nils-herrmann/clean_scirepeval huggingface dataset:
An accurate measuring system for VTR magnetic track

A novel design is presented, and the corresponding measuring system, which can be used to calibrate the servomechanism of a VTR (video tape recorder), to test the assembly errors of the video head drum assemblies, and to determine the exchangeability of the VTR, has been built. This design is based on the principle of the Bitter pattern method to show the magnetic track and the digital image processing technology, as well as the precise electromagnetic micromotion device. The accuracy of the previous measuring system depends on the location accuracy of the specimen stage of the measuring microscope, and it is about 0.5-1 mu m. In the present system, the measuring precision depends on the system amplification and the resolution of the digital image processing interface. Therefore, it is possible to improve the measuring accuracy of this system to deep submicrometer. As a result, the distance measurement precision of the present measuring system reaches 0.2 mu m. >
Backscattering of metamaterial electromagnetic cloak

In order to explore the application of metamaterial in the Radar Cross Section reduction for the electrically large conducting bodies, based on the theory and structures proposed by Prof. J. B. Pendry, an electrically large metamaterial electromagnetic cloak has been designed and manufactured, then its RCS was measured in the anechoic chamber. Both theoretical analysis and experimental result indicate that low backscattering is respectively achieved at 8.5 GHz and around 24 GHz because of the metamaterial characteristics and the resonant characteristic of period structures. Therefore, utilizing the coexistence of multiple characteristic of metamaterial, an effective way is proposed to design metamaterial structure with broadband invisibility characteristic.
An efficient geography registration method for InSAR coherent change detection

In this paper, an efficient geography registration method for INSAR coherent change detection is proposed. In the algorithm, considering Terra-SAR image, firstly we do geography registration on two images by oversampling the geography information in master image, then do coarse and fine registration. In coarse registration, find the range and azimuth shifts by calculating the cross correlation of the intensity sub-images that around ground control points (GCPs). In fine registration, calculate intensity cross correlation of sub-images that around GCPs to find the maximum of correlation map for getting range and azimuth shifts. In coarse and fine registration algorithms, time complexity is determined by the size of sub-image and number of GCPs. The proposed algorithm improves the efficiency while keeping the precision of registration. Experimental results obtained on acquired by Terra-SAR images confirm the effectiveness of the proposed approach.
Different Immobilized Method of CRL to Influence on Chiral Resolution of Racemic Paroxol

Different immobilized method of CRL to influence on chiral resolution of racemic paroxol was explored. First of all, physical adsorption, covalent attachment and enzyme-aggregate coating methods were performed to prepare immobilized enzyme. The immobilization efficiencies of immobilized BCLs by physical adsorption, covalent attachment (CA-BCL-NH2-IL-SBA) and enzyme-aggregate coating methods (EAC-BCL-NH2-IL-SBA) were 69%, 67% and 85%, respectively. CA-BCL-NH2-IL-SBA and EAC-BCL-NH2-IL-SBA possessed higher thermal stability, reusability, storage stability than BCL-NH2-IL-SBA. Lastly, three kinds of different immobilized method to influence on chiral resolution of racemic paroxol were anlysised. The enzyme immobilized by enzyme-aggregate coating showed high ee (95%) and E(78). The physical adsorption showed the high conversion(42%).
A New Digital Control Algorithm to Achieve Optimal Dynamic Performance in DC-to-DC Converters

In this paper, a new optimal control algorithm is proposed to achieve the best possible dynamic performance for DC-to-DC converters under load changes and input voltage changes. Using the concept of capacitor charge balance, the proposed algorithm predicts the optimal transient response for a DC-to-DC converter during the large signal load current change, or input voltage change. The equations used to calculate the optimized transient time and the optimized duty cycle series are presented. By using the proposed algorithm, the best possible transient performance, including the smallest output voltage overshoot/undershoot and the shortest recovery time, is achieved. In addition, since the large signal dynamic response of power converters is successfully predicted, the large signal stability is guaranteed. Experimental results show that the proposed method produces much better dynamic performance than a conventional current mode PID controller
A new LLC converter family with synchronous rectifier to increase voltage gain for hold-up application

For low output voltage application, a half-bridge LLC resonant converter family with synchronous rectifier (SR) that has a boost pulse width modulation (PWM) converter characteristic for hold-up state operation is proposed in this paper. In proposed converters, an auxiliary switch (or an auxiliary switch and a diode) is added at the primary side to provide the charging branch for series resonant inductor. The converter has two different operational characteristics. In the nominal state, the proposed converters show the same operational performance with the conventional LLC converter, which is frequency modulation (FM) method. When ac line is lost and the converters operates at voltage boost operation mode, which needs high voltage gain, the Half-bridge switches keep the minimum switch frequency, and the additional switch operates at PWM mode to charge series inductor to obtain enough voltage gain. To verify the effectiveness of the proposed circuit, operational principle will be explained and simulation and experimental results will be presented with following specification. 250-400 V of input voltage range, 12 V of output voltage, and 300 W output power.
Digital control of switching power converters

