nils-herrmann/clean_scirepeval huggingface dataset:
The Output Characteristics of Galfenol Magnetostrictive Displacement Sensor Under the Helical Magnetic Field and Stress

This paper analyzes the output characteristics of a Galfenol magnetostrictive displacement sensor based on the Wiedemann effect, the Jiles-Atherton model, and the piezomagnetic effect. The sensor which is subjected to simultaneously circumferential excitation magnetic field, bias magnetic field, and stress will induce an output voltage. Experiments were performed to describe the induced output voltage versus the applied magnetic fields and stress with an Fe83Ga17 alloy wire as a function of the circumferential excitation magnetic field from 0.5 to 6 kA/m, the bias magnetic field of 3.5 kA/m, and the stress from 5 to 110 MPa. The induced output voltage increases with an increasing magnetic field and decreases with increasing stress. The experimental results agree well with the model calculations. The sensor with a Galfenol alloy wire can be used in displacement control and interface measurement.
Definition of incremental PI function observer in broad sense and its mathematical analysis

Boiler super-heater steam temperature control object is generally with characteristic of parameters slow time variable, big inertia and larger time lag. Using the IFO-KDeltax and PI state observer for reference, the concept of "Incremental PI Function Observer in Broad Sense" (IFO-PI/BS) is presented. Theorem on stable conditions of control system based on the IFO-PI/BS is proved by mathematical analysis. And deduction shows that the theorem can be extended to control system with character of slow time variable. Taking the new concept applying in boiler super-heater steam temperature control system of a 300 MW power unit, even when the unit quickly change load of 50 MW with rate of 8 MW/min, it has good control result that biggest errors of the super-heater steam temperatures are within 4degC. This is very successful engineering application. It provides an actual example for solving those temperature control systems with character of great inertia and larger time lag and slow time variable.
Identification of active distribution network island based on graph theory

In this paper, an island identification method based on graph theory for active distribution network (ADN) is proposed. It aims at identifying the operation mode of the ADN after some switch actions under fault conditions or other emergency situations. Firstly, a node-edge model of the ADN is established in which the switch is seen as the node while the line connecting two switches is seen as the edge. Secondly, an adjacent matrix of switches is formed to describe the connection relationship among switches in the ADN. Thirdly, the connectivity judgment of nodes is conducted according to the adjacency matrix, and then a partition matrix of the ADN will be obtained which is used to describe the partition coverage. Finally, based on the partition matrix and considering the electrical equipments connected with the switches, a partition type matrix is obtained to describe the operation mode of each ADN partition. The partition type matrix can be used to determine whether the partition is in island operation mode. The island identification method based on graph theory provides valuable reference information for the protection and control of ADN, which is important for the safe operation of ADN. This method provides a new idea for the island identification of ADN. The effectiveness and validity of the proposed method are demonstrated by the case studies.
Sensitivity characteristics of 1–3 piezoelectric composite hydrophones over a wide frequency range

The conventional hydrostatic model based on static analysis is frequency-independent and inadequate to fully evaluate the present hydrophone's full range of receiving sensitivity. To expand the operating limits of the hydrostatic model, a dynamic fluid-structure interaction model for analyzing the sensitivity of piezoelectric hydrophones is presented. An analytical solution that governs the receiving sensitivity of the piezoelectric hydrophones over a wide frequency range, in both the non-resonance frequency and the resonance frequency regions, is derived. The theoretical result shows that the derived receiving sensitivity agrees well with the hydrostatic model. Additionally, the experimental results verify the theory presented in resonance frequency range.
UK-based external business environment analysis of outdoor adventure clothing using the PESTEL tool and its future outlook

In this paper, we will firstly pay attention to the holistically external business environment of the outdoor adventure clothing in the UK and present a full picture of its market based on the UK. By giving this full picture, we will also identify the economic and sociocultural factors as two main factors from the PESTEL tool. They both are believed to have the most significant impact for the market of outdoor adventure clothing. Besides, their commercial effects, inherent marketing mechanisms and significances will also be discussed and analysed in depth. Whereby two potential opportunities of the UK-based outdoor adventure clothing market corresponding to the new entrant will be presented. The first is to reduce the costs of the products by its advanced fabric and improve the performance simultaneously. By this way, they can reduce the brand loyalty to their commercial competitors and thereby attract more consumers. The second is to enhance the recognition of the new entrant and its products by a series of promotion activities and whereupon gain a sound reputation in a short period. Finally in this paper, the potential niche markets will be pointed out and several specific recommendations for the new entrant will be provided.
Indirect fuzzy adaptive backstepping controller design for TCSC

