nils-herrmann/clean_scirepeval huggingface dataset:
City security level mining based on massive criminal data

In this work, we focus on the problem of city security based on the massive amount of crime statistics data. Combined with city crime statistics data, fuzzy comprehensive evaluation method is used to judge the safety grade of the city, and the weight of the evaluation set is calculated based on the analytic hierarchy process. The experiment results show that fuzzy comprehensive evaluation method is effective and feasible, and it can be widely used in the evaluation of general city security level.
Interconnection of large-scale LANs via a two-stage switching hub for multimedia applications

As broadband multimedia applications to the desk top are becoming popular today, the high-speed bandwidth demand from a single user will occupy large shares of the LAN's channel capacity. Therefore, the evolution of LAN technologies has shifted from shared to dedicated media. More and more LANs are being installed and their interconnection will require parallel switching techniques such as a high-speed switching hub. The ATM small cell-size switching approach is intended to accommodate the mixed media such as voice, data and video. To fulfil the switching cost, bandwidth and latency criteria, a two-stage switching hub for LAN interconnection is designed and presented in this paper. The packet switching technique is used in the first stage switching to efficiently interconnect the local LANs. For the second stage design, the ATM cell switching is adopted to accommodate multimedia traffic and internetworking among LANs and WANs. The switching architecture including both the packet and cell switching units is thoroughly described. The message flow and routing mechanism are presented in the paper. This architecture has been proved to have the advantages of very low latency, flexible scalability and easy routing management with two-way learning.<<ETX>>
Minimization of Number of Neurons in Voronoi Diagram-Based Artificial Neural Networks

Artificial Neural Networks (ANNs) have been widely used to deal with various classification problems for decades. Different algorithms for synthesizing ANNs have been proposed as well. The number of neurons in an ANN usually controls the tradeoff between classification ability and computational efficiency. That is, more neurons tend to yield better results but are less efficient in either the training or recalling phase. Furthermore, if the neurons are implemented by physical devices, the implementation cost can be effectively reduced with fewer number of neurons in an ANN. In this paper, we propose a method to minimize the number of neurons used in an ANN that is built by using Voronoi diagrams without suffering any capability loss. We have conducted experiments on a set of benchmarks. The experimental results show that the resultant ANNs reduce the number of neurons by up to 94 percent.
Semi-Blind Spatial Equalisation for MIMO Channels with Quadrature Amplitude Modulation

Semi-blind spatial equalisation is considered for multiple-input multiple-output (MIMO) systems that employ high-throughput quadrature amplitude modulation scheme. A minimum number of training symbols, equal to the number of transmitters, are first utilised to provide a rough least squares channel estimate of the system's MIMO channel matrix for the initialisation of the spatial equalisers' weight vectors. A constant modulus algorithm aided soft decision-directed blind algorithm is then employed to adapt the spatial equalisers. This semi- blind scheme has a very-low computational complexity, and it converges fast to the minimum mean-square-error spatial equalisation solution as demonstrated in our simulation study.
Compact W-band multi-layer four-way SIW power combiner/divider

In this paper, a compact W-band multi-layer four-way substrate integrated waveguide (SIW) power combiner/divider is analyzed and demonstrated numerically/experimentally. The proposed power combiner/divider is realized by using a highperformance transition structure between multi-layer SIWs and rectangular waveguide. Both numerical and experimental results indicate that such power combiner/divider shows the high portisolation, low insertion loss, high efficiency, wide band, and small lateral size.
Negative Bias Temperature Instability for Sputtering Modification in a TiN Diffusion Barrier of p+ Polysilicon Gate Stack in 50-nm DRAM Technology

