bluuebunny/crossref_metadata_2025_split huggingface dataset:
Oral discourse competence-in-performance
Authors: Cañada Maria Dolors , López-Ferrero Carmen 
Published: July 2019

AbstractMastering a language implies being able to deploy a wide variety of speech genres (Bakhtin 1952–1953). However, the features which define these genres are often obscure to students or ‘occluded’ in the sense used bySwales (1996). In this paper, nine dialogues between B1-level French learners in the context of an oral exam are analysed in order to describe the degree of dialogic competence-in-performance (Weigand 2017) achieved. Because these dialogues were of two types, an exchange of opinions and a guided interview, our analysis reveals hybrid results. This hybridity affects the opening and closing sequences of the dialogue, floor-taking in the central part and the linguistic resources used by the students to give their opinions. These findings identify formative needs as well as the indicators of achievement that are required to assess students’ oral competence-in-performance.
The design and implementation of a ROACH2+GPU based correlator on the Tianlai dish array
Authors: Niu Chen-Hui , Wang Qun-Xiong , MacMahon David , Wu Feng-Quan , Chen Xue-Lei , Li Ji-Xia , Tian Hai-Jun , Shippee Guillaume , Werthimer Dan , Zheng Xiao-Ping 
Published: July 2019

Abstract
A digital correlator is a crucial element in a modern radio telescope. In this paper, we describe a scalable design for the correlator system of the Tianlai pathfinder array, which is an experiment dedicated to testing key technologies for conducting a 21 cm intensity mapping survey. The correlator implements the FX design, which firstly performs a fast Fourier transform (FFT) including polyphase filter bank (PFB) computation using a Collaboration for Astronomy Signal Processing and Electronics Research (CASPER) Reconfigurable Open Architecture Computing Hardware-2 (ROACH2) board, then computes cross-correlations by employing Graphics Processing Units (GPUs). The design has been tested both in laboratory and in actual observation.
Orbital and physical parameters of the close binary system GJ 9830 (HIP 116259)
Authors: Masda Suhail G. , Al-Wardat Mashhoor A. , Pathan J. M. 
Published: July 2019

Abstract
We present the complete set of physical and geometrical parameters of the visual close binary system GJ 9830 for the first time by applying Al-Wardat’s complex method. This method combines magnitude difference from speckle interferometry, synthetic spectral energy distributions of the binary components which are constructed based on grids of Kurucz blanketed models (ATLAS9), and the orbital solution using Tokovinin’s dynamical method to estimate the parameters of individual components. The analysis of the system by employing synthetic photometry resulted in the following set of parameters: T
eff = 6220 ± 100 K, log g = 4.30 ± 0.12, R = 1.10 ± 0.08 R
⊙for the primary component and T
eff = 4870 ± 100 K, log g = 4.60 ± 0.11, R = 0.709 ± 0.07 R
⊙for the secondary component. The recently published dynamical parallax from the Gaia space mission was used to calculate the total mass of the binary system as 1.75 ± 0.06 ℳ
⊙, which coincides with those estimated using Al-Wardat’s method as ℳ
A = 1.18±0.10 ℳ
⊙, ℳ
B = 0.75±0.08 ℳ
⊙. The analysis of the system reveals that both components are characteristic of main sequence stars and have an age of around 1.4±0.50 Gyr. The evolutionary tracks and isochrones of the system’s components are discussed, and the fragmentation process is suggested as the most likely process for the formation of the system.
Long-term trends in solar activity. Variations of solar indices in the last 40 years
Authors: Bruevich Elena , Bruevich Vasily 
Published: July 2019

