bluuebunny/crossref_metadata_2025_split huggingface dataset:
An universal GMMs-based sample strategy and collision checker for robot motion planning
Authors: Zha Fusheng , Dai Xuehan , Guo Wei , Liu Yizhou 
Published: August 2019

Abstract
The sampling-based motion planning methods acquire obstacle information by performing collision detection for a large number of samples, which can effectively solve autonomous obstacle avoidance problem in the high-dimensional configuration space. In order to improve the efficiency of planning, this paper proposes a new adaptive sampling strategy and collision checker based on Gaussian Mixture Models(GMMs): For the "narrow corridor" problem, the sample set obtained by Gaussian sampling strategy of adjustable standard deviation is used to train the GMMs. The models fitting the target area in the manipulator configuration space can guide the adaptive sampling; using the GMMs fitting the obstacle region to predict the collision probability of the samples rapidly, and using Greedy K-means initializes the EM algorithm to improve the fitting accuracy of the model. Finally, the sampling strategy and collision detection method are combined with various sampling-based motion planning algorithms, and multiple simulation experiments are carried out to verify the results. The results show that the proposed method has significantly improved planning efficiency compared with the traditional method.
A method of evaluating performance of missile three-loop autopilot
Authors: Sun Xueyang , Chen Wei , He Li 
Published: August 2019

Abstract
Three-loop autopilot is widely used in missile acceleration control. The parameters of the autopilot influence the performance of the autopilot in both frequency-domain and time-domain. However, what we know about the influences are quite qualitative, such as that angular speed feedback parameter provides additional damping to the missile. Problems appear if the control parameters cannot satisfy all the requirements of the autopilot. Based on the qualitative conclusions, it is impossible to meet the frequency-domain or time-domain performance requirements by adjusting the control parameters. This paper provides a method to obtain the first order time constant of the autopilot and frequency-domain performance such as amplitude margin and phase margin of the autopilot. The method can be used to make a rapid evaluation of missile three-loop autopilot performance and provides theoretical guidance to optimize control parameters.
A Novel Wheel Skid Control Based On Motor Energy Distribution Model
Authors: Zhou Qiang , Yin Dejun 
Published: August 2019

Abstract
How to realize wheel slip control with parameters that can be measured and not relying on hardware precision is a difficult problem in vehicle traction control. From the point of view of energy transfer, this paper uses the feature that the rotational kinetic energy of the wheel increases abnormally when slipping, and proposes a wheel slip control method based on the motor energy distribution model. This method only requires the motor phase voltage, phase current and wheel speed that are easy to measure. In this paper, a complete vector control model of permanent magnet synchronous motor is established, and a PI control algorithm framework is built based on one-wheel vehicle model. The simulation results verify the effectiveness of the proposed algorithm.
Research on Variable Structure High Voltage Power Supply Control Strategy Based on Predictive PI control algorithm
Authors: Li Jiaqiang , Huang Yiyun , Pan Shengming , Feng Hulin , Wang Denghui , Lei Hong 
Published: August 2019

Abstract
The research and verification of a variable structure high voltage power supply unit and its control strategy are introduced. According to the mathematical modeling method, the variable structure system is linearized equivalent analysis and closed-loop system design. The actual parameter verification and theoretical verification of the system are carried out by means of experimental identification, and the research of subsequent control strategies is guided. According to the analysis results and the dynamic parameters of the power supply, a control strategy based on Predictive PI is proposed and simulated. In addition, in order to realize the actual verification of the power supply control algorithm, a power controller based on the ARM and FPGA architecture is designed to be applied to the system. Experiments show that the control strategy can solve the complex variation of the nonlinear and variable structure of the power supply under dynamic conditions, and ensure that the system completes the established parameter indicators.
Research on Programmable Logic Controller Security
Authors: Wu Haolan , Geng Yangyang , Liu Ke , Liu Wenwen 
Published: August 2019

