bluuebunny/crossref_metadata_2025_split huggingface dataset:
Linear Model of Information System of Industrial Processes in Crop Production
Authors: Redreev G V , Kiyko P V , Demchuk E V , Shchukina N V 
Published: October 2019

Abstract
the timeliness of information received during the implementation of any production process, as well as its qualitative composition, significantly affect the efficiency of this process. This is particularly important for agricultural production, as field operations are highly time-sensitive, both in terms of start-up and duration. The real possibility of a significant increase in the efficiency of production processes in crop production appeared at the current level of information technology and the spread of digitalization of various fields of activity. On the basis of existing methodological approaches to the system representation of objects of reality, we have developed an information system of the production process in crop production. The elements of the system are the amount of knowledge of specialists in the cultivation of crops, information about the composition of cultivation technologies, information about the objects processed in the implementation of production processes, recorded in any form replenished special knowledge, knowledge about the goals achieved in the implementation of production processes. Elements of the system are interconnected, developing in a certain way and, at the same time, limiting each other. The formalization of the relationships between elements of the information system allowed us to obtain ten equations with fifteen unknowns. To solve this system of equations, a set of simultaneous linear equations is presented. Five sets of simultaneous equations can be defined, depending on which of the relationships of the elements of the information system of the type fi
will be broken. The obtained solutions will allow to quantify the volume of elements of the information system, which makes it very promising to use information technology management of production processes in crop production.
Face Dynamic Modeling Based on Deep Learning and Feature Extraction
Authors: Tong Lijing , Yang Jinqiu , Lai Yuping , Xiao Zequn 
Published: October 2019

Abstract
Facial modeling is a key step to model visual effects in special movie effects and computer games. In this paper, a method based on the combination of deep learning and feature extraction is proposed for the modeling of 3D face model. Firstly, the face region is located for the captured face image. And then, the facial feature points are extracted by the landmark algorithm and the Convolutional Neural Network (CNN) is used to classify the facial expressions. Next, a special expression 3D face model is created by the deformation of the standard 3D face model based on the facial expressions classification result. Finally, the 3D face model and the extracted facial feature points are combined to perform personalized adjustment of the 3D model to complete a 3D facial expression animation system. The experimental results show that the proposed method can effectively perform the dynamic 3D face modeling which has high reality.
A New Approach for Short-term Time Series Forecasting
Authors: Fan Henghai , Wu Shuai , Chen Ning , Gao Bo , Xu Yiming 
Published: October 2019

Abstract
Short-term series forecasting is one of the essential issues in a variety of tasks, such as traffic flow prediction, stock market tendency analysis, etc. Most current methods based on stable or abundant historical data. In this paper, we proposed a novel model called LA-NN. It takes advantages of both long short-term memory (LSTM) network and autoregressive integrated moving average (ARIMA) by a relation integration of them. So as to deal with the situation of insufficient historical data and sudden abnormal changes in data. A comparison with other representative forecast models validates that the proposed LA-NN network can achieve a better performance.
Design of Dual-Rate PIM-Disturbance Regulators for a DC-DC Switching Converter
Authors: Nishinaga Naoya , Hori Noriyuki , Ruan Xinyue 
Published: October 2019

Abstract
Three types of dual-rate digital controllers are designed to suppress the output voltage fluctuations caused by load-current changes for a buck DC-DC switching converter running at 300kHz PWM. The slower-rate outer loop is designed using the IA-PIM method, which stabilizes the outer loop at a slow rate of 25kHz. Since the time lag in sensing the disturbance is critical, a faster loop of 300kHz is added based on three different approaches. The resulting dual-rate control laws are implemented on a single 16-bit fixed-point microcomputer with the clock frequency of 140MHz, via 12-bit A/D and D/A converters. Experiments on the fluctuation of the output voltage caused by load-current transients show that, while the analog regulator suppresses the maximum output fluctuation to be 4.7 % of the output voltage, one of the three digita l control methods achieves 4%, without adding ext ra analog components, such as capacitors as in our previous paper.
Body-Boundary-Refined Human Parsing Network based on Fully Convolutional Network and Conditional Random Fields
Authors: Zhao Hanlin , Ma Xin 
Published: October 2019

