bluuebunny/crossref_metadata_2025_split huggingface dataset:
Design and Implementation of Multi-parameter Healthcare System with Positioning Function
Authors: Chen Hanlin , Yin Jingyi 
Published: June 2019

Abstract
Based on multi-parameter physiological module CSN808 and GSM/GPRS engine SIM508 supporting GPS function, this paper presents a multi-parameter healthcare system with positioning function. The system can acquire ECG, respiration, blood pressure, body temperature signals and GPS position information of patients, analyse signals quickly and feedback diagnoses to patients. Under the circumstance of a sudden heart attack, the system can alarm automatically, and doctors in the healthcare center can guide patients’ self-treatment via GSM audio communication and take quick rescuing measures on the basis of patients’ GPS position information. To ensure the correctness of data transmission, Grøstl hash algorithm is realized to verify the integrity of data. This system can provide a round-the-clock, rapid-response, stable and reliable monitoring.
A Machine Learning-based Software Code Weakness Detect Approach
Authors: Lu AiGuo , Luo KangYi 
Published: June 2019

Abstract
In recent years, machine learning and deep learning have yielded immense success on computer vision, speech recognition and natural language processing. However, exploration of machine learning on software code weakness detect haven’t been fully investigated. Software source code could be thought of a kind of natural language but has the intrinsic difference from common natural language. In this work we propose a novel machine learning based approach to tackle the problem of software code weakness detection. Differing from traditional algorithm based tools, flawfinder, for example, we do not design the code weakness detection processing logics directly, instead we propose to use a variant version of Attribute-Relation File Format (ARFF) to preprocess the source code and utilize a state of the art classification algorithm in machine learning to build a unite code weakness detection model to learn the processing logic indirectly as a general framework. In order to exam the detection performance of our model, we collected a couple of datasets for each common weakness of Common Weakness Enumeration (CWE) List. Extensive results on these collected datasets show that our model achieves comparative results from traditional algorithm based tools in both false positive rate and false negative rate.
Research on Influencing Factors of College Students’ Intention of Online Health Information Behavior Based on Social Cognitive Theory
Authors: Kong Jia , Deng Sanhong , Zhang Yue 
Published: June 2019

Abstract
Based on the Social Cognition Theory, we constructed the influencing factors model of college students’ intention of online health information behavior from three levels of individual, society and information systems, which was analyzed by using the PLS-SEM. Research shows that self-efficacy, information service quality, social support, information literacy and information quality significantly influence college students’ intention of online health information behavior. However, the influence of perceived risk and information system quality is not significant.
The Development of High-Precision & High-Speed Synchronous Data Acquisition System in Vacuum-Thermal Test
Authors: Shao Jingyi , Ning Juan 
Published: June 2019

Abstract
The Vacuum-Thermal test is an important test to verify the correctness of the thermal design and ensure its long-term reliable operation during the development of the spacecraft. At present, the temperature measurement in the Vacuum-Thermal Test mostly adopts the serial mode to complete the data acquisition of the large data volume temperature sensor. This method balances performance and costs well. However, in some special circumstances, it cannot accurately reflect the instantaneous temperature of the test piece. Aiming at this problem, a high-precision and high-speed fully parallel data acquisition system is designed. Based on the accuracy of the original temperature data acquisition, high-speed synchronization technology is used to accurately acquire the transient temperature data of the spacecraft to verify the transient heat of the spacecraft. Features provide a data foundation.
An Intelligent Per-decision Method of State Grid Accidents in Big Data Environments
Authors: Li Dianyang , Tan Chen , Wang Hongzhe , Han Da , Qin Ling , Zhang GuangCheng , Lou Tianyue , Xiu Tian 
Published: June 2019

