nils-herrmann/clean_scirepeval huggingface dataset:
Dimmable light-emitting diode driver with cascaded current regulator and voltage source

This study presents a dimmable light-emitting diode (LED) driver consisting of a flyback power factor corrector (PFC) with two secondary windings. The first secondary output is cascaded by a floating buck current regulator with a dimming switch. Then its unregulated output voltage is connected in series with the second secondary output, which acts as a regulated voltage source. Since either secondary output voltage is lower than that of a single-output topology, low voltage-rating film capacitors with longer lifetime can be used instead of electrolytic capacitors. Most of the load power is supplied by the voltage source. Therefore the reduced voltage stress and switching losses on the dimming switch result in high conversion efficiency in a wide dimming range. The operating principles and design considerations of the proposed LED driver are discussed and analysed. A 20-W laboratory prototype with dimming feature is developed and tested. Satisfactory experimental results verify the feasibility of the studied driver.
Microbrushless DC Motor Control Design Based on Real-Coded Structural Genetic Algorithm

This paper presents the realization of a microbrushless dc motor (MBDCM) feedback system based on a real-coded structural genetic algorithm (RSGA), which combines the advantages of conventional real genetic algorithms and structured genetic algorithms for optimal control design. In the RSGA, a dynamic crossover and mutation probability adjusting method mimicking the characteristics of Butterworth filters is proposed to enhance the search performance. A SinCos encoder with a line drive of 128 sin/cos signals per revolution is implemented to achieve precise positioning. The SinCos encoder possesses the advantage of high resolution via signal interpolation. The method inherited is simple yet effective, based on logic devices. To verify effectiveness of the proposed methodology, simulations are conducted and an experimental platform with a digital signal processing unit, a motor driver, a MBDCM, and a SinCos encoder is built to verify applicability of the proposed method. The experimental results demonstrating the aforementioned method work properties correlate well with the expectation.
An Empirical Study of Object Category Recognition: Sequential Testing with Generalized Samples

In this paper we present an empirical study of object category recognition using generalized samples and a set of sequential tests. We study 33 categories, each consisting of a small data set of 30 instances. To increase the amount of training data we have, we use a compositional object model to learn a representation for each category from which we select 30 additional templates with varied appearance from the training set. These samples better span the appearance space and form an augmented training set OmegaT of 1980 (60times33) training templates. To perform recognition on a testing image, we use a set of sequential tests to project OmegaT into different representation spaces to narrow the number of candidate matches in OmegaT. We use"graphlets"(structural elements), as our local features and model OmegaT at each stage using histograms of graphlets over categories, histograms of graphlets over object instances, histograms of pairs of graphlets over objects, shape context. Each test is increasingly computationally expensive, and by the end of the cascade we have a small candidate set remaining to use with our most powerful test, a top-down graph matching algorithm. We achieve an 81.4 % classification rate on classifying 800 testing images in 33 categories, 15.2% more accurate than a method without generalized samples.
LED driver with a combined energy transfer inductor for current balancing

A two-channel LED backlight driver for LCD monitor application using an integrated magnetic component, which is a combined energy transfer inductor for current balancing, is proposed in this paper. The integrated magnetic component has two functions: boost inductor and differential-mode current balance transformer. With proper design and arrangement, all windings are wound on a single UU-core. This scheme uses leakage inductance as boost inductor for energy transfer and mutual inductance as differential mode transformer for output current balancing. Compared with conventional topology, not only the power density is increased but the overall cost and volume of the magnetic component is also further reduced. The operating principles and design considerations of the proposed LED driver are analyzed. A 10-W prototype converter with two-channel LED string was developed to verify the feasibility of the proposed driver. Experimental results show that the proposed LED driver approach can provide an equally significant two-channel LED string current.
A Wideband Dual-Polarized Array Antenna With Conical Elements for Wi-Fi/WiMAX Application

In this letter, a dual-polarized array antenna with wide bandwidth and high gain is presented for Wi-Fi/WiMAX application. The array antenna comprises a single substrate layer, a radiation patch layer, and conical elements. For comparison, an array antenna with two layers of substrates is designed. The reflection coefficient of the antenna with cones is better than -10 dB in the range of 4.9 ~ 5.96 GHz with a relative bandwidth of 19.52%, which is higher than that of the antenna with two substrate layers (14.05%). The maximum gains of the proposed antenna with cones achieve approximately 19.2 and 18.8 dBi at 5.5 GHz for the two orthogonal polarizations, respectively. In addition, high isolation and low cross-polarization levels are observed.
Ubiquitous display

