nils-herrmann/clean_scirepeval huggingface dataset:
An Improved Multivariate Chart Using Partial Least Squares With Continuous Ranked Probability Score

Reliable fault detection systems in industrial processes provide pertinent information for improving the safety and process reliability and reducing manpower costs. Here, we present a flexible and efficient fault detection approach based on the continuous ranked probability score (CRPS) metric to detect faults in multivariate data. This approach merges partial least squares (PLS) models and the CRPS metric to separate normal from abnormal features by simultaneously taking advantage of the feature representation ability of a PLS and the fault detection capacity of a CRPS-based scheme. The proposed approach uses PLS to generate residuals, and then apply the CRPS-based chart to reveal any abnormality. Specifically, two monitoring schemes based on the CRPS measure have been introduced in this paper. The first approach uses the Shewhart scheme to evaluate the CRPS of the response variables residuals from the PLS model. The second approach merges the CRPS into the exponentially weighted moving average monitoring chart. We assess the effectiveness of these approaches by using real and simulated distillation column data. We also compare the detection quality of PLS-based CRPS charts with that of PLS-based  $T^{2}$ ,  $Q$ , multivariate cumulative sum, and multivariate exponentially weighted moving average methods. Results show that the capacity of the proposed scheme can reliably detect faults in multivariate processes.
A Method for Finding Best Channels in Beam-Space Post-Doppler Reduced-Dimension STAP

A method for finding best channels as the auxiliary channels to cancel the interference components in the main channel in reduced-dimension (RD) space-time adaptive processing (STAP) is proposed. Motivated by the cross-spectral metric (CSM) which evaluates the significance of eigenvectors; the significance of each angular-Doppler channel to output signal-to-interference-noise ratio (SINR) is evaluated and taken into consideration for the auxiliary channels selection in RD STAP. The proposed algorithm can achieve the best output SINR performance by selecting the best channels as auxiliary channels when the degrees of freedom (DoFs) of a STAP system are fixed. It is demonstrated that the proposed algorithm allows the dimensionality of the STAP to be reduced much less than the rank of clutter without significant SINR loss. The SINR loss will be less than 3 dB when only one channel is selected as the auxiliary channel under the condition of known clutter covariance matrix. Generally, 3~5 channels are enough even when the clutter covariance matrix is unknown. Consequently, the proposed approach can reduce the requirement of the sample support dramatically.
Vision-based illegal human ladder climbing action recognition in substation

Nowadays, unattended monitoring system has been widely used in substation for its efficiency and efficacy, and it sometimes may cause safety problems for utility workers. In order to ensure workers' safety, in this paper, we focus on the problem of illegal human ladder climbing action recognition in substation using vision-based algorithm. Specifically, we first detect “forbidden” and “allowing” types of signboards on the ladder to localize the ladder and then define the unsafe area. We use HSV-based algorithm and do hough circle detection to recognize “forbidden” signboard. To recognize “allowing” signboard, we propose HOG-based feature extraction algorithm with SVM classifier, and then use color analysis for further detection. After that, we detect and localize human action applying Visual Background Extractor(ViBE) algorithm. Finally, we can recognize illegal human ladder climbing action based on the relative position between human and signboards. The experiments demonstrate the relative high accuracy of our proposed algorithm.
Intelligent automatic manoeuvring mechanism for computer generated forces using predictive multi-step fuzzy inference system

