nils-herrmann/clean_scirepeval huggingface dataset:
Investigating Duration Effects of Emotional Speech Stimuli in a Tonal Language by Using Event-Related Potentials

Studying event-related potentials (ERPs) is considered as an effective method for investigating cerebral mechanisms of processing emotional speech. It has been shown that the amplitudes of ERP components in the cognitive processing of emotional speech are modulated by acoustic characteristics, such as valence and arousal. However, whether the duration of emotional speech stimuli impacts emotion-related cognitive processing remains unclear. To better understand the effect of emotional speech stimulus duration on emotion-related cognitive processing, we explored whether emotional speech ERPs were influenced by the duration of stimuli presented. Specifically, this paper focused on the ERP investigation of different durations (short: 0.50–1.00 s; medium: 1.50–2.00 s; and long: 2.50–3.00 s) of Chinese emotional speech stimuli. Chinese is a typical tonal language, and the stimuli were excerpted from radio plays in order to make emotions more obvious and easier to distinguish. We investigated the three different stages of the emotional speech processing: sensory processing, salience detection, and cognition. During the experiment, participants passively listened to emotional utterances matched for semantics and prosody with four emotions (sadness, anger, happiness, and surprise). Our results showed significant differences in the amplitudes of ERP components for different emotions during short-duration emotional speech stimuli. These findings suggest that shorter duration emotional speech stimuli may be more effective for separating the ERP components representing different emotions (N100, P200, and N300).
Dynamic Finite Element Analysis on Surgical Ventricular Restoration

A dynamic finite element model that relates a regional myocardial impairment to its effects on overall hemodynamics was used to study the hemodynamic effects of surgical ventricular restoration (SVR). A three-dimensional (3D) finite element model of the left ventricle (LV) was integrated with an electrical analog model of the circulatory system. The model was implemented in customized C++ software with user interface for circulatory parameters and LV geometry. The hemodynamic effects of SVR were studied by progressively reducing the infarct size of a LV with a 40% infarction. A total of nine preoperative left ventricular conditions combining dilation and hypertrophy were studied. The model study suggests that an optimal operative point exists for achieving maximal hemodynamic benefits of the SVR. The optimal amount of infarct removal depends on the preoperative conditions, whereas the LV end-diastolic volume is a more important factor than the LV mass.
Experiential learning in an undergraduate biomeasurement course: Heart-rate meter

This paper describes a hands-on project for an undergraduate biomeasurement course that includes an amplifier for the electrocardiogram (ECG) and an embedded system to measure the heart rate on a beat-by-beat basis. The embedded system uses a PIC18F452 microprocessor and can output text via a LCD character display. The ECG amplifier is constructed with a printed circuit board already designed and provided to the students. The students learn the design of an embedded instrument by building the hardware and programming the device with the C++ language. The project effectively integrates several engineering skills including circuits, microprocessors, programming, and signal processing into a one-semester course. Therefore it is an efficient way to provide biomedical engineering students with skills to design embedded measurement systems.
A Hybrid Forecasting Method for Wind Power Ramp Based on Orthogonal Test and Support Vector Machine (OT-SVM)

In an electric power system with a high penetration of wind power, incoming power ramps pose a serious threat to the power system. To adopt suitable response strategies for wind power ramps, it is important to predict them accurately and in a timely manner. Since power ramps are caused by various factors, their occurrence has irregular characteristics and vary by location, bringing great difficulty in forecasting. To solve this problem, a hybrid forecasting model termed as orthogonal test and support vector machine (OT-SVM) was developed in this paper, which combines an orthogonal test (OT) with a support vector machine (SVM). A novel factor analysis method was established based on the theory of the OT, and applied to determine the optimal inputs of a SVM. The effectiveness of OT-SVM was tested with three wind farms in China, while comparing the results with other related methods. The results show that the proposed OT-SVM has the highest accuracy covering different input numbers and time resolutions. In addition, a novel evaluation index mean accuracy index was proposed, considering both the missed ramps and false ramps, which can be used as a supplementary index for critical success index.
State estimation of complex dynamical networks with channel noise and time-varying delay

The state estimation of complex dynamical networks with time delay coupling under noisy transmission channel is studied in this paper. In order to suppress the effect introduced by the noise and time-varying delay, the state estimation controllers are designed by using integral control approach. A sufficient condition for state estimation is derived by using Lyapunov stability theory and H- Hcontrol technique. Finally, we take the scale-free network as the network topology and the Lorenz chaotic system as the node dynamics, to do some simulations. The simulation results verify the effectiveness of the proposed method.
A Novel Miniature Absolute Metal Rotary Encoder Based on Single-track Periodic Gray Code