Abstract
We analyze long-term variations of several solar activity indices (AIs) that have been measured over the last 40 years. With this goal, we study the AIs that characterize the fluxes from different areas in the solar atmosphere. Our consideration of mutual correlations between the solar indices is based on the study of relationships between them in the period from 1950 to 1990. This period of time, covering activity cycles 19–22, is characterized by relatively stable relations between the indices. We investigate the normalized variations of these indices in recent time in relation to their values which were calculated by considering radiation from the Sun in the radio range at a wavelength of 10.7 cm (F
10.7) in 1950–1990. The analysis of time series, representing variations of the normalized AI (AIFF) in solar cycles 23–24, shows different trends exist for different indices in terms of their long-term behavior. We assume that variations of normalized International Sunspot Number (SSN), F
530.3 and Flare Index, which have shown sharp decreases in the last 40 years, are possibly associated with a decrease in the intensity of large-scale magnetic fields in the photosphere (SSN) and in the corona (the coronal index and the Flare Index).
Radio spectral index from NVSS and TGSS
Authors: Tiwari Prabhakar 
Published: July 2019

Abstract
I extract the radio spectral index, α, from 541 195 common sources observed in the 150MHz TIFR GMRT Sky Survey (TGSS) and the 1.4GHz NRAO VLA Sky Survey (NVSS). This large common source catalog covers about 80% of the sky. The flux density limits in these surveys are such that the observed galaxies are presumably hosts of active galactic nuclei (AGNs). I confirm the steepening of α with increasing flux density for this large sample and provide a parametric fit between α and flux density. Next, I divide the data into low flux (LF) and high flux (HF) density samples with roughly equal numbers of galaxies. The LF sample contains all galaxies below 100mJy TGSS and 20mJy NVSS flux density and the HF sample is all galaxies above 100mJy TGSS and 20mJy NVSS. I observe an increase in α with source size (TGSS measured), saturating for large sizes to 0.89 ± 0.22 and 0.76 ± 0.21 for the LF and HF sources, respectively. I discuss the observed results and possible physical mechanisms to explain observed α dependence with source size for LF and HF samples.
Using FFT to reduce the computational complexity of sub-Nyquist sampling based wideband spectrum sensing
Authors: Liu Changjian , Chen Kai , Zhang Jie , Wang Yifan , Wang Houjun 
Published: July 2019

Abstract
Sub-Nyquist sampling based wideband spectrum sensing can usually be summarized as two steps. The first step estimates the signal power spectrum. The second step uses the energy detection method to make a decision. The traditional method usually adopts the least square algorithm to estimate the power spectrum. In order to reduce the computational complexity of the power spectrum estimation, a novel algorithm is proposed to replace the least square algorithm. We find the system matrix of Multi-Coset Sampling (MCS) based power spectrum estimation has a special structure. Its row vectors are all selected from the row vectors of the Discrete Fourier Transform (DFT) matrix. We exploit this special structure and use Fast Fourier Transform (FFT) to reduce the computational complexity of power spectrum estimation. Simulation shows the proposed algorithm can achieve the spectrum sensing performance similar to the traditional method at much lower computational complexity.
Supervised Kernel Based Nonlinear Unmixing of Hyperspectral Data
Authors: Xiao Hong 
Published: July 2019

Abstract
In hyperspectral imagery problem, pixels are mixtures of spectral component associated with pure materials. Recently, nonlinear models have been taken into consideration to surmount some limitations of linear model. In this paper, the nonlinear hyperspectral image unmixing problem is formulated with kernel learning theory, with the number of kernels being controlled by the coherence rule. To be more physically interpretable, a relationship between endmembers and abundance vectors is introduced as a constraint of the optimization problem. An iterative learning algorithm derived from augmented Lagrangian method is proposed to solve the defined problem. Simulation results show the efficacy of the proposed model and algorithm.
Understanding of the common methods in e-HRM data security
Authors: Guo Yonggui , Cao Lina , Gao Xiao , Lv Xuming 
Published: July 2019

Abstract
Along with the development of the society, the human capital comes to the significant place in the century stage. Not only the business firms but also non-profit organizations pay lots attentions to the HRM (Human Resource Management), to get better working efficiency and lower costs. However, with the advantages of modern approaches, the developing of HRM also exposes many vital challenges, especially the data security issues. Data bear the weight of the whole HRM system and a single negligence of data may cause severe problems. This paper is going to discuss the current approaches of data security management in e-HRM. Also, some recommendations are made at the end of this paper for better applying e-HRM.
Research on Segmentation and Recognition of Printed Chinese Characters
Authors: Wang Xi , Du Hong , Wen Xiping 
Published: July 2019