In this paper, an indirect fuzzy adaptive backstepping control approach is applied for single machine infinite bus system with Thyristor Controlled Series Compensation(TCSC). Firstly, the fuzzy logic systems are employed to solve the uncertainty parameters. Then, the dissipation theory are employed to deal with the external disturbances problems, and storage functions of the system are constructed via adaptive backstepping design. Lastly, a nonlinear L2 gain disturbance attenuation controller along with parameter update law is obtained. Simulation results are given to demonstrate the effectiveness of the proposed method.
Research of Driver Eye Features Detection Algorithm Based on OpenCV

This paper proposes a driver fatigue eye features detection algorithm based on OpenCV image processing and computer vision development platform. This algorithm localizes eye-area and detects its state based on rough to accurate thought, and can localize eye pupils in eye-open state accurately, which has significance to decrease traffic accidents. The experiment shows this algorithm can detect drivers’ eye states accurately in real-time and be of robustness and effectiveness.
Mixing matrix identification for underdetermined blind signal separation: Using hough transform and fuzzy K-means clustering

This paper focuses on the underdetermined blind signal separation problem with sparse representation. The algorithm is proposed to identify the parameters of mixing model which are unknown. The distribution of mixtures are mapping to a new histogram domain by Hough transform which converts the Cartesian image space to the normal parameterization. And then, fuzzy k-means clustering is employed to seek the cluster centers, i.e. parameters of mixing model, on the histogram. Obtaining accurate estimates, the sources can be recovered clearly. The proposed algorithm and three existing algorithms are tested in the simulations. By the simulation results, our algorithm is able to perform a nice accuracy of estimation through a very low computational consumption.
Real-time early detection of R waves of ECG signals

A computer algorithm for real-time triggering at the onsets of the R waves of a one-channel electrocardiogram is described. The algorithm is intended for timing the deflation of intraaortic balloon pumping with a control strategy based on real-time triggering. Thus, early detection of the R waves is the primary design goal. The algorithm consists of three steps: differentiation, correlation, and adaptive thresholding. As tested with an ECG database, the algorithm performs robustly and the point of detection is typically before the peak of an R wave.<<ETX>>
An improved normalized signal to noise ratio method for irrelevant genes removing

With the development of microarray technology, a lot of gene expression datasets have been applied to cancer classification and biomarker detection. Most of these gene expression datasets have small number of samples and tens of thousands of genes, so irrelevant genes eliminating is an important stage of feature selection for microarray expression data analysis. In this paper, an improved global normalized signal to noise ratio (gn-SNR) method for irrelevant genes removing is proposed. The method eliminates irrelevant genes by considering mean value and standard deviation with global normalization of different samples. First, the contributions of mean value and standard deviation between two kinds of samples are measured. Second, the global normalized contribution of the two parts is calculated. Finally, a threshold is used to remove irrelevant genes for microarray expression data analysis. The proposed method is examined on microarray of Leukemia dataset, Prostate dataset and Colon dataset. The best accuracies of the method in these datasets are 96.07%, 91.56% and 94.50%, respectively. The experimental results show that the proposed method has a powerful capability of irrelevant genes eliminating for microarray expression data analysis.
Multiscale, Multiphysics Model of Underfill Flow for Flip-Chip Packages

In this paper, the effects of various conditions on underfill flow including the substrate surface, temperature-dependent underfill properties, nonuniform bump patterns (e.g., missing columns), irregular bump shapes (e.g., slanted bumps), and filler particle redistribution are investigated for flip-chip packages. Experimental studies are first presented for underfill flow in silicon dies with different types of substrate surfaces (ceramic versus organic). Results show that the underfill material cannot wet organic packages well compared to their ceramic counterparts. This is also observed in simulations employing a 2-D global underfill flow model for an isothermal underfilling process. The effects of missing bump columns, temperature-dependent underfill viscosity and surface tension, and irregular bump shapes on underfill flow-out time, flow front shape, and void formation are then investigated in detailed underfill flow models, with each factor resulting in ±4~7% variation in underfill filling time. Finally, the influence of filler particle inhomogeneity due to settling and shear migration is modeled using a full 3-D particle suspension model. The simulated filler particle distribution around solder bumps agrees well with the cross-sectional images of cured underfill samples.
A new similarity measure for deformable image registration based on intensity matching

Deformable image registration plays an important role in medical image analysis. Multi-modal image registration remains a challenging research topic due to the complexity of modeling the relationship between two images. Mutual information (MI) is widely used in the field of multi-modal image registration, however, it suffers from problems such as interpolation artifacts and/or statistical insufficiency. The problem is worsened when bias field and noise are present. There have been attempts to map images to a common modality before image registration process, but the error introduced by the mapping may be detrimental to the registration. In this paper, instead of explicitly mapping the images to a common modality, we introduce a new similarity measure based on intensity matching information, which can be learnt from the existing registered training pairs or images pairs registered by performing MI based registration. Experiments on simulated brain MRI and real myocardial perfusion MR image sequences indicate that our proposed similarity measure outperforms the conventional MI and Kroon and Slump's method .
Design and Evaluation of a DICOM compliant Video-fluoroscopy Imaging System

