nils-herrmann/clean_scirepeval huggingface dataset:
Stochastic charging management for plug-in electric vehicles in smart microgrids fueled by renewable energy sources

Charging electric vehicles (EVs) from smart microgrids fueled by renewable energy resources is becoming a popular green approach. Although some works have been done about renewable energy sources and EVs in smart microgrids, the stochastic characteristics and the dynamic interplay between these two important green solutions should be carefully considered. Furthermore, one of the important performance metrics, service availability for EVs, is largely ignored in the existing works. In this paper, we study the charging policies in smart microgrids with EVs and renewable energy sources. We analyze service availability under different charging policies. Numerical results are presented to show the performance of different charging policies.
Underwater high-power inductive coupling energy transmission system

According to the principle of electric-magnetic-electric transformation relations, the underwater intelligent wireless inductive charging system based on principle of electromagnetic induction, which achieves the effect of wireless charging is proposed in this paper and it is characterized by safety, simple and agility. The details of system's principle, system's working procedure, hardware circuits and inductive coupler's design are introduced in the paper. At last, after analyzing the test results, it shows that the various functional modules of the system work well and the output power and efficiency satisfy the requirement of task design.
An Optimal Handoff Decision Algorithm for Communication-Based Train Control (CBTC) Systems

As an advanced train control system, communication-based train control (CBTC) system can improve the utilization of railway network infrastructure and enhance the level of safety and service offered to customers. In this paper, we propose a seamless handoff scheme for CBTC systems based on Stream Control Transmission Protocol (SCTP) and IEEE 802.11p. The focus of our work is in the handoff decision phase, with the objectives of maximizing the SCTP throughput and minimizing the handoff latency. The handoff decision is modeled as a semi-Markov Decision Process (SMDP). Simulation results show that the proposed SMDP based handoff decision algorithm can significantly improve the SCTP throughput and decrease handoff delay.
A Heuristic Reduced Complexity Computing Method for Multi-Cell Joint Channel Estimation in B3G TDD System

For the concerned TD-SCDMA and its LTE cellular mobile radio system introduced in this paper, there are already some useful algorithms concerning multi-user detection to eliminate inter-symbol interference (ISI) and multiple-access interference (MAI). Since only home cell multiple users are included, those algorithms can only combat ISI and MAI between home cell users. Interferences from users of neighbor cells are treated as white noise. When planning network deployment by assigning same frequency band to all cells, which is a merit for TDD system to increase efficiency and capacity, strong inter-cell interferences occur and the overall performance deteriorates rapidly. To solve this problem, we introduce this new multi-cell detection algorithm and show its benefit. Essentially, the complexity of the new algorithm will increase tremendously. So we also give an efficient simplifying method for it to be practical without imposing hard requirement to the original hardware platform. Simulation results also show that the new algorithm is effective and satisfying.
Inductance evaluation of a 22.9 kV/50 MVA HTS cable with shield by electrical method

In this study, an inductance measurement method by electrical method are originally suggested for a 22.9 kV/50 MVA high temperature superconducting (HTS) cable with a conductor and a shield. Using this method, we experimentally evaluate self-inductances of the conductor and shield, respectively, and also their mutual inductance. To verify the measured data, the self and mutual inductances of the conductor and shield are calculated from finite element method. The main result shows the calculated inductances are in good agreement with measured ones. Therefore, the reliability of the inductance measurement method is confirmed.
The Analysis and Design of Network and Information Security of Electric Power System

Along with the electric power information network system connecting into the Internet, the network and information securities are getting serious. This paper analyzes the characteristics of the electric power information network system, proposes the information network structure, and designs the security architecture of the electric power information network system. Moreover, the concrete security techniques used in the architecture are introduced in detail such as the security insulation techniques, including the physical insulation technique, the protocol insulation technique, firewall technique, VPN and VLAN technique, the security techniques of the system level, secure design strategy on the application level and other security techniques. Because an electric power system needs to send and receive secret messages frequently, an integrated encryption and digital signature algorithm is designed. These designs have applied to an electric power information network system, it is proved to be secure, reliable and practical
A Hybrid Support Vector Regression for Time Series Forecasting

The study applies a novel neural network technique, hybrid support vector regression (SVR), to forecast values of the turbo-generator vibration in time series. The simulation experiment results showed that the hybrid model is superior to the individual models for the test. Most of the individual models evaluated showed poor ability to detect directional change. This problem can be overcome with the use of the hybrid model. Besides superior turning point detectability, the hybrid model could achieve superior predictive performance and showed promising results. Therefore, the results suggested that the proposed hybrid model is typically a reliable forecasting tool for application within the forecasting fields of time series.
Notice of RetractionChemo-Enzymatic Synthesis of Nanofiber Membrane with Glucose by Electrospinning

