nils-herrmann/clean_scirepeval huggingface dataset:
Design of broadband circularly-polarized monopole antenna for wirless communication

A broadband monopole antenna for circularly-polarized (CP) applications is proposed. The broadband property of the antenna is basically achieved not only by the chifre-shaped monople radiator but also its asymmetric microstrip feedline. The CP characteristics is enhanced significantly by adjusting the lacation of the monople feed. The antenna delivers wideband performance in terms of impedance matching and circular polarisation. The measured results agree with the simulaitons reasonablly, and the measurements demonstrate an impedance bandwidth of 72% for the reflection coefficient no more than -10dB and a 3-dB axial-ratio (AR) bandwidth of 41.6% with the central frequency of 2.5 GHz.
Enhanced dynamic data-driven fault detection approach: Application to a two-tank heater system

Principal components analysis (PCA) has been intensively studied and used in monitoring industrial systems. However, data generated from chemical processes are usually correlated in time due to process dynamics, which makes the fault detection based on PCA approach a challenging task. Accounting for the dynamic nature of data can also reflect the performance of the designed fault detection approaches. In PCA-based methods, this dynamic characteristic of the data can be accounted for by using dynamic PCA (DPCA), in which lagged variables are used in the PCA model to capture the time evolution of the process. This paper presents a new approach that combines the DPCA to account for autocorrelation in data and generalized likelihood ratio (GLR) test to detect faults. A DPCA model is applied to perform dimension reduction while appropriately considering the temporal relationships in the data. Specifically, the proposed approach uses the DPCA to generate residuals, and then apply GLR test to reveal any abnormality. The performances of the proposed method are evaluated through a continuous stirred tank heater system.
Adaptive fuzzy search algorithm for improving the efficiency of block motion estimation

This paper proposes an adaptive fuzzy search (AFS) algorithm, based on the spatial and temporal correlation of image sequences, for improving the efficiency of block motion estimation. Due to the fuzzy reasoning method, the proposed algorithm could precisely predict the motion vector and reduce the computational cost. The essential difference between AFS and other related fuzzy methods is the adaptive ability for membership functions that are established according to the relationship of blocks and their neighbors. A Gaussian function is constructed through the differences between current block and its adjacent blocks. According to the Gaussian function of the current block, the weight of each adjacent block could be determined and then predict an initial center for the current block. This is why the AFS is adaptive and robust than other algorithms. Taking both the search point and block distortion measure into consideration, the performance of AFS is indeed better than the general inter-block/inter-frame fuzzy search (IIFS), TSS and LS.
Study Flow Field of Magnesium Electrolyzer by Computer Technology

In modern times, computer technology is used in various fields in the world. In this paper, CFD(computational fluid dynamics) was applied to build mathematical model to simulate continuous and dispersed multiphase flow in the experimental systems and an industrial electrolyzer. The Volume of Fluid model was used in the mathematical model for multi-phases. Cold model system of complex multiphase behavior of argon gas, water and silicon oil system in terms of dynamic similarity was established to validate the math model. Flow field was measured through PIV (particle-image velocimetry) technology. The results show that the built three dimensional mathematical model was valid for the system and suitable for the electrolyzer in electrolysis magnesium industry. The characteristics of complex multiphase in industrial electrolyzer were discussed in the paper.
Phase Relationship and Magnetostriction of Tb–Dy–Ho–Fe Alloys

The phase relationship of Tb<sub>0.26</sub>Dy<sub>0.49</sub>Ho<sub>0.25</sub>Fe<sub>x</sub> (1.6 ≤ × ≤ 2.4) alloys in the Tb-Dy-Ho-Fe system was determined by using optical microscopy, X-ray diffraction, and differential thermal analysis. The vertical section of Tb<sub>0.26</sub>Dy<sub>0.49</sub>Ho<sub>0.25</sub>Fe<sub>x</sub> alloys consists of two single-phase regions, namely, L (liquid) and (Tb, Dy, Ho)Fe<sub>2</sub>, and four two-phase regions, namely, L + (Tb, Dy, Ho)Fe<sub>3</sub>, L + (Tb, Dy, Ho)Fe<sub>2</sub>, (Tb, Dy, Ho)Fe<sub>2</sub> + (Tb, Dy, Ho)Fe<sub>3</sub>, and (Tb, Dy, Ho)Fe<sub>2</sub> + (Tb, Dy, Ho). The range between the liquidus and peritectic temperatures for Tb<sub>0.26</sub>Dy<sub>0.49</sub>Ho<sub>0.25</sub>Fe<sub>x</sub> alloys becomes narrow with addition of Ho, which is beneficial to decrease the properitectic (Tb, Dy, Ho)Fe<sub>3</sub> phase. The magnetic field dependence of magnetostriction (λ<sub>//</sub>, λ<sub>⊥</sub>) for Tb<sub>0.26</sub>Dy<sub>0.49</sub>Ho<sub>0.25</sub>Fe<sub>x</sub> alloys has been determined. The magnetostriction quickly increases with increasing magnetic field value when it is less than 240 kA/m. Among the present studied alloys, the sample with x = 1.9 possesses the largest magnetostriction. It has been found that magnetic annealing improves the magnetostriction λ<sub>//</sub> of Tb<sub>0.26</sub>Dy<sub>0.49</sub>Ho<sub>0.25</sub>Fe<sub>1.9</sub> alloy.
Leak detection and position method for pressure piping using Acoustic Emission

