bluuebunny/crossref_metadata_2025 huggingface dataset:
Devices of alignment
Authors: Gao Hua
Published: July 2019

This study draws on a conversational analysis (CA)-oriented micro-analytical approach and examines the form, placement and function of interviewer (IR) questions prefaced by turn-initial所以suoyi‘so’ and但(是)dan(shi)‘but’ in Chinese TV news interviews. It is found that IRs often employ the resultative connectivesuoyias the first item of their turn immediately after a question-answer (QA) sequence. They do so to preface a declarative, alone or followed by a question tag that invokes an interviewee (IE) opinion on, or the gist of, IE prior talk. While such a design can be a device that IRs use to signal the closing of the ongoing topic, the recipient may orient to it as eliciting confirmation or agreement. By contrast, the adversative connectivedan(shi)in the turn-initial position prefaces either a wh-question or a yes/no question and brings forth a point of contrast and transition for questioning. As a practice with which IRs re-direct the IE’s response to a previous unaddressed concern with the agenda tightened, thedan(shi)-prefaced questions do not convey opposition or disagreement. Rather, they function to deal with the resumption in a way that renders it unproblematic. I argue that both types of connective-prefaced questions together with the responses they elicit demonstrate a particular kind of alignment between IRs and IEs in Chinese TV news interviews.
Conceptual structuring of the English prepositionsbetween, among, andamid, and their Spanish equivalententre
Authors: Morras Javier , Barcelona Antonio
Published: July 2019

Spatial language has been traditionally understood as encoding purely spatio-geometric information. However, much more than that must be considered for a full account of the semantics of space. It turns out that spatial arrangements manifest functional consequences which are non-spatial, so prepositional vehicles cannot be equated solely with spatial elements (Vandeloise 1991,1994). These non-spatial parameters in turn, play a major role in spatial, non-spatial, and temporal conceptions. This provides solid ground to propose a motivation behind these types of meanings that prepositions usually convey. This paper attempts to show how theconceptual basisfor each preposition proposed, is a key component within conceptual processes such as elaboration and extension (Langacker 1987). Such an analysis provides a better understanding of the spatial configuration of the English and Spanish prepositions, as well as an account for the semantic extension of non-spatial and temporal conceptions. Using a corpus-driven methodology to evidence the prepositions’ use types, the results obtained favor the hypothesis that non-spatial conceptions are ultimately motivated by spatial ones. This in turn, shows the language-specific character of parameterization due to the clear differences that exist between the English prepositionsbetween, among, andamid, and their Spanish equivalententre. The cognitive linguistic analysis showed in this research may also offer a new perspective in the area of Language Teaching. The paper concludes with suggestions for further research on the plausibility of psycholinguistic validation and pedagogical applications of the conceptual bases proposed.
Communicating attitudes through metaphor
Authors: Cibulskienė Jurga
Published: July 2019

Metaphor analysis in real-world discourse is increasingly becoming the focus of many cognitive studies. Accordingly, this paper seeks to investigate how euro adoption in Lithuania in 2015 was metaphorically communicated by the media. The study is carried out within the framework of Critical Metaphor Analysis (CMA), which was developed byCharteris-Black (2005, 2011),Musolff (2008),Hart (2010). Thus, a three-step metaphor analysis procedure (Identified→ Interpreted→ Explained) was employed in order to analyze the attitude towards euro adoption presented in Lithuanian media. The findings show that the euro is most frequently conceptualized as aliving organismwith different scenarios (active agentandpassive agent) being realized linguistically. In the final stage – explanation – metaphors were analyzed from a rhetorical perspective, which means that an attempt was made to look into how metaphors communicate positive or negative attitudes about euro adoption in the media. The results demonstrate that personification of the euro makes the idea of euro adoption more understandable, it activates a range of emotions and evaluates it. This leads to further insights about the way the media exercises its power in an attempt to persuade people and manipulate their attitudes, emotions and opinions.
Oral discourse competence-in-performance
Authors: Cañada Maria Dolors , López-Ferrero Carmen
Published: July 2019

Mastering 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.
A New Model of Ferroelectric Phase Transition with Neglectable Tunneling Effect*
Authors: Yin Hong-Mei , Zhou Heng-Wei , Huang Yi-Neng
Published: July 2019

