nils-herrmann/clean_scirepeval huggingface dataset:
Electrothermal-Stress Interactions of LDMOS FET Induced by DCI RF-Pulses

This paper studies the coupled electrothermal-stress interaction mechanisms of a laterally diffused metal oxide semiconductor field effect transistor under direct current injection radio frequency pulses. Based on the measured threshold breakdown power in the high power microwave experiment, an analytical thermal stress model has been derived. Furthermore, the finite element method is used to calculate the transient temperature and stress profiles in comparison with both analytical results and those from commercial software.
Estimating evasive acceleration for ballistic targets using an extended state observer

This paper presents the development of an estimation algorithm for ballistic-target evasive acceleration during the terminal phase of interception. The proposed design is based on an application of the extended state observer, using target information acquired from a seeker to estimate target evasive acceleration. It is applicable to multiple-input multiple-output plants with variable observer gains applied in nonlinear coupled line-of-sight pitch and yaw dynamics. Design and stability analysis are evolved based on the theory of Lyapunov, with noncontinuous, piecewise, smoothly Lyapunov function candidates.
Individual identification based on chaotic electrocardiogram signals

Electrocardiography (ECG) is a transthoracic interpretation of the electrical activity of the human's heart over time captured and is highly irregular, random, and variable from person to person. Recently, the literature has revealed that this kind of signal is, in fact, chaotic. Because of people's ECGs are extremely hard to be artificially duplicated, this paper intends to investigate the way of extracting the ECG signals' biometric features for the possibility of biometric recognition. The ECG signal is converted into the phase plane by using phase space reconstruction. Then, chaos extractor is applied to capture the representative indices of chaotic ECG signals i.e., correlation dimension and Lyapunov exponents spectrum. The root mean square, Lyapunov exponent and correlation dimension are used as the key variables in neural network training and utilized in the identification scheme.
Joint Detection and Identification Feature Learning for Person Search

Existing person re-identification benchmarks and methods mainly focus on matching cropped pedestrian images between queries and candidates. However, it is different from real-world scenarios where the annotations of pedestrian bounding boxes are unavailable and the target person needs to be searched from a gallery of whole scene images. To close the gap, we propose a new deep learning framework for person search. Instead of breaking it down into two separate tasks&#x2014;pedestrian detection and person re-identification, we jointly handle both aspects in a single convolutional neural network.  Experiments show that our framework outperforms other separate approaches, and the proposed OIM loss function converges much faster and better than the conventional Softmax loss.
Design of a 1 MJ/0.5 MVA HTS Magnet for SMES

SMES is a potential solution for power quality issues. The development of a 1 MJ/0.5 MVA SMES is now at its final stage and the device will be put into operation in a live power grid of 10 kV in late of 2006 at a substation in the suburb of Beijing, China. The design and analysis of the SMES coil has been completed and magnetic flux density distribution of and electromagnetic force on the coil has been analysed by means of FEM. The cryogenic system adopts bath cooling method and employs four cryo-coolers to re-liquefy the evaporated helium. And HTS current leads are utilized to reduce heat loss.
Incorporating Structural Alternatives and Sharing into Hierarchy for Multiclass Object Recognition and Detection

This paper proposes a reconfigurable model to recognize and detect multiclass (or multiview) objects with large variation in appearance. Compared with well acknowledged hierarchical models, we study two advanced capabilities in hierarchy for object modeling: (i)``switch'' variables(i.e. or-nodes) for specifying alternative compositions, and (ii) making local classifiers (i.e. leaf-nodes) shared among different classes. These capabilities enable us to account well for structural variabilities while preserving the model compact. Our model, in the form of an And-Or Graph, comprises four layers: a batch of leaf-nodes with collaborative edges in bottom for localizing object parts, the or-nodes over bottom to activate their children leaf-nodes, the and-nodes to classify objects as a whole, one root-node on the top for switching multiclass classification, which is also an or-node. For model training, we present an EM-type algorithm, namely dynamical structural optimization (DSO), to iteratively determine the structural configuration, (e.g., leaf-node generation associated with their parent or-nodes and shared across other classes), along with optimizing multi-layer parameters. The proposed method is valid on challenging databases, e.g., PASCAL VOC 2007 and UIUC-People, and it achieves state-of-the-arts performance.
Robust Feature Point Matching With Sparse Model

Feature point matching that incorporates pairwise constraints can be cast as an integer quadratic programming (IQP) problem. Since it is NP-hard, approximate methods are required. The optimal solution for IQP matching problem is discrete, binary, and thus sparse in nature. This motivates us to use sparse model for feature point matching problem. The main advantage of the proposed sparse feature point matching (SPM) method is that it generates sparse solution and thus naturally imposes the discrete mapping constraints approximately in the optimization process. Therefore, it can optimize the IQP matching problem in an approximate discrete domain. In addition, an efficient algorithm can be derived to solve SPM problem. Promising experimental results on both synthetic points sets matching and real-world image feature sets matching tasks show the effectiveness of the proposed feature point matching method.
Design, Fabrication, and Tests of Three HTS Coils for a Model Fault Current Limiter