In order to improve the resolution and enhance the impact resistance and vibration resistance of encoders, a novel absolute metal rotary encoder based on Single-track Periodic Gray Code is presented. The configuration and working principle of the encoder is introduced, and then the metal code disc which can realize full scale absolute encoding on one single track and its corresponding metal slit disc are proposed. Finally, the data acquisition and processing system based on FPGA of encoder is presented. The resolution of the encoder can reach 5.27" through electronic subdivision and calibration between the precision code and the coarse code with its volume only Φ 48×40mm. The encoder has some advantages such as small volume, low cost, high resolution and strong impact resistance.
Bifurcation of periodic Solution for Rosenzweig-Macarthur system with time delay

This By using some analysis techniques and the bifurcation theory, this paper studies Hopf bifurcation problems of a kind of Rosenzweig-Macarthur system with time delay. A condition is obtained for the existence of a Hopf bifurcation of periodic Solution of the following Rosenzweig-Macarthur system with time delay: equations where all parameters R , c , d , e , α , β are positive constants.
Analysis and Improvement of a Proxy Blind Multi-signature Scheme without a Secure Channel

Proxy blind signature is a cryptographic research hotspot, and has been applied in many occasions. Many proxy blind signature schemes were proposed, however, all the schemes rely on secure channels to transmit proxy secret key. Therefore, Lu, Cao and Zhou proposed a new proxy blind multi-signature scheme recently, which does not need a secure channel and is provably secure under the random oracle model. In this letter, however, we show that their scheme is not secure against the original signer's forgery attack. Moreover, we give four improved proxy key generation algorithms to counter this attack.
A demand side management model based on advanced metering infrastructure

The development of smart grid leads demand side management more opportunity and challenge, the advanced metering infrastructure (AMI) will make more DSM projects possible. A demand side management model based on AMI for smart grid is proposed; the model consists of a metering infrastructure, two-way communication network and application software works at the user side and control side respectively. The subsystems and the interaction among them are described. In this model, the terminal consumer distributed energy resource was considered. The model will enhance the interaction of consumers to power supply side, provide an important basis to the smart distribution system load management and adjustment, and distribution markets.
Adaptation of a piano tuning device for the visually impaired

Piano tuners of all skill levels use electronic tuning devices to assist them in their tuning. These devices provide visual feedback to the user about the state of the note being tuned. A tactile output system was created, enabling the visually impaired piano tuner to be able to use an electronic tuning device. Signals from the tuning device are used to drive vibrating motors in an armband worn by the user.
The effect of dipole scattering on intrinsic breakdown strength of polymers

The introduction of dipoles into a polymer can enhance dipole-induced scattering which tends to "cool" hot electrons and thereby inhibits runaway of hot electrons. A theoretical analysis of electron scattering by dipoles and phonons is presented which provides the basis for explaining temperature dependence of breakdown field on the basis of the dominant scattering process as a function of temperature. By performing electron mobility calculation in non-polar and polar polymers, a quantitative correlation between chemical composition and intrinsic breakdown strength can be established. Calculation of dipole scattering limited electron mobility can be used to assess the effect of dipole scattering on the intrinsic breakdown field of polymers.
Notice of Retraction Key technology of disaster prediction and intelligent decision-making system

How to deign and develop an disaster prediction and intelligent decision-making system of disaster is a hot topic now. Analyses the characteristics of prediction and early warning method of mining engineering disaster, a structure of a technology framework based on spatial agent is presented, and described the structure of a spatial agent, the integrated behaviors of the spatial agent community in case study of a mine, which supports for disaster management and remote engineering control.
Design and implementation of a personal firewall Based on NDIS Intermediate Drivers

Firewall is the core technology of today's network security and the first line of defense against external network attacks and threats, most personal firewall deals with the packets under the user model, there are a lots of limits, in order to protect our privates better some operations need to be done under the kernel model. The NDIS by which we can easy do something under the kernel model is introduced in the windows operating system that is the mostly used system in personal computer. This paper clearly describes the architecture of the NDIS, on the base of the NDIS intermediate drivers presents a personal firewall model which operations under the kernel model.
The Application of RS in Wetland Ecosystem Health Assessment: A Case Study of Dagu River Estuary