The purpose of this paper is to develop an intelligent automatic maneuvering mechanism for computer generated forces (CGF). The proposed CGF can take actions similar to a human pilot to gain an advantageous status over the enemy target using the intelligent automatic maneuvering mechanism. The mechanism will produce the best multi-step tactics combination (MSTC) for the CGF in an air combat environment. The MSTC is composed of CGF's decision space. In this paper, based on our previous work, we propose a predictive multi-step fuzzy inference system (PMSFIS) as the automatic maneuvering mechanism for CGF, which incorporates and mimics human thinking capability and the maximum capacity of CGF. Before PMSFIS executes the fuzzy inference system (FIS) process, it will generate a list of MSTC, and allows CGF to predict its future posture corresponding to the list of MSTC. This paper assumes that CGF can accurately predict an enemy target's future position, then PMSFIS applies the predicted data to generate the best MSTC. We verify the proposed algorithm with a set of fighter flying data that is used as the enemy target's flying trajectory. The simulation of the proposed algorithm shows that PMSFIS will enable CGF to obtain the best status in an air combat environment and improve the performance of our previous work.
Working clothes detection of substation workers based on the image processing

On account of the substation is a basis and important element of the power system, its maintenance plays a pivotal role in the stable operation of power grid. As the maintainer of the substation, the on-site staffs work long-term in strong electromagnetic field environment. Therefore, it is necessary to wear the working clothes strictly. In order to strengthen the working clothes wearing circumstance supervision, its better to carry out the real-time supervision on the on-site staffs. In this paper, a video-based working clothes wearing circumstance detection method was put forward. Firstly, we extract characteristics by HOG(Histogram of Oriented Gradient) method and the color spatial distribution compactness presented in this paper. Secondly, the SVM(Support Vector Machine) classifier is trained to realize the substation maintainer detection. Finally, we model the electricity working clothes in the HSV(Hue, Saturation, Value) color space and combine the performance characteristics to get the final results. The experimental results demonstrate that this method has a high accuracy in the substation surveillance video.
Fall detection using supervised machine learning algorithms: A comparative study

Fall incidents are considered as the leading cause of disability and even mortality among older adults. To address this problem, fall detection and prevention fields receive a lot of intention over the past years and attracted many researcher efforts. We present in the current study an overall performance comparison between fall detection systems using the most popular machine learning approaches which are: Naïve Bayes, K nearest neighbor, neural network, and support vector machine. The analysis of the classification power associated to these most widely utilized algorithms is conducted on two fall detection databases namely FDD and URFD. Since the performance of the classification algorithm is inherently dependent on the features, we extracted and used the same features for all classifiers. The classification evaluation is conducted using different state of the art statistical measures such as the overall accuracy, the F-measure coefficient, and the area under ROC curve (AUC) value.
An MRF framework for joint registration and segmentation of natural and perfusion images

Registration and segmentation provide complementary information about each other. In this paper we propose a method for the joint registration and segmentation (JRS) of images using Markov random fields (MRFs). The use of MRFs allows us to formulate the problem as one of labeling and apply fast discrete optimization techniques like graph cuts. Graph cuts is able to overcome the limitations of previously used active contour frameworks namely, large number of iterations, risk of being trapped in local minima, and sensitivity to initialization. The labels in the MRF formulation indicate joint occurrence of displacement vectors and segmentation class and the energy formulation is able to capture their mutual dependency. Experiments on real patient perfusion data and natural images show that JRS gives better performance than conventional registration and segmentation methods.
Analysis of the EPC period deciding model based on the Game Theory

This paper establishes the decision-making model of the energy saving companypsilas (ESCO) operation period based on the game theory. At first, the whole process of energy performance contracting (EPC) is divided into three stages. Then, based on the game theory, the impact of ESCO operation period on the benefits of both ESCO and its client is analyzed. Finally, the decision-making model of the ESCO operation period is established. The relation of the ESCO operation period, which has been agreed upon by both the ESCO and its client, is positive to the development level of the energy efficiency service industry and the ESCO technique. And, its relation is negative to the client energy cost. So, the transaction cost caused by negotiation and consultation must be reduced. Once these three factors are considered comprehensively, the ESCO can ensure maximum profits by (1) improving advanced technique and maturity and ensuring core technology competence; and (2) choosing the client with potential for energy efficiency.
PSO-based estimation for Gaussian blur in blind image deconvolution problem

