nils-herrmann/clean_scirepeval huggingface dataset:
Admissibility conditions of dynamic input-output economic model with multiple delays

A new dynamic input-out economic model with multiple delays and with probably singular capital coefficient matrices is proposed. A delay-dependent admissibility condition and a delay-independent admissibility condition of the dynamic input-out economic model are addressed respectively. By simple transformation, the economic model is written as a discrete-time singular systems with multiple constant delays, then a delay-dependent and a delay-independent admissibility conditions are presented and expressed in terms of linear matrix inequalities (LMIs) by Lyapunov approach. Finally, numerical examples of the dynamic input-out economic model are illustrated, which show the effectiveness of the proposed methods.
Filter based spatial compounding for strain imaging

Ultrasound elastography is the technique of obtaining tissue relative stiffness information, which plays an important role in early diagnosis. Ultrasonic wave interference produces local fluctuations in both phase and envelope, known as speckle. Compounding reduces speckle by averaging envelope detected data from several decorrelated looks and may also be used to improve motion estimates by averaging the estimate from decorrelated looks. In this paper, we propose filter based spatial compounded strain imaging, which uses a filter band to create multiple looks to produce a compounded motion estimate. In conventional frequency compounding, the filters are applied in the axial direction, whereas in this case, they are applied in the lateral direction to create decorrelation between sub-bands. The effect of filter based receive frequency compounding is investigated through phantom experiments, which confirms the reduction in strain image artifact is accomplished with no sacrifice of real-time ultrasonic imaging as well as a measurable improvement in SNRe and CNRe.
Attitude tracking of rigid spacecraft without angular velocity measurements via passivity approach

In this paper, the attitude tracking problem of rigid spacecraft without inertial or relative angular velocity measurements is investigated. The minimal attitude description, the modified Rodrigues parameters (MRPs), are utilized as the attitude parameters for the non-redundancy. The inherent passivity of the system describing the attitude tracking motion of the spacecraft is exploited. Then an attitude tracking control law using feedback parts of relative angular velocity and relative MRPs is designed. Additionally, to remove the requirement of the relative angular velocity measurements, a lead filter is utilized to provide the information for the tracking control problem with relative attitude measurements only. Finally, a numerical simulation is employed to verify the proposed control algorithm.
A New Approach to H&#8734;Control Design for T-S Fuzzy Time-delay Systems

Sugeno (T-S) fuzzy models can provide an effective representation of complex nonlinear systems in terms of fuzzy sets and fuzzy reasoning applied to a set of linear input/output (I/O) submodels. In this paper , Hinfin control design for T-S fuzzy time-delay system have been studied . New sufficient conditions in the terms of linear matrix inequality (LMI) which guarantee the existence of the state feedback Hinfin control for the T-S fuzzy time-delay system have been proposed
Effects of electrode biasing on fluctuations and transport in the KT-5C tokamak

Electrode biasing experiments are carried out on the KT-5C tokamak to investigate the effects of the radial electric field E/sub r/ on turbulence. A modestly enhanced E/sub r/ gradient layer is formed at the plasma edge by the electrode biasing. In the E/sub r/ gradient layer, reductions in the fluctuation amplitude, radial correlation length and turbulent particle flux are observed. These results support the theoretical models on the turbulence suppression by decorrelation due to E /spl times/ B flow shear.
An improved cluster analysis algorithm using for network traffic flow

With the rapid development of computer network and the network application, network has plays an increasingly important role in the social progress and economic development. Rapid development of information technology makes the network traffic behavior has become increasingly complex, and the reliability of the network becomes crucial. Cluster algorithm using for network traffic flow is an entry to analysis network status. Support Vector Machine (SVM) is a machine learning method to solve binary classification problem. An improved cluster analysis algorithm of combining SVM with supervised subset density clustering is proposed in this paper, and minimize the training set of SVM by means of clustering is researched. A supervised self-adaptive method for the improved density clustering is designed to make out multiple centers choosing and referring the samples to SVM. The experimental results show that the algorithm reduces the iteration time of the whole training process without compromising the accuracy and generalization capacity of the algorithm obviously.
Notice of Retraction Set Pair Analysis for Rural Drinking Water Quality

A large number of uncertain problems existing in rural drinking water safety system, it is of great significances to apply Set Pair Analysis (SPA) theory to analyze and study these uncertain problems in rural drinking water safety system. This study applies SPA theory to conduct an integrated evaluation of water quality to rural drinking water safety in Ya'an City, based on classification values of Sanitary Standard for Drinking Water (GB5749-85). This study has worked efficiently in practice. Compared with the same kind of methods which have been found, this paper has the outstanding results for the uncertain problems of health risk assessment of the rural drinking water safety.
Research on equipment support forces configuration based on field theory

