nils-herrmann/clean_scirepeval huggingface dataset:
A New Algorithm for Auditory Feature Extraction

The human auditory system possesses remarkable capabilities to analyze and identify signals. An auditory feature can improve the performance of speaker recognition system. In this paper, it used gammatone filter to model auditory system, and extracted a traditional auditory feature based on logarithmic energy. On the purpose to reduce the dimension of the traditional auditory feature which was always a high dimensional feature, we took use of discrete cosine transform (DCT). Therefore, it was feasible to apply auditory model extracted in a new way to speech feature extraction. The experiments showed that the GFCC feature, which was extracted in the new method, performed better than the traditional MFCC feature in the speaker recognition system based on GMM model.
Notice of RetractionStudy on widening financial channel of small-medium enterprises in Heilongjiang Province

Nowadays, SMEs of our country has become the main force of economic development. To the current situation, the quantity of SMEs accounts for over 99% of the total number of enterprises, which accounts for the value creation about 60% of GDP, providing new jobs that accounts for 75% of enterprises, import and export volume accounts for 60% of the country. In the meanwhile, SMEs of Heilongjiang Province, the role in economic development have been becoming increasingly significant In Heilongjiang Province, the quantity of SMEs accounts for more than 90% in province. February 2009, only the value of private foreign trade import and export of small and medium enterprises achieved 2.35 billion, accounting for 75.8% of the province's imports and exports, state-owned enterprises, foreign imports and exports $ 580, 000, 000 and $ 160, 000, 000. The data shows that SMEs have become a driving force in Heilongjiang Province which promote the province's rapid economic growth. However SMEs financing channel is narrow, it brought huge pressure to SMEs. This situation hindered its healthy development and economic growth. The thesis starts with the current situations of SEMs financing channels, probes and analysis the existing problems of the channels in Heilongjiang province, proposes the strategy and suggestion to widen SEMs financing channel to promote the rapid economic development in Heilongjiang province.
From mollusk to Matlab: experiential learning for the undergraduate biomedical engineer

Biomedical engineering (BME) is a rapidly growing field, and although it is present in many schools, there is an apparent theme of keeping the biological and engineering aspects separate. However, at the University of Rhode Island, a course exists that brings together accomplished teachers/mentors from both subjects, and as far away as Japan, to assist students in biomedical research. Students acquire microdissection and micro manipulation skills, as well as techniques in data analysis, while attaining an in-depth understanding of the physiological functions of the biological systems. In this specific experiment, the model Lymnaea stagnalis is used. The central nervous system was dissected and removed, neurological signals were recorded, and the results were smoothed using a Butterworth filter. Using this experiment as an example, this paper illustrates how this course combines key concepts from biology, physiology, and electrical engineering, resulting in a unique BME research experience for the undergraduate biomedical engineer.
Detecting Abnormal Ozone Measurements With a Deep Learning-Based Strategy

Air quality management and monitoring are vital to maintaining clean air, which is necessary for the health of human, vegetation, and ecosystems. Ozone pollution is one of the main pollutants that negatively affect human health and ecosystems. This paper reports the development of an unsupervised and efficient scheme to detecting anomalies in unlabeled ozone measurements. This scheme combines a deep belief networks (DBNs) model and a one-class support vector machine (OCSVM). The DBN model accounts for nonlinear variations in the ground-level ozone concentrations, while OCSVM detects the abnormal ozone measurements. The performance of this approach is evaluated using real data from Isère in France. We also compare the detection quality of DBN-based detection schemes to that of deep stacked auto-encoders, restricted Boltzmann machines-based OCSVM, and DBN-based clustering procedures (i.e., K-means, Birch, and expectation–maximization). The results show that the developed strategy is able to identify anomalies in ozone measurements.
A Fully Digital Implementation of Voltage, Current, and Dynamic Clamping Methodologies

Standard electrophysiology experiments utilize a technique known as voltage clamping: the surface of the cellular membrane is held constant, or clamped, which allows the researcher to study the membrane permeability and ion exchange. This process is usually performed with commercially available analog equipment. While analog circuitry provides an accurate and reliable equipment medium, it does not allow for much in the way of real-time data processing. Additionally, there is the issue of data acquisition which must be performed using an analog to digital converter (A/D). A need exists to resolve these issues in one device. The Universal Clamp, a patent pending electronic device designed and built by Dr. Jiang Wu at the University of Rhode Island, addresses this need. The Universal Clamp, however, does much more than data acquisition (DAQ) and signal processing. As the name implies, it has the capability of performing voltage clamping, current clamping, and dynamic clamping, all in one device, with the aid of a digital signal processing (DSP) chip. This functionality provides researchers greater flexibility in the types of experiments they can conduct, as well as simplifying current standard methodologies. Using the visceral ganglion from Aplysia californica, the Universal Clamp has successfully performed voltage clamping, current clamping and dynamic clamping, while simultaneously executing data acquisition and signal processing algorithms.
Efficient Method of Passive Localization for Mixed Far-Field and Near-Field Sources