This study focuses on Gaussian blur estimation for blind image deconvolution (BID) problem. In BID problem, it only uses blurred image and less information of point spread function (PSF) to restore the received the blurred image. Due to restore the received image, the first step is to identify the proper PSF model. The received image does not uniquely define the PSF. Nevertheless these are many applications where the received image have been blurred either by an unknown or a partially know PSF. Therefore, this paper choose Gaussian blur image for further research, which utilized the particle swarm optimization algorithm to search for the unknown PSF. The objective function for searching the parameters of PSF is based on edge detection and image morphology. It can identify the parameters of PSF exactly. Finally, the feasibility and validity of proposed algorithm are demonstrated by several simulations.
Harmonics retrieval based on quaternion matrix

This paper presented a novel method to estimate harmonicspsila parameters with quaternion. First, a kind of quaternion model of harmonic was established. Then, its correlation matrix, a quaternion correlation matrix (QCM), was constructed. Finally, this QCM was decomposed, where quaternion noise subspace was used to estimate harmonicpsilas parameters. Simulations illustrated this special idea and showed that frequency resolution of this method was better than that of classical MUSIC method.
Application of ETSIAT to the toxicity prediction of aliphatic alcohols

ETSIAT was employed in the quantitative structure-activity relationship (QSAR) modeling on the aliphatic alcohol toxicities to the Tetrahymena, tomato, spider, and bacterial luciferases et al‥ The QSAR models were established by partial least squares and further validated by both internal and external validations. The results showed that ETSIAT can characterize the structural information relevant to aliphatic alcohol toxicity very well and the resulting QSAR models were robust and showed high predictive capabilities. Based on the PLS analysis of the QSAR models, it can be inferred that hydrophobicity and steric hindrance effects were key factors influencing the toxicities of the aliphatic alcohols, and there may be different toxicity mechanisms between long-chain and short-chain aliphatic alcohols.
A typical defect in the Bridgman-grown LBO crystals

A typical macro-defect, a veil-like layer in the Bridgman-grown <110> LBO crystals, was discovered. The veil-like layer seems to be a semi-transparent veil which covers the whole or partial cross section in the growth direction. The mechanism for formation of the veil-like layer defect has been explored by determining morphology and distribution of the defect and analyzing the relationship between the crystal growth conditions and the defect. The veil-like layer defect is microcrack in which there is decomposition on surface of the crack or deposition of vapor of LBO melt in as-grown LBO crystals.
Finite Element Analysis for a Two-Layered Spherical High-Pressure Vessel

Stress analysis is of importance for security assessment of pressure vessels in the design and manufacture processes. This paper presents a stress analysis for a two-layered spherical high-pressure vessel of special steel. Firstly, the finite element model was built by the software ANSYS. In order to get an acceptable analysis precision, the proper mesh density distribution was obtained by the adaptive meshing technique. Then the stress distribution analysis was performed and the potential weak zones and the explosion pressure were found. Furthermore, several redesign schemes were analyzed. The results provide a good suggestion for its redesign.
An improved genetic algorithm based on fuzzy inference theory and its application in distribution network fault location

An improved genetic algorithm based on fuzzy inference theory is proposed in this paper, which is applied in faulty location of distribution network. This algorithm improves the problem of faulty operation caused by the distorted signal transmission in traditional faulty location method and the problem of premature convergence and slow convergence speed of standard genetic algorithm. Firstly, a mathematical model for fault location of distribution network is established by the switching function which contains multivariate equality constraints. On this basis, the improved genetic algorithm adopts optimal individual reserve strategy in selection operation and combines adaptive strategy with fuzzy inference theory to calculate cross-over operator and mutation operator, which improves the ability of search to avoid premature convergence. Finally, simulated annealing algorithm is integrated in the algorithm to accelerate the convergence speed. The simulation examples proposed in the paper verify the accuracy and effectiveness of the improved genetic algorithm applied in fault location of distribution network.
PLS-based memory control scheme for enhanced process monitoring

