nils-herrmann/clean_scirepeval huggingface dataset:
Adaptive CR values with fuzzy inference system for differential evolution algorithm

This study proposed fuzzy-based adaptive method for crossover rate (CR) values to improve the convergence rate of Differential Evolution (DE) algorithms. The proposed method decides the CR values according to two factors of the evolutionary environment, the change rate of solution of center of solutions and the density of each dimension. The proposed DE algorithm is tested by the CEC2015 benchmark suits and compared with fuzzy adaptive differential evolution (FADE). The experimental results showed that the proposed method really improved performance for 11 of 15 evaluated functions in 10, 30, and 50 dimensions and enhanced the convergence.
Growth and properties of /spl Phi/3" <011> LBO crystal for leaky SAW devices

/spl Phi/3" <011> LBO crystals have been grown successfully by the modified Bridgman (BR) technique. The feature of <011> LBO growth is to form easily laminar twinning parallel to (100) face and <011> growth direction. The laminar twins can be increased in thickness and size of them or disappear from periphery of LBO boule. Twin-free /spl Phi/3" <011> LBO crystal can be grown by careful preparation of seed crystal and maintenance of stable growth conditions. (011) cut of BR-LBO substrate has phase velocity of longitudinal leaky surface acoustic wave (LLSAW) 6676 m/s, coupling coefficient k/sup 2/ 2.8%, propagation loss 0.0083 dB//spl lambda/, which indicates (011) cut of LBO substrate is suitable for high frequency device fabrication.
A Study of Zero-Crossings with Peak-Amplitudes in Speech Emotion Classification

A number of recent studies have focused on the speech emotion recognition. Emotional features extraction is the key of the whole system. Most of previous work on feature extraction is database dependent. This paper describes the zero-crossings with peak-amplitudes (ZCPA) feature extraction approach, and applies ZCPA approach to emotion recognition. Two kinds of experiments were carried out. The first kind is one language experiments with TYUT database and Berlin database. The results of this kind experiments show that ZCPA features can represent speech emotion effectively. The second kind experiment is cross-database of three languages. Experiments of the second kind indicate that the ZCPA features are database independent.
Thermal modelling of large-format laminated Li-ion battery and experimental validation using embedded thermocouples

Thermal modelling for lithium ion batteries is important to evaluate battery thermal safety and to refine battery thermal designs. To develop a reliable and efficient thermal model, the following key factors needs to be addressed: the techniques to accurately determine the thermal parameters and heat generation rates, the reasonably simplified thermo-electrical equations and the experimental validation. In this study, a new transient method is developed to measure the thermal parameters of a large-format laminated battery. The reversible and irreversible heat generation rates were measured for different states of charge and temperatures. With the measured thermal parameters and heat generation rates, the temperature distribution of the battery was predicted based on a thermal-electrical coupled model. The prediction was found in good agreement with embedded-sensor experimental results.
The Utility Frequent Pattern Mining Based on Slide Window in Data Stream

In traditional study of mining data stream, each item in the data stream is of equal importance. However, in practice, each item has a different significance, which is known as utility. This paper combines frequent mining item sets with utility and proposes an efficient algorithm for utility frequent pattern mining (UFPM). It combines bitmap with tree structure that can store and update the pattern of data stream quickly and completely by scanning only once. The algorithm generated by lexicographic order, proposes a novel tree U-tree and makes convenience for pattern updating and user reading. With a pattern growth approach in mining, the algorithm can effectively avoid the problem of a mass candidacy generation by level-wise searching. The experiments results show that our algorithm which is in high efficiency and good scalability outperforms the existing analogous algorithm.
Designing Android Applications Using Voice Controlled Commands: For Hands Free Interaction with Common Household Devices

Utilizing assistive technology to aid persons with neuromuscular disabilities, this study improves upon previously created offline voice control of household devices through an input-output peripheral interface control processor driven using an application on the Galaxy S Android smart phone. In trial, the most effective type of voice recognition software for offline communication was Pocketsphinx. This offline capability is used and tested for accuracy of several commands on a direct television remote though the exchange of Bluetooth signals between the phone (input) and transfer station (output). The application was designed to recognize key word commands and send signals to corresponding pins on the input-output board. The execution of a command was enabled through the interface of the smart phone with a television remote. In the laboratory, experiments were tested for accuracy taking into account distance between person and device as well as level of ambient noise and the vocalization of the subject.
Modeling Method and Application of Full Scope Non-Linear Simulation Experimental Mathematic Model