The paper reviews the latest advance of the digital control technologies in DC-DC converters. The research on digital control is mainly focused on two areas. One is the methods to generate digital PWM (DPWM) signals to meet the output voltage accuracy requirement. Various dithering techniques have been developed to improve the output voltage resolution and at the same time to reduce the clock frequency requirement. The other is to develop new control methods that can utilize these advantages of the digital controller so as to improve the dynamic performance of the switching power converters. Several new digital control methods have been proposed and significant dynamic performance improvement has been achieved
A novel velocity sensor based on electromagnetic induction

A novel velocity sensor based on electromagnetic induction was proposed in this paper. It was composed of four small inductor chips with circular symmetrical distribution on the bottom of a printed circuit board (PCB) and an elastic body with a permanent magnet embedded into on the top of the PCB. The output voltage of each inductor chip will change when an object moves on the top of sensor and drives the permanent to follow with a specific speed. The principle of velocity measurement was derived and simulation was carried out to determine size of the magnet and size of the whole sensor. Then, a prototype was developed and velocity experiments were executed to evaluate properties of the prototype. The result shows that the prototype was capable of following the velocity curve of a motion platform and measuring the velocity vector of the platform with nonlinear errors of 8.1% and 11.9% along its x-axis and y-axis respectively when the speed was from 1mm/s to 9mm/s.
An investigation on computed tomography image reconstruction with compressed sensing by 1 l norm prior image constraints

This paper aims to investigate the problem of low-dose computed tomography (CT) reconstruction with prior image constraints using the compressed sensing (CS) theorem. The CS theorem states that images can be reconstructed from under-sampled data in an adequate or transfer domain without introducing noticeable artifacts by solving a convex optimization problem if the source signals are sparse. To describe the sparsity, a model of piecewise constant source distribution has recently been assumed for image reconstruction by minimizing the total variance (TV) of the image density distribution in the Fourier domain. However, the assumption may not hold for complicated image structures. It has been observed that a prior image from the same subject or anatomy can provide excellent information to the image to be reconstructed. Based on this observation, this study investigates the problem of image reconstruction from under-sampled data by minimizing the difference between the prior image and the concerned image to be estimated with data constraints in the Fourier domain. Compared to the TV criterion, this presented method doesn't require the piecewise constant assumption where the similarity between the two images specifies a new priori model for a new cost function. The presented method was tested by computer simulations using the Shepp-Logan phantom. In noise-free case, only 64 projections around the phantom are needed to produce an accurate reconstruction. The reconstruction remained excellent until the number of projections was reduced to 22 when a high similarity exists between the prior and concerned images while the well-known filtered backprojection reconstruction failed. In cases with noise variance at 1% level, the signal-to-noise of the reconstruction by presented CS-based approach dropped rapidly when the number of projections decreased from 64 to 22. This investigation reveals the high sensitivity of the CS-based approach for low-dose CT image reconstruction. Modification of the cost function to consider data statistics is needed.
Complex process operating optimality assessment and nonoptimal cause identification using modified total kernel PLS

Due to process disturbances and some uncertainties, the process operating performance will deviate from the optimal operating point along with time, so it is very important to develop strategies for online operating performance assessment on optimality. However, a little work has been published in this research area to our knowledge. In this study, a new online operating optimality assessment method for complex industrial process is proposed. Firstly, a new version of T-KPLS algorithm combined with the modified KPLS is developed and used to establish the assessment models for each of the performance grades. By calculating the similarities between the online data and each performance grade, one can obtain the assessment result online, and the assessment results not only include the certain performance grade but also the performance grade conversion. For nonoptimal operating performance, a method of nonoptimal cause identification based on variable contribution is developed. Finally, the proposed online assessment method is applied in a gold hydrometallurgical process, which indicates the efficiency of the proposed approach.
Deep conditional neural network for image segmentation

Existing joint models of deep Convolutional Neural Networks (CNNs) and Conditional Random Fields (CRFs) face two problems for object segmentation: 1) CNNs can hardly extract high level features; 2) fully connected layers of CNNs are lack of capability of dealing with structured multi-level features. To address these problems, we utilize a Structured Random Forests based border ownership detection method to extract high level border features, which simulates the function of humans secondary visual cortex (V2). Moreover, an improved Conditional Boltzmann Machines (CBMs) are proposed to model predicted labels, local and global contexts of objects with multi-scale and multilevel features. Meanwhile, the proposed model inherits the merits of CNN, i.e., the good simulation of low level feature extraction ability in primary visual cortex (V1). Experiments demonstrate that our models yield competitive results on PASCAL VOC 2012 dataset.
A Unifying Approach to Determine the Blocking Probability for Four Models in the Multicast Three-Stage Clos Network

