nils-herrmann/clean_scirepeval huggingface dataset:
Global Manufacturing Network, Knowledge Transfer and Implication for Chinese Local Firms

Global manufacturing network (GMN) is a new manufacturing system that has super manufacturing and servicing abilities. It is challenging traditional manufacturing conceptions. This paper describes and analyzes evolution of the concept of GMN, its members, and its theoretical bases. This paper also explores the reasons, of knowledge transfer in the GMN, as well as mechanism and process of knowledge transfer in the GMN. Finally, the implication of GMN for Chinese local firms is discussed
Pilot Sequence Design Scheme for MIMO OFDM Systems under Time-Varying Channels

Orthogonal frequency division multiplexing (OFDM) systems encounter performance degradations due to the time varying (TV) channels in wireless environments. As delay spread increases, symbol duration should also increase, and then OFDM systems become more susceptible to time-variations. Time-variations introduce inter-carrier interference (ICI), which must be mitigated to improve the performance in high delay and Doppler spread environments. In this paper, a pilot design scheme for multiple input multiple output (MIMO) OFDM system is proposed under TV channels. The properties of these pilots are described, and the simulation results are presented.
Review on connectivity reliability of road network of large-scale events

At first, it is shown in this paper that the significance and effect of Connectivity Reliability of Road Network of Large-scale Events are introduced very emphatically. Then, the basic conceptions, all kinds of research methods and many related models are summarized and analyzed, and the main applications fields of it are comparative systematically introduced in the operational study. What is more, based on the analysis of it, we indicated that there are several shortage and defects in the operational study. Last but not least, we revealed the direction of this research in the future. The calculated results have practical value.
Resolution enhancement based on sparse distributions of complex-valued SAR Image

According to the sparsity nature of SAR images, the enhancement of the resolution of objects is investigated. Ideal SAR images may be modeled as a small number of dominant scatterers in a nearly black background. Therefore, sparse statistical distributions should be considered to model the complex-valued SAR images. With a statistical perspective, we follow the MAP criterion and present models to enhance the resolution of objects in SAR images. And an iterative algorithm is presented. Numerical simulations using MSTAR data demonstrate the effective performance of resolution enhancement and the computational efficiency.
Effects of electromagnetic pulse on the vimentin of mice testes

To investigate the changes of the mice testes and the tight junction (Tj) relative molecular and to identify the molecular mechanisms of the mice blood-testis-barrier (BTB) permeability increasing after the mice were exposed to electromagnetic pulse (EMP). Observe the changes vimentin of the mice testes by laser scanning confocal technique. After the 200 kVm-1 EMP (the accumulative pulse times was 200) exposure, the vimentin in sustentacular cells of testis became irregularly shortened and derangement, and the intensity of immuno-fluorescence also showed ununiformity compared with control. The increasing of mice BTB permeability perhaps caused by the changing of vimentin.
Expansion-based depth map estimation for multi-view stereo

This paper presents an algorithm for acquiring high-quality models from multiple calibrated photographs by computing and merging depth maps. The algorithm first computes depth maps from multi-view stereo using a proposed expansion-based approach that returns a 3D point cloud with noisy and redundant information. Then the estimated depth maps are merged into an accurate surface model by a cleaning, downsampling, surface normal estimation and Poisson surface reconstruction process. The proposed approach has been implemented and the experimental results with several real datasets demonstrate that the approach can produce accurate surface models efficiently.
Nonlinearity analysis and multi-model modeling of CO2 capture system

Reducing carbon dioxide emissions is an important issue for the environment. The amine-based carbon capture system is a complex system with high energy consumption, and the system needs to be operated flexibly in a wide range. Therefore, advanced control technology is required and an appropriate model is a necessary condition for controller design. To this end, this paper investigates the nonlinearity of the carbon capture system from both the flue gas side and capture rate side. Then, based on the investigation result, a multi-model system is developed which can approximate the dynamics of the CO2 capture process accurately in a wide range and is suited for advanced controller design. Comparisons with single linear model demonstrate the effectiveness of the multi-model modeling approach.
Performance of Low-Density Parity-Check (LDPC) Coded OFDM system based on Adaptive Power Allocation Algorithm

A LDPC-COFDM system model based on adaptive algorithm can allocate transmit power and bits among sub-carriers according to the channel gain of each sub-channel. An adaptive power allocation algorithm, which is beneficial for log likelihood ratio decoding of LDPC coded modulation, is proposed in this paper. The simulation results show that the model can effectively improve the bit-error-rate (BER) performance of the system, compared with the traditional OFDM system based on equal power allocation, adapting to the time-variant behavior of the multi-path fading channel.
An improved neutral-point-potential balance control strategy for three-level PWM rectifier