Abstract
Human parsing is still a big challenge in computer vision task to accurately label every body part in an image. Current methods of sematic segmentation mainly focus on dividing each independent part and ignore the structural priors of human body. However, the position relationships of different parts, especially which around the area of boundary, indicate their associations and also contribute to the semantic segmentation. In our work, we propose a body-boundary-refined part to refine the segmentation result of human part edge by simply utilizing the structure priors around the body boundary. It puts a penalty mechanism on wrong marginal pixels to improve segmentation performance around the area of body boundary. The network achieves competitive performance on the PASCAL-Parts-dataset and especially the area around the body boundary has been refined.
Hybrid Algorithm for Solving Traveling Salesman Problem
Authors: Zhao Ping , Xu Degang 
Published: October 2019

Abstract
The basic genetic algorithm has the disadvantages of falling into local optimum and slow convergence. To solve this problem, a hybrid algorithm combining simulated annealing strategy is proposed. The cooling process in simulated annealing is used to complete the iterative process in the hybrid algorithm. The algorithm is used to solve the traveling salesman problem. The results show that the convergence speed and accuracy of the hybrid algorithm is significantly better than the basic genetic algorithm.
Optimizing the Perimeter Control for Urban Traffic Sub-region by BP Neural Network
Authors: Liu Wenchao , Zhu Wenxing 
Published: October 2019

Abstract
In this paper, we improve the effect of perimeter control for Urban Traffic Sub-region by optimizing signal timing in traffic sub-region. Firstly, we verify the influence of different signal timing on the shape of macroscopic fundamental diagram(MFD) by simulation. Then, we use BP neural network to model the mapping relationship between signal timing and MFD maximum volume(saturated traffic volume of sub-region). In perimeter control based on MFD, the larger the saturated traffic volume, the more vehicles passing through the sub-area. When the output of the BP neural network model reaches the maximum value, the signal timing of the road network is the best one. Comparing the perimeter control effects of different signal timings, we find that the larger the saturation traffic, the larger the traffic in the boundary control and the smaller the vehicle delay.
Ground-based Multi-platform Point Clouds Registration
Authors: Gao Yuan , Li Mingchu 
Published: October 2019

Abstract
Laser scanning system provides an efficient solution to rapidly acquire 3D information of large-scale scenes. Point clouds collected by laser scanning systems contain numerous objects with significant disparities in size, complicated and incomplete structures, holes, varied point densities, and huge data volumes, raising great challenges for automated point clouds registration, segmentation, and object detection. The dissertation presents a hierarchical merging based multi-platform point clouds registration algorithm to align MLS point clouds and unordered TLS point clouds from various scenes and validates its performance on nine challenging datasets. The algorithm improves the efficiency and accuracy of point cloud registration and enhances the registration ability of the algorithm for low-overlap and high-symmetry point clouds.
Research and Design of ERP System for Small and Medium-sized Enterprises under Great Intelligence Mobile Cloud
Authors: Wen Yong 
Published: October 2019

Abstract
Based on the information management needs of SMEs, the article adopts the rapid prototyping method, designs the overall framework of the cloud ERP system, maps out the functional modules, adopts the B/S architecture, uses Java as the development tool, and SQL Server as the background server. The cloud computing and APP technologies are used to realize instant access between the PC and the mobile terminal, and the cloud ERP system with relatively complete system functions, simple interface and mobile operation is realized. The system incorporates new technologies such as big data analytics, artificial intelligence, machine learning and data mining to enable it to realize intelligent financial analysis, intelligent financial forecasting and intelligent financial decisions.
A Hybrid Genetic Algorithm for the Distributed Permutation Flowshop Scheduling Problem with Sequence-Dependent Setup Times
Authors: Huang Jiangping , Pan Quanke , Chen Qingda 
Published: October 2019