An effective second-order statistics (SOS)-based algorithm is addressed for scenarios where both far-field and near-field narrowband sources may exist simultaneously. After estimating the direction-of-arrivals (DOAs) and powers of far-field signals, the related far-field components can be eliminated from the signal subspace. Then, based on the symmetric property of the uniform linear array geometry, a near-field estimator without two-dimensional search or parameter pairing is performed. Compared to the previous SOS based method, the resultant algorithm can provide an improved estimation accuracy, as well as realize a more reasonable classification of the signal types. Simulation results are carried out to demonstrate the performance of the proposed algorithm.
Particle Swarm Optimizer based controller design for Vehicle Navigation System

The purpose of this paper is to develop particle swarm optimizer (PSO) based controller for vehicle navigation system (VNS). This paper regards the mathematical model of car-like mobile robot as the vehicle dynamics behavior to develop the controller for VNS. VNS controls the vehicle via two actual control values, one is the degree variation of the front wheel and the other is the acceleration variation of the vehicle versus time respectively. The proposed algorithm is to find the best feedback gain values of the controller for VNS after two analysis process. First, input-output linearization is applied to transform non-linear dynamic model of vehicle to a linear system through states transformation. Contained within the linear system is a set of pseudo control variables; there is a transformation relationship through the decoupling matrix between the vehicle's actual control variable and the pseudo control variable. Second, a pseudo control is generated by designing a state feedback controller of the linear system. Then the best feedback gain values are determined by particle swarm optimizer (PSO). At once the best feedback gains are found by the PSO, pseudo control could be transformed to the actual control applied to the vehicle through a decoupling matrix. In the paper, the controller for VNS constructs a precise and optimized vehicle's automatic navigation strategy and meets the requirement of system closed-loop stability. This paper uses Matlab as the simulation environment, the simulation results show that the proposed method makes vehicle steering in the crooked change road conditions. The proposed algorithm can adjust the vehicle's trajectory to the road trend and can provide a stable driving strategy for driver.
GLRT Based Anomaly Detection for Sensor Network Monitoring

Proper operation of antenna arrays requires continuously monitoring their performances. When a fault occurs in an antenna array, the radiation pattern changes and can significantly deviate from the desired design performance specifications. In this paper, the problem of fault detection in linear antenna arrays is addressed within a statistical framework. Specifically, a statistical fault detection method based on the generalized likelihood ratio (GLR) principle is utilized for detecting potential faults in linear antenna arrays. The proposed method relies on detecting deviations in the radiation pattern of the monitored array with respect to a reference (fault-free) one. To assess the abilities of the GLR based fault detection method, three case studies involving different types of faults have been performed. The simulation results clearly illustrate the effectiveness of the GLR-based fault detection method in monitoring the performance of linear antenna arrays.
Research on transducer and frequency of ultrasonic guided waves in urban pipe inspection

Guided ultrasonic wave is a new non-destructive pipe inspection technology for its rapid, long distance inspection. It can be used to inspect urban pipes, for example, residential drinking water pipe, natural gas pipe, heating pipe, sewage pipe. Most urban pipes are underground pipes and difficult to access using other conventional NDT methods. The inspection distance, that is, the traveling range of guided wave is dependent on propagation characteristics of ultrasonic guided waves. In this paper, longitudinal wave L(0, 2), which was used as the excited guided wave and L(0, 1), which should be suppressed during the experiment were both discussed. Furthermore, effects of transducers number and transducer ring spacing on characteristics of excited signals were investigated. Factor that may affect the selection of experimental frequency was studied and optimum frequency of guided wave for pipe with different thickness and diameter was recommended. In the end, an experiment was performed on a 40 meter long heating pipe in the residential area of Bohai Oil Company, Tianjin city, China. And the experimental results showed good agreement with the theoretical analysis.
Policy analysis and mode design on incremental investment and financing of building energy efficient market in China