Abstract
The printed character recognition (PCR) is an efficient and automatic information entry method, which will become the important function interface of the computer in the future. A good character segmentation method can greatly improve the speed and accuracy of character recognition. This paper proposes a Chinese character segmentation algorithm based on OpenCV open source library and parallel processing, which can segment Chinese characters efficiently and accurately. And then, using the Tesseract-OCR character recognition engine to identify Chinese characters, the experimental results show that the average recognition time of a single Chinese character is 0.07s, and the recognition rate of Chinese characters is 96.2%, which proves the feasibility of the method.
Discussion on the Technology and Application of Mold NC Machining
Authors: Qian Xuejun , Qin Peng 
Published: July 2019

Abstract
With the continuous development of science and technology in China, new breakthroughs have been made in manufacturing technology. Among them, NC machining and manufacturing technology of mechanical die is the most widely used. In the process of manufacturing, the NC machining technology of die and mould has stricter requirements on the complexity of structure, which means that the NC machining technology of mechanical die and mould plays a decisive role in the working process. In this paper, the characteristics and application of NC machining technology are introduced to analyze the actual situation of using machinery in die manufacturing process, and discuss the future development of data processing technology for mechanical die manufacturing.
Design of Medical Examination Data Mining System Based on Decision Tree Model
Authors: Ma Gang , Zhang Liumei , Cui Guangzhi , Cheng Yimin 
Published: July 2019

Abstract
This paper analyzes the system of OLAP physical examination data mining system, the concept of classification, and the nature of decision tree to define the implementation process of ID3 algorithm. Transaction data of the physical examination information management system of Xi’an Shiyou University Hospital from 2015 to 2018 are selected and prepared for cleaning and preprocessing, then the data is dimensionally reduced and transformed, to design a direct data model suitable for classification analysis. The sampling data set is classified and analyzed by ID3 algorithm, and the classification rules are extracted. Using the prediction conclusions of these classification rules, the medical examiner can quickly and scientifically predict the individual physique of each college teacher, so as to classify college teachers of different physiques, and specifically guide the teacher’s further treatment plan of exercise, diet and work. It has high reference value and promotion towards teachers’ health.
An Improved WNNM Algorithm for Image Denoising
Authors: Wu JunFang , Lee XiDa 
Published: July 2019

Abstract
The traditional weighted nuclear norm minimization (WNNM) has excellent performance for the removal of non-sparse noise such as Gaussian noise, but attains bad performance for the removing of salt&pepper noise and mixed noise of Gaussian noise and salt&pepper noise. This paper proposes an improved WNNM image denoising algorithm. WNNM can effectively remove non-sparse noise such as Gaussian noise and adaptive median filtering algorithm can effectively remove sparse noise such as salt and pepper noise; the improved algorithm combines the characteristics of WNNM and adaptive median filtering. The experimental data demonstrate that the improved WNNM algorithm has better denoising effect than WNNM algorithm.
A Novel Edge Detection Algorithm Based on Distance
Authors: Changhong Yang , Xiong Zou , Jiali Xu 
Published: July 2019

Abstract
Under the framework of Canny algorithm, a distance-based edge detection algorithm is proposed to improve the gradient magnitude of Canny. In our algorithm, the gradient magnitude can be acquired by taking the distance from the center of the mask as the weight factor. The operator not only can calculate the image gradient better, but also has good separability in the horizontal and vertical directions, and its gradient amplitude has a certain degree of rotation invariance. Finally, this operator is compared with various gradient operators for the Lena image simulation and the actual waterfront edge detection experiment. It shows that the operator has a better edge detection effect from the experimental results.
The Perfect Numbers of Pell Number
Authors: Fu Ruiqin , Yang Hai , Wu Jing 
Published: July 2019