Abstract
The distributed permutation flowshop scheduling problem (DPFSP) has attracted many researchers’ attention in recent years. In this paper, we extend the DPFSP by considering the sequence-dependent setup time (SDST). A new hybrid genetic algorithm (HGA) for the DPFSP with the SDST (SDST/DPFSP) is presented to minimize the maximum of the completion time. At first, a new population initialization is proposed. And then, the newly-designed operators are described in details, and we also introduce the mutation rate and the crossover rate to balance the mutation operator and the crossover operator. To further improve the obtained solution, a new local search method is developed. At last, the orthogonal experimental design is applied to adjust the parameters in the HGA, and a comprehensive computational campaign based on the 135 instances demonstrates the effectiveness of the proposed HGA for the SDST/DPFSP.
Research Status and Development Trend of Bioheuristic Computing
Authors: Chai zhijun , Li Zhao 
Published: October 2019

Abstract
Bio-inspired computation aims to study the biology function, characteristic and echanism of the various levels of nature from biological individual, population, colony until ecosystem, and set up a relevant model and computing method, so as to serve the scientific research and engineering application of human society. A few future directions and research challenges are presented, such as parallel bio-in-spired computation, bio-inspired computation with reasoning and knowledge, bio-inspired dynamics computation, bio-inspired computation based on quorumsensing, artificialbrain, evolutionaryhardware, bigdata, swarmrobot, virtualbiological, cloudcomputing, etc.
Chinese Named Entity Recognition for Clothing Knowledge Graph Construction
Authors: Zhu Ming , Zhen De-Sheng 
Published: October 2019

Abstract
Clothing knowledge graph is a kind of vertical domain knowledge base constructed for the description of clothing knowledge in the field of textile and apparel. In this paper, based on the limitations of the clothing knowledge graph in the effect of entity extraction, the deep learning model and the statistical model are combined. A Chinese named entity recognition method based on CNN-BiLSTM-CRF is proposed. Firstly, the convolutional neural network(CNN) is used to extract the text features, and the character-level vectors with morphological features of the words are trained. Then the bi-directional long short term memory networks(LSTM) is used to learn the context features, and the vector representation of the context of each word is output. Finally, the conditional random fields(CRF) model is used for self-learning. Get the best tag sequence for the sentence. The method can automatically recognize the text, and does not rely on the artificial feature to obtain the semantic category information. Finally, the experimental data and evaluation methods are introduced. The experimental results show that the Chinese named entity recognition method based on CNN-BiLSTM-CRF is superior to other models in all indicators, indicating the effectiveness of the method.
A Novel Ground Plane Detection Method Using an RGB-D Sensor
Authors: Chen Li , Zhou Jun , Chu Xuepeng 
Published: October 2019

Abstract
A novel ground plane detection method is put forward based on three-dimensional (3D) point cloud data obtained using an RGB-D sensor. It consists of three stages: data pre-processing, occupancy grid map construction and ground plane segmentation. In order to obtain more accurate 3D point cloud data, the weight median filter (WM) is applied to recover the invalid depth pixel in the depth image. Different from the traditional approaches which process the 3D point cloud data directly, our algorithm transforms the 3D point cloud data into an occupancy grid map. Considering that the occupancy in the occupancy grid map and the distance from the point to the ground plane are distinct between ground points and other points, we will get a part of the 3D points that is definitely in the ground. The points selected are back-projected to the pixel coordinate system to get the result of the ground plane detection. In terms of experiment, the sensor is mounted on the mobile robot, Turtlebot2. The proposed method can detect more than 95 percent of the ground point. It produces accurate ground plane detection in different scenes.
Multi-Agent Aviation Search Task Allocation Method
Authors: Wang Yijuan , Pan Weijun , Liu Kaiyuan 
Published: October 2019

