nils-herrmann/clean_scirepeval huggingface dataset:
Improving Training of Deep Neural Networks via Singular Value Bounding

Deep learning methods achieve great success recently on many computer vision problems. In spite of these practical successes, optimization of deep networks remains an active topic in deep learning research. In this work, we focus on investigation of the network solution properties that can potentially lead to good performance. Our research is inspired by theoretical and empirical results that use orthogonal matrices to initialize networks, but we are interested in investigating how orthogonal weight matrices perform when network training converges. To this end, we propose to constrain the solutions of weight matrices in the orthogonal feasible set during the whole process of network training, and achieve this by a simple yet effective method called Singular Value Bounding (SVB). In SVB, all singular values of each weight matrix are simply bounded in a narrow band around the value of 1. Based on the same motivation, we also propose Bounded Batch Normalization (BBN), which improves Batch Normalization by removing its potential risk of ill-conditioned layer transform. We present both theoretical and empirical results to justify our proposed methods. Experiments on benchmark image classification datasets show the efficacy of our proposed SVB and BBN. In particular, we achieve the state-of-the-art results of 3.06% error rate on CIFAR10 and 16.90% on CIFAR100, using off-the-shelf network architectures (Wide ResNets). Our preliminary results on ImageNet also show the promise in large-scale learning. We release the implementation code of our methods at www.aperture-lab.net/research/svb.
A compact transceiver for narrow bandwidth and high power Ka-band application

Using the GaAs MMICs, other components and advanced package techniques, we realized a compact transceiver module with high power (about 35 dBm), receiver noise figure less than 4.5 dB and bandwidth 1% in Ka-band operating frequencies. This module consists of 15 MMICs and over 100 components, and demonstrates narrow bandwidth with high power in millimeter-wave transceiver module. This work has also laid a good foundation for the technology of combining the MMIC and other component for a versatile millimeter-wave transceiver module.
Recognition of Emotions in User-Generated Videos With Kernelized Features

Recognition of emotions in user-generated videos has attracted increasing research attention. Most existing approaches are based on spatial features extracted from video frames. However, due to the broad affective gap between spatial features of images and high-level emotions, the performance of existing approaches is restricted. To bridge the affective gap, we propose recognizing emotions in user-generated videos with kernelized features. We reformulate the equation of the discrete Fourier transform as a linear kernel function and construct a polynomial kernel function based on the linear kernel. The polynomial kernel is applied to spatial features of video frames to generate kernelized features. Compared with spatial features, kernelized features show superior discriminative capability. Moreover, we are the first to apply the sparse representation method to reduce the impact of noise contained in videos; this method helps contribute to performance improvement. Extensive experiments are conducted on two challenging benchmark datasets, that is, VideoEmotion-8 and Ekman-6. The experimental results demonstrate that the proposed method achieves state-of-the-art performance.
Vehicle Type Classification Using PCA with Self-Clustering

Different conditions, such as occlusions, changes of lighting, shadows and rotations, make vehicle type classification still a challenging task, especially for real-time applications. Most existing methods rely on presumptions on certain conditions, such as lighting conditions and special camera settings. However, these presumptions usually do not work for applications in real world. In this paper, we propose a robust vehicle type classification method based on adaptive multi-class Principal Components Analysis (PCA). We treat car images captured at daytime and night-time separately. Vehicle front is extracted by examining vehicle front width and the location of license plate. Then, after generating eigenvectors to represent extracted vehicle fronts, we propose a PCA method with self-clustering to classify vehicle type. The comparison experiments with the state of art methods and real-time evaluations demonstrate the promising performance of our proposed method. Moreover, as we do not find any public database including sufficient desired images, we built up online our own database including 4924 high-resolution images of vehicle front view for further research on this topic.
WDM switch technology application in smart substation communication network

By analyzing the typical communication networking method of Process Layer in Smart Substation, this paper proposes the problems of current widely used Process Layer communication isolation network by using VLAN Technology. This paper expounds the basic principle and advantage of using WDM technology to realize the Switch, proposes the Security isolation communication networking method of using WDM Switch in Smart Substation Process Layer. This method has obvious advantages than the current VLAN logic isolation method in theory, truly meets the "Three Networks In One" needs of Smart Substation Process Layer communication network.
Delay model for signal controlled intersections

Delay is a significant parameter that is used in the optimization of signal settings for intersections and the estimation of the level of service at signalized intersections, and it is also a parameter that is difficult to estimate. Based on the existing theory of delay at signalized intersection, this paper analyzes the delay at a signalized intersection of each phase for entrance with the arrival and departure diagram for under-saturated and over-saturated conditions. Then, a delay model for signalized intersection is put forward. After that, the cycle length is discussed with delay minimization as an optimal objective based on the delay model of signalized intersection. A possible reason for the optimal cycle length being as small as possible in the minimal delay model is proposed at last.
Study on Line-Break Ferro-Resonance Over-voltage of 35kV Power System and Its Suppression Methods