Abstract
For any positive integer n, let Pn
, Qn
denote the Pell sequence and Pell Lucas sequence respectively. The main purpose of this paper is using the elementary methods to study that Pn
does not contain any even perfect numbers, Qn
just contains one perfect number and this number is Q
2 = 6.
The Influence of Phonetic and Shape Information on Mongolian Students’ Recognition of Mongolian Words
Authors: Hu Axu , Wang Menghuan 
Published: July 2019

Abstract
In the process of vocabulary recognition, the role of shape information and phonetic information has been a hot topic in recent years. There are three more influential theories: straight through theory, phonological mediation, and dual--route theory. The theory of phonological mediation believes that the order of activation of phonological, graphic and semantic in vocabulary recognition is different. The accessibility of semantic is through the voice route, and phonological plays an important intermediary role. The straight-through theory believes that the accessibility of semantic is activated by the graphic. Phonological activation is at the end, which is an additional process. The dual--route theory holds that both phonological mediation and the straight-through theory exist. However, there is still controversy about the role of phonetic and shape information in vocabulary recognition. Some of the reasons for this debate are the differences in experimental tasks and research methods designed by researchers. The results of most researchers using Chinese and English as experimental materials show that in the reading of alphabetic writing, the main route of semantic activation is through the intermediary of phonological, which plays a vital role in the process of acquiring semantics. The semantics of accessibility in the process of Chinese vocabulary recognition is obtained through glyphs. However, there are few studies on minority students’ recognition of their mother tongue and recognition of second-language vocabulary. Then, as one of the alphabetic writing in Mongolian, does Mongolian semantic activation in vocabulary recognition pass through the voice route? Does college students of Mongolian support the theory of phonological mediation or straight through theory in the recognition of second language vocabulary?
RETRACTED: Application on Computer Software Technology under the Background of Big Data
Authors: Wang Hailan 
Published: July 2019

Abstract
With the rapid development of science and technology in the 21st century, computer technology has been applied to all aspects of national life. And it is closely related to people’s life. In the era of big data, an important part of society has already included the development and application of computer software technology. This paper analysis the importance and development status of computer software technology. And then, we study the application of computer software technology in the era of big data. We expect that this study can promote the continuous improvement of the whole social economic and comprehensive benefits.
A Real-time Intra-pulse Recognition Method of Radar Signals Based on Restricted Boltzmann Machines
Authors: Liu Yishan , Tian Xi , Li Xiaopeng 
Published: July 2019

Abstract
Intra-pulse features extraction of radar is of great research significance in electronic reconnaissance technology. With continuous development and equipment of the new system radar, the characteristics of the modern electromagnetic environment could be summarized as density, complexity and variability, which makes the traditional signal identification methods difficult to achieve the desired effect and determines the recognition must be real-time. Therefore, this paper is devoted to the study a fast method and performance analysis in extracting intra-pulse features of radar emitters in complex electromagnetic environment, especially in low SNR environment, and the experiment process could achieve real-time recognition.
Application investigation and technological development of intelligent product in college English teaching
Authors: Zhou Junping 
Published: July 2019

Abstract
Through quantitative and qualitative research methods, this paper investigated the application of intelligent products in College English teaching in China and proposed its future technological development prospect based on application problem and both teachers’ and students’ practical needs. The survey shows that kekenet.com and Chinese Universities MOOC Network are the most popular intelligent products used by teachers and students due to effective intelligent monitor and rich resource support function etc. The application problems and product disadvantages include lack of intelligent monitoring and recording system, lack of error identification and correction function, without learning process evaluation and individualized learning guidance etc. The future improvements will be adding listening error analysis in listening intelligent product, adding speech identification and comparison function in speech teaching software, creating translation teaching platform and adding word-in-use technique for vocabulary teaching product etc.
A Non-learning-oriented Recognition Algorithm of Vehicle License Plate Characters
Authors: Li Fengkun , Dong Benqing , Liu Long 
Published: July 2019

