bluuebunny/crossref_metadata_2025_split huggingface dataset:
Non-LTE chemical abundances in Galactic open and globular clusters
Authors: Kovalev Mikhail , Bergemann Maria , Ting Yuan-Sen , Rix Hans-Walter 
Published: July 2019

Aims. We study the effects of non-local thermodynamic equilibrium (NLTE) on the determination of stellar parameters and abundances of Fe, Mg, and Ti from the medium-resolution spectra of FGK stars.
Methods. We extended the Payne fitting approach to draw on NLTE and LTE spectral models. These were used to analyse the spectra of the Gaia-ESO benchmark stars and the spectra of 742 stars in 13 open and globular clusters in the Milky Way: NGC 3532, NGC 5927, NGC 2243, NGC 104, NGC 1851, NGC 2808, NGC 362, M 2, NGC 6752, NGC 1904, NGC 4833, NGC 4372, and M15.
Results. Our approach accurately recovers effective temperatures, surface gravities, and abundances of the benchmark stars and clusters members. The differences between NLTE and LTE are significant in the metal-poor regime, [Fe/H] ≲ −1. The NLTE [Fe/H] values are systematically higher, whereas the average NLTE [Mg/Fe] abundance ratios are ∼0.15 dex lower, compared to LTE. Our LTE measurements of metallicities and abundances of stars in Galactic clusters are in a good agreement with the literature. Though, for most clusters, our study yields the first estimates of NLTE abundances of Fe, Mg, and Ti.
Conclusion. All clusters investigated in this work are homogeneous in Fe and Ti, with the intra-cluster abundance variations of less then 0.04 dex. NGC 2808, NGC 4833, M 2, and M 15 show significant dispersions in [Mg/Fe]. Contrary to common assumptions, the NLTE analysis changes the mean abundance ratios in the clusters, but it does not influence the intra-cluster abundance dispersions.
Irreducible Volar DRUJ Dislocation with Distal Radius Fracture Dislocation
Authors: Gulbrandsen Matthew T. , Putnam Jill G. , Watson J. Tracy , McKee Michael D. 
Published: July 2019

Abstract
Background Volar dislocations of the distal radioulnar joint (DRUJ) are rare and often missed during initial evaluation. Chronic dislocations and disability can occur when DRUJ dislocations are unrecognized and not reduced. DRUJ dislocations often occur with other wrist injuries, which may complicate reduction. Closed reduction can fail to reduce DRUJ dislocations, in which case open reduction is necessary.
Case Description This case describes a patient who had a volar dislocation of the DRUJ with an associated dorsal distal radius fracture dislocation. Initial attempts at closed reduction were unsuccessful which prompted surgical intervention. After open reduction and internal fixation of the distal radius fracture dislocation, closed reduction of the DRUJ remained unsuccessful. This prompted an open reduction of the DRUJ. Surgical exposure demonstrated that the extensor carpi ulnaris and the distal radius had prevented closed reduction of the DRUJ. Postoperatively, a splint was placed with the wrist in supination. The patient followed-up at the 2- and 4-month intervals with persistent subluxation. However, the patient also reported minimal pain and the ability to return to work and previous level of activity.
Literature Review Current literature regarding irreducible volar DRUJ dislocations with distal radius fracture dislocations includes sparse case reports, which are reviewed in this report.
Clinical Relevance This case illustrates successful treatment for an uncommon volar DRUJ dislocation associated with a dorsal distal radius fracture dislocation and can be utilized to help guide future treatment of similar complex cases.
The lyric present in English translations of Russian poetry
Authors: Piątkowska Józefina 
Published: July 2019

Abstract
Taking English translations of Anna Akhmatova’s poems as a case study, this article investigates whether the lyric
present (a specific use of simple present forms in poetry) is the preferred present tense in poetic translations from Russian into
English. Akhmatova’s verbal craft is remarkably relevant for the issue at hand because of her extensive exploration of temporal
levels. The article examines what stylistic effects stem from a translator’s choice between the lyric present and the present
progressive. In order to provide a more general view of English translations, the study includes data concerning the frequency of
progressives contained in two different English editions of Akhmatova’s poetry. These data are presented in the comparative
perspective, together with data collected from English and American poetry and from English renditions of several Russian
poets.
Parametric resonances and resonant delocalisation in quasi-phase matched photon-pair generation and quantum frequency conversion
Authors: Main Philip B , Mosley Peter J , Gorbach Andrey V 
Published: July 2019