is proposed to being the display interface of radio frequency identification (RFID) smart card. The main feature of e-paper is zero power consumption of normal operation for data display. Only while changing display contents, e-paper needs electric power input. That makes it's a suitable solution for adding display function on a smart card but no needs for embedding a battery additionally. E-paper keeps display without power demands during normal operation. While changing display, it's just the same time that RFID tag chip communicates with reader side to exchange dealing information. E-paper can get power through wireless power transmission accompanied with RFID data exchange and change display contents for users' inspections such like a surplus of money stored in the card or the last dealing record. While the advantage of zero power consumption, but e-paper needs high driving voltage to change its display. It's difficult to achieve by wireless power transmission especially considering interference problems between power transmission and RFID data communication. In this study, a wireless power transmission system includes power emitter on the RFID reader side and coil antenna that attached on the smart card constructed to achieve near field coupling and high efficiency power transfer. A special AC driving schema was developed for effective e-paper driving. That means changing display should be completed in less than 1 sec, just the time to complete data exchange of RFID system. The novel system with the special driving schema was proved successful working and no interferences with RFID communications. The most important is that e-paper driving by wireless power transmission gives a display interface on a smart card. People can easily inspect data stored in RFID smart card in everywhere and anytime but not just have a brief view as they passed the reader. The purpose of ubiquitous display can be achieved.
Trapping and de-trapping characteristics in PBTI and dynamic PBTI between HfO2 and HfSiON gate dielectrics

PBTI degradation for HfO2 and HfSiON NMOSFETs has been demonstrated. The generated oxide trap dominated the PBTI characteristics for Hf-based gate dielectrics. In addition, the reduction of DeltaVTH and oxide trap generation under PBTI indicates that the HfSiON is better than HfO2. On the other hand, the electron trapping/de-trapping effect has been investigated. As compared to HfO2 dielectrics, the HfSiON has shallower charge trapping level due to elimination of deep dielectric vacancies, and the temperature effects are quite different between the HfSiON and HfO2 gate dielectrics.
Low-IRESET unipolar HfO2 RRAM and tunable resistive-switching mode via interface engineering

Resistive random access memory (RRAM) has emerged as a promising candidate for next-generation nonvolatile memory (NVM) due to its low-voltage operation, fast switching speed and high-density integration . Two common resistive switching (RS) modes in RRAM are unipolar and bipolar modes . A unipolar RRAM in series with a rectifying diode, so-called one diode-one resistor (1D1R) cell, is particularly attractive for high-density applications because of the minimal 4F2 cell size . However, high RESET current (IRESET) impedes the cell size scaling in 1D1R array. Recently, we have demonstrated a reliable Ni/HfO2/Si unipolar RRAM, fully compatible with the Si technology [4, 5]. In this paper, we show that unipolar HfO2 RRAM exhibits excellent NVM characteristics promising for low-IRESET, low-power operation in the future high-density 1D1R array. In addition, we show that the RS mode can be tailored by a bottom interfacial layer of Al2O3 between HfO2 and Si. New evidence on the location of filament connections/ruptures and RS mechanism will be discussed in details.
Enhancement in Light Extraction of GaN-Based Light-Emitting Diodes With High Reflectivity Electrodes

In GaN-based light-emitting diodes (LEDs), using gold-based metals to serve as electrodes, light absorption is a problem that severely restricts the light extraction in LEDs. This study demonstrates the GaN-based LEDs with high reflectivity metals (Ag/Pt) onto an n-type GaN surface and transparent contact layer (indium-tin-oxide), to serve as the n-type electrode and the p-type electrode, respectively. By replacing Cr/Au with Ag/Pt to serve as electrodes of LEDs, the light output power of the LEDs was increased by 15.7%, thereby significantly reducing the manufacturing cost of LEDs.
Improving Performance and Reducing Amount of Phosphor Required in Packaging of White LEDs With  ${\rm TiO}_{2}$ -Doped Silicone

White light-emitting diodes (LEDs) assembled by doping TiO2 nanoparticles with phosphor silicone encapsulation are investigated. The proposed method can improve lumen output by 2.7% and correlated color temperature deviation by 39%, and it can reduce the required amount of phosphor by 5% and junction temperature by 6.5 °C in white LED packaging. These improvements are attributed to the enhanced light scattering ability and refractive index of the encapsulation material and reduced light loss due to color mixing inside the packages, and they enhance light performance and reduce thermal accumulation. Therefore, results show that improving light output performance of white LEDs makes these LEDs advantageous for use in solid-state lighting.
Robust output tracking control of a linear brushless DC motor with time-varying disturbances