There are a lot of inductance component and capacitance component in 35kV system, including transformer, current and voltage transformer, generators, arc suppression coil, transmission line's direct-to-ground capacitance and phase-to-phase capacitance, condenser in parallel and series, stray capacity from all kinds of high voltage equipments. Under certain conditions, these elements can form different resonant circuit, cause resonance over-voltage phenomenon, endanger the insulation of the system. In this paper, on the basis of one copper mining company 35kV power supply system, it's carried out the resonance over-voltage studies, reach conclusion about the general rules of how ferromagnetic resonance arises. Finally, corresponding suppression methods are raised.
Unconditionally Stable Non-Foster Element Using Active Transversal-Filter-Based Negative Group Delay Circuit

This letter introduces a novel type of non-Foster element using a microwave transversal-filter-based negative group delay (NGD) circuit that can exhibit unconditional stability. The proposed device is realized by a distributed amplifier, in which the NGD response is synthesized by adjusting the ratio of transconductance of transistors in each stage. On top of this, by properly amending the in-band magnitude and phase characteristics, the NGD circuit can realize non-Foster elements within the operating band. Furthermore, thanks to the distributed topology, the proposed network has very good input and output matching characteristics. As proof-of-concept, a prototype of the proposed non-Foster element is built to validate the proposed scheme. The experimental results show that the proposed circuit can realize a unilateral non-Foster element composed of a −1 pF shunt capacitor and a −1.25 nH series inductor.
Research of printing ink quantity real-time detection system

This paper introduces a method of construct printing ink quantity real-time detection system based on machine vision and digital image processing, describes the principle used in this system, highlights the problems encountered in the process of image analysis, and presents feasible ways to solve these problems. We captured the presswork images by a linear CCD camera and obtained their pixel RGB values. Then convered these RGB values to Lab values and input them into a trained neural network which outputs the ink quantity.
Minimum-contrast dominate visual search on complex-color background

As we know, the visual attention is greatly influenced by color salience although there are many other important factors such as orientation and spatial frequency. In this study, serial experiments of target search on complex background have been performed. As a result, all experiment results indicate that the response time (RT) is mainly dominated by the minimum-contrast rather than the mean-contrast or the maximum-contrast. This paper suggests that the target salience ought to be measured by the minimum-contrast between target and background in visual search based on color, and propose a salience model based on the minimum-contrast.
Multi-objective optimization of oversaturated signalized intersection based on fuzzy logic

Aimed at the problem of multi-objective optimization, solution on the oversaturated signalized intersection by using fuzzy logic control (FLC) is presented. The essential and characteristics of multi-objective optimization in urban traffic signal control are analysed. The performance measures of minimizing average delay, stop times and average queue length are established, according to the initial queue length, real-time arrival rate and departure rate. Given real-time traffic information, the FLC controller decides on whether to extend or terminate the current green phase based on a set of fuzzy rules. Compared with the conventional fixed time traffic controller, the FLC is proved to be useful and effective with the simulation results and have good performance in the average delay of vehicles, and particularly be applicable to over saturated intersection.
A novel UWB bandpass filter based on multi-stub loaded half-wavelength resonator

In this paper, a novel multi-stub loaded half-wavelength resonator (MSLHWR) is proposed, which exhibits multi-mode resonance and is characterized by three resonant modes of interest. Then, an UWB bandpass filter is designed on it, which can cover the desired UWB bandwidth. Especially, λ/4 open-circuited stubs are introduced at input/output ports, which can create an adjustable transmission zero and then play an important role in improvement of frequency selectivity. Finally, an UWB bandpass filter is fabricated and measured. The measured results show that the filter has good frequency selectivity and as high as 50.7 dB suppression can be achieved at 11.7 GHz. In addition, upper stopband suppression level with at least 25 dB is extended to 16 GHz. The measured group delay variation is less than 0.4 ns in the passband, which is relatively flat.
AlN Barriers for Capacitance Reduction in Phase-Change RF Switches