Abstract
With the convergence of computer technology and industrial networks, attackers are not limited to attacking only individual users’ computers, turning to attack industrial control systems that can cause major infrastructure problems. Programmable Logic Controllers (PLC) are the core components of industrial control systems. Its safety has a profound impact on the safety of the entire industrial system. This paper firstly classifies the security research of PLC according to the structure and function, and expounds the existing security defects of PLC from the aspects of firmware security, operation security and program security. Then it summarizes and analyzes four types of security protection measures: the integrity of verification firmware, protocol security encryption, code formal verification, and program security defence detection. Finally, according to the overall safety of the industrial system and the actual development of the current PLC, we discuss the development trend of safety research.
Joint Resource Allocation and Power Control Algorithm for D2D Based Train to Train Communication
Authors: Huan Luo , Xiaojuan Liu , Yingying Xin , Chunlin Fang 
Published: August 2019

Abstract
The next generation Communication based train control (CBTC) system has many new features, one of which is the introduction of train-to-train (T2T) communication. T2T communication can be realized by device-to-device (D2D) communication based on long-term evolution (LTE). However, D2D communications may generate interference in the system if not designed properly. In this paper, a joint resource allocation and power control algorithm is proposed to maximize the overall network throughput while guaranteeing the quality-of-service (QoS) requirements for both T2T links and cellular links. The algorithm has two steps. The first step is to allocate resources according to channel state information (CSI), the second step is to allocate power while maintaining system performance. Simulation results show that compared with random resource allocation, proposed approach provides a significant improvement in the system performance.
Multi-objective Comprehensive Optimization of Distribution Network considering the randomness of DG
Authors: Gao Haishu , Ji Xingquan , Li Kejun , Wu Na 
Published: August 2019

Abstract
In recent years, distributed generation technology develops rapidly due to its’ flexible and environment-friendly nature. In order to better analyze the impact of DG on the economics and safety of distribution networks, a probability model for random load, micro gas turbines and photovoltaic power generation system is formulated. With the objective of minimizing the network loss, lowest static insecurity probability, and the lowest cost of purchasing electricity, the optimization of distribution network with distributed generation is carried out by adjusting the distribution network topology and the output of controllable DG. The stochastic power flow is combined with the particle swarm optimization algorithm to obtain the Pareto non-inferior solution set, and then the subject is selected to obtain the optimal solution. Finally, simulations are carried out on the IEEE 33-bus test system and it is shown that the optimized network can effectively reduce the network loss and static insecurity probability on the basis of low cost of purchasing electricity.
An Inproved Up-scaling Algorithm Combined TSA and PSF
Authors: Bai Xuejiao , Sang Lingzhi , Bai Guichen , Kang Hongxia , Liu Zhen 
Published: August 2019

Abstract
Taking the Guanzhong Plain of Shanxi Province as the research area, the combine method of trend surface analysis method (TSA) and point spread function (PSF) (TSA+PSF) were used to up-scale the vegetation temperature condition index (VTCI) retrieved from Landsat 8 images (Landsat-VTCI) from a finer resolution to a coarser resolution. The up-scaled results were compared with VTCI images retrieved from Aqua MODIS (MODIS-VTCI) to provide technical support for the comprehensive application of drought monitoring results on two spatial scales. Meanwhile, a range of indicators, such as the semivariogram function (SVF), the structural similarity (SSIM), the correlation coefficients (r), root mean square errors (RMSE) were used to systematically compared the up-scaled methods. The results show that TSA+PSF performed better than TSA in terms of SSIM, the correlation and RMSE, the up-scaling model TSA+PSF has the higher accuracy, and it is more effective and robust than TSA. The model that uses PSF to analyze trend surface constructed by TSA is an improvement for up-scaling Landsat- VTCI images from a finer resolutions to a coarser resolutions.
Application Research of Banker Algorithm in Teaching Arrangement in Independent College
Authors: Jiang LI 
Published: August 2019