Abstract
Aiming at the problem of hard to per-alarm the state grid accidents in big data environment, this paper proposes an intelligent per-decision method of state grid accidents. This method divides the management of state grid data into two parts, i.e. analysis of state grid data and intelligent expert database. The part of analysis of state grid data consists of input layer, facility layer and accident layer. Establish the self-learning intelligent expert database by means of connecting weight values of input and output nodes and threshold values of output nodes. Compare with the per-data that comes from the part of analysis of state grid data and the data from intelligent expert database, then achieve the goal of per-decision of state grid accidents and dispatch the accidents. A case and simulation results show that this method is implementable. In addition, this method provides beneficial thinking to solve the state grid accidents per-alarm in big data environment.
An Intelligent Method for Expert Finding Based on Knowledge Organization Systems: Taking the Example of Oncology
Authors: Pei-yan Song , Dong-fang Wang , Yan Cao 
Published: June 2019

Abstract
In this paper, the experts are mapped and found through the concept and semantic relations of knowledge organization systems. First, a hierarchical model of expert description is designed based on the literature data and knowledge organization systems, as foundation of expert rapid finding, intelligent reasoning and dynamic updating. Then, 5 key steps are introduced based on knowledge organization systems, by which the research directions of experts can be identified accurately and visually in TF-IDF and LDA model. Finally, taking the example of Oncology, the experiment indicates that experts with the same or near research direction can be aggregated fast and effectively by semantic linkage compared with VSM agritourism. This method is expected to find out the most suitable experts by calculation and reasoning automatically.
Research on data cleaning technology based on instance level
Authors: Li Chuan , Hou Yunqi , Yu Zhang 
Published: June 2019

Abstract
In the era of current data explosion, data cleaning becomes an important part of data analysis, and it is also one of the important means to improve data quality. In this paper, the concept, principle, process, detection method and related cleaning algorithm of structural data cleaning are introduced in detail through the data cleaning technology based on instance level. In view of the outstanding data quality problems based on instance level, relevant experiment is designed, the operation and verification process of structural data cleaning will explain concretely through visual programming technology and machine learning algorithm. Finally, the research of data cleaning technology in the future is prospected.
Analysis of the normalization theory of intracavity anti-Stokes laser
Authors: Jintian Wang 
Published: June 2019

Abstract
Anti-Stokes laser generation is a frequency up conversion. It is a four-wave mixing process of two fundamental photons, one Stokes photon, and one anti-Stokes photon. So, the conversion efficiency of the anti-Stokes laser is low. Therefore, it is particularly important to guide experiments through theoretical optimizations. In this paper, the rate equations under plane wave approximation of intracavity anti-Stokes lasers are normalized. By numerically solving the normalized equations, a group of adaptable curves are obtained to describe the operation of the intracavity anti-Stokes lasers. The influences of the composite variables on the performance of the lasers are analysed.
An Endoscope Manipulating Robot Design
Authors: Xiaohui Xie , Xiuan Zhang , Lining Sun , Gongxian Wang , Yue Yu , Cheng Zhang , Xiaochen Zhou 
Published: June 2019

Abstract
This paper mainly studies a new type of endoscope manipulating robot to replace the nurse or assistant to manipulate and hold the endoscope in surgery. By analyzing the operating environment of minimally invasive surgery, the paper presented the basic requirements of the endoscope manipulating mechanism design, and developed a endoscope manipulating system with seven degree of freedom. In order to meet the intraoperative spatially invariant point required by the minimally invasive surgery, a new romote-center-of- motion(RCM) mechanism, parallelogram RCM mechanism, was designed by improving composite parallelogram mechanism. In addition, a wire-driven modular joint with single-degree-of- freedom was also developed, which has been used for the endoscope operating in-out the human body. The motion test of RCM mechanism shows that the robot has good flexibility and can fully meet the design requirements of the endoscope manipulating mechanism.
Research on Intelligent Decision-Making Method of Enterprise Financial Crisis Early Warning
Authors: Yuan Ziyan , Hou Yan 
Published: June 2019