The design, fabrication and tests of three high temperature superconductor (HTS) coils for a rectifier-type model fault current limiter (FCL) were presented. The field distributions in the coil were numerically analysed by FEM. Based on the field distributions and the strong anisotropic characteristics of Bi2223/Ag tape, the HTS coils were designed and fabricated. The inner diameter and the height of the coils were 80 mm and 94 mm, respectively. Each of the coils consisted of 8 double pancakes. Every double pancake consisted of 103 turns with 35 meters of Bi-2223/Ag tape. After the characteristics of the coils were tested in liquid nitrogen, three of the coils were assembled in their nonmetallic-material cryostats and works with the model FCL.
Development and Test of 10.5 kV/1.5 kA HTS Fault Current Limiter

Superconducting Fault Current Limiter (SFCL) is an attractive appliance for modern electrical power system. A 10.5kV/1.5 kA three-phase HTS fault current limiter was developed by IEE, CAS. This improved rectifier-type SFCL with HTS coil of 6.25 mH is going on a demonstrated long-term reliable operation in a real 10.5 kV substation located in Hunan, China. In a three-phase-to-ground short circuit test of grid, the prospective fault current of 3.5 kA was limited to 635 A at the pre-setup short-circuit point successfully
Research on Particle Swarm Optimization strategy for forest fire detection system based on Wireless Sensor Networks

In order to improve the network performance, to increase network coverage rate, to achieve the maximization of network coverage and extend the network of life in the forest fire detection system, the present research has proposed a Wireless Sensor Networks (WSNs) coverage Particle Swarm Optimization (PSO) strategy on the basis of probability measuring model. Through the PSO, the strategy achieves coverage control for the optimization objectives of network coverage rate and analyzes the effect of coverage performance about sensing radius. The coverage rate has increased and convergence rate has speeded up with perceived radius increased gradually. The simulation shows that effective coverage has reached 85.63 percent. Compared with the Conventional Genetic Algorithms (CGA) about the optimization effectiveness, the coverage rate has increased by 0.64 percent and the convergence rate has increased 13.7 percent. Therefore, the PSO strategy has a better coverage optimization results than CGA.
Robust asymptotic stability of linear time-varying uncertain system with respect to its state mean

This paper studies a novel kind of robust stability, namely robust asymptotic stability with respect to states' means, of linear time-varying (LTV) uncertain systems. Roughly speaking, the system will feature this robust stability if its state variables' mean values gradually approach to their equilibrium states. Robust input-output finite-time stability (IO-FTS) of the LTV uncertain system over a bounded time interval is first introduced; however, it may suffer steady-state error due to modeling uncertainties. This gives rise to a demand for the stability robustness analysis corresponding to such uncertainties by studying the averaging system behavior focusing on the steady-state error rejection. Furthermore, a case study is provided to endorse significant superiority of our work.
Control and Test of a 0.5 MVA/1 MJ SMES

A 0.5 MVA/1 MJ superconducting magnetic energy storage system (SMES) has been installed in a superconducting power substation. The SMES is designed to compensate active power fluctuations, current harmonics and reactive power of the downstream load. The system configurations and control strategies are described. Experimental and field test results show that the proposed SMES can effectively improve the power quality of the power system.
The Research of Forecasting Model based on RBF Neural Network

In financial forecasting system, because there exists a number of factors to effect economy developing, it is difficult to do effective forecasting by using traditional methods such as time series approach, regression analysis. In this paper, a nonlinear model based on RBF neural network is presented. There are some ameliorated measures in learning algorithm of RBF neural network. The number and the centric value of hidden layer are determined by using immune algorithm. The supervisory algorithm is took as method of adjustable weight of output layer. Using above measures, the network is optimized, and the forecast model obtains the precise and objective solution
Piling Construction Management and Decision Support Using Geographical Information System

This paper investigates the automation of activity-level construction management and decision making. Using piling construction as the target, a specialized piling construction management and decision support system incorporating job site map and daily site production information is developed. Detailed system requirements, an improved automated data process, and a visualization user interface are developed through a thorough investigation on current piling practices in Taiwan. A comprehensive case study on the piling work of World's tallest skyscraper project, Taipei Financial Center (Taipei 101) is conducted. Actual Taipei 101 jobsite map and data is imported to the developed system. The system is then used to run a real decision problem happened during the piling construction from October of 1998 to June of 1999. Decisions is developed by using the system and be compared to the original ones. The purpose is to prove that the integrated visualization technology can be practically useful in the site-level construction management. Research results and principles of this study are also expected to be valuable for developing activity-level management and decision support systems of other trades with similar modular characteristics, such as slurry wall construction, precast construction, steel construction, and curtain wall construction.
A wrapper and broker model for collaboration between a set-top box and home service gateway