Fault detection is important for safe operation of various modern engineering systems. Partial least square (PLS) has been widely used in monitoring highly correlated process variables. Conventional PLS-based methods, nevertheless, often fail to detect incipient faults. In this paper, we develop new PLS-based monitoring chart, combining PLS with multivariate memory control chart, the multivariate exponentially weighted moving average (MEWMA) monitoring chart. The MEWMA are sensitive to incipient faults in the process mean, which significantly improves the performance of PLS methods and widen their applicability in practice. Using simulated distillation column data, we demonstrate that the proposed PLS-based MEWMA control chart is more effective in detecting incipient fault in the mean of the multivariate process variables, and outperform the conventional PLS-based monitoring charts.
R-wave Detection Using A Single-chip Microcomputer

This paper describes the hardware/software design of a system that detects R waves of the electrocardiogram. The system is based on a Motorola 68HC811 single-chip microcomputer, and contains only three discrete components. Under this hardware framework the R-wave detection algorithm cannot include any floating-point operation. Two algorithms have been implemented: one with the pacerspike rejection, the other without the pacer-spike rejection. The results of R-wave detection using the two algorithms are shown. The system presented here provides an effective, flexible, and low-cost solution to real-time R-wave detection.
Notice of RetractionStudy on adsorption mechanism of ammonium ion by aged refuse

To further understand the nitrogen removal mechanism in leachate treatment using aged-refuse-based bioreactor, 10 year aged refuse was used as adsorbent, ammonium chloride as adsorbate. The adsorption isotherms and thermodynamics, and adsorption mechanism were studied. The results show that: (1) The isothermal adsorption process of NH4+ on aged refuse can be fitted by Freundlich equations with a high correlation coefficient (0.9873 ~ 0.9907). (2) The adsorption process of NH4+ on aged refuse is spontaneous and exothermic. Temperature is conducive to the spontaneous adsorption but adsorption decreased. (3) In the absorption of ammonium by aged refuse, the main force is the hydrogen bonding and dipole bond for physical adsorption.
Subpixel registration in renal perfusion MR image sequence

We propose a subpixel registration algorithm to deal with the motion induced by breathing for renal perfusion MR image sequences. Our approach minimizes an energy functional that integrates a motion model and temporal smoothness constraints. We then present a multistage level set method that segments different kidney structures in the registered MR image sequence. Tests with a rat kidney transplantation study show that the algorithm successfully compensates for the breathing motion and extracts the kidneys, cortex, medulla, and pelvis.
Block majorization-minimization algorithms for low-rank clutter subspace estimation

This paper addresses the problem of the clutter subspace projector estimation in the context of a disturbance composed of a low rank heterogeneous (Compound Gaussian) clutter and white Gaussian noise. We derive two algorithms based on the block majorization-minimization framework to reach the maximum likelihood estimator of the considered model. These algorithms are shown to be computationally faster than the state of the art, with guaranteed convergence. Finally, the performance of the related estimators is illustrated in terms of estimation accuracy and computation speed.
Electronic "How Things Work" Articles: Two Early Prototypes

The electronic encyclopedia exploratorium (E/sup 3/) is a vision of a future computer system-an electronic book describing how thing work. Typical articles in E/sup 3/ will describe such mechanisms as compression refrigerators, engines, telescopes, and mechanical linkages. Each article will provide simulations, three-dimensional animated graphics that the user can manipulate, laboratory areas that allow a user to modify the device or experiment with related artifacts, and a facility for asking questions and receiving customized, computer-generated English-language explanations. Some of the foundational technology is discussed, focusing on topics in artificial intelligence, graphics, and user interfaces. The initial prototype system and the technical lessons learned from it, as well as the second prototype currently under construction, are described.
Snow disaster damage to urban building and prevention strategies in Chill Region