Abstract
The existing widely-accepted theory of photon-pair generation via spontaneous down-conversion (SPDC) in nonlinear optical crystals and waveguides is incomplete, as it fails to account for the important physical phenomenon of parametric resonances. We demonstrate that exponential gain of classical fields in the regime of parametric resonance corresponds to resonant delocalisation in the Glauber–Fock model of quantum SPDC. We propose a quantitative measure of localisation of Floquet eigen-modes as an analogue of classical gain to identify regimes of resonant delocalisation. Using this method, we are able to reconstruct the classical ‘Arnold tongues’ map of domains of instabilities for SPDC. We also predict novel regimes of resonant delocalisation in the two-level model describing quantum frequency conversion processes.
Research on Sentiment Analysis of Chinese E-Commerce Comments Based on Deep Learning
Authors: Zhou Hanchen , Wu Gang 
Published: July 2019

Abstract
The analysis of emotional polarity of Chinese phrases in complex contexts has always been a problem in the field of machine learning. The emergence of Artificial Neural Networks has opened a window to solve this problem. Sentiment analysis has also become a hotspot in the research. This paper aims to solve this problem by introducing Attention mechanism to the Temporal Convolutional Nets (TCN) model. This paper chooses the Chinese commodity comment phrase on the E-commerce platform as the research object, to automatically analyse and judge the polarity (positive and negative) of each comment phrase. This paper optimized the design and constructed of the TCN Attention model, which made the TCN Attention model show superior performance in the area of sentiment analysis, and improved significantly compared with other models.
Improved Non-local Means Algorithm for Image Denosing
Authors: Li Menglong , Xu Yi 
Published: July 2019

Abstract
In order to solve the problem that Non-local means method (NLM) results in a weaker retention and noise immunity, an improved non-local means (INLM) is proposed. This paper introduces bilateral structure tensor combined with the spatial distance and the gradient distance to weight the structure tensor matrix. It has stronger noise immunity and can extract the texture structure more accurately. Mahalanobis distance is applied as a measure of the similarity of image pixels to suppress noise interference. Analyses and simulation results prove the validity of the proposed algorithm.
Two-person cooperative games on minimizing the makespan
Authors: Liu Lili , Gu Yanhong , Ren Han , Tang Guochun 
Published: July 2019

Abstract
This paper considers the problem of two-person cooperative games on minimizing the makespan. A special case of this problem is proved NP-hard, and a dynamic programming algorithm is presented for the general case, which runs in pseudo-polynomial time and indicates that this problem is binary NP-hard. This paper also adopts List Scheduling (LS) and Longest Processing Time (LPT) algorithms for classical parallel machines scheduling problem to cooperative game problem and develops the performance ratios of the algorithms.
Research on Path Planning Method of Humanoid Robot Based on Improved Genetic Algorithm
Authors: Zhan Xiaoyi 
Published: July 2019

Abstract
Mobile robot is a comprehensive subject developed rapidly in recent years. In the near future, robots may appear in many aspects of your life. Robots can replace humans to complete many tasks, among which it is very critical to accurately reach the destination, so the path planning of mobile robots has become a research hotspot in related fields.In this paper, the path planning technology of mobile robot based on genetic algorithm is studied. Based on the traditional method, some improved algorithms and new solutions are proposed to improve the computational efficiency of the algorithm and search an optimal path between the starting point and the target point.
Auto-Scaling Cloud Resources using LSTM and Reinforcement Learning to Guarantee Service-Level Agreements and Reduce Resource Costs
Authors: Zhong Jiang , Duan Saisai , Li Qing 
Published: July 2019