If interactive digital television (iDTV) and residential service gateway (RG) could converge, i.e. to share services and resources, add-on values could be created. We propose a wrapper (adaptor) and a broker model with cooperative interfaces and a communication mechanism to support the collaboration between instances of iDTV and RG. The proposed approach has a higher extensibility, and it is better suited to an object oriented approach. Our experimental target iDTV middleware is DVB/MHP Java Profile, and the Residential Gateway middleware is the open service gateway initiative (OSGi). The MHP and OSGi are implemented on a single Java virtual machine. The MHP application manager is wrapped as a bundle, and a broker is responsible for communication between the MHP and the OSGi. Hence, application developers do not need to know beforehand which services are on the iDTV or RG, and services are discovered dynamically.
On the development of a computer-assisted testing system with genetic test sheet-generating approach

Since the last decade, computer-assisted testing has proven to be an efficient and effective way to evaluating students' learning status such that proper tutoring strategies can be adopted to improve their learning performance. A good test will not only help the instructor evaluate the learning status of the students, but also facilitate the diagnosis of the problems embedded in the students' learning process. One of the most important and challenging issues in conducting a good test is the construction of test sheets that can meet various assessment requirements. A previous study has indicated that selecting test items to best fit multiple assessment requirements can be formulated as a mixed integer programming model. The problem is known to be NP-hard in the literature and, hence, computational challenges hinder the development of efficient solution methods. As a sequel, we instead seek quality approximate solutions in a reasonable time. Two approximation methods based upon a genetic approach are developed. Statistics from a series of computational experiments indicate that our approach is able to efficiently generate near-optimal combinations of test items that satisfy the specified requirements or constraints.
Improvement of blue GaN-based light-emitting diodes with nanosphere layers

GaN-based light-emitting diodes (LEDs) with nanosphere layers were fabricated by spin-coating method. It was found that the LEDs with and without nanosphere layers had the same electrical characteristics. With 20 mA current injection, the luminance intensities of the LEDs with nanosphere layers of 300 nm and 500 nm diameters exceeded that of the LED without nanosphere layers by 5.72% and 9.05%, respectively. The improvement of the luminance intensity is attributed to the periodic structure of nanosphere layers increasing the light extraction of photons.
Swarm manifold PSO for solving two-dimensional guillotine cutting problem

Particle swarm optimization (PSO) is an evolutionary computational model which owns a very fast converging characteristic. Guillotine cut refers to an ancient execution device and here is to place as many rectangles into a main frame as possible. Hence, the main purpose is to place a set of rectangles into a main frame and reduce the waste empty spaces as many as possible. It is well known that the 2D_GCP is an NP hard problem. In this paper, we propose a hybrid approach of PSO named swarm manifold PSO (SMPSO) for solving two-dimensional guillotine cutting problem (2D_GCP). The proposed SMPSO for solving the 2D_GCP performs much faster than invoking brute-force algorithm, and more accurate than the traditional random PSO and genetic algorithm (GA).
Study on electro-thermo-mechanical responses of bonding wires arrays used for the package design of LDMOSFET-based RF Amplifier

This paper presents the study of electro-thermo-mechanical responses of bonding wire arrays used for the design of lateral double-diffused MOSFET-based RF amplifier. We at first show a series of ruggedness measurements of bonding wire arrays with a mismatch control system and an IR microscopy used for accurately predicting their surface temperatures. Further, an in-house time-domain finite element solver is employed for simulating the electro-thermo-mechanical responses of bonding wire arrays and their highest temperatures are captured and validated in comparison with those of commercial simulator COMSOL. Finally, an improved design of the bonding wire array is proposed and validated experimentally so as to get both uniform current and temperature distributions, and therefore, a significant improvement of the electrical performance of LDMOSFET RF PA is achieved as we expected.
Density analysis of collagen fibers based on enhanced frangi filter in Second Harmonic Generation virtual biopsy images

The density of collagen fibers are automatically evaluated by the proposed algorithm based on enhanced Frangi filter. In optical virtual biopsy, Second Harmonic Generation (SHG) microscopy has been developed and applied to observe collagen fibers in the dermal layer of the human skin. The density of collagen fibers is a feature to describe the condition of collagen fibers which can provide indicator for the early pathological diagnosis and aging characteristic in SHG images. The proposed algorithm is capable of objectively and effectively reflecting that the distributions of collagen fibers are close or loose in virtual biopsy images as revealed by the experimental results. Moreover, the proposed method provides insight into identifying the correlation between the early symptoms of diseases and the density of collagen fibers.
On the design of stabilizing controllers for singularly perturbed systems