This paper analyzes snow disaster damage to city building to outline that the safety and habitability should be fully considered during architectural creation in the chill region circumstance. Then the suitable prevention strategies for snow disaster damage in designing the safe and livable buildings in cold region is proposed, followed by detailed description in the aspects of site selection and layout, rational building construction and nodes setting, energy saving and heat preservation measures, windproof and skidproof outdoor environment. It is pointed that the problem of snow disaster damage to urban building in chill region is concerned with various aspects of architectural creation. All these aspects need general consideration and thorough thinking with systemic method in analyzing and problems solving, so that building can be created which adapts to the snow and ice climate in frigid regions.
Adaptive passivity-based control with sliding mode for the turbine steam valve

The problem of transient stability for a single machine infinite bus system with the turbine steam valve control is addressed via adaptive feedback passivation approach. In the system, the damping coefficients are measured inaccurately and the transmission line reactance also contains uncertainty. The system is first converted into a new system with a new auxiliary control. An appropriate update law is designed to make the new transformed system passive. Then, the sliding mode control (the auxiliary control) is designed so that the trajectory of the passive system is maintained on the sliding hyperplane and eventually goes to an equilibrium point. Simulation results for the SIMB benchmark case demonstrate the effectiveness of the proposed design.
Decision of Cirrhosis Using Liver's Ultrasonic Images

Feature extraction techniques in the ultrasonic images of a liver were studied firstly. As an initial result, total 25 parameters relating to cirrhosis were extracted. They were obtained from the motion curve of the liver in an M-mode image, and from the texture using a B-mode image. Then the efficiency of every parameter was analyzed, and with the use of a feature fusion method a set of 20 useful features was picked out. With these chosen features, a noninvasive automatic decision system for cirrhosis was constructed based on a Fisher linear decision criterion. The clinical application for 43 cases showed that this quantitative system was effective in the diagnosis of cirrhosis
Microprocessor Based Control of Electromechanical Devices by Using Electromyogram: A "Cricket Car" Model

The Cricket Car is a remote control car that uses electromyographic (EMG) signals to drive the car. Electrodes are inserted into the legs of the common field cricket and the myoelectric signal, also known as a motor action signal, is amplified. This amplified signal is then acquired by the PIC16F88 processor. Using threshold detection and conditional logic algorithms, the PIC processor sends command signals to the circuit of a remote control car. Features such as object/collision detection, cricket stimulus, and additional signal processing algorithms have been studied and developed. The project has been incorporated into a neuroengineering course. Continuation of this project by undergraduate and graduate students will serve as the impetus for further improvements.
A rapid evaluation method for degradation activation energy of n-GaAs ohmic contacts with and without TiN diffusion barrier layers

A rapid evaluation method, the temperature ramp method, for GaAs MESFET ohmic contacts is proposed. By use of this method, activation energy for ohmic contact degradation can be obtained using less time and a smaller number of samples than traditional methods, and the results are in agreement with those obtained by traditional methods. In accordance with some drawbacks of traditional AuGeNi-Au ohmic contacts, a new ohmic contacts system with TiN diffusion barrier layer is proposed. Experimental results show that the reliability of ohmic contacts with TiN is greatly superior to that of traditional AuGeNi-Au ohmic contacts.
PKN-a strong piezoelectric crystal

Dielectric, piezoelectric and electromechanical coupling properties of lead potassium niobate Pb/sub 2/KNb/sub 5/O/sub 15/ (PKN) crystals are reviewed in this paper. PKN has very strong coupling coefficients for bulk wave and surface acoustic wave, k 0.6-0.7 and k/sup 2/>10% in comparison with several piezoelectric crystals such as LN, LT, /spl alpha/-SiO/sub 2/, LBO, LGS, LiIO/sub 3/ and BNN. Transparent, brownish twin-free PKN crystals of 1" diameter by 2" length have been grown by the modified Bridgman method by us for the first time under a furnace temperature 1380-1400/spl deg/C and growth rate <0.5 mm/hr, so that research into the application of PKN crystals has become possible.