nils-herrmann/clean_scirepeval huggingface dataset:
Research of driver fatigue detection system based on ADSP-BF548

To avoid traffic accidents caused by driver's fatigue, this paper designs a fatigue detection system based on ADSP-BF548 and relative algorithm. It captures driver's images in real time by on-board camera and localizes driver's eye position via frame-difference projection, edge extracting, and template matching such kind of methods. At last, makes a warning in time according to the eye states in a period of time. The experiment shows this driver fatigue detection system based on ADSP-BF548 is of high accuracy.
Effective and stable feature selection method based on filter for gene signature identification in paired microarray data

A huge amount of microarray datasets are produced with big number of genes and small samples. Feature selection methods have become a very sharp tool to select the gene signatures from the whole gene set. In recent years, researchers are concerned much about the datasets containing samples of cancer as well as corresponding control tissues. However, few feature selection methods consider the effect of paired samples. In this article, we propose a new feature selection method for paired microarray datasets based on the original paired t-test approach. We apply on the paired datasets across six common cancer types. Through comparison with some widely used methods on the performance of prediction power, stability of gene lists and functional stability, our method shows excellent performance. The proposed method has good effectiveness, stability and consistency, which enables the method to be applicative to feature selection for paired microarray expression data analysis.
Research on the service recovery system of Chinese real estate industry

Real estate industry as the third industry of national economy, it plays the important role strengthening service management, decreasing the possibility of service failure and making the service recovery work better. It can guarantee the continuity of real estate industry offering service, circulation of the supply and demand chain and stability of profit chain. On the basis of qualitative analysis of the service recovery system (SRS), the study takes Chinese real estate industry as the design object, analyzes the affecting service failure factors from the customer view, realizes the anticipative aim according to the input-output principle and designs the SRS in term of the time series. Through the questionnaire of real estate enterprise executing the SRS, the results show that the solved problem ratio is increasing and time space shorten. And the different culture background of different enterprise, the attitude of enterprise employee and whether taking the immediate measures are the subjective and uncertain factors. These are the main factors affecting the overall system execution.
Automatic Vulnerability Locating in Binary Patches

This paper proposes an approach to locate the patched vulnerability by analyzing the differences between two versions of an executable file. The approach comprises two parts: finding the differences and auditing the differences. To find the differences, a heuristically method is presented to compute an isomorphism between two callgraphs, based on the definitions of similarity between functions, and the similarity between graphs. The approach of auditing differences is also discussed in this paper. To show the advantages of our approach, we implemented a system called NBDS and apply it in four real-world patches. Experiment results show that our approach is able to locate patched vulnerability with high accuracy and performance.
Light-guided environmental control device

The application of the light-guided environmental control device will greatly increase the quality of life of certain persons with disabilities. This hands-free mechanism will allow the user to perform many daily tasks without the need of an aid. It is an environmental control and a wheelchair control that is driven by a light emitting head switch. One of the main foci of the project is to remove many of the cumbersome control switches being implemented today, and replacing them with one compact model. This product is to perform all operations currently performed by head arrays and switches, as well as standard joysticks. It is being designed to be used primarily by those people without the use of their limbs, especially those looking to gain a great deal of independence.
The research situation and prospect analysis of meta-search engines

Meta-search engines are put forward to solve the problem that independent search engines have far too low Internet information coverage rate. Although there are many research literatures about meta-search engines, never a comprehensive analysis research literature about the current situation and market situation of meta-search engines is given. This paper tries to analyze meta-search engines from two aspects: the academic research aspect and the market aspect. In the academic research aspect, the paper mainly focuses on the basic structure and advantages of meta-search engines, as well as researches at home and abroad on the architecture, personality processing mechanism, scheduling mechanism, and merging mechanism of search results of meta-search engines. In the market aspect, the present market situations at home and abroad of meta-search engines are introduced. The ones which have higher market shares are also presented. Finally, problems and solutions of meta-search engines are given from different angles and the development prospects of meta-search engines are also analyzed.
Waveguide-to-Microstrip Antipodal Finline Transition at W Band

This paper researched the waveguide-to-microstrip antipodal finline transition at W band, analyzed and simulated antipodal finline transition of Cosine-squared taper function curve and flexible spline curve, designed and fabricated an spline curve antipodal finline transition of back-to-back structure. The measured results show that the insertion loss is less than 1.3dB, and the return loss is less than -13dB in whole W-band, the insertion loss of a single transition is less than 1.0dB, and the return loss is less than -20dB in 90GHz~ 99GHz, achieve good performance. It can provide low transitions between the wave guide and micro strip line. It is loss easy designing and machining, it achieve good performance in a wide band range. It is useful to design circuit in W-band.
A statistical-based approach for fault detection and diagnosis in a photovoltaic system