Detection and position of defects in pipeline based on acoustic emission was investigated. The theory of AE pipeline detection and position method was analyzed and a serial of experiments were carried out. Parameters, such as pressure in the pipe, diameter of the leaking hole (leaking hole), and distance from transducers to the leaking hole, were adjusted to show its effects on AE signals caused by the leak. It shows that AE technique could be applied in detecting and positioning of defects in pressure pipe during normal operation of the pipeline, and it is insensitive to the geometry structure of inspected component. In the end, the leak was positioned through continuous AE signals using cross-correlation analysis, and the relative error of the test was 2.63%.
Study on mechanism and properties of Alcohol-based polyurethane adhesives

Toluene diisocyanate (TDI), Polyether diol, and diethylenetriamine were used to synthesize the A-component of adhesives. B-component was prepared by the EP (E-51) and acetic ether. A series of polyurethane adhesive was obtained by A-component and B-component in different proportions. Infrared spectrum, peel strength, shear strength and bibulous rate were measured, the results indicated that the sample had a highest peel strength, shear strength and lowest water absorption, when the ratio of curing agent and adhesive was 1:10.
The design of converter circuit in distributed power generation system

With the micro-turbine technology continues to improve, Micro-Turbine Generator(MTG) has become the most mature and most competitive business in distributed power generation equipment. This article designed a converter circuit that applied to distributed power generation system by micro-turbine drived a high-speed motor. PWM rectifier and PWM inverter can use the same topology for the whole system design. Space vector pulse width modulation(SVPWM) control algorithm is applied to this converter. A simulation model of converter circuit system applied to distributed generation can be designed. The simulation results show the feasibility of the proposed structure and the control strategy. Using SVPWM control method can improve the utilization ratio of direct current voltage and is easy-to-digital realization. It reduce harmonic currents and loss of the generator and improve system stability.
Linear infinite horizon quadratic differential games for stochastic systems: Discrete-time case

This paper deals with the infinite horizon linear quadratic (LQ) differential games for discrete-time stochastic systems with both state and control dependent noise. The Popov-Belevitch-Hautus (PBH) criteria for exact observability and exact detectability of discrete-time stochastic systems are presented. By using them, we give the optimal strategies (Nash equilibrium strategies) and the optimal cost values for infinite horizon stochastic differential games. It is indicated that the infinite horizon LQ stochastic differential games are associated with four coupled matrix-valued equations.
Medication reminding activity analyzer for guided independent living environments (MRAAGILE): Implementing Motion Dependent Medication Reminders

The MRAAGILE is a device designed to monitor and reinforce medication consumption as well as promote a healthy daily regimen for those who choose to live independently. The device provides interactive reminder messages to inspire the user to follow directives. The purpose of this is to implement motion detection following a reminder to determine whether the user is responding. The device will receive instructions from the user manually on the device or by using a bluetooth wireless link to transmit the times for which medication is to be taken. After reminders are set, the mobile device will continue to function until the first reminder time is reached. A message will be played. If motion is detected, it will serve as an indicator that the message was acknowledged. If not, it will trigger an alarm to remind the user to complete the action. The alarm will deactivate once motion is detected. This device will be useful for increasing the independence for older adults who live in the community as well as assistive living environments.
Modeling effects of infarction on cardiac function with dynamic finite element analysis

A computational model has been developed that combines a 3D finite element model (FEM) of the left ventricle (LV) with an electrical analog model of the circulatory system. The model is used to assess the effects of infarction on LV function. LV geometry is modeled as a truncated ellipsoid. The stress-strain relationship for each element is assumed to be linear but with a time-varying Young's modulus. For a given LV pressure (Plv) generated by the electrical analog model, LV volume (Vlv) is determined by a 3D model constructed from multiple 2D FEM slices. The left ventricular elastance (Elv), determined by Plv over Vlv, is used to drive the electrical analog model. Time-varying Young's modulus functions over a cardiac cycle are assigned to normal and infarct finite elements, defining the infarct zone for a certain size and location. The model provided good representations of the LV geometry for normal and infarct cases. The LV ejection fraction, pressure, and volume curves were consistent with typical clinical observations. The dynamic finite element model developed in this study is effective and computationally efficient. The model can be used to relate regional LV impairments to overall circulatory dynamics.
Quality design and shelf investment in different distribution channels