Abstract
Many situations in the crisis of enterprise development are caused by financial crisis. This situation not only makes the enterprise suffer great economic losses, but also affects the normal production and operation of the enterprise. Therefore, in the face of this situation, how can we timely and accurately warn the financial crisis of the enterprise? This is the problem we need to solve. This paper puts forward the enterprise finance. Intelligent decision-making method of crisis early warning is expected to provide theoretical support for dealing with financial crisis of enterprises.
The Analysis of Heart Rate Fragmentation for Congestive Heart Failure
Authors: Yiqi Wang 
Published: June 2019

Abstract

Background: Congestive heart failure (CHF), also known as chronic heart failure, is the end stage of all kinds of cardiovascular diseases with high mortality. Heart rate fragmentation (HRF) indices may be a potentially valid approach to diagnose CHF.

Objective: The aims of this study were to: (1) find out the differences of HRF indices between healthy subjects and patients with CHF; (2) explore whether HRF indices can be applied to diagnose CHF.

Methods: Open-access cardiac interbeat (RR) interval databases (Physiobank) were introduced here. Twenty subjects were selected from CHF RR interval database and normal sinus rhythm RR interval database, and included into CHF group and healthy group respectively. Then the values of PIP, IALS, PSS, and PAS were calculated and compared according to these 40 subjects. Statistic difference between two groups on same indice was computed.

Results: PIP (Healthy vs CHF, 0.72 VS 0.77, P=0.006), IALS (0.72 VS 0.78, P=0.0036), PSS (0.86 VS 0.95, P=0.0008), and PAS (0.11 VS 0.12, P=0.8392) of CHF group are significantly higher than that in healthy group.

Conclusion: HRF indices could be used as an efficient and easy tool to diagnose CHF. What’s more, HRF indices are a valuable approach to analyse heart rate.
Real-Time Data Analysis and Processing Based on UDP Communication Platform Based on LabVIEW
Authors: Liu Wenjing , Li Zhi , Wang Jianguo 
Published: June 2019

Abstract
In order to solve the problem that the portable data acquisition device cannot analyze the on-site data.Design a processing, analysis, and display scheme for transmitting critical data blocks to a computer with processing capabilities through network transmission. The UDP communication method based on LabVIEW is proposed to realize the data analysis and processing method in the professional computer calling MATLAB through network transmission. The method not only realizes the data analysis and processing function without replacing the hardware device, but also has a simple implementation method and a short development cycle. Therefore, the method provides a solution for real-time data processing of the portable data acquisition device system.
A Method of Characterizing the Filling Power of Cut Tobacco Through the Cigarette Maker Parameters
Authors: Yuliang Li , Shuai Yang , Lihong Zhang , Qiang Zhu , Yucan Qiu , Ming Li 
Published: June 2019

Abstract
Filling power is one of the important parameters to characterize the physical structure of cut tobacco. At present, the detection method of cut tobacco filling power cannot reflect the true filling power value of tobacco in real time and accurately, so an intelligent online filling power detection method of the cigarette machine is designed. According to the mechanical position of the suction forming part and the position parameters of the suction belt of the cigarette maker, the linear regression relationship between simulated filling power value and standard filling power value was obtained, the regression relation is applied to the cigarette manufacturing process, then calculate filling power value of cut tobacco in real time. This method has the following advantages:1. in real time;2. reflecting the abnormality of tobacco structure in the cigarette manufacturing process when the filling power exceeds a certain range;3. realizing the linkage between the change of cigarette cut tobacco structure and the physical indicators of cigarettes, then guaranteeing the stability of mainstream smoke chemical indicators and sensory intrinsic quality.
An Overview of the Application on Big Data Technology in Intelligent IOV
Authors: Wan Xing 
Published: June 2019

Abstract
The traditional automotive industry is currently moving towards intelligent and informational technology. IOV (Internet of Vehicles) technology is the latest technology which can adapt to the future. At present, IOV technology faces many unresolved technical problems, and one of the core technologies is big data technology. This paper introduces the application of big data technology in intelligent IOV, and introduces various aspects of big data technology in IOV.
Data And Content Analysis For Social Network Using LDA Text Model
Authors: Zhang Linxiang 
Published: June 2019