This paper reports a development of a statistical approach for fault detection and diagnosis in a PV system. Specifically, the overarching goal of this work is to early detect and identify faults on the DC side of a PV system (e.g., short-circuit faults; open-circuit faults; and partial shading faults). Towards this end, we apply exponentially-weighted moving average (EWMA) control chart on the residuals obtained from the one-diode model. Such a choice is motivated by the greater sensitivity of EWMA chart to incipient faults and its low-computational cost making it easy to implement in real time. Practical data from a 3.2 KWp photovoltaic plant located within an Algerian research center is used to validate the proposed approach. Results show clearly the efficiency of the developed method in monitoring PV system status.
The Identification of Human Cryptic Exons Based on SVM

Alternative splicing is the main mechanism expanding proteome diversity. Cryptic exon is an important alternative splicing form that is different from skipped exon in statistical characters. We introduce a process to identify the human cryptic exons in candidate ones. This method contains two steps performed by two classifiers based on the support vector machine (SVM). The first classifier distinguishes authentic exons from pseudo exons; the second classifier distinguishes cryptic exons from constitutive and skipped exons. It can achieve the accuracy of 94.25% and 69.75% in the two steps, respectively. This method uses no expressed sequence tags (ESTs) or conservation information, so it can be used more widely and easily. The performances are higher than an existing method predicting splice sites of cryptic exons.
Acoustic emission sound source localization for crack in the pipeline

This paper investigates the use of acoustic emission (AE) for simulated crack in a stainless steel pipeline. An approach to liner sound source localization in pipeline using two or more acoustic sensors is described, and rules to define timing parameters - peak definition time (PDT), Hit definition time (HDT) and Hit lockout time (HLT) of acoustic emission signal is studied in order to improve the sound localization accuracy. Experiments were conducted on a stainless steel pipeline with no special features, such as branch, weld, and flange on the experimental part. The detail process of Nielsen-Hsu Pencil Lead Break method which is used to simulate the crack, and main considerations in acoustic emission transducer selection are also introduced in this paper.
Blind Image Deconvolution via Particle Swarm Optimization with Entropy Evaluation

This study addresses a blind image deconvolution which uses only blurred image and tiny point spread function (PSF) information to restore the original image. In order to mitigate the problem trapping into a local solution in conventional algorithms, the evolutionary learning is reasonably to apply to this task. In this paper, particle swarm optimization (PSO) is therefore utilized to seek the unknown PSF. The objective function is designed according to entropy theorem whose evaluation can distinguish characteristics between a blurred image and a clear image. Finally, the feasibility and validity of proposed algorithm are demonstrated by several simulations; further, its performance is compared with that of another state of the art evolutionary algorithm.
A Hill-Type Submaximally-Activated Musculotendon Model and Its Simulation

Hill-type models are ubiquitous in biomechanical simulations because of their computational simplicity and efficiency. But these models are designed to describe the maximally activated muscles and muscle properties are linearly scaled when they are applied to sub maximally activated conditions. This scaling approach should be based on the independence of muscle activation and force-length properties, which has not been proven yet. Actually, muscles in vivo are unlikely to be often maximally activated during daily life. Therefore, effective methods should be taken to modify the existing Hill-type model to insure the accuracy of their applications. This paper analyzed the sub maximal activation conditions, developed a sub maximally-activated musculotendon model on the basis of Millard damped equilibrium model and implemented the benchmark experiments to verify effectiveness of the modified model.
Optimization of Advertising Budget Allocation Over Time Based on LS-SVMR and DE

The advertising budget allocation problem for financial service is dealt with based on statistical learning and evolutionary computation in this paper. Taking the carry-over effects of the advertising into account, the least squares support vector machine regression (LS-SVMR) is used to construct the response model. A comparison between the proposed response model and traditional regression method based market response models is implemented. The results show the effectiveness and validity of the former model. Taking the budgets allocated to every month in the planning horizon as decision variables, the budget allocation optimization model is built and an improved differential evolution algorithm is used to find the optimal solutions. Finally, the proposed budget allocation method is illustrated by a practical problem.
Gesture recognition with two 3-axis accelerometers

This paper is talking about using two digital accelerometers to recognize the gestures composed of thumb and forefinger. Two accelerometers were placed by parallel with y-axis and z-axis of accelerometers toward opposite direction. Then add up two accelerations of the same axis from different accelerometer to eliminate the anti-gravitational acceleration. Integrate the pure acceleration to find the velocity and uses the curve of velocity to recognize the gestures.
RETEX (RElay Testing EXpert): an expert system for analysis of relay testing data