To investigate the state and degradation degree of wetland ecosystem in Dagu River estuary, the comprehensive assessment index (CEI) method was employed. A set of assessment indicator system was established based on the pressure-state-response (PSR) model. In this study, wetland landscape pattern and some data was interpreted from Landsat-TM images in 2000 and 2003 for the subsequent ecosystem health assessment. Eleven indicators were elaborated and standardized by determining uniform criterion. It is found that the wetland ecosystem health in Dagu River estuary was bad both in 2000 and 2003, and human disturbance was the most important factor influencing it. During the three years, the wetland landscape has suffered serious fragmentation, and there was a downtrend both in rationality of organization and in resistibility of the wetland ecosystem. Thus, the chief measure to protect Dagu River estuary wetland should be setting a limit to human development activities.
Study on Hybrid Heuristic Algorithm for Vehicle Routing Problem with Backhauls

In order to satisfy with the individual and various demand of customer, establish vehicle scheduling with backhauls model. According to the characteristics of model, hybrid genetic heuristic algorithm is used to get the optimization solution. First of all, use natural number coding so as to simplify the problem; retain the best selection so as to guard the diversity of group. Improved ordinal crossover operators can avoid destroying good gene parts during the course of ordinal crossover so as that the algorithm can be convergent to the optimization as whole. Secondly, stock elite adopting genetic algorithm take the hybrid genetic algorithm with taboo searching algorithm to improve the convergent speed and searching efficiency of algorithm. The emulation and calculation proves that it is better than only using genetic algorithm and taboo searching algorithm.
Entanglement-assisted nonbinary quantum LDPC codes with finite field method

Based on quantum stabilizer formalism over multi-level quantum system, non-binary entanglement-assisted quantum coding theory was described in this paper. Then two classes of 2r-ary quantum quasi-cyclic LDPC codes were constructed by using algebraic finite field method over Fq with q = 2r. By iteratively decoded with q-ary sum-product algorithm (QSPA), the constructed 2r-ary quantum LDPC codes have shown significantly better performances than the present binary quantum LDPC codes.
The empirical analysis of sensation in customer lifetime value

One of the core competitive ability of company is regarding the customer management as the center issue. The view that long-term and stable customer is an important invisible asset of company has been commonly accepted by most scholars. This article analyzes the customer value sensation, the factors that influence the customer value and the ones that related to the building up of customer accounting system of our airline companies. The results of the survey indicate that the customer management of the airline companies is still on a poor level. However, the sensation level of the employees of the airline company exceeds the average level of measurement. All the employees want to manage the long-term and stable customers as an asset of company, accounting them and publish the information in the future.
Development of a Pressure-Sensing Handle for a Stethoscope

Acoustic signals recorded with a stethoscope could be significantly affected by the probe-skin interface. The goal of this study was to develop a pressure-sensing device to measure and control the applied pressure at the probe-skin interface. Since placing a pressure sensor directly at the interface would block the transfer of acoustic signals, a custom-made handle was attached to the top of the stethoscope head. A handle was made of silicone rubber with an embedded pressure sensor that measures the force transferring from the hand to the stethoscope head. A microprocessor based device was also developed to provide a numerical readout of the force. This system was successfully built, providing accurate and repeatable pressure measurements. The resulting device should be useful for standardizing the applied pressure at the probe-skin interface for acoustic measurements with a stethoscope.
TOA-Based Location Estimation Accuracy for 3D Wireless Sensor Networks

WSNs are a physical impossibility to be deployed into the area of absolute plane in the context of real-world applications. For all kinds of applications in WSNs accurate location information is crucial. In this article, we focus on 3D location accuracy in WSNs. We quantify the estimation accuracy for the TOA measurements by deriving the Cramer-Rao bound (CRB), and discuss the performance in two application scenarios, 2D WSN and 3D WSN. Matlab simulation indicates that the 3D location accuracy is superior to the 2D location accuracy for WSNs with reference devices and blindfolded devices being deployed randomly.
Wastewater treatment plant monitoring via a deep learning approach

This paper presents a fault detection method based on an unsupervised deep learning to monitor operating conditions of wastewater treatment plants (WWTPs). This method uses Deep Belief Networks (DBNs) model and one-class support vector machine (OCSVM). Here, DBN model is introduced to account for nonlinear aspects of WWTPs, while OCSVM is employes to reliably detect a fault in WWTP. The developed DBN-OCSVM approach has been tested through practical application on data from a decentralized wastewater treatment plant in Golden, CO, USA. Results show the effectiveness of the developed approach to monitor the WWTP.
Switching Robust H infinity Control for a Class of Uncertain Fuzzy Systems