Development barriers of building energy efficient market (BEEM) in China mainly centralize on unitary construction capital source channel and deficient effective capital supply. To the key problems of capital financing in BEEM, this study takes the incremental investment and financing (IIF) as research object. Establish two-stage leader-followers game model based on Stackelberg with government and other investors during the course of IIF for BEEM, and prove that government's participant degree and mode have important influence on market investment efficiency and proposed policy path improving IIF influence factors. Propose three types of policy path including CAC, MBI and market standardization policy type (MSP). On the basis of research result, propose three IIF modes suit for this stage in China, which include IIF mode combining market admittance and energy efficient label, IIF mode based on existing residential building energy efficient retrofit mode and IIF mode under energy efficient supervision framework.
Mean-CVaR Portfolio Optimization Problem under Concave Transaction Costs and Minimal Transaction Unit Constraints

In the paper, considering the fact situation that the transaction number is an integer and associated with portfolio construction is a fee for purchasing assets in the stock market in China at present, we increase minimal transaction unit constraint. And with the concave transaction cost function more conforming to the actual situation, introducing the condition risk value (CVaR) to measure the portfolio risk, we propose a mean- CVaR concave integer programming model under concave transaction costs and minimal transaction unit constraints. In the same time, we give a genetic algorithm to solve this model, and the numerical experiment shows that the model is reasonable and the algorithm is efficient.
A modified forecasting algorithm for wind power based on SVM

Aiming at the saturation characteristic of SVM in large sample environment, a modified SVM forecasting algorithm for wind power forecasting is proposed in this paper. The key point of the modified SVM forecasting algorithm is converting large sample set to small sample set by making classification. In this method, the optimal regression size for SVR is firstly sought out for the actual sample, and then the training samples are divided into several categories according to wind power output with different class labels. Based on SVC, train out classification model; based on SVR, regression model of each class can be built. Forecast data of wind power can be obtained by taking the text data into above classification model and corresponding regression model. At last, the proposed algorithm is applied to a wind farm of Shandong Province; and the results verify its validity and effectiveness.
A New Type Dual Temperature Box

A dual temperature box is researched. The dual temperature box adopts cascade refrigeration system. R22 is the refrigerant in the high temperature circle system, and R13 is the refrigerant in the low temperature circle system. The R22 system can operate both alone and with the R13 system. So the dual temperature box can achieve two vapor temperatures of -65 ¿Z and -20 ¿Z. And the refrigerant system of it can operate stable while the temperature is -65 ¿Z.
A Computational Method for Prediction of Saliva-Secretory Proteins and Its Application to Identification of Head and Neck Cancer Biomarkers for Salivary Diagnosis

Human saliva is rich in proteins, which have been used for disease detection such as oral diseases and systematic diseases. In this paper, we present a computational method for predicting secretory proteins in human saliva based on two sets of human proteins from published literatures and public databases. One set contains known proteins which can be secreted into saliva, and the other contains the proteins that are deemed to be not extracellular secretion. The protein features with discerning power between two sets were firstly gathered. Then a classifier was trained based on the identified features to predict whether a protein was saliva-secretory one or not. The average values of the sensitivity, specificity, precision, accuracy, and Matthews correlation coefficient value by 10-fold cross validation repeated 100 times were 80.67%, 90.56%, 90.09%, 85.53%, and 0.7168, respectively. These results indicated that our selected features are informative. We applied the classifier for prediction saliva-secretory proteins out of all human proteins, if a known biomarker was likely to enter into saliva, and the potential salivary biomarkers for head and neck squamous cell carcinoma. We also compared the top 1000 proteins predicted by computational methods in different kind of fluids. This work provided a useful tool for effectively identifying the salivary biomarkers for various human diseases and facilitate the development of salivary diagnosis.
Cluster Guide Particle Swarm Optimization (CGPSO) for Underdetermined Blind Source Separation With Advanced Conditions

The underdetermined blind source separation (BSS), which based on sparse representation, is discussed in this paper; moreover, some difficulties (or real assumptions) that were left out of consideration before are aimed. For instance, the number of sources, , is unknown, large-scale, or time-variant; the mixing matrix is ill-conditioned. For the proposed algorithm, in order to detect a time-variant mixing matrix, short-time Fourier transform is employed to segment received mixtures. Because is unknown, our algorithm use more estimates to find out the mixing vectors by particle swarm optimizer (PSO); and then, surplus estimates are removed by two proposed processes. However, the estimated accuracy of PSO will affect the correctness of extracting mixing vectors. Consequently, an improved PSO version called the cluster guide PSO (CGPSO) is further proposed according to the character of sparse representation. In simulations, several real assumptions that were less discussed before will be tested. Some representative BSS algorithms and PSO versions are compared with the CGPSO-based algorithm. The advantages of the proposed algorithm are demonstrated by simulation results.
Dynamic Strain Model With Eddy Current Effects for Giant Magnetostrictive Transducer

