nils-herrmann/clean_scirepeval huggingface dataset:
Analysis of Projection Accuracy of Synthetic Image in Combined Vision System

Combined Vision System (CVS) that provides pilots a combination display with synthetic image and enhanced real vision requires critical image alignment. However, airborne navigation sensors are not accurate enough to support ideal alignment of synthetic and real image in CVS naturally. In this paper we investigate the effects of aircraft position and attitude errors on the projection accuracy of synthetic image in CVS. The major contribution of this paper lies in two aspects. Firstly, a projection model is established and the probability distributions of pixel errors are estimated. Secondly, four simulation scenarios are developed to evaluate the effects of position and attitude errors on the projection accuracy. The experimental results show that aircraft attitude error has more significant impact than position error on the pixel projection accuracy. The impacts of yaw error and roll error on the pixel error of synthetic image are larger and belong to primary factors. The probability distribution of pixel error obeys Gaussian, but the standard deviation of pixel row error is greater than column error with the same aircraft position and attitude parameters.
A time sequence generator for 14-bit SAR ADCs in 90nm process

A time sequence generator (TSG) in 90nm process is introduced which uses 8 latches to generate 16 pulses, of which 14 ones are used to drive the 14 latches in the successive approximation register (SAR) of our 14-bit SAR ADCs. The 14 latches of the SAR are set and decided, successively on the command of the TSG. The simulation shows that the 14-bit SAR ADC in 90ns process with the TSG has a SNR of 68.9dB and SFDR of 81.9dB, which is better than the ADCs with similar architecture but without our time sequence generator.
A Genetic Training Algorithm of Wavelet Neural Networks for Fault Prognostics in Condition Based Maintenance

The main idea of condition based maintenance (CBM) is to monitor the health of critical machine components and system almost continuously during operation and maintenance actions based on the assessed condition. If done correctly, CBM has the benefits such as reducing catastrophic failures, minimizing maintenance and logistical cost, maximizing system security and availability and improving platform reliability. A CBM system usually has four major functional modules, namely feature extraction, diagnostics, prognostics and decision support. Among them, fault prognostics is the most important enabling technology. It is the most challenging research area which is so called crystal ball of CBM. But it has the potential to be the most beneficial. This paper presents a fault prognostic algorithm based on a generic wavelet neural networks (WNN) architecture. Its training process based on genetic algorithm is described in detail. Finally, the fault prognostic algorithm has been verified using a simulation experiment, and the results are very satisfactory.
Design of 24-GHz High-Gain Receiver Front-End Utilizing ESD-Split Input Matching Network

This brief presents an electrostatic discharge (ESD)-protected receiver front-end for wireless communications around 24 GHz. A Π-type input matching network incorporating two split ESD capacitances and an on-chip inductor is constructed to realize the source impedance transformation for high gain, good input matching, and only slightly degraded noise figure (NF). The measured results show that the front-end has an input return loss of less than -12 dB, a 36-dB voltage gain, a 6.8-dB NF, and a 2-dBm output CP1dB. The chip, fabricated in 0.13-μm RF CMOS process, has a protection level equivalent to ±2-kV human body model ESD and consumes 40 mA from a 1.2-V supply with a total area of 1 × 0.8 mm2.
A Universal Method for Constructing N-Port Nonblocking Optical Router for Photonic Networks-On-Chip

We propose a universal method for constructing N-port nonblocking optical routers based on microring resonators. The topologies for five-, six-, seven-, and eight-port nonblocking optical routers are presented. As a case study, we compare the five-port optical router constructed by our method with the previously reported ones. The simulation results show that the mesh photonic network constructed by the proposed five-port optical routers has low insertion loss and high optical signal-to-noise ratio. Moreover, high-radix optical routers can be easily constructed by the proposed method, which can support more complicated and efficient network.
Advertising based on users' photos

In this paper, we tackle the problem of learning a user's interest from his photo collections and suggesting relevant ads. We address two key challenges in this work: 1) understanding a user's photos to detect his interest, and 2) bridging the lexical and semantic gap between the vocabulary of ads and that of general users' photos. We solve the first problem by employing a data-driven image annotation approach to annotate each photo and modeling a group of photos, and tackle the second problem by learning and matching the topics of users' photos and ads. The experiments based on real Flickr data showed the effectiveness of the approach.
Distributed Aggregate Privacy-Preserving Authentication in VANETs

Existing secure and privacy-preserving vehicular communication protocols in vehicular ad hoc networks face the challenges of being fast and not depending on ideal tamper-proof devices (TPDs) embedded in vehicles. To address these challenges, we propose a vehicular authentication protocol referred to as distributedaggregate privacy-preserving authentication. The proposed protocol is based on our new multiple trusted authority one-time identity-based aggregate signature technique. With this technique a vehicle can verify many messages simultaneously and their signatures can be compressed into a single one that greatly reduces the storage space needed by a vehicle or a data collector (e.g., the traffic management authority). Instead of ideal TPDs, our protocol only requires realistic TPDs and hence is more practical.
A cascaded online uninterruptible power supply using reduced semiconductor