In this paper, the equipment support forces configuration based on field theory is analyzed considering the complexity and uncertainty of equipment support requirements and environment. Firstly, concept of equipment support field from the point of comparability is introduced. Secondly, the factors affecting the configuration of equipment support forces are analyzed. And a method about partitioning service range of equipment support force based on equipment support field potential is proposed. Finally, the optimum allocation of equipment support forces based on potential energy is studied. The allocation optimization process is presented, which is adaptive and flexible for the configuration of equipment support forces, and the optimum results can provide reference for command decision of equipment support.
A fast faulty phase selection algorithm based on S-transform

This paper proposes a novel approach to faulty phase selection using S-transform and phase current integration for the fast transmission line protection. The paper analyzes the modulus characteristics of various types of fault and the characteristics of phase current for two phases to ground fault. On the basis of it, the phase selection algorithm first uses S-transform to get single frequency phasor of module components at a specific time, and then the relation among module phasors is analyzed to classify the fault type. The algorithm use phase current integration distinguishes the faulty phases in the two phases to ground circumstance. The PSCAD simulation results show that the algorithm can quickly and accurately identify the fault phases, and the identification performance is not affected by the fault position, fault inception angle, fault resistance and the structure of bus.
Strain Image with Spatial Angular Compounding

Ultrasound elastography has been well applied in medical detection as a tool to aid diagnosis. However, in conventional ultrasound elastograms, there are patterned artifacts from non-white estimation errors. In this paper, we investigate spatial angular compounding methods to reduce the errors. The method involves averaging ultrasound angular elastograms around the same region-of-interest but from different angle views. N decorrelated sub-elastograms are weighted averaged to produce the compounded elastrogram. For our experiments, we use 3 different angled elastograms calculated from alternating frames with different steering angles obtained from base-band data captured by the iMago c21. We present results from a commercial elastic phantom showing improvement in the elastogram's quality parameters such as SNR and CNR.
New evolution algorithm based on the standard particle swarm optimization

The particle swarm optimization (PSO) is an alternative for global optimization. A standard for PSO (SPSO) was defined which took into the latest developments, and was used as a baseline for performance testing of improvements. In SPSO, however, particles need to search the optimal solution in the constraint space, and the item velocity in PSO makes particles difficult to adjust themselves to meet those complicated constraints. A new PSO without the item velocity based on SPSO is proposed in this article. The new algorithm inherits the capability of SPSO with fast convergence and high accuracy. This research proves that the convergence process of PSO has nothing to do with the velocity and the proposed method modified simple PSO (msPSO) can converge. The experiments show that msPSO is able to achieve a good result.
Lateral Resolution Enhancement of Ultrasound Image Using Neural Networks

Ultrasound imaging techniques are widely applied for medical diagnoses. However its main disadvantage compared with other techniques are low resolution and speckle artifacts. Therefore, improving the spatial resolution of ultrasound images has been a very active research area. System parameters that affect resolution include the size of the active transducer aperture, the center frequency and the bandwidth of the transducer, and the selected transmit focal depth. This paper presents an approach to enhance the lateral resolution by reproducing the underlying mapping between a low resolution image and a high resolution image obtained with different aperture size. Artificial neural networks are used to build the mapping. A generalization parameter is added to neural network and fuzzy logic is used to perform the resulting data fusion. In addition, a local histogram algorithm is used to filter the speckle like sample data when training network.
A zero-voltage switching control strategy for dual half-bridge cascaded three-level DC/DC converter with balanced capacitor voltages

The input capacitors' voltages are unbalanced under the conventional control strategy in a dual half-bridge cascaded three-level (TL) DC/DC converter, which would affect the high voltage stresses on the capacitors. This paper proposes a pulse-wide modulation (PWM) strategy with two working modes for the dual half-bridge cascaded TL DC/DC converter, which can realize the zero-voltage switching (ZVS). More significantly, a capacitor voltage balance control is proposed by alternating the two working modes of the proposed ZVS PWM strategy, which can eliminate the voltage unbalance on the four input capacitors. Therefore, the proposed control strategy can improve the converter's performances in: 1) reducing the switching losses and noises of the power switches; and 2) reducing the voltage stresses on the input capacitors. Finally, the simulation results are conducted to verify the proposed control strategy.
Reference Clip for Inter Prediction in Video Coding