Negative bias temperature instability (NBTI) in plasma-nitrided oxide affected by the nitrogen incorporation of a TiN diffusion barrier layer of gate stack is first proposed. In the standard 50-nm DRAM technology, three different groups including high, medium, and low N2 flow were deposited by sputtering to investigate in this paper. The high N2 flow group was with higher drive current and higher transconductance, but worse NBTI performance in pMOSFETs than that of the low N2 flow group. Boron (B) concentration at the bottom of p+ polycrystalline silicon (poly-Si) for the high N2 flow group is 5.4% higher than that for the low N2 flow group, which is verified by the secondary ion mass spectroscopy depth profile. A vertical electric field across gate nitrided oxide enhanced by high B concentration in the interface of p+ poly-Si/nitrided oxide resulted in the degradation of NBTI and time-dependent dielectric breakdown of the high N2 flow group. However, process optimization still needs to be studied between device performance and reliability of pMOSFETs in future generation.
Global Synchronization for Discrete-Time Stochastic Complex Networks With Randomly Occurred Nonlinearities and Mixed Time Delays

In this paper, the problem of stochastic synchronization analysis is investigated for a new array of coupled discrete-time stochastic complex networks with randomly occurred nonlinearities (RONs) and time delays. The discrete-time complex networks under consideration are subject to: (1) stochastic nonlinearities that occur according to the Bernoulli distributed white noise sequences; (2) stochastic disturbances that enter the coupling term, the delayed coupling term as well as the overall network; and (3) time delays that include both the discrete and distributed ones. Note that the newly introduced RONs and the multiple stochastic disturbances can better reflect the dynamical behaviors of coupled complex networks whose information transmission process is affected by a noisy environment (e.g., Internet-based control systems). By constructing a novel Lyapunov-like matrix functional, the idea of delay fractioning is applied to deal with the addressed synchronization analysis problem. By employing a combination of the linear matrix inequality (LMI) techniques, the free-weighting matrix method and stochastic analysis theories, several delay-dependent sufficient conditions are obtained which ensure the asymptotic synchronization in the mean square sense for the discrete-time stochastic complex networks with time delays. The criteria derived are characterized in terms of LMIs whose solution can be solved by utilizing the standard numerical software. A simulation example is presented to show the effectiveness and applicability of the proposed results.
SMC-based mobile robot stability control considering both matched and mismatched disturbances regulation and chatter alleviation

In this paper, a SMC based mobile robot controller is designed, which can achieve chatter alleviation, matched and mismatched disturbances regulation and stability at the same time. Specifically, there are four main contributions in this paper. First, new hierarchical sliding surfaces are designed in the paper for mobile robot subject to matched and mismatched disturbances. Second, a robust disturbance observer (DOB) is designed for disturbance estimation. The observer utilizes knowledge about approaching road disturbances to minimize the estimation error. Third, a new control law is design to filter out the chatter in control input. Finally, the evolutions of both yaw angle and lateral position errors are also investigated in the study, and the asymptotic stabilities of the system are proved. Simulation is carried out for mobile robot tracking highly curved roads. Simulation results show that the proposed controller has strong robustness despite the presence of disturbances in both lateral and yaw motion dynamics. Compared with two control schemes which frequently used in literatures, the control input generated by this controller exhibits less control action while maintains satisfactory tracking performance. Our matlab code is publically available from http://pan.baidu.com/s/1mhtWros.
Task scheduling and management in single-chip multi-processor system

The single-chip multi-processor system, which uses the technique of parallel processing, can well improve the performance and processing ability of the CPU. This paper proposes a method of parallel processing based on the task library, and presents a strategy about task distribution and scheduling. It has been implemented by hardware and the verification about task loading and task scheduling has made, based on a single chip multi-processor system, comprised of 4 sub-processors which are all based on the architecture of Intel 8051. The verification result indicates that this method can well improve the working efficiency and parallel computing ability of SCMP system.
Permittivity measurement of Ba0.5Sr0.5TiO3 ferroelectric thin films on multilayered silicon substrates