A new expert system application to power system protective relay evaluation testing, a crucial but time-consuming engineering task, is presented. An expert system called RETEX (relay testing expert) has been developed as a computer aid for analysis of relay testing data. A knowledge base for relay testing data analysis has been developed. A relay logic model is used to determine the expected relay operation for simulated faults. Hierarchical test reports and comparison reports can be automatically generated by RETEX, which is designed with basic language processing capabilities. The generality necessary for handling various relay models is provided by a description file approach. The expert system is implemented in a rule-based and object-oriented architecture with the expert system development tool NEXPERT Object. The feasibility of the prototype has been demonstrated with Bonneville Power Administration (BPA) relay testing data.
Biologically Adaptive Artificial Bee Colony for Numerical Optimization

The artificial bee colony (ABC) algorithm is a well-known algorithm for solving numerical optimal problems. In this paper, a biologically adaptive artificial bee colony (BAABC) algorithm is proposed. In BAABC, the initialization of population is performed by the Halton Sequence so the population is generated in potential solution space. Besides, the size of population is varying according to status of solution searching. If BAABC finds a good solution, the size of population is increased for enhancing solution searching and vice versa. To examine the proposed method, fifteen evaluated functions are adopted in experiments. The result shows that BAABC performs better than related ABC methods on most of the test function.
A Sequential Algorithm for Biological Event Detection Using Statistical Nonstationarity

High dimension complex dynamical systems, such as those found in physiological processes, are often accompanied by nonstationarity. In many cases, the nonstationarity is caused by a physiologically significant event such as the prelude to ventricular fibrillation in cardiac arrest or the change of stasis by introducing pharmaceuticals. A need exists to be able to detect and monitor this change. Most conventional attempts at addressing this problem involve segmenting the time series and evaluating the statistics of the segments. The difficulty with this approach is that the nature of the nonstationarity can be transient, such that it is bounded by two, or more, regions of stationarity. Further, vacillation between stationary and nonstationary segments may continue for a significant portion of the time series. This paper will discuss the underlying statistical justification for asserting stationarity and the use of segmentation time series analysis techniques.
Impulsive Discharges in Water: Acoustic and Hydrodynamic Parameters

Underwater spark discharges are used in multiple practical applications including plasma closing switches, water treatment, plasma channel drilling and mineral processing, waste recycling, treatment of metals, and medical lithotripsy. Spark discharges in water have been studied for several decades; however, despite significant research efforts and progress in this area, further investigation into the efficiency of plasma acoustic sources and their optimization is required in order to expand their practical application. This paper is aimed at investigation of the electrical and hydrodynamic parameters of underwater plasma-generated cavities, including plasma resistance, energy delivered into the plasma cavity, period of cavity oscillations, and characteristics of pressure impulses. Different energy levels, breakdown voltages, and gap distances were used in the present study to allow systematic analysis of these electrical and hydrodynamic parameters. Empirical scaling relations that link the maximum acoustic pressure and the period of cavity oscillations with the energization parameters and the resistance of plasma have been obtained. These empirical functions can be used for optimization of the plasma acoustic sources and for tailoring their parameters for specific practical applications.
Beamforming and power control for multirate CDMA systems with per-path-per-weight beamforming scheme

Joint beamforming and power control is a powerful means for suppressing interference and increasing capacity in direct-sequence code-division multiple-access (DS-CDMA) systems. In micro or picocell environment, the angular separation between each path of the same user is relatively large, thus per-user-per-weight (PUPW) beamforming scheme suffers from strong inter-finger interference (IFI). In order to suppress both multiple-access interference (MAI) and IFI effectively. In this paper, we consider the problem of joint beamforming and power control when per-path-per-weight (PPPW) beamformer is employed in a multirate DS-CDMA system with multicode scheme. The optimal solution of the beamforming weights and transmitted powers is obtained by taken into account the data information of all users and minimizing the power radiated by the mobile terminals while maintaining the SIR requirements. Computer simulations show that for 5 user environment with SIR threshold of 6.8 dB, PPPW scheme saves about 7 dB total transmission power than PUPW scheme when the angular spread is 20 degree.
On the chaotic nature of biological signals: linear and nonlinear data analysis of neuronal action potentials