Based on the Jiles-Atherton model and transducer's structural dynamics principle, the magnetoelastic dynamic strain model of giant magnetostrictive transducer is founded. This model accounts for the eddy current losses and the variety of stress. Simulation results are in good agreement with the experimental ones. This indicates that the dynamic strain model can describe the relation between the applied field and the output vibration at different driving levels
Management Motivation and Earnings Management Methods

In this paper, we study the effectiveness of the management motivations on earnings management methods based on thousands of samples between 2006 and 2011. The empirical results indicate that Real Earnings Management is used to manipulate the earnings in order to turn a profit, avoid loss, refinance, and change executives. The companies with higher executive compensations intend to use REM. However, making big profits by using Real Earnings Management activities is not popular because the capital market in China is not perfect enough.
A self-calibrating distance lookup method for camera-equipped vehicular system

An image based distance self-calibrating method for automotive electronic system is proposed to ease the difficulty in setup procedure and offset the possible changes caused by moving the camera that used to capture image for distance measurement. By process the information from vertical edge of dashed road line, the lookup table is established to translate the pixel distance to real distance. The only parameter needs to be provided by user is the practical distance that bottom row of captured image stand for. In addition, a noise-insensitive filter is designed to find the edge of dashed road line. As a result, the error is within 1 meter inside the range of 30 meter.
Geometrically Consistent Stereoscopic Image Editing Using Patch-Based Synthesis

This paper presents a patch-based synthesis framework for stereoscopic image editing. The core of the proposed method builds upon a patch-based optimization framework with two key contributions: First, we introduce a depth-dependent patch-pair similarity measure for distinguishing and better utilizing image contents with different depth structures. Second, a joint patch-pair search is proposed for properly handling the correlation between two views. The proposed method successfully overcomes two main challenges of editing stereoscopic 3D media: (1) maintaining the depth interpretation, and (2) providing controllability of the scene depth. The method offers patch-based solutions to a wide variety of stereoscopic image editing problems, including depth-guided texture synthesis, stereoscopic NPR, paint by depth, content adaptation, and 2D to 3D conversion. Several challenging cases are demonstrated to show the effectiveness of the proposed method. The results of user studies also show that the proposed method produces stereoscopic images with good stereoscopics and visual quality.
Study on Grid Capability to Accommodate Wind Power Based on DSM

DSM (Demand Side Management) strategies are modeled and the grid capability to accommodate wind power is analyzed in the power system dispatching optimized software Balmorel in this paper. The influences of DSM improvement to wind power penetration are analyzed by investing the new pumped-storage unit and implementing peak-valley price mechanism. The conclusion is drew that the output of wind farms can be increased and the wind curtailment and power fluctuation can be mitigated, as well as considerable economic benefit is also obtained by case studies.
Effectively multi-swarm sharing management for differential evolution

This paper presents a novel multi-swarm sharing management for differential evolution (MsSDE) to deal with numerical optimization effectively. Multi-swarm is an effective search concept to keep the original search characteristic or effective balance strategies. However, it still has some defects need to overcome, such as weak search ability for smaller swarm and easy to fall into local optimal position. In order to overcome the problem mention above, the proposed multi-swarm sharing management can adjust each swarm size, share and analyze their information for other swarms to get more effective search ability. Testing and comparing results with original DE and EPUS-PSO by several benchmark functions, it showed that the proposed method has satisfying performance.
A Zero Module Current Obtaining Approach Based on Magnetic Induction for Single Phase Grounding Fault

A new approach based on the magnetic field induction is presented to obtain transient zero module current for single phase grounding gault of overhead lines. The paper analyses the characteristics of magnetic field around the overhead lines and presents the magnetic field under the lines is proportional to the zero module current, and the zero module current can be measured by inducting the magnetic field. The paper proposes a zero-module current obtaining approach using a hall sensor to induct magnetic field, and elaborates the solution to the key issues in practical applications, at last simulation and experiment results demonstrate the feasibility of the approach.
Progress in speech emotion recognition

Emotional information in speech signal is an important information resource. When verbal expression combined with human emotion, emotional speech processing is no longer a simple mathematical model or pure calculations. Fluctuations of the mood are controlled by the brain perception; speech signal processing based on cognitive psychology can capture emotion better. In this paper the relevance analysis between speech emotion and human cognition is introduced firstly. The recent progress in speech emotion recognition was summarized including the review of speech emotion databases, feature extraction and emotion recognition networks. Secondly a fuzzy cognitive map network based on cognitive psychology is introduced into emotional speech recognition. In addition, the mechanism of the human brain for cognitive emotional speech is explored. To improve the recognition accuracy, this report also tries to integrate event-related potentials to speech emotion recognition. This idea is the conception and prospect of speech emotion recognition mashed up with cognitive psychology in the future.