Model with dynamic characteristic of nonlinear controlled object is a significant technical problem in process control field. Taking controlled object boiler steam temperature’s full scope simulation mathematic model as example, and considering the effect of zeros and poles in the new model upon dynamic characteristic, explore a sort of practical and effective modeling method, which use a unified mathematical model to describe static and dynamic characteristics of controlled object, and avoid some technique problems brought by multitude transfer functions with modeling method of piecewise linear. It is making convenient to practical application, at the same time, with the consideration of zeros and poles can enlarge the research, the unification of static characteristic and dynamic characteristic can also be proved, that is when time turn to infinite , the final steady value of all the parameters decided by the dynamic mathematical model is the same with that decided by static mathematical model. The modeling method is brief and practical.
Characterization of the Coronary Vascular Capacitance, Resistance, and Flow in Endocardium and Epicardium Based on a Nonlinear Dynamic Analog Model

An electrical analog model consisting of capacitors, diodes, linear, and nonlinear resistors was used to characterize the coronary pressure-flow relationships from the arterial side of the coronary circulation. Based on this analog model, an identifiable system was formulated whereby the coronary vascular capacitance and resistance in the endocardial and epicardial layer of the heart were estimated. This was done by solving a constrained least-squares problem using a nonlinear programming technique. Experimental data were obtained from 28 animal studies using swine with an artificially induced coronary stenosis. The analog model showed a very consistent representation of the coronary hemodynamics. The model also generated accurate estimates of the endocardial to epicardial blood flow ratios compared to those independently measured by the radioactive microsphere technique. The model-predicted epicardial capacitance had a mean of 4.2 ×10-3 mI/mmHg per 100 g tissue; while the endocardial capacitance was negligible in most cases. The result indicated that, in the stenosed coronary circulation of swine, capacitive flow contributes 20 percent in root-mean-square value to the total flow activity in epicardium; while flow in the endocardium is dominated by a resistive, vascular waterfall effect.
Adaptive robust H∞ control of the generator excitation system

The robust H∞ control problem for the generator excitation system with the damping coefficient uncertainty and external disturbances, is addressed. Storage functions of the control system are constructed based on modified adaptive backstepping sliding mode control method and Lyapunov method. A nonlinear robust H∞ controller and a parameter updating law are obtained simultaneously. The controller can not only attenuate the influences of external disturbances on the system output, but also has strong robustness for system parameters variation. Since the controller design is based completely on the nonlinear dynamic system without any linearization, the nonlinear property of the dynamic system is well preserved. The simulation results show that more rapid speed response and stronger robustness can be obtained by the proposed method than the conventional adaptive backstepping and adaptive backstepping sliding mode control methods.
Online model-based fault detection for grid connected PV systems monitoring

This paper presents an efficient fault detection approach to monitor the direct current (DC) side of photovoltaic (PV) systems. The key contribution of this work is combining both single diode model (SDM) flexibility and the cumulative sum (CUSUM) chart efficiency to detect incipient faults. In fact, unknown electrical parameters of SDM are firstly identified using an efficient heuristic algorithm, named Artificial Bee Colony algorithm. Then, based on the identified parameters, a simulation model is built and validated using a co-simulation between Matlab/Simulink and PSIM. Next, the peak power (Pmpp) residuals of the entire PV array are generated based on both real measured and simulated Pmpp values. Residuals are used as the input for the CUSUM scheme to detect potential faults. We validate the effectiveness of this approach using practical data from an actual 20 MWp grid-connected PV system located in the province of Adrar, Algeria.
Research on Service Innovation Performance Structural Model

Modern enterprise need to continuously provide customers with perfect services to maintain its competitive edge. Therefore, the enterprises attach great importance to service innovation activities. For enterprises, how to assess the success of service innovation, to guarantee the rate of service innovation success has become urgent practical problems. Based on this real problem, this paper takes empirical research methods to explore the service innovation performance model. Data were analyzed to verify the research hypothesis by using a variety of statistical analysis methods. And the results were explained and discussed. Ultimately, propose and verify the four-dimensional model of service innovation performance. The results showed that service innovation performance concludes four dimensions, which are financial targets, business growth, customer indicators and internal indicators. On the one hand, this conclusion complements the theory of service innovation performance, on the other hand, the results can provide evaluation for service innovation activities, and help companies determine the success of service innovative activities.
Trihalomethane Occurrence in Chlorinated Hospital Wastewater

Chlorination as a disinfection process is often used for disinfecting hospital wastewater in order to prevent the spread of pathogenic microorganisms and causal agents of nosocomial infectious diseases, but harmful byproducts might be formed and cause adverse ecological and health effects. In this study, the generation of trihalomethane (THMs) in the effluent of hospital wastewater during chlorine disinfection process was evaluated. The results showed the formation of THMs increased gently along the increasing chlorine dosages at beginning of the chlorine disinfection, but increased significantly after the chlorine dosages over 20 mg/L. Chloroform was the most abundant THM species and occupied above 40% of the total concentration. The second-order model interpretation of the long-term formation of THMs showed a good linearity and a second-order rate constant of 0.8857 (mg/L)-1s-1 in this experiments. Additionally, THM formations in these water samples well correlated with SUVA with generally exponential (R =0.9987).
A conjugate-gradient sparse-matrix method for efficient computation of a cardiovascular model