Linear time invariant system analysis represents the educational core of the contemporary electrical engineer. While many of the analytical tools that are employed to perform linear analysis, i.e., mean, standard deviation, Fourier transforms, and the like, establish reliable and effective measures of prediction with regard to linear signals, biological signals such as those generated by the central nervous system, require additional considerations. Since the very nature of analysis is to make sense of what is and to apply it to what will be, the concept of predictability is of paramount concern. It has been established that various biological signals, including those used in neuronal communication, are in fact chaotic, making predictability a much more complex issue. A method of decomposing nonstationary and chaotic signals into stationary signals is proposed. By separating nonstationary signals into smaller time intervals, the segmented signal can be evaluated as a stationary signal. As a result, the stationary signal can be studied using linear and nonlinear analysis methodology, since observed chaotic parameters could otherwise be attributed to the nonstationarity. Using the neuronal signals from the pond snail Lynmaea stagnalis as a biological signal source, this research identifies and examines the relationships between linear and nonlinear systems.
Research on the problem space and curriculum system of discipline “information service”

Along with service based economy has been the domination all over the world, it is necessary for universities to establish a corresponding discipline and specialty on service science to train college graduates with service-related skills and knowledge to facilitate the development of service economy in China. Service Science or Service Science, Management and Engineering (SSME) is a growing multi-disciplinary research and academic effort that integrates aspects of established fields like computer science, operations research, engineering, management sciences, business strategy, social and cognitive sciences, and legal sciences. This paper briefly introduces the strategic vision on the development of discipline named “Information Service” in College of Information, Beijing Union University, including the problem space and curriculum system.
Application of a force-clamp system to study auxotonic muscle contractions

The investigation of auxotonic muscle contractions is dependent on the understanding of both isometric (constant length) and isotonic (constant force) muscle contractions. An auxotonic contraction occurs when neither the force nor the length remain constant; essentially a combination of the variable isometric and isotonic states of contraction. In this study, previous research  using a force-clamp system was improved upon to yield more accurate results. Circuitry along with instrumentation was redesigned and programmed to simulate a realistic muscular contraction waveform and later used in combination with the Aurora Dual Mode Lever System (ADMLS). The system uses feedback controls to regulate force and length in real-time according to user-defined specifications. The heart of a quahog (hard shell clam) was used for the experimental component of this study.
The Risk Assessment of E-commerce Based on BP Neural Network

In order to effectively evaluate the risk of e-commerce, this paper applies BP neural network to establish risk assessment model, and then use the MATLAB neural network toolbox to process the learning, training and simulation of the model, at last the model is applied to the practice to make the sensitivity analysis of e-commerce risk factor. The result shows that: the method provides an effective method for e-commerce risk assessment, and has broad application prospects.
Structure and Magnetoelasticity of R(Zn$_1 - rm x$Fe$_rm x$) ($hboxR=hboxTb$, Dy) Polycrystalline Alloys

The structure, magnetization, and magnetostriction of R(Zn<sub>1-x </sub>Fe<sub>x</sub>)(R=Tb, Dy) polycrystalline alloys were investigated by X-ray diffraction, vibrating sample magnetometry, and standard strain gauge techniques. It was found that TbZn<sub>1-x</sub>Fe<sub>x</sub> consists of a single Tb(Zn,Fe) phase with the cubic CsCl-type structure when x les 0.2. DyZn<sub>1-x</sub>Fe<sub>x</sub> was found to consist of nearly a single Dy(Zn,Fe) phase in the range 0 les x les 0.15. A second Dy-rich phase appears when x > 0.15. The Curie temperature of the RZn<sub>1-x</sub>Fe<sub>x</sub> alloys increases with increasing Fe content when x les 0.2. When Fe is substituted for Zn in RZn compounds, the magnetization increases with increasing Fe content. The magnetostriction of Tb(Zn<sub>1-x</sub>Fe<sub>x</sub>) alloys increases with increasing Fe content when x les 0.1, and that of Dy(Zn<sub>1-x </sub>Fe<sub>x</sub>) alloys increases in the composition range 0 les x les 0.05
Automated algorithm to delineate Z-bands in electron microscopic images of the human skeletal muscle

The effects of exercise, nutrition, and aging on the development of human skeletal muscles can be observed from the morphological changes of the Z-band under the electron microscope. Quantification of the Z-band damage has provided useful information to exercise physiology research but is usually a labor-intensive process. In this study, an automated image-processing algorithm has been developed to delineate the Z-band with a given start point. The algorithm detects the borders of the Z-band in an incremental fashion along the long axis. At each step of the iteration local border points are detected along radial directions and the centerline is extended toward both ends of the Z-band. The process iterates itself until a stopping criterion is met. The algorithm has been coded in C++ and used in our laboratory for exercise science research. The software has significantly reduced the processing time and provided reliable high-quality data for the study of Z-band damage.