Abstract
Independent colleges are an important part of private higher education. There are many kinds of elective courses for undergraduates. Students are multi-disciplinary and have a large number of students across the grades. The limited resources at the end of the semester are facing enormous challenges. The banker algorithm is a dynamic strategy to eliminate deadlock algorithms. It can effectively and reasonably arrange the resources already in the system. This paper mainly discusses the application of the algorithm in the course scheduling system for the elective course classroom arrangement, so that each classroom can get full and reasonable application.
An improved index for clustering validation based on Silhouette index and Calinski-Harabasz index
Authors: Wang Xu , Xu Yusheng 
Published: August 2019

AbstractThe evaluation of clustering effects has been an important issue for a long time. How to effectively evaluate the clustering results of clustering algorithms is the key to the problem. The clustering effect evaluation is generally divided into internal clustering effect evaluation and external clustering effect evaluation. This paper focuses on the internal clustering effect evaluation, and proposes an improved index based on the Silhouette index and the Calinski-Harabasz index: Peak Weight Index (PWI). PWI combines the characteristics of Silhouette index and Calinski-Harabasz index, and takes the peak value of the two indexes as the impact point and gives appropriate weight within a certain range. Silhouette index and Calinski-Harabasz index will help improve the fluctuation of clustering results in the data set. Through the simulation experiments on four self-built influence data sets and two real data sets, it will prove that the PWI has excellent evaluation of clustering results.
Path Planning Research Based on An Improved A* Algorithmfor Mobile Robot
Authors: Xin Wang , Wanlin Lu , Chao Feng , Likai Hao 
Published: August 2019

Abstract
With the development of technology, the path planning technology of mobile robots has received extensive attention. The principle and process of A* algorithm are outlined. Because there are many break points in the A* algorithm, the path is not smooth and there are too many problems in searching for grid points. So we need improve the A-star algorithm. Firstly, in order to reduce the number of search grid points, a threshold value N is added to the openlist. If the number of search times is greater than N and the first node inserted is not expanded, the node is set to the highest priority. Secondly, we use the path planning based on the combination ofFloyd algorithm and A* algorithm to remove redundant nodes and reduce the sharpness of the breakpoints. Finally, the geometric optimization process results in a smooth path. Simulations verify that the improved A* algorithm reduces the path length and the path is smoother, more suitable for robot navigation.
Simulation and Experimental Research on Underwater Target HBT Interference Positioning Method
Authors: Zou Jing , Nie Lei , Jiang ChuanKai , Liu Mengran 
Published: August 2019

Abstract
To realize the positioning of underwater sound sources, a target positioning method based on acoustic field HBT interference is proposed. The precision of HBT interferometric target locating principle is verified by simulation under different parameters. The positioning effect is simulation analyzed at different frequencies with multiple sound sources. The results show that the position of the sound source can be found accurately by this method for single frequency source and multiple sources. At the same time, the positioning experiment in lake is carried out. The results verify the correctness of HBT positioning method and realize the orientation of single and multiple frequencies with the level of 180 dB which the distance of the sound source is 59 meters.
Research on the College Students’ Ideological and Political Education in the vision of the Internet Plus
Authors: Zhao Guiyang 
Published: August 2019

Abstract
The technological revolution has pushed mankind into a new era -- the "Internet plus" era. With powerful functions and super charm, the Internet affects the development of human society. It also brings new opportunities and challenges for the college students’ ideological and political education. In the era of "Internet plus", it is a great responsibility and a glorious mission for ideological and political education. Colleges need constant self-development and innovation. Only in this way can we better serve the ideological and political education. This paper first analysis the characteristics of the Internet from the perspective. And then this paper explains the problems of ideological and political education in the Internet plus era with the method of social investigation. Finally, this paper puts forward the measures of ideological and political education mode reform and innovation.
Face recognition method with feature fusion and error feedback
Authors: Yeping Fan , Yu Li , Desheng Yang , Tao Wan , Dong Ma , Dian Jiao , Yiting Cai , Mengxian Chen 
Published: August 2019