Neutral point potential balance control is very important to three-level neutral-point-clamped (NPC) rectifiers. In this paper, the balance control strategy is studied with three-level space vector pulse width modulation (SVPWM) algorithm based on reference voltage decomposition. An improved neutral-point potential balance control strategy based on balance factor is proposed and the principle is analyzed. Simulation and experimental results verify the validity of the control strategy.
Design and Implementation of a Reading Auxiliary Apparatus Based on Electrooculography

Eye movements have been proven the most frequent of all human activities; therefore, research on a relationship between different eye movement patterns become a hotspot in human–computer interface fields. The motivation of this paper is to develop a reading auxiliary apparatus by measuring and analyzing the electrooculography signals. We first describe the saccade detection algorithm based on the wavelet packet decomposition and the derivation blink detection algorithm. Furthermore, consecutive blinks were used to control the system’s working state and a magnifier, whose position is adjusted according to the results of saccade detection. Experiential results on six participants show that recognition accuracy ratio (F1 score) is 90.096%, which reveal that the proposed system has a good recognition performance on reading activity detection and analysis.
FMI based multi-domain modeling and simulation for extraction and retraction of EHA nose landing gear in Dymola

The Electro-Hydrostatic Actuation (EHA) nose landing gear system is a complex multi-domain system. in order to study the coupling characteristics of EHA system, a multi-domain simulation tool is needed. In this paper, a EHA block diagram based on extraction and retraction of nose landing gear is described and established from the mathematic model, and then completed the modeling and simulation of EHA system in Dymola. A controller of EHA system is exported as the Functional Mock-up Unit (FMU) model from Simulink to Dymola according to the Functional Mock-up Interface (FMI) standard.
Improved RSSI-based localization algorithm for park lighting control and child location tracking

Based on the ZigBee wireless network, a park lighting control and child location tracking system is designed in this paper. Considering that there may be a number of children that needs to be tracked concurrently, distributed localization is needed, so an improved RSSI-based algorithm is introduced in this paper. As a goal of our system, the new method, unlike commercial digital-hardware-block based strategy used in CC2431, can be implemented by using ordinary 8-bit MCU. In the new distributed localization strategy, instead of ‘lognormal’, ‘piecewise linear’ path loss model was established, which needs only linear operation when estimating range from RSSI. Besides, min-max method, other than maximum likelihood estimation method, was used to simplify coordinates calculation. Furthermore, ZigBee compatible node modules were developed as the system hardware platform to carry out the experiments, and results demonstrate the new method has close or even better precision compared with basic algorithm, and therefore meets the demand of child location tracking system in the park.
Design and Analysis of an Autotransformer Based 24-Pulse Rectifier

This paper presents the design and analysis of an autotransformer based 24-pulse rectifier. The proposed ac-dc converter is based on a star connected autotransformer, designed for producing 15-phase shifted ac voltages for 24-pulse rectifier for effective harmonic reduction. Compared with 3-phase rectifier, the proposed 24-pulse rectifier can reduce the equivalent capacity of transformers and realize the purpose of reducing the transformers' bulk and weight in same power. Meanwhile the proposed method can greatly minish the total harmonic distortion (THD) of supply current and make it near sinusoidal in shape.
Improved Mean Shift Spectral Clustering Based on Reduced Set Density Estimator

Mean shift spectral clustering (MSSC) brings us an alternative for image segmentation. However, owing to being based on the classical Parzen window estimator (PW) and employing the full data sample for density estimation, the usefulness of MSSC is weakened. In this paper, the improved mean shift spectral clustering (IMSSC) algorithm is proposed by replacing PW with the reduced set density estimator (RSDE). Due to just a few sample points in the reduced set being referred to, the time complexity of mean shift embedded in IMSSC decreases to O(mN) and the total computational costs of IMSSC are sharply reduced.
Grid scale research on Chaohu Basin's farmland fragmentation based on entire-array-polygon indicator method