This paper presents a method for measuring the complex permittivity of Ba/sub 0.5/Sr/sub 0.5/TiO/sub 3/ (BST) ferroelectric thin films on a four-layered substrate at frequencies from 50 MHz to 26.5 GHz. Coplanar waveguide (CPW) lines are employed to measure the permittivity at high frequencies, whereas at low frequencies interdigital capacitors (IDCs) are used instead to avoid the calibration errors of CPW at those frequencies. A quasi-TEM transmission-line model and a lumped-element model, both on a four-layered substrate, are developed for CPW and IDC, respectively, using quasi-TEM analysis, conformal mapping, and partial-capacitance technique. The combinations of CPW model with measured transmission parameters and IDC model with measured scattering parameters allow extraction of the dielectric properties of the BST film. On-wafer through-reflect-line calibration is used to de-embed the true responses of the CPW lines. Dielectric constants of 400-600 and loss tangents of 0.05-0.1 are obtained at frequencies from 50 MHz to 26.5 GHz.
High-Power Highly Linear-Polarized Nanosecond All-Fiber MOPA at 2040 nm

We demonstrate a nanosecond all-fiber master oscillator power amplifier with linear-polarized output at 2040 nm, seeded by an in-band-pumped gain-switched thulium-doped fiber laser, which can directly output tens-of-microjoules pulses with designable pulse duration and Gaussian-like pulse profile. After only two stages of amplification, we achieve an average power of 70 W at a pulse width of 114 ns and a repetition rate of 10 kHz, corresponding to a pulse energy of 7 mJ and a peak power of 53.8 kW. Benefit from the on-site polarization control technique we proposed, a polarization extinction ratio (PER) of 25 dB at the highest output is also obtained. To the best of our knowledge, this is the highest power nanosecond all-fiber laser reported at 2-μm waveband and the PER is also a record among high-power fiber lasers.
A Novel Distributed Secondary Coordination Control Approach for Islanded Microgrids

This paper develops a new distributed secondary cooperative control scheme to coordinate distributed generators (DGs) in islanded microgrids (MGs). A finite time frequency regulation strategy containing a consensus-based distributed active power regulator is presented, which can not only guarantee the active power sharing but also enable all DGs’ frequencies to converge to the reference value within a finite time. This enables the frequency and voltage control designs to be separated. Then an observer-based distributed voltage regulator involving certain reactive power sharing constraints is proposed, which allows different set points for different DGs and, thus, accounts for the line impedance effects. The steady-state performance analysis shows that the voltage regulator can accurately address the issue of global voltage regulation and accurate reactive power sharing. Moreover, all the distributed controllers are equipped with bounded control inputs to suppress the transient overshoot, and they are implemented through sparse communication networks. The effectiveness of the control in case of load variation, plug-and-play capability, communication topology change, link failure, time delays, and data drop-out are verified by the simulation of an islanded MG in MATLAB/SimPowerSystems.
Motion/pattern adaptive interpolation of interlaced video sequences

A hybrid motion/pattern adaptive scheme for the conversion of interlaced video sequences to the progressive format is presented. It normally operates in the temporal interpolation model and switches to spatial interpolation when motion is detected. The filter for spatial interpolation is adapted according to the local image pattern. Directional filters are designed for oriented features based on their representation by oriented polynomials. Although the proposed scheme has only been applied to the interpolation of interlaced signals, its principle is applicable to other problems in video signal resolution enhancement.<<ETX>>
Sequential Deep Trajectory Descriptor for Action Recognition With Three-Stream CNN

Learning the spatial-temporal representation of motion information is crucial to human action recognition. Nevertheless, most of the existing features or descriptors cannot capture motion information effectively, especially for long-term motion. To address this problem, this paper proposes a long-term motion descriptor called sequential deep trajectory descriptor (sDTD). Specifically, we project dense trajectories into two-dimensional planes, and subsequently a CNN-RNN network is employed to learn an effective representation for long-term motion. Unlike the popular two-stream ConvNets, the sDTD stream is introduced into a three-stream framework so as to identify actions from a video sequence. Consequently, this three-stream framework can simultaneously capture static spatial features, short-term motion, and long-term motion in the video. Extensive experiments were conducted on three challenging datasets: KTH, HMDB51, and UCF101. Experimental results show that our method achieves state-of-the-art performance on the KTH and UCF101 datasets, and is comparable to the state-of-the-art methods on the HMDB51 dataset.
Constrained dynamic traffic grooming in WDM mesh networks with link bundled auxiliary graph model