This paper investigates product quality design and shelf investment decision for a manufacturer considering that consumers' perception of product quality can be affected by shelf display in retailing industry. We discuss production quality decision and shelf display investment in decentralized and centralized channel with heterogenous consumers. In decentralized supply chain, the manufacturer first decides his marketing mix, i.e., product quality level and wholesale price, the retailer then determines her shelf display investment and retail price. The subgame perfect Nash equilibrium of the manufacturer- Stackelberg game shows that, comparing with centralized channel, the manufacturer will improve his product quality and the retailer will invest more in shelf display in decentralized channel. The price is also higher than that in centralized channel. In addition, the first-move advantage is achieved in decentralized channel.
A simple strategy for fall events detection

The paper concerns the detection of fall events based on human silhouette shape variations. The detection of fall events is addressed from the statistical point of view as an anomaly detection problem. Specifically, the paper investigates the multivariate exponentially weighted moving average (MEWMA) control chart to detect fall events. Towards this end, a set of ratios for five partial occupancy areas of the human body for each frame are collected and used as the input data to MEWMA chart. The MEWMA fall detection scheme has been successfully applied to two publicly available fall detection databases, the UR fall detection dataset (URFD) and the fall detection dataset (FDD). The monitoring strategy developed was able to provide early alert mechanisms in the event of fall situations.
Memory usage reduction method for FFT implementations on DSP based embedded system

When computing large scale Discrete Fourier Transform (DFT) in an embedded system, the external memory will be filled with a great deal of signal and twiddle factor data. As the transform length grow, CPU cycle stall due to memory cache miss is increased because there is a lot of data to be fetch in an external memory. Thus, to reduce size of data is an important issue in embedded system. Since signal data is unknown, it cannot be compressed through mathematical relation, but twiddle factor can. According to the above problem, the method to reduce the size of twiddle factor and cache-optimized is proposed. This method uses the relationship between cosine and sine to minimize memory usage by twiddle factor, and optimize cache operation to enhance [9]. As the result, the size of twiddle factor is reducing to almost 50% and has significant improvement when data size is great than cache size.
Photovoltaic integration capacity of grid considering peak load regulation capacity and operating economy

With the increasing integration of photovoltaic, it is of much significance to study the capacity of grid-connected photovoltaic integration because peak load regulation capacity of power grid has become the bottleneck problem. This paper applies the Lagrangian Relaxation method of unit combination problem to find the photovoltaic integration capacity. With the consideration of peak load regulation, the optimal goal is to find the minimum system operating cost with wind power and photovoltaic introduced in the start-up mode model of unit combination. This method is applied to the analysis of future photovoltaic integration capacity of a solar resourceful province in north China according to the power structure and spinning reserve capacity, obtaining that the accommodating capacity is greater than planned. Some suggestions are put forward to magnify the integration capacity according to actual situation. These results provide reference to power supply plan, grid frame construction, operation and dispatch.
Kidney segmentation in MRI sequences using temporal dynamics

We propose an energy-based image segmentation algorithm that uses the correlation information among pixels in the same image as well as the temporal correlation across the images in the sequence. We focus on MRI sequences that are extremely difficult to segment on the basis of single images. Our method detects motion-free objects whose intensities change across the image sequence. We introduce an energy functional that exploits the difference in the dynamics of the temporal signals associated with distinct pixels. We develop a level set approach and a region-growing algorithm to minimize the energy functional. Our tests in a transplantation study show that we successfully extract automatically the kidneys and their structures in magnetic resonance (MR) image sequences.
Hemodynamic effects of infarct location in left ventricular wall based on an integrated finite element and circulatory model

An integrated finite element and circulatory model was developed and used to assess the differential impact of infarct location on left ventricular hemodynamics. In this study a finite element model of the left ventricle (LV) was fully integrated with an electrical analog model of the circulatory system. The model was capable of generating pressure and volume waveforms that are consistent with the clinical observations. Simulations based on this model determined the hemodynamic effects of an infarction located near the base, mid-wall, or apex of the LV. Infarction near the apex showed lesser effects than infarctions near the base or the mid-wall. Infarctions near the base and mid-wall showed similar effects. The decrease in ejection fraction was most sensitive to infarction near the base, while the increase in end-systolic volume and end-diastolic volume was most sensitive to infarction near the mid-wall
Research on logistics distribution center location model and fuzzy comprehensive evaluation under electronic commerce