Due to the obvious deviations of the existing theoretical models from the experimental results of ferroelectric phase transition, a new model is proposed on the basis of the coupling between spontaneous polarization and spontaneous strain in ferroelectrics. The spontaneous polarization and specific heat of ferroelectric phase transition predicted by the model are in better agreement with the corresponding data of triglyceride sulfate, a typical ferroelectric. In addition, the model predicts a new type of ferroelectric in which a phase transition and a phase-like transition coexist.
Demonstration of a Sub-Sampling Phase Lock Loop Based Microwave Source for Reducing Dick Effect in Atomic Clocks*
Authors: Li Wen-Bing , Hao Qiang , Du Yuan-Bo , Huang Shao-Qing , Yun Peter , Lu Ze-Huang
Published: July 2019

We demonstrate a simple scheme of 6.835 GHz microwave source based on the sub-sampling phase lock loop (PLL). A dielectric resonant oscillator of 6.8 GHz is directly phase locked to an ultra-low phase noise 100 MHz oven controlled crystal oscillator (OCXO) utilizing the sub-sampling PLL. Then the 6.8 GHz is mixed with 35 MHz from an direct digital synthesizer (DDS) which is also referenced to the 100 MHZ OCXO to generate the final 6.835 GHz signal. Benefiting from the sub-sampling PLL, the processes of frequency multiplication, which are usually necessary in the development of a microwave source, are greatly simplified. The architecture of the microwave source is pretty simple. Correspondingly, its power consumption and cost are low. The absolute phase noises of the 6.835 GHz output signal are −47 dBc/Hz, −77 dBc/Hz, −104 dBc/Hz and −121 dBc/Hz at 1 Hz, 10 Hz, 100 Hz and 1 kHz offset frequencies, respectively. The frequency stability limited by the phase noise through the Dick effect is theoretically estimated to be better than 5.0 × 10−14τ1/2 when it is used as the local oscillator of the Rb atomic clocks. This low phase noise microwave source can also be used in other experiments of precision measurement physics.
Secular Motion Frequencies of 9Be+ Ions and 40Ca+ Ions in Bi-component Coulomb Crystals*
Authors: Li Hai-Xia , Li Min , Zhang Qian-Yu , Tong Xin
Published: July 2019

We obtain bi-component Coulomb crystals using laser-cooled 40Ca+ ions to sympathetically cool 9Be+ ions in a linear Paul trap. The shell structures of the bi-component Coulomb crystals are investigated. The secular motion frequencies of the two different ions are determined and compared with those in the single-component Coulomb crystals. In the radial direction, the resonant motion frequencies of the two ionic species shift toward each other due to the strong motion coupling in the ion trap. In the axial direction, the motion frequency of the laser-cooled 40Ca+ is impervious to the sympathetically cooled 9Be+ ions because the spatially separation of the two different ionic species leads to the weak motion coupling in the axial direction.
Generation of Gaussian-Shape Single Photons for High Efficiency Quantum Storage*
Authors: Li Jian-Feng , Wang Yun-Fei , Su Ke-Yu , Liao Kai-Yu , Zhang Shan-Chao , Yan Hui , Zhu Shi-Liang
Published: July 2019

We report the generation of heralded single photons with Gaussian-shape temporal waveforms through the spatial light modulation technique in an atomic ensemble. Both the full width at half maximum and the peak position of the Gaussian waveform can be controlled while the single photon nature holds well. We also analyze the bandwidth of the generated single photons in frequency domain and show how the sidebands of the frequency spectrum are modified by the shape of the temporal waveform. The generated single photons are especially suited for the realization of high efficiency quantum storage based on electromagnetically induced transparency.
Nanosecond Pulses Generation with Samarium Oxide Film Saturable Absorber*
Authors: Zulkipli N. F. , Batumalay M. , Samsamnun F. S. M. , Mahyuddin M. B. H. , Hanafi E. , Izam T. F. T. M. N. , Khudus M. I. M. A. , Harun S. W.
Published: July 2019