Abstract
WhatsApp is a popular cross-platform application for communicating and connecting people. In this paper, the author analyzes massive data from WhatsApp public groups and obtains so-called tacit knowledge and social complex knowledge. During the processing, the author uses LDA(Latent Dirichlet Allocation) model to analyze the content which helps us to be aware of many aspects from public groups such as social trend, sentiment analysis and other hidden information. In the end, author get the results about topic for each group and the occurrence of words for each topic.
The PEk Algorithm of Solving the Quasi-Block Tridiagonal Systems
Authors: Xuefei Lu , Fengjuan Dong 
Published: June 2019

Abstract
In this paper, the
PEk

method of solving special linear algebraic systems-block quasi-tridiagonal systems is presented. On the condition that the coefficient matrix is Hermitian positive definite, the solvability and convergence of the new method are proved, and the selection range for the parameters k is also given.
Whale Optimization Algorithm with Chaos Strategy and Weight Factor
Authors: Li Yintong , Han Tong , Han Bangjie , Zhao Hui , Wei Zhenglei 
Published: June 2019

Abstract
Whale optimization algorithm (WOA) is a novel optimization algorithm inspired by humpback whale hunting behavior. Due to the defect of unbalanced exploration and exploitation by using control parameter with linear change, WOA has slow convergence and is easy to fall into local optimum. Thus, a novel whale optimization algorithm with chaos strategy and weight factor (WOACW) is proposed to improve the convergence speed and accuracy. In this work, the chaos strategy is executed to initialize the population to enhance the diversity of the initial population. The weight factor is introduced to adjust the influence degree of the current optimal solution on the generation of new individuals in order to improve the convergence speed and accuracy. At the same time, the convergence factor is adjusted by cosine function to better balance the relationship between exploration and exploitation. In addition, using greedy strategy to fully retain the dominant individuals from the parents and the generated candidates to generate offspring, improves the convergence speed of the algorithm. To verify the performance of our approach, WOACW is benchmarked on 13 classical benchmark functions, and the statistical results are compared with the original WOA and three other WOA variants, IWOA, WOAWC, and two state-of-the-art algorithms, SSA, GWO. The experimental results and Wilcoxon signed ranks test show that WOACW has a higher convergence speed and precision than compared algorithms, which verifies the effectiveness of WOACW in this work.
Research of Ant Colony Algorithm Based on Multi-objective Optimization in Cloud Platform Virtual Machine Initialization
Authors: Wang Zhen , Du Jing , Miao Quanqiang , Cheng Ruosi 
Published: June 2019

Abstract
In order to solve the problem of resources waste in the process of virtual machine deployment in the cloud platform, we propose an ant colony algorithm based on multi-objective optimization. Firstly, the multi-objective optimization combination model is established. Then, we apply the model to ant colony algorithm. Finally, we modify the ant colony algorithm to adapt to cloud platform virtual machine initialization. In order to verify the effectiveness of the algorithm, cloudsim cloud simulation platform was used to carry out simulation experiments. The experimental results showed that the algorithm proposed in this paper could reach a relatively good level in SLA violation rate, power consumption, and resource loss of cloud platform compared with other commonly used algorithms.
An Approach Inspired from Nuclear Reaction Processes for Numerical Optimization
Authors: Wei Zheng-lei , Zhang Zhuo-ran , Huang Chang-qiang , Han Bo , Tang Shang-qin , Wang Le 
Published: June 2019