Abstract
The multi-agent technology is used to reasonably allocate the search area determined after the aircraft crash, and the research on the task assignment problem of aircraft crash area based on multi-agent system is proposed. In the simulation experiment, the model of multiple rescue points, single disaster points and multiple emergency resource allocations is shown. The results show that the method can optimize the allocation of the search task in the aircraft crash area and dynamically change with the change of the crash area. The aircraft’s search-assisted decision-making system provides some support.
Vision-based Autonomous Landing of UAV on Moving Platform using a New Marker
Authors: Huang Xiaoyun , Xu Qing , Wang Jianqiang 
Published: October 2019

Abstract
The research of Unmanned Aerial Vehicle (UAV) flight autonomous landing on a moving platform based on computer vision has important significance, especially for the rescue and spray UAV in the future. A vision-based relative position and attitude estimation algorithm with a novel color marker and its recognition method was proposed for the UAV autonomous landing system. The new marker is designed with a pattern which make it is as visible as possible in the whole landing process. The proposed relative position and attitude estimation algorithm is based on the four corner points on the marker which are detected by the combined approach of vanishing point of parallel lines and Levenberg-Marquardt (L-M) optimization method. Indoor and outdoor experiments were carried out. The results indicate that the method of marker detection has real-time and robust performance and the position and attitude estimation accuracy attain cm-level, which shows the feasibility of landings on moving platform automatically.
Trajectory Estimation of Flexible Needle Using PVA Tissue Material
Authors: Zhao Shijian , Gao Dedong , Zhao Mengxiao , Fu Jiajie 
Published: October 2019

Abstract
In order to determine the movement trajectory and characteristics of puncture needle in tissue, a series of puncture is selected for the puncture of PVA prosthesis. The image captured by CCD camera is preprocessed, and the starting coordinate point and target in the image are extracted. A fitting model based on least squares method is proposed to fit the radius of puncture needle. Comparing the simulation trajectory of forward kinematics and experimental trajectory, the experimental results show that the fitting model has a high success rate over 93% in the trajectory radius of the prosthesis puncture needle, and has a high success rate, stability and accuracy. It has a certain reference significance for the future path planning and guidance process.
An Implementation Method of SVPWM Modulation Algorithm
Authors: Chao Wang , Qiang Gao , Jing Tang 
Published: October 2019

Abstract
SVPWM algorithm is widely used in the field of power electronic frequency conversion power supply, motor frequency conversion control, power quality optimization and other technical fields. In this paper, the principle of SVPWM modulation is analyzed, in order to make the over-modulation algorithm more simplistic, the adverse effects on the system are smaller, and a phase and amplitude are used to change the modulation method to optimize the algorithm of the cross modulation II zone[1,2]. And using Matlab software to build SVPWM model for simulation verification. Explains the correctness of this method.
Modeling and Simulation Analysis of a Two-degree-of-Freedom Nonlinear Piezoelectric Energy Harvester
Authors: Jiang Junxiang , Liu Shaogang , Wu Junchao , Feng Lifeng 
Published: October 2019

Abstract
In order to improve energy harvesting efficiency, this paper shows the design of a two-degree-of-freedom (2-DOF) nonlinear piezoelectric energy harvester. The proposed harvest is realized by introducing magnetic attraction to a 2-DOF piezoelectric cantilever beam in order to broaden the energy harvesting bandwidth. Electromechanical equations describing this nonlinear system are presented. The simulation results confirmed the advantage of this new 2-DOF nonlinear harvester. Performance comparison shows that the 2-DOF nonlinear harvester has much higher energy harvesting efficiency than a conventional one-degree-of-freedom (1-DOF) nonlinear one.
Study on the Damping Problem in Circular Plates of Radial Phonon Crystals
Authors: Mu Di , Shu Haisheng , Su Yuqiang 
Published: October 2019