We demonstrate four-terminal GeTe-based RF switches with independent thermal actuation (switching). These devices incorporate an AlN-based dielectric separating high-conductivity W micro-heaters from the RF signal path. With dc, pulsed, and RF testing, we show that an AlN barrier decreases the switch parasitic capacitance with minimal increases in the switching power. Decoupling these design variables, with the high thermal conductivity of the AlN, makes it possible to increase the electrical separation with a thicker AlN film for lower parasitic capacitance with minimal decrease in desirable thermal coupling. Increasing the AlN thickness from 105 to 170 nm results in switches with an improvement in cutoff frequency, fCO from 5.3 to 8 THz, a COFF improvement from 15 to 10 fF, while maintaining the RON at 2 Ω. This improvement was accompanied by normalized minimum power to amorphize increases of only 14% (from 1.5 to 1.7 W) for a 100-ns heater pulse.
Towards accelerometry based static posture identification

Human activity classification has wide-spread applications ranging from human computer interaction to disease progression studies. In this paper we propose a body posture model based on the Euler angles of the torso, arms and legs. The Euler angles are computed based on data streams originating from a wireless Body Sensor Network (BSN) comprising of nine accelerometers. Thereafter they are used to reconstruct different body postures based on an unsupervised learning and clustering algorithm. We validate our algorithm by implementing a classification engine in Matlab, capable of classifying subtle changes in posture with 97% accuracy.
Statistical modeling of GaN HEMT based on Monte Carlo simulations

A statistical model of GaN high electron mobility transistor (HEMT)'s parameters is presented. This statistical modeling approach includes principal component analysis and factor analysis and multiple regression model. When applied to the database of extracted equivalent circuit parameters (ECPs) for GaN HEMT devices, it has been validated that this approach can generate accurate statistical model by comparing original and Monte Carlo simulated means, standard deviations, correlation matrix and S-parameters. In particular, the primary goal of this work is that the statistical model has been used to perform a ku-band power amplifier design and analysis for the first time. From the results, it has proven that the parameters are statistically indistinguishable from a measured ones.
Design of motion control system for robot car based on DSP

Based on research of the robot car's motion control system, TMS320f2811 chip which produced by Texas Instruments (TI) was used as the core chip of the control circuit. How to design the control circuit of robot car was illustrated in this paper from hardware part and software part. The design of motion control system for robot car based on DSP technology and integrated-separated PI control algorithm was put forward, which guarantee the control accuracy and improve the real time control. It is proved by practice that this scheme of design is effective for the robot car's motion control system.
Notice of RetractionExperiment and analysis of vibration model of large-scale hydraulic gate

Vibration has serious effects on working condition of hydraulic gate. The vibration characteristics, such as natural frequencies, modal damping and modal shape, of a plane gate with violent vibration in the outlet of inverted siphon are obtained by experiment and analysis with hammer excitation method. The results show that the distribution of natural frequencies of the hydraulic gate in a wide range is the main cause of flow-induced vibration. The first natural frequency of the hydraulic gate in vertical direction is lower than in water flowing direction and in transverse direction, which indicates that the modal stiffness of the hydraulic gate in vertical direction is significantly lower than the other two directions.
Computer Tournaments in N-person Stochastic Iterated Prisoner's Dilemma

This paper generalized the strategy selection problem in 2-person iterated prisoner's dilemma to n-person stochastic cases. The concept of n-person stochastic iterated prisoner's dilemma was proposed to accommodate to new game problem caused by technology advancement. Every player's history information of choice could be seen by all other players. At each round, two players were selected randomly to play the prisoner's dilemma game. This paper designed a computer tournament to investigate which is the best strategy and described in detail the design and experiments of the tournament. The experimental results showed that TIT-FOR-TAT is not always the best strategy, and the best strategy is closely correlated with the repeated game round and the strategy distribution
Accurate extraction of parasitic series resistances and inductances for GaAs HFET

An accurate extraction method of the parasitic series resistances and inductances for a GaAs HFET is presented. The measurement of S-parameters is under the condition of cold FET (vds=0 V, vgs=0 V), the extraction procedure is not a direct extraction method, but a based-on optimisation method using a genetic algorithm. Good agreement compared with measurement is achieved.
The application of line-labeling algorithm to on-line defect detection system for printed-matter

The Application of Line-labeling algorithm to on-line defect detection system for printed-matter was studied in this paper and it was compared with Pixel Labeled Algorithm. The algorithm is based on the line between rows. Connected regions of defect were marked and their parameters (position, area,etc) were obtained rapidly by scan the full image only once, while the full image has to be scanned twice and an equivalent mark table has to be produced in Pixel Labeled Algorithm. Practical application shows that Line-labeling algorithm is more suitable for on-line defect detection system.
Classification Performance Comparison between RVM and SVM

Both relevant vector machine and support vector machine are newly promoted pattern recognition algorithms. An extensive relevant literature displays that they have become hot topics in the field of machine learning. Due to the difference of their mechanism, little research is done to compare their performance. This paper experimentally compared several features of RVM with SVM which can characterize the classification performance on the basis of deeply understanding their algorithms. The results show that RVM is almost equal to SVM on training efficiency and classification accuracy, but as to sparse property, generalization ability and decision speed, RVM performs better. So it is recommended to study RVM deeply and extend its application areas further.
A hybrid control method for elderly companion robot based on behavior-based reaction and RNNPB model