Abstract
Auto-Scaling cloud resources aim at responding to application demands by automatically scaling the compute resources at runtime to guarantee service-level agreements (SLAs) and reduce resource costs. Existing approaches often resort to predefined sets of rules to add/remove resources depending on the application usage. However, optimal adaptation rules are difficult to devise and generalize. A proactive approach is proposed to perform auto-scaling cloud resources in response to dynamic traffic changes. This paper applies Long Short-Term Memory (LSTM) to predicting the accurate number of requests in the next time and applies Reinforcement Learning (RL) to obtaining the optimal action to scale in or scale out virtual machines. To validate the proposal, experiments under two real-world workload traces are conducted, and the results show that the approach can ensure virtual machines to work steadily and can reduce SLA violations by up to 10%-30% compared with other approaches.
Research and Countermeasure of Network Education Teaching Based on Online Learning Behavior Data Analysis
Authors: Yang Shi 
Published: July 2019

Abstract
Compared with traditional teaching mode, network teaching has advantages, but its defects are obvious. This paper selected some samples and analyzed them according to certain standards, pointed out the shortcomings of modern network education teaching, and finally put forward some suggestions and measures from the aspects of education mode, resource integration, system norms and so on.
Arrhythmia classification based on multi-domain feature extraction
Authors: Yin Li , Chen Fumin , Zhang Qi , Ma Xu 
Published: July 2019

Abstract
Arrhythmia is a common abnormality of cardiac electrical activity. Arrhythmia classification has enormous significance for the clinical diagnosis of cardiovascular diseases. In this study, a method of multi-domain electrocardiogram feature extraction was put forward as to classify arrhythmia precisely. The RR intervals were extracted as time domain feature. The fifth level approximation coefficients of wavelet decomposition were adopted to represent frequency domain feature. Besides, the sample entropy values of six wavelet coefficients were employed as nonlinear feature. These three features were fed to classifier for automated diagnosis. Furthermore, ten-fold cross-validation scheme was adopted to train and test classifier whose parameters were optimized by genetic algorithm. In this study, eight classes of the most frequently occurring arrhythmia from MIT-BIH arrhythmia database were validated. The result turned out that the SVM classifier yields an average accuracy of 99.70%. Compared with the existing methods, the proposed method shows better results.
An Azimuth Frequency Domain NCS Algorithm for Missile-borne SAR
Authors: Zhang Yan , Shi Xiaomin , Zhang Mingxuan 
Published: July 2019

Abstract
SAR data in highly squint mode features large range walk and small range curvature. Therefore, an advanced Frequency Phase Filtering Algorithm based on line range walk correction is proposed in this paper. Firstly, range walk is removed in range frequency and azimuth time domain. Then, a chirp scaling (CS) algorithm is adopted to correct range curvature. Based on the above operation, a novel high-order of phase filtering factor is introduced into the azimuth time and frequency domain in order to correct the azimuth-dependence. Finally, the signal is focused in the Doppler domain by SPECtral Analysis technique. Simulation results illustrate that it satisfies the imaging quality of SAR in high squint mode and large scene swath.
Application Research of Evolutionary Algorithm in Synthesis of Reversible Logic Circuits
Authors: Han Jiaxin , Zhang Xin , Wang Xiaoxiao 
Published: July 2019

Abstract
In order to avoid the algorithm falling into premature convergence, a big mutation adaptive evolutionary algorithm for reversible logic circuit synthesis with tabu list is proposed. Big Mutation Variable Length Evolutionary Algorithm Reversible Logic Circuit (BM_VLEA_RLC) is based on Variable-Length Evolutionary Algorithm Reversible Logic Circuit (VLEA_RLC) algorithm that designs the corresponding fitness function, adaptive evolution probability, etc., and tests using benchmark functions. The experimental results show that the proposed algorithm can obtain several feasible solutions, and some solutions are better than the existing algorithms, which verifies the feasibility of the algorithm.
Propagation characteristics of underwater plasma pulse sound source
Authors: Chen Zhenyang , Yan Bing , Zhang Xiaobing 
Published: July 2019