The robustness of output feedback control designs for singularly perturbed systems based on the reduced systems is discussed. A frequency-domain approach is presented to determine the conditions for the stability of linear time-invariant systems subject to neglected high-frequency dynamics. In contrast with the qualitative analyses for robust stability that have appeared in the literature, this approach gives an explicit, computable bound on unmodeled dynamics which does not destabilize the systems. Stability conditions for various feedback control schemes are presented. It is noted that the approach, extended to systems with mixed singular-regular perturbations, can be used to derive the robust stability condition.
Feature extraction for fault diagnosis utilizing supervised nonnegative matrix factorization combined statistical model

A new method for separating the feature automatically with supervised nonnegative matrix factorization (NMF) is proposed for fault diagnosis. Because of the shortage of lacking prior knowledge in existed NMF, a supervised NMF combined statistical model for fault diagnosis is proposed. The basis matrix achieved in training stage is treated as the sources' features. Besides, Gaussian Mixture Model is introduced to estimate the distributions of the base vectors and then keep them as the prior knowledge. The rotation machinery with faults was used to evaluate the performance of the proposed method. The results show that the proposed method has a good source separation capability. Its performance is better than NMF.
LED backlight driver circuit with dual-mode dimming control and current-balancing design

A dimmable LED driver circuit with dual-mode dimming control and current-balancing design for backlight application was examined and implemented in this study. Parallel current balancing can be achieved by a passive differential-mode (DM) transformer. The driver has the main power stage constructed by one boost converter. Owing to the high switching frequency, continuous current mode operation and DM transformer magnetizing inductance, the output side only needs an ultra low capacitor. Through the constant current and constant voltage dimming scheme, the LED has smoothed temporary voltage transient and will extend the lifetime of a LED lamp. Furthermore, simplicity, low cost, less capacitor, and gradual voltage rising slope can be achieved. This study included the analyses and discussions for the operational principles of the proposed LED driver. A 10 W-laboratory prototype was built and tested to verify the feasibility of the studied driver.
Robust active control of flexible systems with structured perturbations

The authors present a simple method to investigate robust stability and performance criteria for flexible systems under low-order observer-based controller designs. In the present approach, stability is defined in the internal sense, instead of the pure input-output (I/O) sense. This is superior to the usual methods based on I/O descriptions, in the sense that the situation for systems formulated in state-space models subject to joint structured unmodeled residuals and parametric perturbations can be treated simply.<<ETX>>
A linear arrangement problem with applications

A linear arrangement problem, called the minmax mincut problem, emerging from circuit design is investigated. Its input is a series-parallel directed hypergraph, and the output is a linear arrangement (and a layout). The primary objective is to minimize the longest path, and the secondary objective is to minimize the cutwidth. It is shown that cutwidth D, subject to longest path minimization, is affected by pattern number k, which is also a lower bound on the cutwidth but not a tight one. There exist examples with k=/spl Omega/(N), where N is the number of vertices. We propose an algorithm producing cutwidths D=O(k+log N). We also show that every series-parallel directed hypergraph, after reordering the serial paths, can be linearly placed with cutwidth D=O(log N). Simultaneously, its dual series-parallel directed hypergraph can be linearly placed with the same vertex order and with cutwidth D=O(log N). Applications on gate-matrix layout style in very large-scale-integrated (VLSI) CMOS circuit design are demonstrated.
Realization of Stabilizing Network Control Systems with Round-Trip Time Delays

The purpose of this paper is to present a stable network control design with uncertain time-varying communication delays. In the typical networked control systems (NCSs), there are inherent plant delays and network delays. It has been know that time delays may not only degrade the system performance, but also destabilize the controlled plant. To alleviate the influence resulting from time delays while maintaining performance, we propose a compensating scheme which consists of two compensators-a fuzzy-PID controller and a neuron network compensator. The proposed design has also been experimentally verified to show its effectiveness and superiority.
Development of 3-D Modified Proportional Navigation Guidance Law against High-Speed Targets

The work presented here proposes a terminal guidance law against very high-speed targets. Proportional navigation guidance (PNG) is mostly effective for interceptors and targets with ideal dynamics and constant speeds during the collision course, however, it is nonrobust for the objects with nonconstant speeds, such as the interceptor equipped with thrust-vector-control (TVC). To resolve the problem the interceptor considered here is guided by a 3-dimensional (3-D) modified proportional navigation guidance (MPNG) law, which is developed to account for the interceptor's axial acceleration. The guidance law is potentially applicable to interceptors with TVC to provide lateral accelerations.