A hybrid control method based on the behavior-based reaction and the recurrent neural network with parametric bias (RNNPB) model is proposed for the elderly companion robot. Firstly, a multimodal human-robot interaction framework is proposed using agent technology,which is composed of multimodal interaction module, cognitive module, and interaction control module. Then a hybrid control method for elderly companion robot is given, which is composed of behavior-based reaction control and evolutional control using the recurrent neural network with parametric bias (RNNPB) model. Finally, the experiments and results show the effectiveness of the hybrid control method.
Even data placement for load balance in reliable distributed deduplication storage systems

Modern distributed storage systems often deploy deduplication to remove content-level redundancy and hence improve storage efficiency. However, deduplication inevitably leads to unbalanced data placement across storage nodes, thereby degrading read performance. This paper studies the load balance problem in the setting of a reliable distributed deduplication storage system, which deploys deduplication for storage efficiency and erasure coding for reliability. We argue that in such a setting, it is generally challenging to find a data placement that simultaneously achieves both read balance and storage balance objectives. To this end, we formulate a combinatorial optimization problem, and propose a greedy, polynomial-time Even Data Placement (EDP) algorithm, which identifies a data placement that effectively achieves read balance while maintaining storage balance. We further extend our EDP algorithm to heterogeneous environments. We demonstrate the effectiveness of our EDP algorithm under real-world workloads using both extensive simulations and prototype testbed experiments. In particular, our testbed experiments show that our EDP algorithm reduces the file read time by 37.41% compared to the baseline round-robin placement, and the reduction can further reach 52.11% in a heterogeneous setting.
Three Mathematical Approaches for Trust Trend Evaluation

Trust is a critical issue in e-commerce and e-service applications. Usually, the value of trust is in a dynamic process of change. At present, most of studies and applications regarding trust are focus on methods that result in a single final trust level (FTL) value to represent the trust level of sellers or service providers. Such simple trust evaluation methods may not be able to depict the trust history exactly, and may not be able to obtain the trust trend information. In this paper, presents three mathematical approaches for trust trend evaluation, these mathematical approaches can depict and predict the trust change trend. Experimental data confirm the feasibility and effectiveness of these mathematical approaches, meanwhile, analyze their different capacity for depicting the trust change trend.
New insight into Fermi-level unpinning on GaAs: Impact of different surface orientations

We have systematically studied NMOSFETs, MOSCAPs, and the interfacial chemistry on GaAs (100), (110), (111)A and (111)B-four different crystalline surfaces with direct ALD Al2O3. We found that a much higher drain current on GaAs(111)A NMOSFET can be achieved compared to that obtained on the other 3 surfaces. Also, the results of MOS-CAPs and the interfacial chemistry obtained on the (111)A surface are very different from those others. These experimental results conclusively demonstrate that Fermi-level on the GaAs (111)A surface is indeed unpinned and Fermi-level pinning is not an intrinsic property of GaAs, but is orientation dependent thus related to surface chemistry.
Bacteria size determination by elastic light scattering

Light extinction and angular scattering measurements were performed on three species of bacteria with different sizes and shapes ( Pseudomonas aeruginosa, Staphylococcus aureus, and Bacillus subtilis). The Gaussian ray approximation of anomalous diffraction theory was used to determine the average bacteria size from transmission measurements. A rescaled spectra combining multiple angular data was analyzed in the framework of the Rayleigh-Gans theory of light scattering. Particle shape and size distribution is then obtained from the rescale spectra. Particle characteristics (size and/or shape) retrieved from both methods are in good agreement with size and shape measured under scanning electron microscopy. These results demonstrate that light scattering may be able to detect and identify microbial contamination in the environment.
ChipEst-FPGA: a tool for chip level area and timing estimation of lookup table based FPGAs for high level applications

The importance of efficient area and timing estimation techniques for hierarchical design methodology is well-established in High-Level Synthesis (HLS), since the estimation allows more realistic exploration of the design space, and hierarchical design methodology matches well with HLS paradigm. In this paper, we present ChipEst-FPGA, a chip level estimator for designs implemented using a hierarchical design methodology for Lookup Table Based FPGAs. In FPGAs, the wire delay may contribute to a significant portion of the overall design delay. ChipEst-FPGA uses a realistic model which takes the component area/delay as well as wiring effects into account. We tested our ChipEst-FPGA on several benchmarks and the results show that we can get accurate area and timing estimates efficiently.