A conjugate-gradient (CG) sparse-matrix (SIM) method was applied to an integrated cardiovascular model for improving its computational efficiency. The model was previously developed by combining a 3D finite element model (FEM) of the left ventricle with an analog electrical model of the circulatory system. The computation of this integrated model was dominated by the FEM, which consumed 99.9% of the run time. A computational bottleneck (98.6%) was the solution of the simultaneous equations in the global stiffness matrix and the nodal displacement vectors. For a 40% infarct size in the FEM the computational time for a cardiac cycle with a 5-ms time resolution and a heart rate of 71 bpm was reduced from 20 min to 6 min. Depending on the infarct size, the CGSM method reduced the computational time to 30-60% of that obtained by use of a conventional QR decomposition method.
A digital watermarking algorithm based on hyperchaos and discrete fractional Fourier transform

Based on hyperchaos and discrete fractional Fourier transform (DFRFT) algorithm, a digital image watermarking algorithm based on hyperchaos sequence and the discrete fractional Fourier is presented in this paper. First, the original image and the watermarking image are transformed, respectively. At the same time, according to cipher sequence generated by the hyperchaotic array, the watermarking image's real part and imaginary part are encrypted, respectively. Second, the encryption watermark image's real part and imaginary part alternative embedded into the host FRFT coefficients. Then, the watermarking image is obtained after Fourier inversely transformed. Moreover, different attacks such as noise, JPEG compression and the cropping have been analyzed for the robustness of the watermark image. The results of the experiment have shown that the proposed algorithm is robust against common image manipulations.
Dynamic Experiments of Strain and Magnetic Field for Galfenol Rod and Its Modeling

Dynamic actuation experiments of an Fe83Ga17 (Galfenol) rod sample were conducted by the authors. A permanent magnet was used to apply a 2.25-kA/m bias field. Dynamic current through the excitation coils was applied to obtain a dynamic magnetic field. The frequencies of the dynamic field are 1, 10, 20, 40, 60, 100, 200, and 300 Hz. Hysteresis between the strain and dynamic magnetic field increases with increasing frequency. The power losses consist of hysteresis loss, classical eddy current loss, and anomalous (or excess) loss when Galfenol is excited by a dynamic field. To describe the hysteresis, a dynamic hysteresis model of Galfenol based on the energy-weighted average hysteresis equation, eddy current loss, and anomalous loss was used. The hysteresis loss was calculated using incremental volume fractions, which was evaluated using the energy-weighted average formula. The experimental results and model calculations agree well for frequencies below 200 Hz. The model can be used to guide the design of Galfenol dynamic applications in low frequency such as actuators and vibrators.
Application of Dynamic Recurrent Neural Network in Power System Short-Term Load Forecasting

Convergence speed of the traditional BP neural network is slow, and it is easy to fall into local minimum. A novel dynamic recurrent fuzzy neural network model is proposed, which is used to resolve the power system short-term load forecasting. The fuzzy inference function is realized easily by using a product operation in the network. The simulation results indicate that the proposed network can overcome the limit of back-propagation-based static network methods and accurately forecast the short-term load.
In vivo estimation of cardiovascular flows with surface integration of velocity vectors from color Doppler imaging

Ultrasound can be used to noninvasively study the pumping heart. To be able to obtain more accurate flow estimates, we have designed the Surface Integration of Velocity Vectors (SIVV) echocardiographic method for angle independent determination of cardiac flow. The aim is to develop a noninvasive method for quantification of volume flows that can be used instead of the invasive methods that exist today. Using gated and time-delayed electrocardiographic acquisitions, Doppler data (Vingmed CFM 800) was collected for consecutive heart beats. Left ventricular inflow and outflow regions were studied. The SIVV analysis with velocity information from a variable number of planes as well as different wall filters and the time correction algorithm as described by Eidenvall et al. (1992), are implemented. Preliminary data from stroke volume determination agrees well (8% difference, 67 ml by SIVV versus 62 ml by the Fick equation).
Optimal Disturbance Rejection with Zero Steady-state Error for Linear Discrete-time Systems

The problem of optimal disturbance rejection with zero steady-state error for linear discrete-time systems is considered. Based on the internal model principle, external persistent disturbance is compensated by constructing a disturbance compensator. Then, the optimal controller with an infinite-time horizon cost functional is designed by using classical optimal control theory, and the convergence of the cost functional can be guaranteed. A dynamic optimal feedback loop controller with zero steady-state error is obtained. A simulation example is given to test the validity of the presented algorithm
Early detection of abnormal patient arrivals at hospital emergency department