Nanosecond pulse generation is demonstrated in a mode-locked erbium-doped fiber laser (EDFL) utilizing a samarium oxide (Sm2O3) film. The Sm2O3 film exhibits a modulation depth of 33%, which is suitable for mode-locking operation. The passively pulsed EDFL operates stably at 1569.8 nm within a pumping power from 109 to 146 mW. The train of generated output pulses has a pulse width of 356 nm repeated at a fundamental frequency of 0.97 MHz. The average output power of 3.91 mW is obtained at a pump power of 146 mW, corresponding to 4.0 nJ pulse energy. The experimental result indicates that the proposed Sm2O3 saturable absorber is viable for the construction of a flexible and reliably stable mode-locked pulsed fiber laser operating in the 1.5 μm region.
Magnetic and Electronic Properties of β-Graphyne Doped with Rare-Earth Atoms*
Authors: Ren Juan , Zhang Song-Bin , Liu Ping-Ping
Published: July 2019

Structural, electronic and magnetic properties of La-, Ce-, Pr-, Nd-, Pm-, Sm- and Eu-doped β-graphyne are investigated by comprehensive ab initio calculation based on density functional theory. The adsorption energies indicate that the dopings are suitable. The doped β-graphyne undergoes transition from semiconductor to metal. Furthermore, the doping of Nd, Pm, Sm and Eu atoms can induce magnetization. The results are useful for spintronics and the design of future electronic devices.
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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.
Sentence Similarity Computation in Question Answering Robot
Authors: Si Shijing , Zheng Weiguo , Zhou Liuyang , Zhang Mei
Published: July 2019

Computing semantic similarity between sentences or texts is vital in many natural language processing (NLP) tasks such as search, query suggestion, and question answering (QA). Many methods have been developed, based on lexical matching, distributional semantics, etc. However, lexical features, like string matching, fail to capture semantic similarity. In this research, our focus lies on the implementation of distributional representations and how to tune parameters when obtaining representations of words with commonly used word embedding techniques, e.g., Word2Vec and GloVe. We conduct experiments in the setting of Chinese semantic sentence matching tasks on the finance-domain. We examine the goodness of word embedding by both the cosine similarity of semantically similar sentence pairs and semantically dissimilar pairs. Based on our experiments, Word2Vec performs better than GloVe in the sense that Chinese character embedding from Word2Vec yield larger disparity of cosine distances between similar sentence pairs and dissimilar pairs. Also we report the optimal parameters for Word2Vec continuous bag-of-word (CBOW) through our trials, with window size being 6 and embedding dimension being 400, which can be good initial values for other projects.
Big Data Technology Progress And Development Trend
Authors: Jin Wei
Published: July 2019

In the era of Internet+, big data technology has been widely used in all walks of life, and has achieved good application results, including university education industry. From the perspective of the overall structure, big data technology can not only maintain campus network security, but also improve the university education platform, assist students to obtain valuable information, and promote effective communication between teachers and students. This article will layer on the progress and development of big data technology, and put forward some personal opinions.
Fourier transform and correlation analysis for CSEM data processing
Authors: Li Guang , Xu Congcong , Li Jin , Mu Liangyin , Lin Huangzhou , He Jinjian , Liu Jun
Published: July 2019

Controlled Source Electromagnetic Method (CSEM) has the advantages of large depth of exploration and high efficiency. It has a wide range of applications in resource exploration and engineering surveys. However, CSEM data is often contaminated by strong cultural noise. In this paper, a novel method for CSEM data processing is proposed by combining the Fourier transform and correlation analysis. First, the observed data is performed by the Fourier transform, and the power-line noises are accurately removed in the frequency-domain. Second, the inverse Fourier transform is performed to the de-noised spectrum. Third, the correlations between transmitted and received data are calculated to quantitatively evaluate the data quality. Finally, high quality received data are selected by setting a proper threshold of correlation. We applied our approach to measured CSEM data. As a conclusion, the results obtained using our scheme are greatly improved over the previous.
Study on Naphthalene Sulfonic Acid Formaldehyde Condensate by Ultraviolet Absorption Spectrum
Authors: Yan-Min Zhang
Published: July 2019

Naphthalene sulfonic acid formaldehyde condensate is a kind of surfactant with excellent performance, which is widely used in printing, dyeing, cement, paint and other industries. There are various analytical methods for naphthalene sulfonic acid formaldehyde condensate, such as optical density analysis, electrophoresis, chromatographic analysis and spectral analysis. A series of formaldehyde condensates were synthesized from naphthalene, formaldehyde solution and concentrated sulfuric acid solution. The products were qualitatively analyzed by infrared and ultraviolet absorption spectra.
Discrete Bare Bones Particle Swarm Optimization Algorithm for Solving Multidimensional Knapsack Problem
Authors: Liu Shengjian , Yang Yan , Luo Lin
Published: July 2019