Farmland fragmentation is a land use pattern contrary to land formula management. It would lead to farmland's shrinking and decentralization, and reduce the output efficiency. Carrying out spatial evaluation of farmland fragmentation is the premise and foundation of improving the land use efficiency. The paper selected Chaohu Basin as the research object, regarded 3km size grid as research unit, constructed farmland fragmentation evaluation index system based on landscape indices, and calculated each grid's farmland fragmentation using entire-array-polygon indicator method. The results show that: The area of Chaohu Basin is 19785 km2, it is divided into 2326 grids by 3km size grid. Farmland accounting for about 57% of the total area distributes in 2238 grids, which is a wide range. The space difference of farmland fragmentation in Chaohu Basin is significant. The proportion of non-fragmentation region (603 grids) is 26.94%. They mainly concentrate in the northwestern and the eastern. Slight fragmentation region (662 grids) occupies 29.58%. They scattered in the whole basin; Moderate fragmentation region (663 grids) occupies 29.62%. They mainly distributes in four districts and the surrounding area of Hefei City; Severe fragmentation region (310 grids) which has the smallest percentage about 13.85%, mainly distributes in the southwestern mountainous area of the basin. Then, there were three policy recommendations being put forward, such as vigorously prompting the development of modern agriculture, promoting the development of characteristic agriculture and forestry, weighing the construction land and the farmland. By establishing the reasonable evaluation system, measuring farmland fragmentation of Chaohu Basin and analyzing the cause of this phenomenon, we can provide recommendations for Chaohu Basin's land use and land regulation. It's beneficial for improving farmland use efficiency.
Implicit fitting and smoothing using radial basis functions with partition of unity

A new scheme for 3D reconstruction of implicit surfaces from large scattered point sets based on the radial basis functions (RBFs) is proposed in this paper. The partition of unity (POU) method and a binary tree is used to organize the point sets into some overlapping local subdomains and reconstructing a local surface for each of the subdomains from non-disjunct subsets of the points, we use only a single point at the offset of the surface to avoid the trivial solution of RBF linear system. When the offset point is chosen properly, the technique is not only efficient but also robust, offering a higher level of scalability. The global solution can be obtained by combining the local solutions with POU equations. We also adapt the methodology of level set propagation of a dynamic surface and employ it for smoothing the reconstructed surfaces. We develop versatile computational framework with many benefits in topological flexibility and numerical efficiency.
Research on Control Strategy of Two-Wheeled Self-Balancing Robot

The structure of two-wheeled self-balancing robot is equivalent to the combination of the linear inverted pendulum and wheeled mobile robot. But compared to the linear inverted pendulum, two-wheeled self-balancing robot can move freely and turn flexibly. So the system is more complex and difficult to control. As the two-wheeled self-balancing robot is a high order and multi variable system, PID controller based on output feedback can't have a satisfactory control effect. The LQR control strategy is implemented, and the weight matrix Q and R of the LQR controller are optimized by using multi-population genetic ideas. Taking two wheeled self balancing robot as the test platform, the two control modes of LQR and PID are used to carry out experiments and analysis. In the simulation experiments of balance control, position control and speed control, the LQR controller has a better performance in the system's robustness and fast response.
A quasi fixed frequency constant on time controlled boost converter

Continuous conduction mode (CCM) boost converter is difficult to compensate due to the right half plane (RHP) zero. This paper presents a quasi fixed frequency constant on time (COT) controlled boost converter, it has no loop compensation requirement. With the proposed COT control, pulse frequency modulation (PFM) comes free at light load, which improves the light load efficiency compared with traditional PWM control. A compact on-time generator that controls the operation frequency is proposed. And a current sink based feedback circuit is used to improve the quality of feedback signal.The COT controller is designed with 1.5 mum BCD process. Simulation results demonstrate that the COT boost converter has fast load transient response and quasi fixed frequency operation.
Face Detection, Bounding Box Aggregation and Pose Estimation for Robust Facial Landmark Localisation in the Wild

We present a framework for robust face detection and landmark localisation of faces in the wild, which has been evaluated as part of `the 2nd Facial Landmark Localisation Competition'. The framework has four stages: face detection, bounding box aggregation, pose estimation and landmark localisation. To achieve a high detection rate, we use two publicly available CNN-based face detectors and two proprietary detectors. We aggregate the detected face bounding boxes of each input image to reduce false positives and improve face detection accuracy. A cascaded shape regressor, trained using faces with a variety of pose variations, is then employed for pose estimation and image pre-processing. Last, we train the final cascaded shape regressor for fine-grained landmark localisation, using a large number of training samples with limited pose variations. The experimental results obtained on the 300W and Menpo benchmarks demonstrate the superiority of our framework over state-of-the-art methods.
A Novel Approach Based on Support Vector Machine to Forecasting the Construction Project Cost

Construction project cost forecasting is a key procedure to the mangement project. An accurate forecast can support the investment decision and ensure the project's feasible at the minimal cost. So reasonable determining and controlling the project cost become the most important task in the budget management of the construction project. A novel regression technique, called Support Vector Machines (SVM), based on the statistical learning theory is exploded in this paper for the prediction of construction project cost. SVM is based on the principle of Structure Risk Minimization as opposed to the principle of Empirical Risk Minimization supported by conventional regression techniques. Through introduced the theory of the SVM-Regression, considered and extracted substances components of construction project as parameters, this paper seted up the Model of the Construction Project Cost Forecasting based on the SVM. The research results show that the prediction accuracy of SVM-Regression is better than that of neural network.
A Trusted Computing Technology Enabled Mobile Agent System