Inter prediction is a fundamental technology in video coding to remove the temporal redundancy between video frames. Traditionally, the reconstructed frames are directly put into a reference frame buffer to serve as references for inter prediction. Using multiple reference frames increases the accuracy of inter prediction, but also incurs a waste of memory of the buffer since the content of reference frames is highly similar. To address this problem, we propose to organize the references at clip level in addition to frame level, i.e. the reference buffer stores not only reference frames, but also reference clips that are cropped regions selected from the reconstructed frames. Using clip-level references, we can manage the reference content more economically, since the content of multiple reference frames is divided into the singular content of each frame as well as the repetitive content that appears in multiple frames. For the repetitive content, only one copy is stored in reference clips so as to avoid duplicate. Moreover, using reference clips also facilitates the bit-rate allocation among reference content, i.e. the quality of each clip can be decided adaptively to achieve the rate-distortion optimization. In this paper, we propose a complete video coding framework using reference clips, and investigate the problems including how to generate reference clips as either singular content clips or repetitive content clips, how to manage the clips, how to utilize the clips for inter prediction, and how to allocate bit-rate among clips, in a systematic manner. The proposed video coding framework is implemented upon the state-of-the-art video coding scheme, High Efficiency Video Coding (HEVC). Experimental results show that our scheme achieves on average 5.1% and 5.0% BD-rate reduction than the HEVC anchor, in low-delay B and low-delay P settings, respectively. We believe that reference clip opens up a new dimension for optimizing inter prediction in video coding, and thus is worthy of further study.
Modulation Characteristics Enhancement of Monolithically Integrated Laser Diodes Under Mutual Injection Locking

Modulation characteristics enhancement by mutual injection locking of monolithically integrated distributed feedback (DFB) lasers is studied. Locking bistability in mutually coupled integrated lasers is observed. Resonance frequency as high as 34.3 GHz is recorded, corresponding to more than fivefold enhancement over the relaxation oscillation frequency at free running state. The mutually injection-locked lasers exhibit reduced harmonics and third-order intermodulation distortion, as well as suppressed relative intensity noise near the relaxation oscillation frequency. The spurious-free dynamic range is improved from 75 to 80 dB·Hz2/3. Furthermore, alleviation of chirp-induced power fading in analog optical links has been demonstrated. To our knowledge, this is the first time that suppressed nonlinear distortion and noise as well as chirp reduction are simultaneously demonstrated for monolithic mutually injection-locked DFB lasers.
Social Diffusion Analysis With Common-Interest Model for Image Annotation

Automatic image annotation has been extensively studied, mostly from a content-based approach, whose effectiveness is restricted by the “semantic gap” between low-level image features and semantic annotations, and by the irrelevance of annotations to image content. We propose a social diffusion analysis approach to image annotation, which exploits abundant social diffusion records about how images are disseminated within online social networks. Specifically, we propose a common-interest model to analyze social diffusion records, with the assumption that the diffusion pattern of an image in social networks is highly related to the relevance between image annotations and user preferences. In our proposed model, user preferences are represented as common interests of pairwise users instead of individual user interests. We find the notion of common interests not only facilitates the analysis of social diffusion patterns, but also leads to more accurate profiling of user preferences compared to individual interests. Based on the common-interest model, we design an image annotation framework via social diffusion analysis, which consists of the mining of common interests from social diffusion records, the feature extraction from diffusion graphs and common interests, and the automatic annotation by the learning-to-rank method. Experimental results on real-world data sets show that our proposed common-interest based approach outperforms individual-interest based methods, and also achieves superior performance than state-of-the-art content-based image annotation methods.
A new design of VLFSR-based mutual authentication protocol for RFID

A new security strategy based on Galois linear feedback shift register structure is proposed in this paper. To make the VLFSR's details unpredictable from the key stream out, a novel circular variable polynomial and independent feedback loop is presented and designed. Through the cryptanalysis, the mutual authentication requirements between Reader and Tag is met, as well as increases the security capability, while maintains low cost and low power consumption. Furthermore, the authentication protocol is implemented in HJTC 0.25μm 2P5M EEPROM process, only extra 3370 gates is needed for the proposed authentication protocol, and the power consumption is as low as 35.5 μW.
Service restoration with consideration of rush repair

The problem of service restoration in distribution network has been widely studied. Most of the researches focus on the reconfiguration of the distribution network and omit the trivial procedure of rush repair. In this paper, the problem of service restoration considering the constraints of emergency-response logistics is studied. The main objective of the problem is to reduce the interruption cost of customers. The interruption cost rate may be different and varying along outage time for different customers. The detail solution of service restoration is a series of time-stamped actions that contain both the reconfiguration of distribution system and the dispatch of available resources. So the reconfiguration and the resources dispatching must be considered systematically to figure out a feasible and optimal solution. The genetic algorithm and simulated annealing algorithm are employed to solve the problem. Test results are given to demonstrate the validity of the algorithm.
Sensorless Rapid On-line Evaluation for Slide Level