Robust output tracking control of a linear brushless DC motor for transportation within a manufacturing system is presented. System identification for a linear motor with a driver is performed by a dynamic signal analyser, thus providing a linearised model for the motor. External disturbances corrupting the driver and modelling uncertainties due to payload variations and identification errors are considered. A tracking control scheme with a guaranteed H∞ tracking performance is proposed. It is shown that a state feedback control law achieving the desired objective can be obtained by solving a Riccati matrix equation. Computer simulation and experimental implementation are completed and compared. These results demonstrate the effectiveness of the proposed scheme for output tracking control of the linear brushless DC motor, and also confirm the feasibility of its implementation in industrial applications.
Time-delay compensation for time-varying delayed systems using extended network disturbance

Design of a time-delay compensation based on the extended network disturbance (END) with disturbance observers for nonlinear systems under time-varying delays is presented. The distinguished advantage of the approach is that the time-delay behavior in systems can be viewed as a result of including END into a system without delays. This allows the proposed method to work without any delay estimation. In addition, we apply a proportional, multiple-integral and derivative observer to estimate the network disturbance. The proposed strategy is verified under the congestion control design for a local wired network system with time-varying delayed states and inputs.
Nonlinear H∞ Guidance and Control for Fish-Robot

Nonlinear equations of motion for fish-robot have been derived based on two basic behaviors, swimming and orientating. By incorporating the fish-tail mechanism and autonomous underwater vehicle-like dynamics model, the fish robot motion and maneuverability are developed in earth-fixed frame motion. A nonlinear H∞ robust controller for swimming, orientating, and tracking control of the fish robot is developed. Simulation results demonstrate excellent maneuverability and tracking performance of the fish-robot in two-dimension motion, which shows effect of the nonlinear H∞ robust control against ocean's current turbulence.
Full body human attribute detection in indoor surveillance environment using color-depth information

With the advent of depth enabled sensors and increasing needs in surveillance systems, we propose a novel framework to detect fine-grained human attributes (e.g., having backpack, talking on cell phone, wearing glasses) in the surveillance environments. Traditional detection and recognition methods generally suffer from the problems such as variations in lighting conditions, poses, and viewpoints of object instances. To tackle these problems, we propose a multi-view part-based attribute detecting system based on color-depth inputs instead of purely utilizing color images. We address several important attributes in the surveillance environments and train multiple attribute classifiers based on features inferred from 3D information to construct our discriminative model. Several state-of-the-art methods are compared and the experimental results show that our method is more robust under large variations in surveillance conditions.
Multiobjective PID control for a linear brushless DC motor: An evolutionary approach

A robust output tracking control design for a linear brushless DC motor with modelling uncertainties is presented. Frequency-domain design specifications directly related to the mixed sensitivity function and control energy consumption are imposed to ensure stability and performance robustness. A generalised two-parameter PID control framework is developed via an evolution algorithm, which searches the available solutions over a certain specified domain. The proposed design paradigm is intuitive and practical in the sense that it offers an effective way to implement simple but robust solutions covering a wide range of plant perturbation and, in addition, provides excellent tracking performance without resorting to excessive control. Experimental and numerical studies have been presented to confirm the proposed control design.
Improving efficiency and light quality of white LEDs by adding ZrO2 nano-particle and red phosphor in encapsulant

Efficiency and light quality of white light-emitting diodes (LEDs) were improved by adding ZrO2 nano-particle and red phosphor in encapsulant. ZrO2 nanoparticles can enhance the light scattering ability of encapsulant on LED chip. Doping ZrO2 nanoparticles with YAG phosphor into encapsulant package (LED II) luminous flux increase of 7.7 % compared conventional doping YAG phosphor package (LED I). Conformal YAG phosphor on LED chip and doping ZrO2 nanoparticles into encapsulant package of white LED (LED III) the luminous flux increase of 19.8 % compared LED II. Doping red phosphor into encapsulant of LED II produced LED IV, CRI can improved from 47 to 90 and R9 from 0 to 90.
Learning to Segment Human by Watching YouTube.

An intuition on human segmentation is that when a human is moving in a video, the video-context (e.g., appearance and motion clues) may potentially infer reasonable mask information for the whole human body. Inspired by this, based on popular deep convolutional neural networks (CNN), we explore a very-weakly supervised learning framework for human segmentation task, where only an imperfect human detector is available along with massive weakly-labeled YouTube videos. In our solution, the video-context guided human mask inference and CNN based segmentation network learning iterate to mutually enhance each other until no further improvement gains. In the first step, each video is decomposed into supervoxels by the unsupervised video segmentation. The superpixels within the supervoxels are then classified as human or non-human by graph optimization with unary energies from the imperfect human detection results and the predicted confidence maps by the CNN trained in the previous iteration. In the second step, the video-context derived human masks are used as direct labels to train CNN. Extensive experiments on the challenging PASCAL VOC 2012 semantic segmentation benchmark demonstrate that the proposed framework has already achieved superior results than all previous weakly-supervised methods with object class or bounding box annotations. In addition, by augmenting with the annotated masks from PASCAL VOC 2012, our method reaches a new state-of-the-art performance on the human segmentation task.
Current distribution in high-Tc composite tapes

