties are investigated by simulations. The power consumption is 3.024 mW and the truly random output bit rate is 20 Mbit/s
Modeling of gas reactions in denitrification from flue gas by discharge plasma

Modeling of plasma discharge is a necessary complement for experimental investigation not only because it helps in understanding the fundamental chemistry and physics governing the discharge but also because it is necessary for the design and analysis of the performance of plasma devices. In this paper, a kinetics model was developed to characterize the chemical reactions taking place in a nonthermal plasma denitrification processes using a Matlab programs. The typical gas composition in this model is N/sub 2//O/sub 2//H/sub 2/O/CO/sub 2/=74/5/6/15 with 500 ppm NO and 1000 ppm SO/sub 2/ at the atmospheric pressure and 300 K. The calculations indicate that nitrogen oxide is removed principally by reactions with OH radicals to produce nitric acid. The removal rate of NO increased with increasing water vapor and oxygen content in the flue gas indicates. The presence of both O/sub 2/ and H/sub 2/O in the gas mixture gives the possibility to form a more extensive and reactive set of radicals for the oxidation of NO.
Pol-SAR Classification Based on Generalized Polar Decomposition of Mueller Matrix

In this letter, we investigate an application of a generalized polar decomposition of the Mueller matrix for polarimetric synthetic aperture radar (Pol-SAR) classification. Six roll-invariant parameters (diattenuation, retardance, polarization power, depolarization anisotropy, depolarization power, and transmittance) are selected as features for the classification of scattering types. Experimental results using the AIRSAR data over Flevoland show that, for most field types, the D-R-A<sub>Δ</sub>- Δ-m<sub>00</sub> set provides the highest classification accuracy, followed by the D-R-P<sub>Δ</sub>-Δ-m<sub>00</sub> set which also provides better accuracy than the widely used H -α-(δ-γ)-A-span set. The proposed method would be valuable for Pol-SAR interpretation.
Two-dimensional wavenumbers analysis of one-stationary bistatic circular SAR

Compared with the traditional one-stationary bistatic linear synthetic aperture radar (SAR), the coupling between two-dimensional (2D) wavenumbers for the one-stationary bistatic circular SAR (OS-BCSAR) is much larger due to the circular trajectory and 360° integration angle of the moving radar with respect to the scene, which may affect the behavior of the impulse response in OS-BCSAR imaging. In this paper, 2D wavenumbers of the target echo data for the OS-BCSAR are analyzed. First, the geometry of the OS-BCSAR is built, and then 2D wavenumbers of the target echo data are derived. Besides, the effect of the 2D wavenumber domain support on the impulse response in the OS-BCSAR imaging is discussed, which can provide a basis for the OS-BCSAR imaging. Finally, simulation results are shown to prove the correctness of the analysis of the 2D wavenumbers.
A Supervising and Controlling System for Batch Dyeing Process Based on Multi-agent

Aiming at the diversities and decentralization of dyeing equipments in batch dyeing enterprises, a new type of supervising and controlling (S&C) system for batch dyeing process based on multi-agent is introduced in this paper to achieve the acquisition of machine status data and downloading of process parameters. Dyeing machines are interconnected through Field bus or industrial Ethernet to form the control network under the framework of hierarchy structure. The multi-agent technology is used to integrate the heterogeneous control networks to implement function integration. The model and framework of multi-agents on different layers are discussed. This multi-agent-based system can be integrated with different ERP systems, process management systems and dyeing control systems. Therefore it can help a dyeing enterprise to achieve the integrated management and control function, thus realize the purpose of quick response production.