Abstract
Based on the fact that characters of vehicle license plate are standardized, a recognition algorithm of Vehicle License Plate Characters based on non-learning-oriented method is proposed. This method uses some concepts such as Shape Feature Vector (SFV, for short) to describe the shape of the to be recognized characters. Each character will be evaluated with a vector and the recognition is realized by calculating the similarity of vectors. This method achieves character recognition by vector arithmetic avoiding the learning/training process often used in some algorithms, such as artificial neural network, and SVM and so on. The recognition is simplified tremendously. The feasibility of using SFV to recognize vehicle license plate characters is proven theoretically, and then, the character recognition algorithm of vehicle license plate is evaluated by simulation. The result of the simulation shows that SFV can be used as license plate character recognition. And the license plate recognition algorithm based on SFV has an accuracy rate of 97.31%. This method is a helpful attempt of character recognition based on non-learning-oriented method.
Optimization of the Grid Mapping Algorithm for Mobile Robots
Authors: Wu Ruoxi , Shu Leizheng , Zhao Xin 
Published: July 2019

Abstract
Navigation precision, which is an important performance index of mobile robots, is closely related to the precision of grid mapping (Gmapping) algorithm. The modeling of the Gmapping algorithm is completed on the basis of Rao-Blackwellized particle filter (RBPF), with a light detection and ranging (LiDAR) robot as the research background, and the factors that influence the accuracy error of the Gmapping algorithm are analyzed. Firefly algorithm is introduced into the Gmapping system to complete the modeling and simulation analysis. The simulation results show that applying the firefly algorithm to the Gmapping system can effectively smooth the fluctuations of position, attitude angle, and other data output using sensors, which can decrease the number of particles and reduce object feature degradation. This method can effectively improve the accuracy of the Gmapping algorithm, reduce navigation error, and provide reference and guidance for the Gmapping system design of mobile robots.
Research and Improvement of Image Encryption Algorithms Based on Chaos
Authors: Wang Ruoyu , Cao Sanxing 
Published: July 2019

Abstract
Due to user privacy protection and other demands, image encryption is always a hot spot in the research field. In view of these problems, this article proposes a chaotic image encryption algorithm, which is named permutation-diffusion algorithm. Specifically, the image of the pixels is permuted, so that the pixel position changes, and then spreads, to change the pixel value. It can be observed from the test results that the algorithm is better in terms of efficiency and safety, compared with the state of the art.
Research on Coverless Text Steganography Based on Single Bit Rules
Authors: Wu Ning , Shang Poli , Fan Jin , Yang Zhongliang , Ma Weibo , Liu Zhenru 
Published: July 2019

Abstract
Text steganography has become a hotspot in the field of information security in recent years. As an important steganographic carrier, text does not have the advantage that other multimedia could easily use more redundancy to hide information. Traditional methods were realized by changing the appearance attributes of text or by equivalent replacement based on grammar and semantics, but there were some shortcomings more or less. Based on Markov chain model, this paper proposed a coverless text steganography method. In order to enhance the effect of steganography, the method focused on the most important concepts in Markov model, the transition probability, and guided the generation of steganographic text based on it. The relevant experiments were designed to evaluate the model. The experimental results showed that the model had higher concealment and hiding capacity.
Research on Musical Sentiment Classification Model Based on Joint Representation Structure
Authors: Zheng Chunjun , Jia Ning 
Published: July 2019

Abstract
In the traditional music emotion classification process, there are problems such as low classification accuracy rate, long period, and difficulty in satisfying the individualized needs of the theme music in people’s lives. Based on this, a neural network model based on joint representation structure is designed. The model uses low-level descriptors and spectrograms to construct a joint representation of the characteristics of the manual and convolutional recurrent neural network, thus realizing the discrimination of music emotion subclasses. At the time of the experiment, the model was designed and the CRNN traditional model was used as the baseline. The experimental results show that this model can improve the classification accuracy of music emotions compared with the traditional single model.