Abstract
The signal propagation characteristics of underwater plasma pulsed sound source have important guiding significance for the research and application of underwater directional radiation technology. In this thesis, the model propagation method is used to analyze the signal propagation law of underwater plasma pulse source with different depths. Firstly, the propagation model of underwater plasma sound source is established. Secondly, the distribution characteristics of underwater sound field at different depths are simulated. The research results show that the simulation results can express the underwater sound field characteristics at different depths, which proves the effectiveness of the simulation model, and lays a foundation for further research on underwater pulse directional radiation technology and improving the underwater application of pulse sound source.
RETRACTED: Research on Network Information Security and Privacy Protection in the Age of Big Data
Authors: Gao Zhang 
Published: July 2019

Abstract
The rapid development of big data has brought more problems in network information security and privacy protection. This paper will study the specific network information security and privacy protection technologies in this context. The first part of this paper firstly discusses the connotation and characteristics of big data, and then puts forward the information security and privacy protection problems in the era of big data. The last part deeply studies how to solve the solutions corresponding to these problems.
Predict Consumers’ Automobile Purchase Behavior Based on the Preferences of Explicit Features and Implicit Topic
Authors: Yanan Du , Yang Qian 
Published: July 2019

Abstract
In order to know the role of online reviews in predicting consumers’ automobile purchasing behavior in the social network environment, this paper uses online reviews to construct a consumer interest preference model to obtain consumers’ explicit feature preferences and implicit topic preferences. Based on the preferences of consumers, introduce the tree structure to construct hierarchical prediction model to predict consumers’ purchase behavior. Meanwhile, consider the effect of online interactive comment on consumers’ automobile purchases. Several results are obtained in this paper:(1) The proposed hierarchical model introducing more information could achieve multi-granularity purchase-decision predicting;(2) the predictive effect based on implicit topic preference is better than that based on explicit feature preference; (3) integrating online interactive comments have positive effect in analyzing and predicting consumers’ purchasing behavior.
A Blind Recognition Algorithm for Digital Amplitude Modulated Signals
Authors: Li Zhengdong , Yang Cui , Wu Bin 
Published: July 2019

Abstract
A blind recognition Algorithm of amplitude modulation-ASK and QAM signals is proposed in this paper. Without requiring any prior information of the accepted signal, this algorithm employs the instantaneous amplitude of the incoming signal to recognize the modulation order, i.e., M, using the clustering centers of the amplitude. It is found that this new algorithm is practical and steady in recognition amplitude modulation signal in the presence of AWGN.
Process Security Sequence Improvement Algorithm Based on Banker Algorithm
Authors: Jiang Li 
Published: July 2019

Abstract
By analyzing the core idea of the banker’s algorithm and the essential meaning of the security state, an algorithm for applying multiple resources at a certain time in the system is proposed. The algorithm is implemented using object-oriented programming language C++. By analyzing security sequences and processes, the number of application resources can provide support for system resource allocation and process scheduling optimization. This algorithm can also be used as an improved implementation algorithm for deadlock detection algorithms or banker algorithms.
Exploration and Application of SPOC-based Belended Teaching Mode in Comprehensive English Course
Authors: Chen Jun 
Published: July 2019

Abstract
As the new direction of education reform in the “Internet +” epoch, the SPOC-based blended teaching mode can enrich the teaching content and meet the learning needs. Based on the SPOC teaching concept, this paper studies the advantages of the blended teaching mode and explores its application in the teaching of Comprehensive English course for English majors. Through teaching practice, it is found that the SPOC-based blended teaching mode can improve students’ enthusiasm for learning English, enhance their learning interaction, and finally optimize the effectiveness of English teaching. In view of this, through the study of the blended teaching mode in English teaching practice, this paper aims to provide useful enlightenment for the future implementation of SPOC-based blended teaching mode.
Application of Improved Decision Tree C4.5 Algorithms in the Judgment of Diabetes Diagnostic Effectiveness
Authors: Liu Jiawei , Ning Bo , Shi Daosheng 
Published: July 2019