Aiming at the characteristics of multi-dimensional knapsack problem, the widely used bare bones particle swarm optimization algorithm is discretized, and the traditional objective function based on large penalty parameters is improved. The infeasible solution is transformed into a feasible solution by using the repair mechanism. The typical examples of 10 multi-dimensional knapsack problems are simulated and compared with four intelligent optimization algorithms. The simulation results show that the discrete bare bones particle swarm optimization algorithm has good convergence efficiency, high precision and good robustness when solving multi-dimensional knapsack problem.
Mathematical analysis for phase noise characterization of pulse modulation signal
Authors: Peng Cuiling , Chen Xiaolong , Huan Huiting , Nian Fushun , Yang Baoguo
Published: July 2019

Pulse modulation is of great importance in radar system. The performance of pulse modulated oscillating signal is usually characterized by its phase noise. The phase noise of pulse modulated signal can be hardly measured by phase demodulation. The correlation between the carrier and modulated signal needs to be established for the purpose of noise characterization. In this work, a mathematical form of phase noise of pulse modulated signal was proposed in the frequency domain. After pulse modulation, phase noise distribution of the oscillator shifts and superimposes upon the harmonics of the modulating pulse. Experiments were carried out to verify the phase noise property. The obtained results show that by referring to the phase noise of carrier, the phase noise measured by instrument is in good agreement with the mathematical prediction. The phase noise of pulse width modulated signal can be well depicted by the proposed mathematical form.
Cluster analysis of Xi’an restaurants by Self-organizing maps
Authors: Kong Jie , Ren Meng
Published: July 2019

To investigate the segmentation features of restaurants in Xi’an, China, the Self-organizing maps are applied in this study to analyse the information of online reviews obtained from Dazhong Dianping, which is a famous Chinese social network. Through the clustering and visualization performed by Self-organizing maps, 10 segments of restaurants are identified and some representative features are summarized. The findings of this study could help managers to improve restaurant competitiveness, as well as customers’ decision making.
The cross-project defect prediction based on PSO and Feature Dependent Naive Bayes
Authors: Yao Zhexi , Sun Li , Zhang Tao , Wang Jinbo
Published: July 2019

The software defect prediction often assumes that the software under test has rich historical information, which is a harsh condition in reality. Cross-project defect prediction can predict projects with rare historical information by using historically informative projects. The differences in software architecture and code environment pose challenges to cross-project software defect prediction. Based on the characteristics of software defect prediction sets, this paper introduces a two-stage algorithm based on particle swarm optimization algorithm and Feature Dependent Naive Bayesian classifier.
Multi Channels Data Fusion Algorithm on Quantum Genetic Algorithm for Sealed Relays
Authors: Qian Xin , Wang Shujuan , Li Chao , Wang Guotao
Published: July 2019

Particle Impact Noise Detection (PIND) is a screening test that must be done before the sealed relay is released. PIND signals are mostly occasional weak, which are difficult to measure and identify. In this paper, the three channel sensor is used to detect the remainder signals, and the weak signal is enhanced by weighted data fusion. For the first time, quantum genetic algorithm (QGA) is used to self-adaptively configure the weight, taking the place of arti-ficial settings. Experiments show that after data fusion, and the variance is only about 20% of the single input signal, which verifies the effectiveness of the algorithm. The computational complexity of QGA is offered.
Research on Security Protocol of RFID System Based on Public Key Cryptography
Authors: Wang Song , Zhang Bo
Published: July 2019

As one of the key technologies of the Internet of Things, RFID technology has increasingly become a part of people’s daily life. Because of the openness of the RFID system, its security problem becomes more and more serious. This paper improves the public key encryption authentication protocol and proposes a new protocol scheme. This scheme can provide better security authentication for the RFID system by using random number and session key, and it can satisfy the requirements of the RFID system in performance.
Research on Missile Data Security Based on Blockchain
Authors: Wang Yidong , Cong Linhu , Fang Yi , Deng Jianqiu , Chen Yuliang
Published: July 2019