Glycopolymers/PAN fibers were successfully prepared by electrospinning method from co-dissolving solutions of PAN and glycopolymersl in Dimethylformamide (DMF) as the spinning solutions. The samples thereby obtained were characterized by SEM and FTIR measurements. The polymerizable glucose monomers were synthesized by selective enzymatic synthesis methods using divinyl dicarboylates with different carbon chain length as acyl donor. FT-IR were used to characterize the synthesized monomer. Polymerizable glucose monomers were copolyymerized using AIBN as initiator. The structure and molecular weight of the glycopolymers was confirmed by FT-IR and GPC. The molecular weight of the glycopolymers reached 2.35×104. Composite membranes of glycopolymers/PAN nanofibers with different weight ratio of glycopolymers were fabricated successfully using electrospinning. Results from SEM showed that the glycopolymers was distributed evenly in PAN nanofibers and the intermolecular interactions of the complex were evaluated by Fourier transform infrared spectroscopy (FT-IR). Results show that the blends prepared here have unique structures that could be developed further to expand the applications of nanofibers such as lipase immobilization, lectin recognition abilities, biosepartion techniques and hepatocyte adhension.
The research of J-Quinn ranging algorithm for LFMCW Radar

For improving the range accuracy of LFMCW Radar with triangle wave modulation, frequency estimation performance of Jacobsen algorithm and Quinn algorithm are discussed. When the signal frequency is close to the midpoint of two neighboring discrete frequencies, Jacobsen algorithm has poor accuracy, while Quinn algorithm has good one. A novel combined algorithm named J-Quinn algorithm is proposed. Firstly, Jacobsen algorithm is employed for coarse frequency estimation. Secondly, the signal frequency is shifted to the midpoint of two neighboring discrete frequencies, and then Quinn algorithm is employed for fine frequency estimation. The simulation shows that J-Quinn algorithm has higher range accuracy and good stability. Ranging experiments are performed with LFMCW Radar, and the results show that range error can be diminished to 0.04m, so the ranging performance is improved.
In-sequence video duplicate detection with fast point-to-line matching

A computational geometry approach is developed to detect video duplicate with mild transformations. We model the video sequence as a trajectory after scaling and projection. Through interpolation and equal curve length sampling, part of the frame points is selected. A simplified video representation is the line segment set connecting the left neighboring points. For a given query, match distortion is calculated by projecting the query frame points to the line segment set guided by the frame temporal relationship. Experiments demonstrate the effectiveness of the proposed approach.
A kind of SAaGA Hybrid Meta-heuristic Algorithm for the Automatic Test Data Generation

Test data generation is very labor-intensive and expensive in software testing. The automation of test process can achieve significant reductions in the cost of software development. Combining the parallel search ability of the adaptive genetic algorithm (aGA) with the controllable jumping property of simulated annealing (SA), a kind of effective hybrid meta-heuristic algorithm (SAaGA) with the operators and parameters well designed is proposed for automatic test data generation in this paper. The experiments have shown that the SAaGA hybrid meta-heuristic algorithm may significantly reduce the cost and improve the percentage of code coverage compared to the genetic algorithm and simulated annealing
Indium-Zinc-Oxide Neuron Thin Film Transistors Laterally Coupled by Sodium Alginate Electrolytes

Neuromorphic devices are of great significance for capturing the computation power of the neural network with ultralow energy consumption and extremely high efficiency. Here, multigate indium-zinc-oxide-based neuron thin film transistors laterally coupled by sodium alginate electrolyte films were fabricated polyethylene terephthalate substrates for neuromorphic system application. The dynamic range of the synaptic response can be effectively modulated by the third modulatory input. More importantly, multiplicative operation was realized successfully based on the rate-coding mode. Such laterally coupled oxide-based neuron transistors could be used as the potential building block in neuromorphic systems.
Dynamic Trajectory Optimization Design for Railway Driver Advisory System

Driver Advisory Systems (DAS) aim to provide reliable and efficient driving instructions to the driver with optimized trajectory. This paper studies trajectory optimization method to achieve energy efficiency and punctuality for DAS. Firstly, the design of offline trajectory optimization is studied, using the Genetic Algorithm (GA) to optimize the energy-efficient trajectory. The performance of offline optimization is evaluated by the application of three different driving styles. Online optimization is constructed to dynamically adjust the trajectory when a driving deviation occurs. The combination of offline optimization and online optimization method is simulated as a dynamic trajectory optimization system, to represent a practical solution for DAS systems to achieve energy efficiency and punctuality by real-time adjustment during the journey. An evaluation of energy saving and computation efficiency for the trajectory optimization is conducted based on a simulation of a real-scale route.
Lossless point cloud geometry compression via binary tree partition and intra prediction