The Mobile Agent (MA) has been seen as a promising distributed computing technology. According to the analysis of security problems of current mobile agents that are exposed in opening environment, a model system for mobile agent is proposed in this paper. In this system, the mobile agent security is enhanced by the Trusted Computing Technology. The mobile agent security supporting environment (MASSE) is designed by using trusted software stack (TSS) and trusted computing platform (TCP). To improve the security of MA system, some MA security services, such as authentication, role based access control and MA negotiation, are discussed in this paper. The working process of MASSE is also described.
Low-Power and Hardware Efficient Decimation Filters in Sigma-Delta A/D Converters

The power and area formulas for four popular Sinc-filter structures used in decimation filters were discussed in this paper. It was proved that the formulas are very useful in power or area estimation and comparison. The circuit implementations of each structure are illustrated. And the power and area comparisons of the four structures were simulated and analyzed. A further optimization technology for one of the efficient filter structures was also proposed.
Decentralized Formation Control and Obstacles Avoidance Based on Potential Field Method

A new decentralized formation control based on electric field artificial potential is proposed in two dimensions. Making reference to the potential in electric field, the control of agent derived from a weighting of the relative importance of different artificial potential while formation keeping, obstacles avoidance and collision free. The research is based on the model of double integral equation. A strategy of the decentralized formation control based on the artificial potential is given and the proof of stability of this new formation control is presented. The simulation results show that agents can avoid the different shape obstacles effectively
Modeling non-idealities of Sigma Delta ADC in simulink

Non-ideal behavior models of switched capacitor sigma delta ADC are presented. The modulator non-idealities such as operational amplifier parameters (GBW, colored noise, SR, saturation voltage and so on), clock jitter, capacitor mismatch, nonlinear switch on-resistance and are included. The operational amplifier nonlinear DC Gain is modeled with emphasis and simulation results show it introduces odd harmonic distortion.
Pattern data acquisition for high-speed electronic jacquard circular knitting machine

High-speed electronic jacquard circular knitting machine was recognized as a green machine to protect environment. It can easily produce any kind of pattern on cloth without pollution, while the printing and dyeing cloth technology may produce wastewater, which hardly polluted the environment. A new electronic jacquard technology has replaced the traditional printing and dyeing technology. A control system must be researched to satisfy the high-speed jacquard circular knitting machine. This paper introduced the control system structure and the organization of the pattern data, tested the pattern data accuracy by feedback acquisition system, and used Electronic Design Automation (EDA) technology implemented the production of the acquisition system, emulated the time sequence accuracy by EDA professional software, and tested the frequency of the pin selector. The result is that the pattern data organization and acquisition testing and implementation have offered the theoretical foundation for the production of control system.
Adaptive Hysteresis Window Control (AHWC) Technique for Hysteretic DC-DC BUCK Converter with Constant Switching Frequency

This paper presents a new adaptive hysteresis window control (AHWC) technique for hysteretic DC-DC buck converter, which can adaptively adjust the hysteresis window according to input and output voltages to keep the switching frequency constant. This technique was designed and fabricated in TSMC 0.35 ?m standard CMOS process. Simulation results showed that by using the proposed AHWC technique, the fast line and load transient responses as well as the constant switching frequency were achieved, as input and output voltages varied.
Chinese traditional visual cultural symbols recognition based on the combination of depth hierarchy features and SVM

Chinese traditional visual culture symbols (CT-VCSs) is formed in the tradition and has the characteristic of Chinese unique ideological and cultural connotation. It is a visual cultural heritage of Chinese culture. So the research on CT-VCSs has important practical significance. In this paper, it is mainly about the recognition and classification of CT-VCSs based on machine learning. We make use of the advantages of both shallow learning and deep learning, and then we combine them together to achieve the purpose of recognition. In other words, we regard the traditional convolutional neural network as a feature extractor and extract the features of two full-connected layers as depth hierarchy features. At last, we take them into SVM with Histogram Intersection Kernel function for classification. Experimental results show that the recognition effect is very good.
Fuzzy-neural theory applied to Web-based proactive service

In order to realize proactive service, we design and improve relative fuzzy-neural approaches. Generally, the network can be classified into two. One is that fuzzy logic reasoning is completed by fuzzy weight in neural system. The other is that the input data must be fuzzified in the first or second level, but not weight. We discuss and study the second sort fuzzification in this paper. For proactive decision, fusion method based on fuzzy-neural can make Web-based intelligent system keep advantage of fuzzy logic system and remain adaptive optimum in proactive/attentive service. The correctness and validity of our new approach have been tested.