Fluoroscopy is a special type of X-ray that provides continuous X-ray images (or live video) of a patient's organ structures in real time. It is used in many types of examinations and procedures, such as percutaneous nephrostomy (PCN), barium swallow, cardiac catheterization, and so on. The live fluoroscopy video is valuable for diagnosis review, teaching and research. They need to be stored as a part of the patient's medical records. Traditionally, the live fluoroscopic video can be saved by using video tapes. Since the nature of sequential access to a video tape, we cannot directly play or view a specific image. This makes the management of video tapes inefficient. Currently the DICOM 3.0 (digital imaging and communications in medicine) standard supports the MPEG-2 live video compression format. Most hospitals in Taiwan have developed their picture achieving and communication systems (PACSs) based on the DICOM standard to store and manage static X-ray images. Thus, it is the time for live fluoroscopic video to be captured, digitalized and integrated into the PACS for better storage, sharing and management. Although the DICOM supports the MPEG-2 compression scheme, it indicates that whether the clinicians can accept the lossy compression of MPEG-2 images is beyond the scope of the DICOM Standard. The paper presented here proposes approaches to develop a DICOM MPEG2 compliant fluoroscopic video management system integrated seamlessly with other hospital systems, and presents methods to evaluate the system acceptance from the viewpoint of clinicians. We conclude that the quality of the fluoroscopic video represented by the DICOM MPEG-2 specification is as good as or better than that represented by traditional video tapes.
Joint space-time block code and downlink beamforming in FDD DS-CDMA systems

Joint space-time block coding (STBC) and beamforming schemes for DS-CDMA are introduced in this paper. STBC scheme and beamforming technique have been considered separately as means to increase the bit rate and capacity in DS-CDMA systems. In STBC scheme, a user's stream is split two independent streams to transmit in two antennas, which will result in intersymbol interference at receiver in multipath environment. Thus, a STBC-beamforming scheme is discussed to compensate for the intersymbol interference. The beamforming weight is determined by downlink channel covariance (DCCM). Computer simulations show that using the STBCB scheme can provider better BER performance than conventional STBC scheme and single array diversity.
Particle swarm optimization for macrocell overlap removal and placement

This paper proposes a novel algorithm based on the particle swarm optimization (PSO) technique to obtain a feasible macrocell floorplanning without overlaps in VLSI circuit physical placement. The PSO was applied with an overlap detection and removal mechanism in search for optimal placement solution. Results employing MCNC and GSRC benchmarks revealed that the proposed PSO exhibited rapidly convergence features and led to more optimal solutions than other approaches.
Preparation of visible-light active N-doped nano-TiO2 photocatalyst by hydrothermal method

The nitrogen doping nano-titania (TiO2) photocatalyst was synthesized through a hydrothermal method. Ethylene Diamine Tetraacetic Acid (EDTA) was selected as the nitrogen resource to combine with titanium sulfate (Ti(SO4)2) via chemical complexation. The crystal size and phase, morphology, chemical state and photocatalytic ability were analyzed and characterized by X-ray diffraction (XRD), UV-visible spectrophotometer(UV-Vis), field emission scanning electron microscopy (FE-SEM) and X-ray photoelectron spectroscopy (XPS). A strong absorption in visible light region was observed. The results showed that the nitrogen was doped effectively and the chemical state of the nitrogen was Ti-N-O and Ti-O-N. Furthermore, the nitrogen doping TiO2 was expressed as TiO1.9697N0.0303 by calculating the concentration of nitrogen. The photocatalytic ability in visible light region could be improved by nitrogen doping in comparison with commercial P25 through the photodegradaton of organic pollutant methylene blue (MB), demonstrating its promising potential in environmental application.
The analysis of vehicles electromagnetic environment based on TLM method

Utilizing the TLM (Transmission Line Method) method, this paper discussed the electromagnetic environment of vehicles under the condition of high electromagnetic pulse (EMP). The simulation results show that the amplitude of electromagnetic intensity of external is higher about an order than that of internal. While the nearer the stimulation, the greater the amplitude of electromagnetic intensity amplitude, that is the amplitude of upper part in the vehicles is bigger than that of the bottom. The amplitude of electromagnetic intensity is symmetrical following with the symmetrical of the position of electromagnetic pulse stimulation. The amplitude of electromagnetic intensity of the polarization direction and propagation direction perpendicular to the body is higher than that of parallel to the body.
Majorization-Minimization Algorithms in Signal Processing, Communications, and Machine Learning