Multicast communication is one of the most significant collective communication operations and is highly demanded in data communications and scalable parallel and distributed computing systems. In this paper, we consider the issue of supporting multicast in the far and wide used well-known three-stage Clos network C(N, n, m; f2). We make use of Hwang¿s unifying approach and Pattavina and Tesei¿s method to determine the blocking probability for models 0, 1, 2 and 3 in the multicast three-stage Clos network. As the unifying approach¿s application, we also respectively give the blocking probability for each model. Compared to previous results the newly proposed unifying approach can more correctly and comprehensively describe the blocking behavior of the general Clos type network.
A modified zero voltage switching forward converter topology with self core reset

A self-core-reset zero voltage switching (ZVS) forward converter topology is presented in this paper. In this topology, ZVS in the main switch is achieved with a simple auxiliary circuit and, importantly, the power transformer self resets without the use of the conventional tertiary reset winding. The transformer becomes simplified, and the cost in manufacture is reduced. Analysis of the circuit is presented. The flux swing in such a topology is investigated, and optimal operating point of flux is determined. Experiments on a 5 V, 100 W prototype circuit switched at a frequency of 200 kHz verify the design.
A novel method of detecting insulation faults in power transformer

This paper proposes a novel method of detecting insulation faults in power transformer based on damped oscillating voltage waves (DOVW). With reference to IEC60270, the insulation faults of a single-phase transformer are identified by the partial discharge (PD) signals. In this research, the PD signals were attained under two energizing methods individually. A comparison of PD behavior corresponding to the conventional AC 50 Hz energizing method and DOVW energizing method has been presented. Based on laboratory tests, detecting PD in power transformer by the DOVW is judged to be effective. This research enabled us to identify and prevent power transformer insulation damage in time.
Chemical Passivity of Pb in Ore Soil by Using Improved Red-Mud Materials

Red mud can use as remediation material to remediation for metal contaminated soil. On the basis, the particles were made and added in the soil from lead-zinc district. Through the five-step sequential extracting, different phases of lead have been extracted and determined. Effectiveness of remediation was measured by residue phase lead increased and other phases decreased. Experimental results show that red mud-based particles have significant effect on fixation of Pb in long-term contaminated soil. The largest increase ratio of residue phase was 81.26% and the concentration of carbonate phase, iron-manganese oxide phase and organic phase were lower than blank samples. Comparing appLication of particles to red-mud powder, the rising trend of pH reLieved.
A Trust Model in P2P E-Commerce Systems

In Peer-to-Peer (P2P) e-commerce systems, peers' features such as heterogeneity, anonymity and autonomy lead to some security problems, such as forging, slandering and collective cheating, which affect the quality of service a lot. A trust model in P2P e-commerce systems based on the recommendation is proposed, each peer in the system has a unique credibility of recommendation, two trust parameters for updating the credibility of recommendation are introduced, namely updating range and updating strength. The trust model proposes an algorithm to update the credibility of recommendation; a peer selects recommendation peers whose evaluation criteria are similar, evaluation criteria of peers are determined through the AHP method(Analytic Hierarchy Process). Simulations show that, the trust model can identify malicious peers, and improve the quality of service in P2P e-commerce systems effectively.
An Efficient Remote User Authentication Scheme with Strong Anonymity

Many remote authentication schemes attempt to preserve user anonymity from the eavesdropper. However, authentication schemes in many e-commerce transactions require not only anonymous to the eavesdropper but also to the authentication server. In this paper, we propose a remote authentication scheme using smart card to fulfill both of the requirements. The proposed scheme achieves mutual authentication and allows users to choose and change their own passwords freely and securely. We only use one-way hash function and bitwise XOR operation in the proposed scheme and so the scheme has a low computational complexity. By using timestamp and random numbers, the proposed scheme can resist the denial of service attack and the replay attack. Also, the scheme is secure against guessing attack, insider attack, stolen-verifier attack, reflection attack, and impersonation attack.
Chaos control of the permanent magnet synchronous motor using an improved sliding mode controller

