nils-herrmann/clean_scirepeval huggingface dataset:
Analysis and Design of a Novel Four-axis Plane Laser Welding System

This paper details a novel plane laser welding machine system which combines two large-scale steel blanks superposed together. Several methods are developed in order to solve the technical problems existing in plane laser welding system: It presents major-minor pressing sets which can control the deformation and eliminate the gap effectively; the design of the 4-axis machine which makes the X axis moving in small range and U axis moving in long range in the same direction can improve the precise and dynamic performance of the system. The experimental results show that this new system has potential for future industry application.
Design and Implementation of Clinical Data Center Based on Hadoop

This paper considers the actual needs of the hospital for data storage and the characteristics of the Hadoop framework, builds a clinical data center using Hadoop, Hive and so on which are widely used in modern society. This new clinical data center overcomes the shortcomings of traditional Unix servers, meets the hospital demand for data storage and provides Cloud Computing platform. First, this paper describes the current trends of hospital clinical data center. Then the paper describes the design of clinical data center with EMR and PACS and realizes the storage of structured data and unstructured data.
Communication Protocols Realization of the Prediction and Evaluation Light Environment Embedded Systems

A novel approach to achieve real-time protocol implementations is presented in this research. TWI, μC/OS-II, light sensor and our testing tools execute the protocol in the prediction and evaluation embedded systems of the light environment. The protocol is used by software simulation instead of TWI hardware. The method saves the hardware cost and brings the TWI protocol to a popular application. Furthermore this method is valid by validation test.
A Classifying and Exploring System Based on Users' Tagging Behaviors

Nowadays, as information explosion, it becomes increasingly important for users to find a resource fast and efficiently in social tagging systems. To deal with the problem, this paper constructs an information classifying and exploring system based on users' tagging behaviors. We group the tags and resources by their semantic relations to construct Tag Bundles automatically, and generate a suitable category name for each group according to our category knowledge database, which generated by the open web information resources. Meanwhile, the system allows users to browse their interests by the histogram and analyze their interests' changing. Finally, we build a prototype system to validate the effectiveness of the proposed method.
Centralized sparse representation for image restoration

This paper proposes a novel sparse representation model called centralized sparse representation (CSR) for image restoration tasks. In order for faithful image reconstruction, it is expected that the sparse coding coefficients of the degraded image should be as close as possible to those of the unknown original image with the given dictionary. However, since the available data are the degraded (noisy, blurred and/or down-sampled) versions of the original image, the sparse coding coefficients are often not accurate enough if only the local sparsity of the image is considered, as in many existing sparse representation models. To make the sparse coding more accurate, a centralized sparsity constraint is introduced by exploiting the nonlocal image statistics. The local sparsity and the nonlocal sparsity constraints are unified into a variational framework for optimization. Extensive experiments on image restoration validated that our CSR model achieves convincing improvement over previous state-of-the-art methods.
A Nonlinear Filter-Based Volterra Model With Low Complexity for Wideband Power Amplifiers

A nonlinear filter-based Volterra model with low complexity is proposed for modeling and characterizing wideband power amplifiers. This model has a similar form of a simplified second-order dynamic deviation reduction (DDR)-based Volterra model but without complex square root calculations and high order terms, which are replaced by a first-order nonlinear filter. The model parameters with smaller magnitude distribution range and lower precision in storing and calculation can be estimated by least-square method, and then the model has lower complexity than the second-order simplified DDR Volterra model. Experimental results verified that good performance and lower complexity can be achieved by using this model for a wideband Doherty power amplifier. Finally, the model is employed to compensate the nonlinearity of the Doherty power amplifier, and over 12 dB adjacent channel leakage ratio (ACLR) improvement is achieved for a five-carrier long-term evolution advanced (LTE-A) signal of 100 MHz bandwidth.
A Pc Software Design for Monitoring Receiver of Beidou Navigation Satellite System

Satellite navigation monitoring receiver makes it possible that navigation system can provide high-reliability and high-precise measurement data. In this paper, the Personal Computer (PC) software controls the work status of a receiver. Therefore, it is necessary to design a reliable PC software for receiver working. This paper proposes a programming method with Microsoft Foundation Classes (MFC) of PC software for monitoring receiver which monitors the BeiDou Navigation Satellite System (BDS) of new civil signal. PC software reads the data from NPort and necessary information can be exactly displayed on the interface. Besides, the information can also be saved as a specified file. Compared to the traditional serial port, data can be transmitted by more than one port simultaneously through NPort. It has been proved that this method makes the transmission more effective than the traditional serial port.
Comments on "Robust Kalman Filter for Descriptor Systems