This paper gives an overview of the majorization-minimization (MM) algorithmic framework, which can provide guidance in deriving problem-driven algorithms with low computational cost. A general introduction of MM is presented, including a description of the basic principle and its convergence results. The extensions, acceleration schemes, and connection to other algorithmic frameworks are also covered. To bridge the gap between theory and practice, upperbounds for a large number of basic functions, derived based on the Taylor expansion, convexity, and special inequalities, are provided as ingredients for constructing surrogate functions. With the pre-requisites established, the way of applying MM to solving specific problems is elaborated by a wide range of applications in signal processing, communications, and machine learning.
Automatically labeling of Brainstem Auditory Evoked Potential based on vector algorithm

Brainstem Auditory Evoked Potential (BAEP) is one of the widely-used evoked potentials in clinical application. For many applications such as auditory threshold estimation and surgical monitoring, automatic analysis of BAEP waveform is required to provide BAEP determination threshold for clinical analysis. This paper describes one new vector algorithm which is used to perform automatic labeling of BAEP thresholds on collected BAEP data, and experiment results have shown that label accuracy is more than 90% under a stimulus intensity of 75dBnHL.
Research on unburned combustible forecast in fly ash of the coal-fired boiler based on Genetic Algorithm and Artificial Neural Network

The boiler fuel burning is the main basis to evaluate the energy saving. This paper combined the genetic algorithm and artificial neural network to model the burning process of the boiler fuel, in order to forecast the unburned combustible in flue dust of the coal-fired boiler. Use the powerful optimizing of GA to narrow the search range, then use ANN to optimize accurately. It can prevent the BP from sinking into local minimum, low convergence rate oscillation effect and other disadvantages. And then, more accurate output data of the black box can be obtained.
Review of on-line defects detection technique for above ground storage tank floor monitoring

Facilities with tanks often present additional risks beyond site risks, such as potential injury to site personnel, damage to equipment and environment. The floor of an above ground storage tank is the most difficult part to access using online inspection method. In this paper, four on-line defect detection methods, such as volumetric or mass methods, acoustic emission (AE), soil vapor monitoring and inventory control are presented and their advantages and disadvantages in testing of above ground storage tank containing fluid are discussed. Acoustic Emission (AE) corrosion monitoring method is investigated in detail as an effective non-destructive method for prioritizing inspection of Aboveground Storage Tanks not only because of the significant time and expense savings of not having to enter the tank for inspection, but also the feature of maintenance plan recommendation to balance valuable maintenance resources. The application of such an approach may reduce the potential cost for maintaining tanks in safe operating condition, and making repairs and determine if and when replacement is necessary.
Optimal vibration control for stochastic discrete-time systems

The problem of optimal disturbance rejection control (ODRC) with zero steady-state error to sinusoidal disturbances for stochastic discrete-time systems is considered. Based on the internal model principle, external sinusoidal disturbance is compensated by constructing a disturbance compensator. Then, an optimal linear quadratic Gaussian (LQG) controller with an infinite-time horizon cost functional is designed. The state estimator from measurements of the output makes the dynamic ODRC law physical reliable and the convergence of the cost functional can be guaranteed. A simulation example shows the approach proposed is effective.
Wavelet-based non-zero order joint transform corrlator for target recognition in noisy scenes

A novel joint transform correlator for target recognition under noisy conditions is proposed. In this design, strong zero order term is eliminated by modifying joint transform power spectrum through wavelet transform. To obtain sharp correlation peak and noise resistance ability, logarithmic algorithm is applied and yields far better results compared with widely used modified fringe adjusted filter. Computer simulation results are presented to confirm the performance of the proposed technique in additive Gaussian noise environment.
Approximate optimal rejection to sinusoidal disturbance for nonlinear systems

The problem of approximate optimal rejection to sinusoidal disturbances with zero steady-state error (ZSSE) for nonlinear systems is considered. Based on the internal model principle, a disturbance compensator is constructed through which the plant model with external disturbances is transformed into an augmented nonlinear system without disturbances. Introducing a sensitivity parameter and expanding power series around it, the original optimal control problem is transformed into a series of linear two-point boundary value (TPBV) problems. The obtained optimal control law consists of a linear analytic term which is obtained by solving a Riccati matrix equation and a nonlinear compensatory term in form of series which is obtained by a recursive algorithm. By intercepting a finite sum of the compensation series, an approximate optimal control law is obtained. A numerical simulation shows that the algorithm is easily implemented and has a fast convergence rate. The designed controller has more robustness.