Characterized by geometry and photometry attributes, point cloud has become widely applied in the real-time presentation of various 3D objects and scenes. The development of even more precise capture devices and the increasing requirements for vivid rendering inevitably induce huge point capacity, thus making the point cloud compression a demanding issue. Considering the non-uniform sampling and time-variant geometry, appropriate structural representation for point cloud is important. In this paper, we propose a lossless geometry compression algorithm for 3D point cloud which serves as the basis of future adaptive improvement. We utilize the binary tree structure for effectively partitioning unorganized points into block structure. This hierarchical representation obtains roughly the same quantity level for each leaf node. Further analysis is conducted on an intra-geometry prediction via extended Travelling Salesman Problem (TSP), achieving an impressive performance in eliminating point-wise redundancy while preserving one single reference position for each block. The residual encoding is accomplished via a shallow neural network-based lossless compression algorithm, PAQ. Simulation results confirm the lossless compression of geometry from high quality capture, achieving approximately 3.5 times efficiency gain over the state of art algorithm implemented as MPEG Point Cloud Compression (PCC) reference software.
Incremental Mining of Frequent Query Patterns from XML Queries for Caching

Existing studies for mining frequent XML query patterns mainly introduce a straightforward candidate generate-and-test strategy and compute frequencies of candidate query patterns from scratch periodically by checking the entire transaction database, which consists of XML query patterns transformed from user queries. However, it is nontrivial to maintain such discovered frequent patterns in real XML databases because there may incur frequent updates that may not only invalidate some existing frequent query patterns but also generate some new frequent ones. Accordingly, existing proposals are inefficient for the evolution of the transaction database. To address these problems, this paper presents an efficient algorithm IPS-FXQPMiner for mining frequent XML query patterns without candidate maintenance and costly tree-containment checking. We transform XML queries into sequences through a one- to-one mapping and then mine the frequent sequences to generate frequent XML query patterns. More importantly, based on IPS-FXQPMiner, an efficient incremental algorithm, Incre-FXQPMiner is proposed to incrementally mine frequent XML query patterns, which can minimize the I/O and computation requirements for handling incremental updates. Our experimental study on various real-life datasets demonstrates the efficiency and scalability of our algorithms over previous known alternatives.
An Improved NIRA Algorithm of Nash Equilibrium and Its Application

Theoretical studies have shown that a relaxation algorithm can be used to find noncooperative equilibrium of synchronous infinite games with nonlinear payoff functions and coupled constraints based on Nikaido-Isoda function. In this study, this paper introduces an improvement to the Nash equilibrium algorithm with linear search step-size control. Compared with the other two choice of step-sizes, i.e constant step size and steepest-decent step-size, this algorithm performs a well balance between iterative steps and time efficiency. In the end of this paper, it provides a case study of financial investment in order to determine the optimal financial investment ratio by this algorithm.
Synaptic Behaviors Mimicked in Flexible Oxide-Based Transistors on Plastic Substrates

In the human brain, synapses are the crucial connective parts between neurons, which endow neurons with significant computational abilities. Here, indium-zinc-oxide (IZO) based flexible synaptic transistors are fabricated on a plastic substrate by a simple self-assembly method. Proton conducting phosphorus-doped nanogranular SiO2 electrolyte is used as the gate dielectric. Excitatory postsynaptic current, paired-pulse facilitation, and long-term memory are mimicked in the flexible artificial synapses. Such IZO-based flexible electronic synapses are promising for building neuromorphic systems.
Modeling and simulation of Meteor Burst Communication network

Meteor Burst Communication is characterized by intermittence, time-varying channel, which limit the network stability and throughput significantly. How to improve the network stability and throughput has become one of the challenges. In this paper, to overcome the shortcomings of network reliability, we use high-speed wired links connecting the base stations according to the structure of ring topology, and a meteor burst communication network based on stop-wait protocol is constructed. We analyze and simulate the packet length and the packet rate based on the platform of Opnet. Finally, the simulation results are given.
Water quality remote sensing monitoring research in China based on the HJ-1 satellite data

The domestic interior water body was monitored Based on an HJ-1 satellite multi-spectrum data. Chlorophyll a density is inverted from the empirical model based on the different area and different season. Suspension density inversion is based on the photobiology model of near-infrared waveband method. Based on chlorophyll a and the suspension density, the interior water body trophic level index is monitored using remote sensing data. There was a synchronized observation experiment in Lake Chaohu in June, 2009. The measurement data confirms the water quality parameter inversion algorithm. The results indicated that the chlorophyll a density inversion precision is inferior to the suspension density, but both inversion precision meets the water environmental monitoring service demand.
High speed, ultra-compact spectrometer using high contrast grating swept-wavelength detector