Abstract
In order to perfect the theoretical framework of the radial phonon crystal circular plate, a damping type radial circular plate is constructed. The localization factor of damping is solved by transfer matrix method, and the finite element simulation and experimental verification are carried out. Furthermore, the effect of elastic modulus on the bandgap is investigated from the perspective of its frequency nonlinearity. The results show that the damping effect of viscoelastic materials has a significant effect on the bandgap, which is mainly reflected in the fact that the cut-off frequency of bandgap moves to the high frequency with the increase of material loss factor, thus broadening the bandgap. The damping effect of damping alloy has no obvious influence on the bandgap characteristic, which is related to the inherent impedance characteristic of the alloy.
Zirconium-Based Cladding Coating Technique for Oxidation, Corrosion and Embrittlement Reduction at High-Temperature: An Overview
Authors: Sagiroun Mamoun I. A. , Xinrong Cao 
Published: October 2019

Abstract
Fukushima Daichii accident attracted attention to one important factor for nuclear reactors safety – overcoming the high hydrogen emissions under accident conditions. The coating on zirconium-based cladding is one of significant approach to protecting the cladding materials from corrosion, accelerated oxidation at high temperature, embrittlement and (oxygen and hydrogen) uptake at aggressive water-chemical environments inside the core of Light Water Reactors (LWR). This paper presents a compact review of the most common technologies used to apply coating on zr-based cladding superstrates. The paper also discusses the coating materials, substrate preparations and recent advances in deposition techniques.
Using Absorbent Paper Strips for the Collection of Cell-Free DNA in Patients with Periodontal Diseases
Authors: Thaweboon Boonyanit , Suwannagindra Sukhumchawee , Kerdvongbundit Varunee , Thaweboon Sroisiri 
Published: October 2019

Abstract
The cell-free DNA in gingival crevicular fluid (GCF) is a recent interesting diagnostic marker in patients with periodontal disease. The methods used to collect GCF are very important to get the proper specimen. There are several techniques used for sample collection, such as gingival washing or using a capillary tube, however, these methods are not practical to perform in the clinic since they need well-trained examiner. This study aimed to use absorbent paper strips to collect cell-free DNA fragment in GCF of patients as a diagnostic measure for periodontal diseases comparing to conventional washing technique. Thirty-nine periodontitis and 26 gingivitis teeth were selected from 26 patients according to clinical parameters. The GCF sample was randomly collected from each tooth by either paper strips or washing technique. Then, after one week, the collection of samples from the same tooth was repeated with another technique. The samples were centrifuged to get cell-free DNA in the supernatant and extracted by InstaGene Matrix. The concentration and purity of extracted DNA were determined by NanoDrop spectrophotometer. Three sets of specific primers to the human β-globin gene were used to evaluate the DNA fragment lengths, by amplifying 110 base pair (bp), 536 bp, and 2000 bp products in the polymerase chain reaction (PCR). The results showed no significant differences in the cell-free DNA fragment concentrations and the prevalence of PCR products between using absorbent paper strips and washing technique in either gingivitis or periodontitis groups. Therefore, with the ease and rapidity of the technique, using the absorbent paper strips for the quantitative and qualitative investigation of cell-free DNA fragment in patients with periodontal diseases instead of washing technique is recommended. Further studies are still required to confirm this finding in a large group of patients as well as in patients with other systemic health problems.
Finite Time Cascade Control Scheme for Tracking Control of an Underwater Exploring Robot
Authors: Liu Zhimin , Zhou Xiaozhong 
Published: October 2019

Abstract
In this paper, we discuss the curve trajectory tracking problem of an underactuated underwater robot in the horizontal plane. We use global diffeomorphism transformation method to transform the sixth-order dynamic tracking error model into a nonlinear cascaded system, by using the cascaded systems’ finite time stability theory, along with the back stepping technique to design the controller. Two discontinuous finite time controllers are designed for the two subsystems respectively. In the existing literature, finite time control is used for the first order nonholonomic system, we extended this method to two order nonholonomic system in this paper. The finite time controller can tune not only the gain, but also the fractional power, it is more convenience for engineering implementation. The results show the control laws can achieve the control objective with good performance for the horizontal trajectory tracking control.