The current distributions within HTS tapes are important for the study of heat dissipation and thermal stability of the composite conductors. In this presentation, current distributions between superconducting ceramic core and silver sheath are measured explicitly under different DC magnetic fields with different orientation at 77 K. Three new parameters I/sub cc/, I/sub oo/ and B/sub cc/ are defined to describe the I-V characterization of HTS tapes when the current is higher than the critical current, where I/sub cc/ is almost equal to I/sub oo/ when external field is higher than B/sub cc/.
Optimal design for passion of a light rail vehicle using constrained multiobjective evolutionary search

This research proposes a systematic and effective optimization process for the design of vertical passive suspension of light rail vehicles (LRVs) using a new constrained multiobjective evolution algorithms. A multibody dynamic model of the three-car train set is presented and the suspension spring and damping parameters are optimally designed. Design of the passive suspension is aided by the use of evolution algorithms to attain the best compromise between ride quality and suspension deflections due to irregular gradient tracks. Extensive simulations are performed to verify the proposed design scheme. The preliminary results show that, when the parameter design of the passive suspension are optimized via the proposed approach, a substantial improvement in the vertical ride quality is obtained while keeping the suspension deflections within their allowable clearance when the light rail vehicle runs on to the worst track condition.
Core-Selecting Auction Based Spectrum Allocation Scheme in Cognitive Femtocell Networks

Cognitive Femtocell Networks(CFNs) has been envisioned as a promising technology to provide high data rate and better coverage simultaneously. However, the existing spectrum allocation problem cannot ensure the true requirement and effectiveness for CFNs. A new dynamic spectrum allocation scheme with reputation model (DSA-RM) is proposed in this paper, in which core-selecting auction is adopted to solve the Winner Determination Problem and minimize femtocell user's incentive for deviating from truthful-telling. The analysis results show that the algorithm can effectively prevent the user from cheating at the time of applying for spectrum resources and improve the spectrum efficiency.
A Real-Time Measuring and Control System for the World's First HTS Power Substation

The world's first high-temperature superconductor (HTS) power substation (the substation) for the only power distribution grade has been successfully developed in live grid in 2011 in Baiyin, Gansu Province of China. This 10 kV HTS power substation is an integration of 75 m/1.5 kA HTS power cable, 10 kV/1.5 kA HTS fault current limiter, 1 MJ/0.5 MVA high Tc superconducting magnetic energy storage and 630 kVA/10 kV/0.4 kV HTS power transformer. The HTS power substation is operated automatically by a real-time measuring and control system, and it is not necessary to have anyone on duty. Software is developed by using LabView program. The cooling system providing a low-temperature environment for the cryogenic devices is an independent system, and is also the key part to ensure the run of the substation. The real-time measuring and control system for the substation, which comprehensively measures and controls the related signals of the HTS power substation, is introduced, and the controlling system for the cooling system is described in detail in this paper.
Layered Graph Matching with Composite Cluster Sampling

This paper presents a framework of layered graph matching for integrating graph partition and matching. The objective is to find an unknown number of corresponding graph structures in two images. We extract discriminative local primitives from both images and construct a candidacy graph whose vertices are matching candidates (i.e., a pair of primitives) and whose edges are either negative for mutual exclusion or positive for mutual consistence. Then we pose layered graph matching as a multicoloring problem on the candidacy graph and solve it using a composite cluster sampling algorithm. This algorithm assigns some vertices into a number of colors, each being a matched layer, and turns off all the remaining candidates. The algorithm iterates two steps: 1) Sampling the positive and negative edges probabilistically to form a composite cluster, which consists of a few mutually conflicting connected components (CCPs) in different colors and 2) assigning new colors to these CCPs with consistence and exclusion relations maintained, and the assignments are accepted by the Markov Chain Monte Carlo (MCMC) mechanism to preserve detailed balance. This framework demonstrates state-of-the-art performance on several applications, such as multi-object matching with large motion, shape matching and retrieval, and object localization in cluttered background.
Research of Decision Classification of Underwater Object Echo based on Fuzzy Integral

Underwater object recognition is one of three crucial technologies of underwater acoustic equipments development. Only partial information describing objects can be acquired in single sensor that is not enough for object classification. Method of decision fusion of underwater object echo signal, based on theory of fuzzy integral and fuzzy measure, was studied to integrate primary recognition result from multi-general-sensors to raise recognition rate. Five features were extracted from data collected on the sea to prove the performance of this method, including modul maxima power feature of continual dissymmetry Gauss wavelet, crossing-zero feature, wavelet coefficient amplitude feature, Wigner feature and Walsh feature. Recognition rate is increased by approximately 9 percent