Slide level is one of the most important indexes of CNC machine tool performance. A novel kind of sensorless rapid on-line evaluation technology for machine tool slide level based on linear or rotary scale, motor encoder and AC servo motor current/output torque is proposed. To acquire the level information, the sensorless test principle is profoundly investigated, and the relationship mathematical model between the slide level and the sensorless data is established. Furthermore, according to the Stribeck effect, the various amplitude and velocity triangular wave test curve and a kind of precise nonlinear model identification method are suggested to get the key parameters such as static friction torque, coulomb friction torque, viscous coefficient and total moment of inertia. And then CNC slide level can be identified. The analyses results of the experiments show that it is simple, rapid, feasible and reliable for evaluating slide level.
Application of multi-centrality in human metabolism

Lots of studies have focused on the structure and function of high-quality human metabolic networks. Recently, hub-based centrality is used to analysis of human metabolic network core. However, it is clear that this specific centrality measure is not sufficient alone. In the present paper, by comparing 10 different centrality measures with their application to human metabolic network core, be similar but smart, we give the top 10 center metabolites in the core, and discuss their biological and curatorial signification.
Localized adaptive bounds for uncertain MIMO nonlinear system

A robust controller with localized adaptive bounds is proposed for a class of uncertain multiple-input-multiple-output nonlinear systems. Command filtered backstepping (CFBS) is used to design virtual control laws recursively. With spectral radius introduced into the control law, the assumption on nonsingularity of control coefficient matrix estimation is eliminated. Localized modification can overcome the parameter drift of standard σ-modification when states change and tracking errors are small. Adaptive bounding control is employed to compensate inherent approximation errors and external disturbances. It is proved that the proposed method can guarantee the boundedness of all signals in the closed-loop system theoretically. Simulation example demonstrates the effectiveness of the proposed method.
Research on Plug-and-play of DER-Network Coordinate Controller Based on IEC61850

It has been more challenging to monitor and control plenty of DERs (Distribution Energy Resources) when interconnected to distributed networks continuously. The ADN (Active Distributed Network) with hierarchical zoning control mode provides a way to monitor and control quantities of DERs effectively and efficiently. The EMS of ADN (ADMS, Active Distribution Network Energy Manager System) communicates with and controls DERs through DER-network coordinate controllers. This paper proposes a kind of plug-and-play solution of the controller based on IEC61850. The controller aims to maximize the incomes of the controlled area or other goals based on certain control logic. According to research on ADN's control framework and strategy, this paper defined some general functions of different kinds of DER-network controllers and corresponding Logic Nodes based on IEC61850. Besides, this paper defined the discover/register model achieved that when new DER installed or updating one DER, the DER can register in the ADMS through DERs' ICD files and update these configure files. The ADMS will acknowledge related controllers the new DERs' information and the new topology by sending them the new configure files. Based on this information, the ADMS and controllers are able to modify the communication and control parameters automatically. On the one hand, the communication between DERs and controllers is established automatically, and achieved the plug-and-play of information flow.
A novel nonlinear filter based on f-discrepancy rep-points

In practice, the statistics of many systems is usually regarded as Gaussian. Filtering these systems is an attractive field. This paper introduced the F-discrepancy rep-points (FDRP) of multivariate distribution in number theory into the nonlinear filter algorithm, and presented a novel approach for filtering nonlinear Gaussian system based on F-discrepancy rep-points set and Kalman filter (FDRP-KF). The advantage of the method is that there is no parameters needing to set and it can improve the precision increasingly. So it is easy and flexible to use in practice. The results of computer simulations also show that the performance of the algorithm is better than UKF, generic PF. The practical application of the approach also demonstrates its good performance.
A Wireless Sensor Monitoring Node Based on Automatic Tracking Solar-Powered Panel for Paddy Field Environment

In order to realize the collection, management, visualization, and uploading of real-time information in the paddy field, an information monitoring node based on automatic tracking solar-powered panel is presented in this paper. First, the node consists of information collecting sensors, STM32 MCU, LCD, GPRS module, automatic tracking solar-powered module, and monitoring interface. Second, data gathered from sensors can be displayed on the LCD and sent to the host computer interface. Moreover, host computer can also save the data packages to management server for examination and analysis. Finally, in the practical test, data are gathered every 2 h. At nontest time, the node works in low-power mode to achieve rational use of electric energy. The results of this experiment show that the node can achieve an accurate transmission and display of data, and the power supply system can meet the demand for electricity in continuous rainy days.