A cascaded online uninterruptible power supply (UPS) is proposed here that uses 25% lesser semiconductor, as compared to its traditional H-bridge cascaded precedence. Unlike other component-saving configurations where compromises are unavoidable, almost no performance degradations and constraints are experienced by the presented UPS, as guaranteed through proper topological and control design. Advantages of the cascaded UPS can therefore be summarized as reduced system cost, improved redundancy, better waveform quality and the same reliable protection expected from an online system. The only disadvantage, if considered so, is the requirement for slight logic manipulation of the switch gating signals, which in practice can simply be done by discrete logic gates without involving expensive programmable devices. Simulation results are presented to verify the discussed concepts.
A New Provably Secure Certificateless Signature Scheme

Certificateless public key cryptography was introduced by Al-Riyami and Paterson to overcome the key escrow problem of ID-PKC. In this paper, we present an efficient certificateless signature scheme using bilinear maps. The scheme can be proved secure in the strongest security model of certificateless signature schemes. In terms of computational cost, totally, only two pairing operations are required for signing and verification. It is more efficient than the other existing certificateless signature schemes secure against a super type I/II adversary.
Distributed filtering with random sampling and delay

The problem of estimation and filtering in a distributed sensor environment is considered. The sensors obtain measurements about target trajectories at random times which transmit to the fusion center. The measurements arrive at the fusion with random delays which can be due to queuing at the sensor buffer and to delays in the transmission time as well as in the propagation time. The fusion generates estimates of the target tracks using the received measurements. The measurements are received from the sensors at random times, can have unknown time-origin and can arrive out of sequence. Optimal filters for the estimation of target tracks based on measurements of uncertain origin received by the fusion at random times and out of sequence have been derived for the cases of random sampling, random delay, and both random sampling and random delay. It is shown that the optimal filters constitute an extension to the Kalman filter to account for the uncertainty involved with the data time-origin.<<ETX>>
All-Solid Silicate Photonic Crystal Fiber Laser With 13.1 W Output Power and 64.5% Slope Efficiency

We demonstrate an all-solid Nd 3+-doped silicate photonic crystal fiber with 13.1 W output power at 1061 nm and 64.5% slope efficiency. We also theoretically investigate and prove the effects of confinement loss and overlap fraction on a double-clad photonic crystal fiber laser. An innovative design is suggested to improve the laser beam quality.
Analysis and Diagnosis of Conducted EMI Generated by Automatic Voltage Regulator (AVR) System in Synchronous Generator

With the power integrated technology is adopted, the capacity of power system in ships became larger and larger. More and more equipments are connected in the same power mains, and the requirement of system EMC become stricter than before. In such power system, the generator output should not only satisfy the demand of power quality, but its high-frequency effect to environment should also be considered. Thus, the interference which spread from power frequency to several mega Hz should all be reduced. Since the power electronics technology is introduced, automatic voltage regulator (AVR) system becomes the main interference source in conducted radio-frequency span. Furthermore, the interference could conduct to the generator output by the exciter transformer. In this paper, the interference generated by AVR system is analyzed and the diagnosis method of generator output interference is illustrated.
Automatic inpainting of linearly related video frames

This paper addresses automatic inpainting of a specific but common kind of videos captured by imaging a far or planar scene with a moving camera. The projective model tells that the frames of such videos can be approximately aligned by linear mappings except for some to-be-inpainted small regions. Mathematically, we treat inpainting as a global optimization with a linear system incorporating both the temporal consistency and the priors of the inpainting regions: (i) temporally registered frames form a low rank matrix; (ii) the pixels in the given inpainting regions destroy the low rank-ness with gross sparse errors. Besides, we also use a soft mask to ensure consistent global brightness before and after inpainting. Further, we propose a numerical solution to above optimization based on Augmented Lagrangian Method. The experiment results demonstrated our advantageous in both preserving thin scene structures and the details prone to be smoothed out by previous methods.
A novel Middleware for the Mobility Management Over the Internet

The features of mobility, which enormously impact on how communication is evolving into the future, represent a particular challenge in todaypsilas wireless networking research. After an identification and evaluation of the gap between the discontinuities of the communication service inherent to the physical layer of mobile networks and the continuity requirements issue from the stream centric multimedia applications, we propose a novel middleware 3MOI (Middleware for the Mobility Management Over the Internet) which can support efficient and context-aware mobility management and satisfy new mobility requirements such as dynamical location management, fast handover, and continuous connection support.
A New Torque Control Method for Torque Ripple Minimization of BLDC Motors With Un-Ideal Back EMF