Permanent magnet synchronous motors (PMSMs) have chaotic phenomena under specific operating state due to the uncertainty of their parameters. The chaotic phenomena result in the great degradation of performance of PMSMs. This paper presents the chaos control of a PMSM for eliminating the chaotic phenomena using an improved sliding mode controller. Based on the mathematical model of the PMSM, a Lorenz chaotic model of the PMSM is deduced by affine transformation and time-scale transform. With the Lorenz chaotic model, the chaotic phenomena of the PMSM are discussed under the specific parameters based on MATLAB. By the saturation function applying to the closer-rate, the improved sliding mode controller is developed to control the chaotic phenomena of the PMSM. Simulation of the PMSM with the chaos control is performed based on MATLAB. Simulation results show that the chaos control of the PMSM using the improved sliding mode controller is valid for erasing the chaotic phenomena.
An Adaptive Scoring Method for Block Importance Learning

The estimation of the block importance could be defined as a learning problem. First, a vision-based page segmentation algorithm is used to partition a Web page into semantic blocks. Then spatial features and content features are used to represent each block. Considering the difference of Web pages, an entropy-based method is adopted to analyze the individual contribution of each feature to the overall effectiveness in the given page. Thus, the entropy value of each feature is used to obtain feature's weight utilized in the further scoring algorithm. Experiments compare the influence both by adaptive weight and by constant weight. The result indicates that the BlockEvaluator algorithm could highly enhance the flexibility in the learning of block importance. The approach is tested with several important Web sites and achieves precise results, correctly extracting 96.2% of news in a set of 2430 pages distributed among 10 different sites
A new adaptive fuzzy logic control method for DC-to-DC converter

This paper introduces a new fuzzy logic controller (FLC) using inductor current feedback for significantly improving the dynamic performance of DC-to-DC converters. Inductor current plays a very important role in high performance DC-to-DC converter control and FLC is suitable to deal with time-varying nonlinear nature of power converters. Based on the feedback of the inductor current, the new control method combines the merits of both the conventional FLC and current mode control. Furthermore, extended state observer (ESO) has been developed to ensure high dynamic performance of DC-to-DC converters. By using ESO, the influence of load disturbances and parameter changes are accurately estimated and compensated. The simulation results show that the proposed FLC with ESO ensures very good robustness and adaptability under modeling uncertainty and external disturbance, such as load current variation, supply voltage changes and converter parameter changes. In addition, small signal frequency response analysis demonstrates that by using the proposed FLC, the bandwidth and phase margin of the closed loop system have been significantly increased.
A CMOS architecture allowing parallel DNA comparison for on-chip assembly

This paper introduces a CMOS based system that has been designed to allow parallel comparison of fragmented DNA sequences for on-chip assembly. The compatibility of different existing PC-based algorithms for implementation in CMOS is compared and the overlap-layout-consensus approach is found to be the most suitable one. The designed system comprises a scalable processing array capable of parallel computation, which allows identification of overlaps in DNA fragments in addition to error tolerance through dynamic programming. Analysis shows that there is a “pixel area vs computation time” trade-off when implementing such a parallel architecture. Results from a hypothetical assembly confirm good overlap detection and error tolerance, with up to 94% similarity in the detected overlaps, when the error is as much as 10%.
An Adaptively Weighted Least Square Estimation Method of Channel Mismatches in Phase for Multichannel SAR Systems in Azimuth

Multichannel synthetic aperture radar (SAR) systems in azimuth can achieve high-resolution and wide-swath imaging. However, the quality of final SAR image can be degraded by the channel mismatch in phase which increases the energy outside the processed Doppler bandwidth (PDB). To address this problem, a calibration algorithm is proposed in this letter by minimizing the energy outside the PDB. Theoretical analysis shows that the presented method can be interpreted as an adaptively weighted least square estimation problem, where the weights are related to the signal-to-noise ratio (SNR) of the echoes from different directions. Simulation results reveal that our method outperforms the conventional methods in the case of quasi-uniform sampling, particularly at the low-SNR region.
A New Remediation Model Based on Trusted Network

A new and feasible trusted remediation model was put forward, and the functions as well as the work flow of remediation model were explained in detail. Moreover, the communication and authentication process of remediation model were discussed. Simulations results show that by the proposed model, not only the safety and reliability of network can be ensured, but also the convenient and reliable remediation services are able to be provided to those terminals without according with the security policy of local network.
An algorithm to analyze circulating current for multi-phase resonant converter

An algorithm based on new circulated current model is proposed to analyze the circulating current in the multiphase LLC converter. First of all, a virtual-open concept is introduced and LLC phases are decoupled from each other, Thus, A circulating current model can be achieved from fundamental harmonic approximation (FHA). Secondly, the ac voltages on the equivalent resistor of different phases are assumed same magnitude but different angle viewing from the primary-side. From mentioned above, current sharing error can be calculated, two types calculated results are shown under two-phase independent LLC converter and two-phase common inductor LLC converter. Simulation results from different input voltage levels, different resonant component tolerances, and different total load are compared. A two-phase 600W prototype is built to verify the effectiveness of the proposed analysis method.