In the above paper, a Kalman-type robust filter is derived for descriptor systems on the basis of the framework suggested in . The performance of the resulting descriptor filter in , however, is generally not very good, as structured perturbations in the corresponding regularized least-squares problem are directly replaced by unstructured ones. In this comment, we show that through off-line convex optimization, the filter's performance can be improved without sacrificing its recursiveness. The idea is to use the ellipsoid with the smallest volume to replace the intersection of several ellipsoids that are determined by the actual plant states and structured model uncertainties, and to re-scale the inputs and outputs of a model uncertainty block with the semi-axes of the optimal ellipsoid. Using the same numerical example and design parameter, the variance of the estimation error can be reduced by approximately 10%. Moreover, it has been shown by simulations that when a standard state-space model is adopted and model uncertainties do not include zero, the method of does not always outperform that of .
A simulation study of air-inflated seating comfort parameters on seating comfort

In this paper, a model was built using visual.studio‥net.2005 to represent the relationship between Pcrms and different aspects of the cushion, such as cell radius, cell number, cell height, outlet number, outlet diameter, material elasticity driver weight in different cases. By analyzing these varied relations, each parameter's effect on comfort performance was determined according to the theory: when Pcrms decreases comfort performance will increase.
A CELP variable rate speech codec with low average rate

This paper presents a variable-rate CELP codec which achieves good communications speech quality at an average rate of about 3 kb/s. The codec operates as a source-controlled variable rate coder with rates of 4.9 kb/s for voiced and transition sounds, 3.0 kb/s for unvoiced sounds and 670 b/s for silent frames. New techniques used in the codec include prediction of the fixed codebook target vector and joint optimization of the adaptive and fixed codebook search. The prediction of the fixed codebook target vector is based on fixed codebook selections in previous subframes and a running estimate for the fundamental frequency. Informal subjective testing (MOS) indicates that the proposed codec, at an average rate of less than 3.2 kb/s, achieves better quality than fixed rate standard codecs with rates in the range 4-4.8 kb/s.
3-D Registration Of Intermodality Medical Images

We report a technique for registering functional and structural 3-D images of patient images (particularly applicable to the human brain). The registration is modeled as a solid rotation, translation and magnification of one image to fit the other. In increasing order of complexity, we developed a hierarchy of landmarks which consist of points, lines, curves, planes, surfaces and volumes. We allow for three different kinds of matches between landmarks: a complete match, a fragmented match, and a containment match. Our technique allows for explicit constraints on the possible rotation, translation and magnification obtained as a result of matching the landmarks. Finally, we show that the above can be cast as a linear programming problem and provide preliminary evidence that it leads to a fast and provably convergent algorithm for 3-D registration promising clinical registration accuracy on the order of one millimeter.
An Optimal Digital Pulse-Width-Modulated Dither Technique to Enhance the Resolution of High-Frequency Power Converters

Wide bandgap semiconductor switches have been increasingly utilized to improve the power density and efficiency of power converters, as such devices are able to operate at very high frequencies, e.g., up to 100 MHz, with reduced power losses. However, such a high-frequency operation may impose a challenge to the digital control system, and the system clock frequency should be up to 100 GHz in high-precision applications, which is difficult to realize in low-cost microprocessors. Instead of using extremely high-frequency clocks, preprocessing-based solutions that utilize digital pulse-width-modulated (DPWM) dither techniques can also enhance the DPWM resolution with moderate frequency clocks. Unfortunately, this is usually achieved at the expense of introducing low-frequency harmonics, which may complicate system controller and output filter design. In this paper, an optimal dither technique is proposed to enhance the resolution of DPWM power converters. The concepts of positive dither and negative dither are first proposed in this paper. Furthermore, vector-diagram-based analysis indicates that with proper utilization of positive dithers and negative dithers and carefully selected dither sequences, the lowest order harmonic introduced by the conventional dither technique can be completely eliminated when the dither period is multiples of six switching periods. In other cases, the proposed optimal dither technique can produce minimized lowest order harmonic. Finally, experimental results obtained from a Gallium Nitride (GaN) devices-based synchronous buck converter validate the feasibility of the proposed dither technique.
An Improved Progressive Transductive Algorithm Based on One Class SVM

Based on the analysis of the One-Class SVM theory, we apply progressive transductive learning method to the One-Class SVM. During the process the training samples be progressively given by label and can be dynamically adjusted. This paper propose progressive transductive OCSVM learning methods. The PTOCSVM classifier can be used in the training process and effectively step by step to make identification and classification, It has self-repair of error and get better test results than directly transductive learning.
A Kind of Improved Drive Interface Circuit for AMOLED