In classical control of brushless dc (BLDC) motors, flux distribution is assumed trapezoidal and fed current is controlled rectangular to obtain a desired constant torque. However, in reality, this assumption may not always be correct, due to nonuniformity of magnetic material and design trade-offs. These factors, together with current controller limitation, can lead to an undesirable torque ripple. This paper proposes a new torque control method to attenuate torque ripple of BLDC motors with un-ideal back electromotive force (EMF) waveforms. In this method, the action time of pulses, which are used to control the corresponding switches, are calculated in the torque controller regarding actual back EMF waveforms in both normal conduction period and commutation period. Moreover, the influence of finite dc bus supply voltage is considered in the commutation period. Simulation and experimental results are shown that, compared with conventional rectangular current control, the proposed torque control method results in apparent reduction of the torque ripple.
Cyclic Prefix-Based Universal Filtered Multicarrier System and Performance Analysis

Recently proposed universal filtered multicarrier (UFMC) system is not an orthogonal system in multipath channel environments and might cause significant performance loss. In this paper, the authors propose a cyclic prefix (CP) based UFMC system and first analyze the conditions for interference-free one-tap equalization in the absence of transceiver imperfections. Then the corresponding signal model and output signal-to-noise ratio expression are derived. In the presence of carrier frequency offset, timing offset, and insufficient CP length, the authors establish an analytical system model as a summation of desired signal, intersymbol interference, intercarrier interference, and noise. New channel equalization algorithms are proposed based on the derived analytical signal model. Numerical results show that the derived model matches the simulation results precisely, and the proposed equalization algorithms improve the UFMC system performance in terms of bit error rate.
Chaotic characteristics of fifth nonlinear duffing system under parametric excitation

Consider the parametric excitation, studied the characteristics of fifth nonlinear duffing chaotic system. By applying geometric theory of dynamical systems, bifurcation theory and infinitesimal calculus, obtain the homoclinic orbit of fifth duffing equation. Using Melnikov method determines the initial chaotic condition of system and perturbation equation. By means of numerical calculation and computer simulation analysis, get the numerical solution, and on this basis to draw a clear chaos picture and continuous repetition of the Poincare map. Numerical simulations show that this method is an extraordinary effective method to study the fifth nonlinear duffing system.
Adaptive spatiotemporal background modelling

In this study, one adaptive spatiotemporal background modelling algorithm is proposed for robust and reliable moving object detection in dynamic scene. First, a modified adaptive Gaussian mixture model (GMM) is presented to describe the temporal distribution of each pixel, based on which the spatial distribution of background is constructed by using non-parametric density estimation. By fusing the temporal and spatial distribution model, a heuristic strategy is presented for background subtraction. To reduce the computational cost, a novel criterion for adaptively determining the components number of GMM and the integral image method for calculating the spatial distribution model are proposed. Several experiments show that the proposed method can effectively reduce false positives caused by sudden or gradual changes of the background, and maintains lower false negatives, compared with some representative algorithms.
Appraisal of University's Technovation Ability

Technovation ability is one of the most significant strengths for universities. It has a positive influence to orient and support talent cultivation and society service and so on. So it plays important role to appraise and give rein to the technovation ability. The text establishes appraisal index system, made up of such four broad headings as resources into ability, social influence power, domestic radiating capacity and sustainable development ability. Based on Delphi, analytic hierarchy process, grey relation degree and fuzzy system theory, a grey comprehensive appraisal model is put forward to appraise university's technovation ability quantitatively. The paper appears that it is feasible and effective to appraise the university's technovation ability with the grey comprehensive appraisal model by researching and calculating.
BP neural network control of single inverted pendulum

The BP neural network can combine with Levenberg-Marquardt algorithm, which effectively overcomes the disadvantages of traditional neural network such as slow convergence speed, always converging to local minimum point and poor stability. Neural network capture the data of inverted pendulum with LQR optimal control method, set up multilayer forward feedback neural network. We through matlab simulate the control system to get the each state variable and control response curve of Single inverted pendulum. Experimental results show that the improved BP neural network can successfully control the inverted pendulum and have faster speed of control response and good stability than LQR optimal control.
A Novel Ant-based Clustering Algorithm with an Attractive Force Field

This paper presents a novel ant-based clustering algorithm. Different from conventional ant-based clustering algorithms in which the objects are picked up or dropped down by virtual ants, our propose algorithm looks each object as an ant. The objects are first projected to a plane randomly. Then an attractive force field is created. The object (ant) is attracted by the similar ones in its local surrounding and moves to a certain place. The moving direction and moving range are determined by the composite of all attractive forces. The clusters are created by this attractiveness after many iterative cycles. The paper gives the detailed process of the algorithm. The performance of the algorithm is compared with other classic algorithms on several simulated and real datasets. The results are very encouraging in terms of the computation efficiency and clustering quality.
ACTA: Will the Developing Countries Follow the TRIPS-plus Initiative?