The H8 switching robust control problem for a class of uncertain fuzzy system is studied. Finite fuzzy state feedback controllers are provided in a given set of controllers, and the gain matrix of each controller is known. Though none of the individual controllers can make the systems stable with H8 disturbance attenuation, using single Lyapunov function and multiple Lyapunov functions technique the switching law is designed, such that the H8 control problem is solvable through design switching laws. Simulation results show the effectiveness of the design method.
Driver fatigue detection algorithm based on eye features

This paper proposes a method of driver fatigue detection based on eye features — utilizing frame-difference projection to localize right and left boundaries of the face, then horizontal gray projection curve to localize approximate horizontal position of the eyes, and third, template matching to get the accurate eye position of the initial frame. After reliable localization of it, use dynamic template matching to track the eye position of next frames. Finally, detect eye state through similarity, which provides a basis for further fatigue detection.
Moving Object Detecting and Tracking with Mobile Robot Based on Extended Kalman Filter in Unknown Environment

In order to solve the problem of moving object tracking in unknown environment, an algorithm based on extended kalman filter is proposed. The states of robot, landmark and object are used to form whole system state, such that the covariance between different object state become more and more intensive in process of iteration, so improves accuracy of object state estimation. For practical application, a method of moving object detection based on occupy grid map is combined with our algorithm to obtain the measurements of moving object and environment landmarks. Moreover, the using of data verification step gives system more ability to tackle problem of disturbance sourced from false object observations. Real robot experiment and simulation results prove the effectiveness and accuracy of presented approach.
Designing Android applications with both online and offline voice control of household devices

Utilizing assistive technology to aid persons with neuromuscular disabilities, this study compares two methods for voice control of household devices through an input-output board driven by an Android application on a smart phone. Two types of voice recognition software, online Google and offline Pocketsphinx, were used and tested for accuracy of several commands on a television remote. Each application was designed to recognize keywords 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. Applications were tested for accuracy depending on distance between person and device as well as level of ambient noise.
Accelerated dynamic MRI via inter-frame motion estimation

The sparsity of MR images has been utilized to significantly undersample k-space measurements for accelerated MRI. In dynamic MRI, besides the spatiotemporal structures of images, the motion information should be considered to improve the reconstruction performance. Motivated by this, we propose a new method to recover dynamic MR images using partial k-space data based on the estimation of inter-frame motion. Our method consists of three main steps: single frame reconstruction, inter-frame motion estimation, and image sequence recovery. In contrast to algorithms which use a single reference frame for motion estimation, the motion information of each image in a dynamic MRI sequence is estimated according to adjacent frames. Since motion is estimated from the reconstructed images, the recovery process is robust against both noise and artifacts. The proposed method was evaluated on two dynamic MRI datasets, and compared with several state-of-the-art reconstruction methods. Experimental results demonstrate the effectiveness and robustness of the proposed method.
Graded muscle contractions determined by temporal recruitment

Electromyogram (EMG) signals have the potential to allow patients without total muscle controls to operate electronic or mechanical devices, such as a power wheelchair. A muscle contraction can be interpreted as a switching signal and its strength can determine the intended level. The purpose of this study is to implement an algorithm to accurately detect the strength of a muscle contraction. Muscle contraction strength can be increased by temporal or spatial recruitment. In this case, the graded muscle contraction is detected by the temporal recruitment, where the frequency of the EMG signal is evaluated. A nonlinear detection algorithm is used to define the duration of a contraction episode. The frequency of the spikes within the contraction episode is used to determine the contraction strength. The algorithm should be useful for designing myoelectrically controlled devices.
Distributed energy storage system in wind power generation

With the rapid development of wind power generation during these years, many large wind farms were established, and the adverse impact of wind power fluctuations on power grid has become significant. In this paper, we put forward an improvement scheme of distributed energy storage system to cope with this effect, and to maximize the utilization ratio of wind power. Energy storage systems can smooth the fluctuations of wind power, and they perform better in larger wind farms. Unlike traditional methods, the energy storage systems are located besides load centers rather than wind farms, causing no more investment. In our plan, charging stations for electric vehicles are built within some of the energy storage stations and these electric vehicles can also be regarded as energy storage devices. Different kinds of devices are applied to improve the response speed and capacity of energy storage system. Furthermore, these distributed energy storage systems have a better performance if combined with other kinds of renewable energy generation. Our research is based on digital simulation and dynamic experiment, and the results show that this distributed energy storage plan is more effective than traditional methods.