Existing aviation missile business data records and storage have the disadvantage of being tampered with easily, being traced difficultly, and other security risks. Aiming at these problems, this paper applies blockchain technology to the data recording and storage scene of aviation missile business, carries on the network structure design, uses the current mainstream encryption algorithm and the encryption technology, constructs the block chain based aviation missile service data recording storage system, and describes the system working principle and how the system protects the data. Security analysis shows that the system can effectively protect the security record and storage of data, and lays a certain foundation for further exploring the application of blockchain in military.
Research on Intelligent Campus Monitoring Management System Based on Deep Neural Network Algorithm
Authors: Liu Xia , Wang Xuelong , Ren ChangLin
Published: July 2019

With the development of the economy and the advancement of science and technology, the informationization of education management has become an inevitable trend, and the construction of a intelligent campus cannot be delayed. In order to comply with the current social development, major universities have invested heavily in IoT equipment to improve the management level of the school. Based on the large number of video cameras installed in colleges and universities, this paper uses the monitoring image big data and the CNN algorithm to train a set of graphical features that are easy to manage, without adding additional hardware purchases. In addition, combined with the camera position and other information, an intelligent campus monitoring system is built to help the campus administrator to understand the people flow, traffic flow and physical condition in real time, which is convenient for enhancing the effective monitoring and management of campus crowds, environment and security.
Study on Optimization of automatic train operation based on Grey genetic algorithm
Authors: Gao Fan , Li Fan , Yu Zhe , Wang Huihui
Published: July 2019

The speed controller is the kernel module of Automatic Train Operation system, and is also a key core technology of the intelligent high-speed train. The research of the intelligent speed controller of ATO system is of great significance for automatic high-speed train operation. Through the analysis of the principle and function of CTCS-3 system, the scheme of adding the speed controller of ATO system in CTCS-3 system was proposed. The connection way between the speed controller of ATO system and ground equipment was designed to realize information interaction. The model of speed controller of ATO system for high-speed trains which is researched by grey system theory was used for prediction and decision making. In the grey prediction module, the metabolic GM (1,1) model was established, and the optimal strategy was generated by the multi-objective intelligent weighted grey target decision. Finally, a reasonable control strategy of train automatic operation was obtained. The optimal control strategy was got by using genetic algorithm. Designing software for the simulation test, the simulation results show that the method achieves automatic high-speed train operation under the CTCS-3+ATO system through the actual line data, and the efficiency of train operation, the energy saving index and all the performance indexes of the train were improved.
Research and Analysis in Fine-grained Sentiment of Film Reviews Based on Deep Learning
Authors: Zheng Jin , Zheng Limin , Yang Lu
Published: July 2019

Films are one of the main entertainment ways for people. By exploring, analyzing and summarizing the reviews that people published on the internet, audiences can make better viewing choices, while investors can get a more convenient way to understand the audience’s feedback. The text proposes a method of deep learning to perform fine-grained sentiment analysis on the film reviews, and restores the user’s real emotion as much as possible. The method first preprocesses the data, and converts the words into vectors using the Word2Vec model, then inputs the word sequence in the Long Short-Term Memory network (LSTM) to learn the semantic dependence. Finally, the logical regression classifier is used to classify. Compared with Naive Bayes (NB), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Back Propagation Neural Network (BPNN), and Convolutional Neural Network (CNN) models, the method achieves 83.6% accuracy in the binary classification, and 76.1% and 51.2% accuracy in the positive and negative fine-grained emotional classification, which has achieved the best results proved by experiments.
Sleep Quality Assessment of the Elderly Based on Intelligent Mattress Monitoring Data
Authors: Huang Yongfeng , Xiao Bo , Liang Liwei
Published: July 2019

Due to the special nature of the elderly in nursing homes, their sleep problems are difficult to evaluate conveniently and in a timely manner. Based on the guardian data of smart mattresses in nursing homes, according to the sleep characteristics of the elderly, combined with the opinions of medical experts, the Analytic Hierarchy Process(AHP) was used to construct the sleep evaluation model for the elderly in nursing homes. The results of sleep evaluation model is compared with the results of the professional sleep evaluation scale. The correlation coefficient between Pearson Correlation Coefficient and Spearman Correlation Coefficient is 0.930 and 0.956, respectively, The experimental results show that there is a strong correlation between the two. And consistency, proved the reliability of this model.