This paper addresses the two-layer routing problem in wavelength division multiplexed (WDM) optical mesh networks subject to resource constraints and generalized wavelength continuity (GWC) constraint. The GWC constraint is a relaxed wavelength continuity constraint in networks which have different kinds of wavelength conversion capabilities. As an improvement over the existing approach which represents each wavelength separately in the auxiliary graph, we introduce a largely simplified link bundled auxiliary graph (LBAG) and propose a new,method to find paths and assign wavelengths for new lightpaths subject to the GWC constraint. We propose a constrained grooming algorithm based on the LBAG model. We also propose two grooming policies which improve the existing grooming policies by integrating the wavelength and transceiver metrics and considering the relative resource utilization ratio. Simulations are conducted to evaluate the performance of the grooming policies in terms of blocking probability.
A fast skip and direction adaptive search algorithm for Sub-Pixel Motion Estimation on HEVC

Motion Estimation (ME) is one of the most time-consuming parts in video coding loop. It is important to develop fast Sub-Pixel ME (SPME) algorithm which brings higher prediction accuracy as well as higher computational complexity. In this paper, we propose a fast skip and direction adaptive search algorithm for SPME in order to balance the coding performance and complexity. Firstly, a fast skip algorithm is utilized to skip SPME directly in most stationary regions and an error-tolerant algorithm is introduced to avoid over-optimization. Next, a direction adaptive search algorithm with early-termination technique is applied to 1/2-pixel and 1/4-pixel motion search. Experimental results demonstrate the advantage of the proposed algorithm on HEVC reference software HM-16.0, which succeeds in reduction of the total encoding time averagely for up to 42.37% on surveillance videos and 26.60% on conference videos with a negligible coding efficiency loss.
Integration of audio and visual information for content-based video segmentation

A video sequence usually consists of separate scenes, and each scene includes many shots. For video understanding purposes, it is most important to detect scene breaks. To analyze the content of each scene, detection of shot breaks is also required. Usually, a scene break is associated with a simultaneous change of image, motion, and audio characteristics, while a shot break is only accompanied with changes in image or motion or both. We propose to use audio information along with image and motion information to accomplish segmentation at different levels. Promising results have been obtained with videos digitized from TV programs.
Multiple description image coding for noisy channels by pairing transform coefficients

Multiple description coding (MDC) is a way of trading off coding gain with robustness to channel errors. This paper presents a new method for MDC using the framework of transform coding. Instead of using the Karhunen-Loeve transform (KLT) that decorrelates all the coefficients, we choose the transform bases so that the coefficients are correlated pair-wise. This is accomplished by rotating every two basis vectors in the KLT. Each pair of correlated coefficients are then split between two descriptions. Only 45/spl deg/ rotation is considered which leads to two balanced streams. In the actual implementation, the DCT is employed in place of the KLT and the rotation of transform bases is accomplished by rotating the DCT coefficients. Experimental results show that this method can lead to satisfactory image reconstruction from any one description with a relatively small (20% for "lena") overhead over a standard JPEG coder.
Neural network ensemble based on rough sets reduction and selective strategy

Based on rough sets reducts, a new neural network ensemble method is proposed. Reducts with robustness and good generalization ability are achieved by a dynamic reduction technology. Then according to different reducts, multiple BP neural networks are designed as base classifiers. And with the idea of selective ensemble, the best neural network ensemble can be found by some search strategies. Finally, by combining the predictions of component networks with voting rule, classification can be implemented. Compared with conventional ensemble feature selection algorithms, less time and lower computing complexity is needed of the method in this paper.
A novel ACO-based pattern generation for peak power estimation in VLSI circuits