This paper presents an improved Drive Interface Circuit (DIC) of signal transformation for Active-matrix Organic Light Emitting Diode (AMOLED) display. The proposed circuit consists of a multi-format signal interface, a power management, and a signal decoder controlled by a MCU. A novel method of display parameters real-time correction is applied to keep the consistency of display parameters throughout the temperature range. The proposed circuit has the following features. The circuit can directly transform analog signal into Low-Voltage Differential Signaling (LVDS) level instead into TTL level then into LVDS level. Secondly, the circuit can acquire the environment temperature in real-time status and adjust the display parameters (e.g. brightness, color temperature) accordingly. Besides, built-in software with On Screen Display (OSD) function is designed to get the circuit to work well. It also adds a switch circuit to solve the problem of enable control of voltage between AMOLED's anode and cathode. Some problems are discussed at the end.
Circuit design and verification for ultra low current sensing amplifier aimed at bio-sensor applications

It has become increasingly apparent that ultra low current sensing amplifiers (LCSA) play a critical role in many sensor applications, especially for bio-sensing systems. The challenging tasks in LCSA design include achieving adequate performance in gain, noise, and stability, and the integration with sensor array on a single chip. In this paper, two CMOS LCSA circuits are described with current sensitivity in the range of pico-ampere. The detailed design considerations are discussed and simulated results which verify the design are presented
A control middleware for cloud robotics

Future robot applications will require cloud computing. Using an architecture of cloud robotics would increase performance over hardware constraints (e.g., processors, memory, and power). In this paper, we propose a control middleware for cloud robotics, which not only can receive the robots' requests and allocate the cloud resources based on the robots demand, but also can ensure the connection between the robots and the cloud more stability. And then, we use an autonomous, humanoid robot to test the first stage of the control middleware. Effectiveness of this control middleware is demonstrated by experiments.
An Approach to Semantic Annotation for Metadata in Relational Databases

The solution to semantic heterogeneity of the integrated data is a key point in the integration of heterogeneous databases. To aim at adding semantic information to tables and fields in relational databases, a semantic annotation method was developed. The method integrates many different string similarity algorithms to improve similarity algorithms. Firstly, extracting implicit semantic information from metadata in relational databases according to similarities between metadata and the ontology entity; then, the extracted information is annotated using name similarities and structural similarities between metadata and the ontology entity. Tests annotating the metadata in dozens of heterogeneous relational databases had an accurate rate of 82%.
Automated Retinal Vessel Segmentation Using Multiscale Analysis and Adaptive Thresholding

Computer based analysis for automated segmentation of blood vessels in retinal images helps eye care specialists screen larger populations for vessel abnormalities. Because the width of retinal vessels can vary from very large to very small, and the local contrast of vessels is unstable especially in unhealthy ocular fundus, the automated retinal segmentation is difficult. We propose a novel method with the consideration of these problems. Our method includes: 1) a multiscale analysis scheme using Gabor fillers and scale production, 2) an adaptive thresholding scheme using adaptive tracking and morphological filtering. Our method is good for detecting large and small vessels concurrently. It is also efficient to denoise and enhance the responses of line filters so that the vessels with low local contrast can be detected
Automatic Chinese text error correction approach based-on fast approximate Chinese word-matching algorithm

A fast approximate Chinese word-matching algorithm is presented. The algorithm can be used to implement the Chinese fuzzy-matching conception. Based on the algorithm, an automatic Chinese text error correction approach using confusing-word substitution and language model evaluation is designed. Compared with Zhang's (1994) confusing-character substitution method, this new approach can deal with not only character substitution errors but also insertion, deletion and string substitution errors. Besides, the algorithm can handle Chinese "non-word" error, making it possible and easy to establish a two-level structure in Chinese spelling correction.
Considering damage relevance in evaluation model of standard for appraisal of dangerous buildings

Considering the influence of relevance among multi-factors on buildings' damage, the power transmission mechanism that can reflect the damage relevance is introduced to the appraisal standard of damage in dangerous houses (JGJ125-99) hierarchical fuzzy evaluation model. The item description model uses the model of force-delivery tree, puts forward new housing risk and risk rating formulas derivation method of model parameters. The safety appraisal of practical application for Ezhou city primary school by Hubei province shows that the item dangerous evaluation model considering damage can reduce error of judgment.
Convex Discriminative Multitask Clustering