Proposed on the basis of increasing inflow of counterfeited products, Anti-Counterfeiting Trade Agreement (ACTA) is a treaty intended to be enacted by a number of developed countries as a TRIPS-plus mandate for increased enforcement against counterfeited products. ACTA is evaluated by us and others as very pro-rights holder & pro importing countries, in the sense it presents options to withhold allegedly infringing goods at variable stages of the value-chain, at minor grounds, with potential more extreme civil and criminal procedure consequences. Albeit ACTA is expected to effect the decrease in counterfeited goods, a side-effect could be the inhibition of otherwise free movement of legal goods between countries. One example of this could be inhibition of free movement of drugs and their resources for production ¨C especially because establishment of actual infringement is difficult due to the nature of the good. We foresee an increased number of disputes surrounding withholding the free movement of goods ¨C especially medicines ¨C between countries acceding to TRIPS resp.
Color demosaicking via directional linear minimum mean square-error estimation

Digital cameras sample scenes using a color filter array of mosaic pattern (e.g., the Bayer pattern). The demosaicking of the color samples is critical to the image quality. This paper presents a new color demosaicking technique of optimal directional filtering of the green-red and green-blue difference signals. Under the assumption that the primary difference signals (PDS) between the green and red/blue channels are low pass, the missing green samples are adaptively estimated in both horizontal and vertical directions by the linear minimum mean square-error estimation (LMMSE) technique. These directional estimates are then optimally fused to further improve the green estimates. Finally, guided by the demosaicked full-resolution green channel, the other two color channels are reconstructed from the LMMSE filtered and fused PDS. The experimental results show that the presented color demosaicking technique outperforms the existing methods both in PSNR measure and visual perception.
AN adaptive L1–L2 hybrid error model to super-resolution

A hybrid error model with L<inf>1</inf> and L<inf>2</inf> norm minimization criteria is proposed in this paper for image/video super-resolution. A membership function is defined to adaptively control the tradeoff between the L<inf>1</inf> and L<inf>2</inf> norm terms. Therefore, the proposed hybrid model can have the advantages of both L<inf>1</inf> norm minimization (i.e. edge preservation) and L<inf>2</inf> norm minimization (i.e. smoothing noise). In addition, an effective convergence criterion is proposed, which is able to terminate the iterative L<inf>1</inf> and L<inf>2</inf> norm minimization process efficiently. Experimental results on images corrupted with various types of noises demonstrate the robustness of the proposed algorithm and its superiority to representative algorithms.
Adaptive Stochastic Gradient Descent on the Grassmannian for Robust Low-Rank Subspace Recovery

In this study, the authors present GASG21 (Grassmannian adaptive stochastic gradient for L 2,1 norm minimisation), an adaptive stochastic gradient algorithm to robustly recover the low-rank subspace from a large matrix. In the presence of column outliers corruption, the authors reformulate the classical matrix L 2,1 norm minimisation problem as its stochastic programming counterpart. For each observed data vector, the low-rank subspace S is updated by taking a gradient step along the geodesic of Grassmannian. In order to accelerate the convergence rate of the stochastic gradient method, the authors choose to adaptively tune the constant step-size by leveraging the consecutive gradients. Numerical experiments on synthetic data and the extended Yale face dataset demonstrate the efficiency and accuracy of the proposed GASG21 algorithm even with heavy column outliers corruption.
Airborne experiments validating the spaceborne RFSCAT on CFOSAT

Airborne experiments were carried out to validate the spaceborne scatterometer. Airborne scatterometer use all the instruments of the spaceborne scatterometer to validate the system design and reliability, except the power amplifier and the antenna. The software of the scatterometer is redesigned due to the observation geometry of airborne platform. The wind retrieval results are compared with the HY-2A scatterometer and the real time wind vector measured on the ship at the center of testing region.
Bioinformatics databases for network pharmacology research of traditional Chinese medicine: A systematic review

Network pharmacology which is based on bioinformatics and system biology knowledge has been employed into the field of Traditional Chinese Medicine (TCM) researches in recent years. In order to summarize current available bioinformatics databases, especially those can be used for TCM formulae study; a systematic search of Chinese literature by May 2017 was conducted. Results showed that research methods of network pharmacology have been widely applied in a variety of diseases and TCM formulae since 2012. Four comprehensive TCM bioinformatics databases with multi-functions were briefly introduced.