Chip-scale optical spectrometers have been drawing more and more research interests for its increasing applications in various lab-on-a-chip systems, e.g. medical diagnostics, biochemical sensing, and environmental monitoring, etc. It is also desirable in optical networks as a compact wavemeter. Significant progress has been made and chip-scale spectrometers have been demonstrated with various configurations, such as superprism or arrayed waveguide grating [1,2], Fabry-Perot filter array , micro-resonator array , etc. However, there is a fundamental tradeoff between the resolution and footprint on these dispersive components or resonance array. Tunable Fabry-Perot filter, on the other hand, turns the spectrum splitting from the spatial domain into temporal domain. It requires only one photodetector, and can achieve high resolution and small footprint at the same time . To further reduce the footprint of the whole system, here we monolithically integrate the tunable Fabry-Perot filter with the photodetector into one single device, herein referred as a swept-wavelength detector. It employs quantum well structures in a Fabry-Perot cavity, with a high contrast grating (HCG)  as a microelectromechanical actuable top reflector and a distributed Bragg reflector (DBR) as the bottom reflector, shown in Figure 1. The ultrahigh reflectivity and light-weight of the HCG ensures a high finesse and a high tuning speed. A total bandwidth of 33.5 nm at 1550 nm and an operation speed of 200 kHz are experimentally demonstrated.
A Wideband One-Ring MIMO Reference Channel Model for Non-isotropic Scattering Environments

In this paper, we propose a wideband one-ring multiple-input multiple-output (MIMO) reference channel model for non-isotropic scattering environments. The model is designed in such a way that the delay power spectral density (PSD) of the reference channel model is identical to a given delay PSD. Furthermore, closed-form solutions are provided for the temporal autocorrelation function (ACF), the two-dimensional (2-D) space cross-correlation function, and the frequency correlation function (FCF). Finally, numerical results are presented for the reference channel model. The proposed reference channel model is an important framework for the derivation of an efficient wideband MIMO channel simulator with given space-time-frequency correlation properties.
Laser patterned junctionless neuron thin-films transistor arrays

Indium-zinc-oxide (IZO) thin film transistors (TFT) have been fabricated on ITO/glass substrate with a laser scribing process at room temperature. Such transistors are composed of a bottom indium-tin-oxide (ITO) floating gate and multiples of in-plane control gates. The multiple input gates are not truly independent gates, capacitively coupling with the floating gate together, thus Neuron MOS (vMOS) operation is realized. The control gates, coupling with the floating gate, control the “on” and “off” of the neuron transistor. Robust AND logic is demonstrated on such neuron transistor.
Uniform Test Comparison of ULSI, PMMLCG, GFSRG and Super-Prime Method

A new random number generate algorithm (ULSI) which is based on users' location information and spectrum information is proposed in  .In this paper, we continue analyze uniform test results and compares ULSI algorithm with PMMLCG, GFSRG, and Super-prime method. Simulation results show that ULSI algorithm has better performance in uniform statistical distribution.
File synchronization of multi-machine system design and implementation based cloud storage

With the popularization of computers and social development, it is become more and more common the personal remote office and electronic office. The question is becoming that how to synchronization of large amounts of files between multiple computers. In this paper, the mechanisms of metadata is used to directory synchronization and control file version. According one of the properties of the cloud storage which can store additional and to improving the efficiency of large file transfers, file segmentation is used. To achieve synchronization between multiple computers, we used cloud storage to save and transit through the file.
Analytical Modeling of Open-Circuit Air-Gap Field Distributions in Multisegment and Multilayer Interior Permanent-Magnet Machines

We present a simple lumped magnetic circuit model for interior permanent-magnet (IPM) machines with multisegment and multilayer permanent magnets. We derived analytically the open-circuit air-gap field distribution, average air-gap flux density, and leakage fluxes. To verify the developed models and analytical method, we adopted finite-element analysis (FEA). We show that for prototype machines, the errors between the FEA and analytically predicted results are <1% for multisegment IPM machines and <2% for multilayer IPM machines. By utilizing the developed lumped magnetic circuit models, the IPM machines can be optimized for maximum fundamental and minimum total harmonic distortion of the air-gap flux density distribution.
Virtual resource allocation in a network virtualization based integrated train ground communication system

Train ground communication systems for different applications are deployed and managed independently in current urban rail transit systems with Wireless Local Area Network (WLAN) technology. Investing and constructing communication infrastructures repeatedly not only waste substantial social resources but also bring many difficulties to maintain all these infrastructures. In this paper, we design a network virtualization based integrated train ground communication system for urban rail transit systems. The virtual resource allocation in the integrated system is formulated as an optimization problem. On the premise that the train ground communication requirement of communication based train control system is guaranteed, the optimization objective is to maximize the long-term general utility for all the urban rail transit applications. We use the distributed method based on alternating direction method of multipliers (ADMM) to solve the optimization problem. Simulation results show that the designed integrated train ground communication system quality of service (QoS) can be improved effectively with the proposed approach.