Multitask clustering tries to improve the clustering performance of multiple tasks simultaneously by taking their relationship into account. Most existing multitask clustering algorithms fall into the type of generative clustering, and none are formulated as convex optimization problems. In this paper, we propose two convex Discriminative Multitask Clustering (DMTC) objectives to address the problems. The first one aims to learn a shared feature representation, which can be seen as a technical combination of the convex multitask feature learning and the convex Multiclass Maximum Margin Clustering (M3C). The second one aims to learn the task relationship, which can be seen as a combination of the convex multitask relationship learning and M3C. The objectives of the two algorithms are solved in a uniform procedure by the efficient cutting-plane algorithm and further unified in the Bayesian framework. Experimental results on a toy problem and two benchmark data sets demonstrate the effectiveness of the proposed algorithms.
An Optimal Scheme for TDD Beamforming Systems with Imperfect Channel State Information

An optimal scheme on uplink pilot time interval (UPTI) to maximize average post-processing SNR (signal to noise ratio) is proposed in order to overcome the impact of channel estimation error and delay on a time division duplex (TDD) multiple input single output (MISO) beamforming system. In TDD system, the base station estimates the channel state information (CSI) at transmitter based on uplink pilots and then uses it to generate the beamforming vector in the downlink transmission. Because of the constraints of the TDD frame structure and the uplink pilot overhead, there inevitably exists delay and channel estimation error between CSI estimation and its use. In this paper, we first derive average post-processing SNR for TDD MISO beamforming system with channel estimation error and delay. We then obtain the optimal UPTI, which maximizes average post-processing SNR, given the normalized pilot overhead (the number of pilot symbols per data symbol). The simulation results validate that the optimal UPTI not only maximizes the average post-processing SNR but also minimizes the BER. Especially our research is valuable for the uplink sounding reference signal design in LTE- Advanced system.
Characterization of palmprints by wavelet signatures via directional context modeling

The palmprint is one of the most reliable physiological characteristics that can be used to distinguish between individuals. Current palmprint-based systems are more user friendly, more cost effective, and require fewer data signatures than traditional fingerprint-based identification systems. The principal lines and wrinkles captured in a low-resolution palmprint image provide more than enough information to uniquely identify an individual. This paper presents a palmprint identification scheme that characterizes a palmprint using a set of statistical signatures. The palmprint is first transformed into the wavelet domain, and the directional context of each wavelet subband is defined and computed in order to collect the predominant coefficients of its principal lines and wrinkles. A set of statistical signatures, which includes gravity center, density, spatial dispersivity and energy, is then defined to characterize the palmprint with the selected directional context values. A classification and identification scheme based on these signatures is subsequently developed. This scheme exploits the features of principal lines and prominent wrinkles sufficiently and achieves satisfactory results. Compared with the line-segments-matching or interesting-points-matching based palmprint verification schemes, the proposed scheme uses a much smaller amount of data signatures. It also provides a convenient classification strategy and more accurate identification.
Ontology-Based Metadata Model for Agriculture E-Commerce Knowledge Management

Knowledge representation and organization takes an important role in an e-learning system. In this paper, we put forward a metadata model for agriculture e-commerce knowledge management on the base of our investigation. The metadata model contains three classes which are personnel information class, agriculture e-commerce knowledge class and agriculture e-commerce domain class. Furthermore, we also gave the subclasses of these three classes. Then these three classes and their subclasses are integrated together through the description of their relationships. Finally the metadata model is formalized by resource description framework. And the metadata model is proven to be useful in our knowledge searching system.
Adaptive Synchronization of Generalized Lorenz Systems with Unknown Parameters

The generalized Lorenz system contains a class of three-dimensional autonomous quadratic chaotic systems, which include Lorenz system, Chen system, Lü system and unified chaotic system. In this paper, an adaptive controller for the synchronization of two generalized Lorenz systems is designed by utilizing Lyapunov method, in that the parameters of the drive system are unknown and different from those of the response system. Simulation results also verify the effectiveness of the proposed control scheme.
A Game-Theoretic Approach to Optimal Scheduling of Parking-Lot Electric Vehicle Charging

Parking-lot electric vehicle (EV) charging promises reduced on-board battery capacity for commuters, which would decrease the payback time. However, the parking-lot EV charging scenario is rendered complicated by the large number of agents involved and highly dynamic price of electricity during the day. This study solves the parking-lot EV charging scheduling problem through a noncooperative game approach that considers the coupled constraint therein. The total charging amount is restrained by the transformer capacity. Such a coupled constraint makes the parking-lot EV charging game distinct from other EV charging scenarios. The theoretical framework of the Rosen-Nash normalized equilibrium is applied to deal with such a problem. The Nikaido-Isoda relaxation algorithm is used to calculate the equilibrium point. The dynamic game extension is then provided. Numerical simulation validates the proposed framework. Moreover, the impact of major parameters of the EV charging game on the equilibrium point that can be achieved is investigated.