Abstract
As optimization problems become more complex, the need of new algorithms becomes greater. In this paper, a new powerful algorithm based on nuclear reaction process, namely, nuclear reaction optimization, is proposed for numerical optimization. The NRO algorithm which includes nuclear fission and fusion phases mimics the fission and fusion processes. In the first phase, the Gaussian walk and differential evolution operators are used for modeling fission process. In the second phase, the variants of differential evolution operators are employed for modeling the ionization stage and fusion stage. Additionally, six benchmark functions and unconstrained engineering design problem are evaluated by NRO and other compared algorithms. The optimization results indicate that the NRO has presented feasibility and superiority performance.
Personalized Diet Recommendation Based on K-means and Collaborative Filtering Algorithm
Authors: Yuan Zhicai , Luo Fang 
Published: June 2019

Abstract
With the improvement of people’s living standards, people pay more and more attention to the health of diet, and traditional dietary recommendations are difficult to meet the user’s dietary preferences and nutritional balance. This paper first uses the k-means clustering algorithm to divide the food set into multiple disjoint subsets, then uses the user-based collaborative filtering algorithm to recommend the food that the user may like. The recommended food and food in standard recipes set by user’s own situation are in the same cluster, which meets the user’s nutritional balance. The experimental results show that the recommended effect of this method is effective, and the recommended accuracy rate is over 70%.
An algorithm based on ABNL-MRF model for SAR image segmentation
Authors: Qingping Wang , Tao Xie , Boyuan Liu , Chang Wang , Naichang Yuan 
Published: June 2019

Abstract
In this letter, a segmentation method is proposed based on an adaptive Bayesian non-local MRF (ABNL-MRF) model. Aimed at the multiplicative speckle existing in SAR images, a patch-similarity measure based on a ratio of probability is introduced firstly. Then non-local similar pixel-blocks are adopted to guide the segmentation of the noisy image. However, non-local method over-smoothes edge regions and makes them inaccurate though it is robust for speckle. A rectification index is designed according to the homogeneity degree of local window. Based on the value of rectification index, a non-local constraint term is adaptively integrated into the potential function. Thus a suitable prior is defined that guarantees both the smoothness of the denoised image and the preservation of its structure. Experimental results demonstrate the very good performance of the proposed method.
ISAR Imaging Based on Block Sparse Smoothed L0 Norm Recovery Algorithm
Authors: Feng Junjie , Zhang Xuwen , Wang Yonghui 
Published: June 2019

Abstract
In order to obtain high resolution inverse synthetic aperture radar (ISAR) sparse images, a block sparse signal recovery ISAR imaging algorithm is proposed by considering the cluster characteristics of target in this paper. Firstly, the ISAR sparse imaging model is established, the imaging is converted to L0 norm optimization problem. Secondly, one negative exponential function sequence is used as smoothed function to approach the block L0 norm. Finally, the revised step is added to ensure solving the optimization problem along the steepest descent gradient direction and the cost function is updated for the next loop. Simulation results verify the proposed algorithm is effective.
Influence of feature scaling on convergence of gradient iterative algorithm
Authors: Wan Xing 
Published: June 2019

Abstract
Feature scaling is a method to unify self-variables or feature ranges in data. In data processing, it is usually used in data pre-processing. Because in the original data, the range of variables is very different. Feature scaling is a necessary step in the calculation of stochastic gradient descent. This paper takes the computer hardware data set maintained by UCI as an example, and compares the influence of normalization method and interval scaling method on the convergence of stochastic gradient descent by algorithm simulation. The result of study has a certain value on feature scaling.
A New Power Flow Algorithm for Hybrid AC/DC Power Grid
Authors: Li Jiawei , Han Xueshan , Li Wenbo , Jiang Zhe 
Published: June 2019

Abstract
Aiming at the problem of grid power flow calculation with VSC (Voltage Source Converter) unit in the context of the energy internet, this paper presents a new converter equivalent model. This study introduces a novel unified power flow algorithm for hybrid AC/DC power grids. The method simplifies the converter model by means of equivalent substitution and power conversion. The model better inherits the advantages of traditional AC power flow calculation. Finally, a unified iterative method is used to calculate an IEEE-57 node.