Abstract
A face recognition method with feature fusion and error feedback is proposed to imitate human cognition process. The intelligent recognition mode with multi-level feedback from global to local and from coarse to fine is implemented. Firstly, based on the idea of feedback control, a multi-level feedback model of face recognition with performance index constraints and supervised learning under finite domain is established. Secondly, based on entropy theory and Stochastic Configuration Networks (SCN), a facial feature space and face image classification network model with multi-feature fusion and sufficient separability under certain feature performance conditions are established from the perspective of information theory. Thirdly, based on entropy theory and error theory, the face recognition error representation and calculation model under certain feature performance conditions is established. Finally, the adjustment index of facial feature performance based on recognition error is constructed, and the face recognition algorithm with feature fusion and error feedback is given out. Test and comparison experiments show that our method is effective and feasible.
Parameter Estimation via Deep Learning for Camera Localization
Authors: Chong Mina , Li Qiming , Li Jun 
Published: August 2019

Abstract
This paper proposes a method based on deep learning to estimate parameters for camera localization. The parameters are 6-DOF camera pose and regressed from a single RGB image by an end to end convolution neural network. The proposed network makes use of batch normalized method, which relieves the disappearance of gradient, leading to drastic improvements in convergence speed. In addition, inspired by decomposing convolutions, the network breaks large convolutions into more small convolutions to cascade, which reduces the computational complexity, and enhances network feature representations owing to adding a layer of convolution. This CNN-based method is able to learn effective feature for camera localization in state of motion blur and illumination changes, while the traditional SHIF-based methods fail. Experimental results on both indoor and outdoor public datasets show the improved network achieves an increase in accuracy, and outperforms with the compared methods.
An Improved Approach based on Balanced Keyword Weight to Traceability Recovery
Authors: Wang Xinye , Cao Qinghua , Sun Qing 
Published: August 2019

Abstract
Software traceability recovery has become more and more important to the software life cycle recent days with the increasing complexity of software system. However, it is a tedious and error-prone task by manual. Many researchers have devoted themselves in building and predicting traceability links. In this paper, we approach a novel method to calculate text similarity and improve our results by a learning to rank method. And a couple of experiments are conducted to verify our method.
Circadian Blood Pressure Variations Computed From 1.7 Million Measurements in an Acute Hospital Setting
Authors: Mahdi Adam , Watkinson Peter , McManus Richard J , Tarassenko Lionel 
Published: August 2019

Abstract

BACKGROUND
Knowledge of the circadian blood pressure (BP) variations in the acute hospital setting is very limited.

METHODS
This is a retrospective analysis of BP data for in-hospital patients stratified by age and sex. We used data collected with the help of a standardized electronic health record system between March 2014 and April 2018 on the adult general wards in 4 acute hospitals in Oxford, UK.

RESULTS
A total of 41,455 unique patient admissions with 1.7 million sets of vital-sign measurements have been included in the study. The typical 24-hour systolic BP profile (dipping pattern during sleep followed by a gradual increase during the day) was only seen in the younger age groups (up to 40–49 for men and 30–39 for women). For older age groups, there was a late nocturnal rise in systolic BP, the amplitude of which increased with age. The late nocturnal BP rise above the age of 50 was seen whether or not the patient was treated for or previously identified with hypertension.

CONCLUSION
Hospitalized patients’ circadian patterns of BP largely mirror those found in the community. High-quality hospital data may allow for the identification of patients at significant cardiovascular risk through either opportunistic screening or systematic screening.
Performance of gene expression analyses using de novo assembled transcripts in polyploid species
Authors: Chen Ling-Yun , Morales-Briones Diego F , Passow Courtney N , Yang Ya 
Published: August 2019

Abstract

Motivation
Quality of gene expression analyses using de novo assembled transcripts in species that experienced recent polyploidization remains unexplored.