This study establishes the logistics distribution center location model under electronics commerce and modifies alternative expenses and time-restricting conditions of logistics distribution center location model according to the specific feature of model under electronics commerce. Because location model is a NP question, the result is solved through heuristic arithmetic. It's difficult to consider all the factors during the course of establishing the logistics distribution center location model. And it is also difficult to quantify the restricting condition in model. Therefore, it is very necessary to ask for the experts' opinion and advice and do some qualitative decisions. On the basis of this hypothesis, this study makes certain the logistics distribution center location under electronic commerce using the combined method of quantitative heuristic arithmetic, qualitative analytic hierarchy process and fuzzy comprehensive evaluation (FCE).
Compressive GLRT detector for radar system

This paper investigates the compressive signal detection problem for radar system in the presence of compoundGaussian clutter. An effective random measurement matrix is designed for unknown signal detection problem in clutter-dominated environment. In order to not use reconstruction algorithm which would increase computational burden, we first represent the signal component within the basis of a dictionary, whose elements have a physical interpretation. Furthermore, a compressive GLRT detector is derived. The performance of compressive GLRT detector is analyzed. We also provide its theoretical bounds with experimental results.
Successive Boolean Optimization of Planar Pixel Antennas

We propose a novel heuristic method for optimizing planar pixel antennas which we refer to as successive exhaustive Boolean optimization (SEBO). The key step in SEBO is to cyclically optimize a multivariable binary optimization problem by exhaustively searching a subset of binary variables.  We provide both simulation and experimental results for optimized antennas covering single and dual bands for mobile phone applications. Comparisons with genetic algorithms, binary particle swarm optimization, and angle modulate differential evolution are also provided and these show that SEBO and adaptive SEBO have up to 50% less computational complexity and can satisfy the design objective more consistently. A major advantage of SEBO and adaptive SEBO is that only one parameter needs to be set up for the optimization, while for evolutionary optimization two or more parameters usually need to be set up.
A robust signal subspace estimator

An original estimator of the orthogonal projector onto the signal subspace is proposed. This estimator is derived as the maximum likelihood estimator for a model of sources plus orthogonal outliers, both with varying power (modeled by Compound Gaussians process), embedded in a white Gaussian noise. Validity and interest - in terms of performance and robustness - of this estimator is illustrated through simulation results on a low rank STAP filtering application.
Research on Requirement for High-quality Model of Extreme Programming

Aiming at the core values of Extreme Programming and the barriers to the demand communication process, introducing the two-dimensional model characteristics with satisfactory situation of quality characteristics and customer satisfaction in Kano model to demand access field of software development, it does two-dimensional analysis with the expectation requirements of business customer and software development practices during the process of software development demand. At same time, it explores the demand for high-quality and combines with the original features of Extreme Programming to establish the model of Extreme Programming demand access. As the result, it reduces non-normal demand, improves software quality and user awareness of software products. Consequently, lets the software development enter the virtuous cycle in the requirement phase, and reduce unnecessary demand changes and hidden risks.
Vision-Based Human Action Classification Using Adaptive Boosting Algorithm

Precise recognition of human action is a key enabler for the development of many applications, including autonomous robots for medical diagnosis and surveillance of elderly people in home environment. This paper addresses the human action recognition based on variation in body shape. Specifically, we divide the human body into five partitions that correspond to five partial occupancy areas. For each frame, we calculated area ratios and used them as input data for recognition stage. Here, we consider six classes of activities namely: walking, standing, bending, lying, squatting, and sitting. In this paper, we proposed an efficient human action recognition scheme, which takes advantages of the superior discrimination capacity of adaptive boosting algorithm. We validated the effectiveness of this approach by using experimental data from two publicly available databases fall detection databases from the University of Rzeszow’s and the Universidad de Málaga fall detection data sets. We provided comparisons of the proposed approach with the state-of-the-art classifiers based on the neural network,  $K$ -nearest neighbor, support vector machine, and naïve Bayes and showed that we achieve better results in discriminating human gestures.
Modified backstepping control for time-delay system of SVC

A new modified backstepping approach was suggested for time-delay system of static var compensator (SVC). The transient stability problem is studied for a single machine-infinite bus system. In the recursive design procedure of the feedback control law, the class- k functions are introduced. The method preserves useful nonlinearities, improves the transient response of closed-loop system, and effectively resolves the time-delay problem of response process of static var compensator. Simulation results of MATLAB expatiate in further verification, that the actual sample simulated shows the effectiveness of the proposed method.
Online context-based person re-identification and biometric-based action recognition for service robots

In this paper, we address the problem of person re-identification and action recognition for service robots, which undergoes lack of training dataset for model learning, reduction of feature set discriminative power in changing scenarios, and high complexity of the algorithm computation. An online context-based person re-identification algorithm is proposed, which learns the person model online without pre-collect dataset and adjusts the weight of features according to the context information. An online biometric-based action recognition algorithm is proposed, actions are recognized by simply matching the skeleton vectors extracted from five linkage mechanisms of human body. The proposed algorithms are evaluated on a service robot system, extensive experimental results show that they performs efficiently and effectively in various real-life scenarios.