Abstract
C4.5 algorithm needs to scan data sets repeatedly when constructing decision tree, which leads to its inefficient operation. A C4.5 decision tree optimization algorithm based on data dimension reduction is proposed, which generates a more concise decision tree and improves the efficiency of the algorithm. At the same time, it eliminates the interference of redundant attributes and improves the accuracy of the algorithm prediction.The simulation results of the improved C4.5 algorithm and the traditional algorithm show that the accuracy and efficiency of the improved C4.5 algorithm are greatly improved.This algorithm is applied to the prediction system of diabetes diagnosis effect, which provides decision support for the diagnosis of diabetes in hospitals, realizes better precise medical treatment, and makes better use of social medical resources.Successful application of diabetes diagnosis and treatment results also provides technical ideas for large data decision-making in other fields.
The Research on Internet Financial Flow Risk Measurement and Statistical Based on Analytic Hierarchy Process
Authors: Li Shuyi 
Published: July 2019

Abstract
As a decision-making method of qualitative and quantitative analysis, AHP has the advantages of flexibility, system, simplicity and convenience. It has important instrumental significance in the assessment of Internet financial liquidity risk. This paper adopts the concept and formation of Internet financial liquidity risk. The reason is discussed. On this basis, the analytic hierarchy process tool is introduced. The model is used as the carrier to measure and count the Internet financial risk, so as to provide a useful reference for the prevention and control of Internet financial flow risk.
Short-term and Fast Tracking Algorithm of Vehicle with Distance Information
Authors: Qi Shuaihui , Li Zhiyuan , Ma Jianfeng , Zhang Qinghui , Xu Shasha 
Published: July 2019

Abstract
To solve the contradiction between speed and performance in vehicle tracking, this paper designs a short-term and fast tracking algorithm which integrates vehicle distance information. Millimeter wave radar is used to get accurate range information to optimize the scale of vehicle, so as to achieve fast and accurate vehicle tracking. The effectiveness of the algorithm in scale optimization is proved by experiments.
Research and analysis of threshold segmentation algorithms in image processing
Authors: Niu Zuodong , Li Handong 
Published: July 2019

Abstract
Image segmentation is one of the most difficult and important tasks in digital image processing. The accuracy and effect of segmentation determine the final success or failure of the calculation and analysis process. Therefore, analysis and improvement on basic image segmentation algorithms should be paid attention to in a quite wide range of applications. This paper mainly introduces and studies the principle and characteristics of threshold segmentation algorithm, and analyses the application scenarios of global threshold segmentation and adaptive local threshold segmentation related algorithms, which has certain reference significance for digital image processing related research.
Business Anomaly Detection Based on QoS Benchmark of Resource-service Chain in Collaborative Task
Authors: Li Haibo , Tong Juncheng , Zhang Zheng , Yu Yongbo 
Published: July 2019

Abstract
To detect business anomaly caused by resource services in collaborative task, an approach based on QoS benchmark of resource-service chain is presented. Firstly, taking QoS of resource services as feature, the QoS benchmarks are obtained by clustering the relationships between the features of resource services in resource service chains. Then, thresholds of QoS benchmarks are calculated. A dynamic calibration strategy to the threshold is used to perform online detection of business anomaly in global and local views of a collaborative task. Finally, experiments and case studies show that the proposed approach has a high accuracy rate for business anomaly detection.
Research on network load balancing method based on simulated annealing algorithm and genetic algorithm
Authors: Yingzhuo Xu , Qing Yang Geng 
Published: July 2019

Abstract
Due to the high burstiness and high real-time performance of modern network load, it is difficult to meet the requirements of purely simulated annealing algorithm or genetic algorithm for network resource utilization and flow control problems, resulting in low network resource utilization. Congestion is serious. In order to make network load balancing more reasonable, a method of combining simulated annealing algorithm with genetic algorithm is proposed. Firstly, the genetic algorithm is used to globally search the network load balancing problem, so that the solution of the problem is quickly in the vicinity of the global optimal region. Then the simulated annealing algorithm is used to further local optimization near the global optimal region, and the optimal solution for the network load balancing problem is found. The simulation results show that the method improves the global search speed, improves the network resource utilization, and significantly improves the network load imbalance.