Estimation of maximal power consumption is an essential task in VLSI circuit realizations since power value significantly affects the reliability of the circuits. The key issue of this task is which pattern pair would cause this peak power value. An exhaustive search from all possible combinations is time-consuming and impractical for VLSI circuits with hundreds of inputs. In this paper, a new pattern generation approach with Ant Colony Optimization, which imitates the behavior of ants looking for foods, is proposed for peak power estimation. The approach returns patterns which are highly suspicious to consuming the peak power. The gate delay issue is considered in this work. Furthermore, the valid state issue in sequential circuits is considered as well. Since the real delay value is technology-dependent, these generated patterns of our approach and other approaches are then applied into a commercial power calculation tool, PrimePower, to demonstrate the effectiveness of the approach under the TSMC 0.18 µm and TSMC 0.13 µm library. The experimental results show that an average of 76% tighter lower bound for the ISCAS'85 combinational benchmarks and 52% for the ISCAS'89 sequential circuits are obtained as compared to random patterns under the TSMC 0.18 µm library. For TSMC 0.13µm library, our patterns obtain 90% and 56% improvements over the random patterns for ISCAS'85 and ISCAS'89, respectively. As compared with the previous work, our results are also competitive.
Onboard optical flow and vision based localization for a quadrotor in unstructured indoor environments

This paper considers problem of localization for an aerial robot in unstructured indoor environments. A vision correction method based on linear characteristics is proposed. The dynamic model is established using an optical flow sensor. Use a strap-down camera to capture the frame of perpendicular line on the ground, and calculate the global position of their intersection point. As an observation, the vision position is input to the KALMAN filter in order to eliminate the accumulated error. Experimental results from indoor hover test verified the accuracy and real-time of the approach.
Modeling and Analysis of Skype Video Calls: Rate Control and Video Quality

Video-conferencing has recently gained its momentum and is widely adopted by end-consumers. But there have been very few studies on the network impacts of video calls and the user Quality-of-Experience (QoE) under different network conditions. In this paper, we study the rate control and video quality of Skype video call, and analyze the network impacts in large-scale networks. We first measure the behaviors of Skype video call on a controlled network testbed. By varying packet loss rate, propagation delay and available network bandwidth, we observe how Skype adjusts its sending rate, FEC redundancy, video rate and frame rate. It is found that Skype is robust against mild packet losses and propagation delays, and can efficiently utilize the available network bandwidth. We also find that it employs an overly aggressive FEC protection strategy. Based on the measurement results, we develop rate control model, FEC model, and video quality model for Skype video calls. Extrapolating from the models, we conduct numerical analysis to study the network impacts. We demonstrate that user back-offs upon quality degradation serve as an effective user-level rate control scheme. We also show that Skype video calls are indeed TCP-friendly and respond to congestion quickly when the network is overloaded. Through a case study of a 4G wireless network, we demonstrate that the proposed models can be used in user-QoE-aware network provisioning.
A co-evolutionary teaching-learning-based optimization algorithm for stochastic RCPSP

A co-evolutionary teaching-learning-based optimization (CTLBO) algorithm is proposed in this paper to solve the stochastic resource-constrained project scheduling problem (SRCPSP). The activity list is used for encoding, and resource-based policies are used for decoding. Also, a new competition phase is developed to select the best solution of each class as the teacher. To make two classes evolve cooperatively, both the teacher phase and student phase of the TLBO are modified. Moreover, Taguchi method of design of experiments is used to investigate the effect of parameter setting. Computational results are provided based on the well-known PSPLIB with certain probability distributions. The comparisons between the CTLBO and some state-of-the-art algorithms are provided. It shows that the CTLBO is more effective in solving the problems with medium to large variance.