Overcrowding is one of the most crucial issues confronting emergency departments (EDs) throughout the world. Efficient management of patient flows for ED services has become an urgent issue for most hospital administrations. Handling and detection of abnormal situations is a key challenge in EDs. Thus, the early detection of abnormal patient arrivals at EDs plays an important role from the point of view of improving management of the inspected EDs. It allows the EDs mangers to prepare for high levels of care activities, to optimize the internal resources and to predict enough hospitalization capacity in downstream care services. This study reports the development of statistical method for enhancing detection of abnormal daily patient arrivals at the ED, which able to provide early alert mechanisms in the event of abnormal situations. The autoregressive moving average (ARMA)-based exponentially weighted moving average (EWMA) anomaly detection scheme proposed was successfully applied to the practical data collected from the database of the pediatric emergency department (PED) at Lille regional hospital center, France.
Microcontroller based pulse oximeter for undergraduate capstone design

Pulse oximeters are used worldwide as a non-intrusive way to monitor a patient's pulse and blood-oxygen saturation instantaneously. The purpose of this design is to examine the possibility of using a simple microcontroller to measure pulse and blood-oxygen saturation in real time, as well as the level of difficulty and learning curve associated with assigning such a task as a senior capstone design project. The circuit consists of a PIC18F452 microcontroller, transistor network, photoplethys-mogram amplifier (PPG), pulse oximeter probe, digital-to-analog converter (DAC), and an LCD screen to display results. Software is written in C++ for the microprocessor, which supports a limited C syntax. The project requires various engineering proficiencies such as signal processing, programming, circuitry, and microprocessors. Overall, the project is a good introduction to medical instrumentation and capstone design for undergraduate biomedical and electrical engineers.
Hydrodynamic parameters of air-bubble stimulated underwater spark discharges

Considerable amount of research work has been focused on investigation and optimization of strong acoustic waves generated by spark discharges in water. There are several methods to achieve and to stimulate underwater spark breakdowns, including free-discharges, wire-guided and gas-bubble stimulated discharges. In the present work, air bubbles are injected into water in order to achieve spark discharges in relatively long inter-electrode gaps. This paper reports on hydrodynamic and acoustic characteristics of spark discharges stimulated by air bubbles and presents the functional relationships between the hydrodynamic and electrical parameters of such discharges, including breakdown voltage, spark plasma resistance and energy available in the discharge. A hydrodynamic analytical model has been developed and used to calculate the acoustic efficiency of the underwater spark discharges.
An efficient noise reduction algorithm using empirical mode decomposition and correlation measurement

Noise reduction has a lot attention no matter in practical applications or a signal processing research field. Recently, a novel denoisy method which removes noise from received signals by threshold operation on wavelet coefficients was developed and its efficiency has been confirmed. However, its definition of parameters is not general-purpose enough to deal with variant cases. In order to seek high quality to denoisy, this study introduces a frequency analysis tool, empirical mode decomposition (EMD), to separate received signal into several elements which are termed intrinsic mode functions (IMF). And then, according to the order from high frequency to low frequency, IMFs could be separated into finite pair consisting of estimated noise and estimated original signal. Each estimated pair is calculated the correlation measurement which involves second-order correlation and high-order correlation since original signal and noise are mutually independent. A smallest measure value implies an optimal pair approximating to the real. In simulations, four benchmarks and three noise level are tested; moreover, two state of the art algorithms are compared with the proposed method. Finally, the excellent robustness and efficiency of proposed method are demonstrated by simulation results.
Dynamics of intraaortic counterpulsation with double-segmented balloons

The dynamics of a double-segmented intraaortic balloon and its interaction with the cardiovascular system were characterized by use of an analog electrical model. With computer simulations the model generated a broad spectrum of data regarding the effectiveness of the cardiac assistance. The result showed that, with proper balloon configurations and inflation/deflation rates, a double-segmented design improved the diastolic augmentation. However, no improvement on the systolic unloading was observed.<<ETX>>
Transport processes associated with inkjet printing of colloidal drops for printable electronics fabrication

This paper presents an experimental investigation of deposition dynamics of inkjet-printed colloidal drops on glass and PET substrates. Using fluorescent particles and confocal microscopy, the evaporatively-driven and thermal Marangoni flows inside a colloidal drop, as well as the particle self-assembly and deposition on the substrate are directly observed. In addition, Ar plasma treatment is used to modify the substrate surfaces. Wetting properties (i.e., advancing /receding contact angle and contact angle hysteresis) of colloidal drops on different substrates, substrate surface roughness, and final particle deposition morphologies are characterized using goniometer, AFM, and SEM. A correlation between the substrate surface roughness, static receding contact angle, contact line pinning/de-wetting, and final particle deposition morphology is explored. This study seeks to provide design guidelines for substrate surfaces that will improve the resolution and edge definition of printable electronics fabrication.