Results
Differential gene expression (DGE) analyses using putative genes inferred by Trinity, Corset and Grouper performed slightly differently across five plant species that experienced various polyploidy histories. In species that lack recent polyploidy events that occurred in the past several millions of years, DGE analyses using de novo assembled transcriptomes identified 54–82% of the differentially expressed genes recovered by mapping reads to the reference genes. However, in species that experienced more recent polyploidy events, the percentage decreased to 21–65%. Gene co-expression network analyses using de novo assemblies versus mapping to the reference genes recovered the same module that significantly correlated with treatment in one species that lacks recent polyploidization.

Availability and implementation
Commands and scripts used in this study are available at https://bitbucket.org/lychen83/chen_et_al_2018_benchmark_dge/; Analysis files are available at Dryad doi: 10.5061/dryad.4p6n481.

Supplementary information
Supplementary data are available at Bioinformatics online.
Comparison of Real-World Treatment Outcomes With Vedolizumab Versus Infliximab in Biologic-Naive Patients With Inflammatory Bowel Disease
Authors: Patel Haridarshan , Latremouille-Viau Dominick , Burne Rebecca , Shi Sherry , Adsul Shashi 
Published: August 2019

Abstract

Background
Little is known about long-term real-world effectiveness of vedolizumab versus infliximab in biologic-naive patients with inflammatory bowel disease (IBD).

Methods
Biologic-naive IBD patients who received vedolizumab or infliximab in the US Explorys Universe database (May 2014–September 2018) were weighted using Entropy-balancing.

Results
Persistence rates were higher for vedolizumab (N = 542) versus infliximab (N = 1,179) cohort at 12 (84.5% vs 77.5%; P = 0.0061) and 24 (77.6% vs 64.6%; P = 0.0005) months post-maintenance therapy. Healthcare resource utilization composite end point rates were lower in vedolizumab versus infliximab cohort at 12 (36.2% vs 48.2%; P &lt; 0.0001) and 24 (46.9% vs 59.9%; P &lt; 0.0001) months post-treatment initiation.

Conclusions
Biologic-naive IBD patients who received vedolizumab had better long-term real-world effectiveness measures versus infliximab patients.
Impact of trainee involvement in esophagectomy on clinical outcomes: a narrative systematic review of the literature
Authors: Prasad P , Navidi M , Immanuel A , Griffin OBE S M , Phillips A W 
Published: August 2019

SUMMARY
Changes in the structure of surgical training have affected trainees’ operative experience. Performing an esophagectomy is being increasingly viewed as a complex technical skill attained after completion of the routine training pathway. This systematic review aimed to identify all studies analyzing the impact of trainee involvement in esophagectomy on clinical outcomes. A search of the major reference databases (Cochrane Library, MEDLINE, EMBASE) was performed with no time limits up to the date of the search (November 2017). Results were screened in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, and study quality assessed using the MINORS (Methodological Index for Non-Randomized Studies) criteria. Four studies that included a total of 42 trainees and 16 consultants were identified, which assessed trainee involvement in open esophagogastric resectional surgery. A total of 1109 patients underwent upper gastrointestinal procedures, of whom 904 patients underwent an esophagectomy. Preoperative characteristics, histology, neoadjuvant treatment, and overall length of hospital stay were comparable between groups. One study found higher rates of anastomotic leaks in procedures primarily performed by trainees as compared to consultants (P &lt; 0.01)—this did not affect overall morbidity or survival; however, overall anastomotic leak rates from the published data were 10.4% (trainee) versus 6.3% (trainer) (P = 0.10). A meta-analysis could not be performed due to the heterogeneity of data. The median MINORS score for the included studies was 13 (range 11–15). This study demonstrates that training can be achieved with excellent results in high-volume centers. This has important implications on the consent process and training delivered, as patients wish to be aware of the risks involved with surgery and can be reassured that appropriately supervised trainee involvement will not adversely affect outcomes.