bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation and Comparison of Deformable Image Registration Algorithms for 4D CT Images
Authors: Hu Xiaokun , Shao Guangpu , Yang Jimin , Yang Juan 
Published: March 2020

Abstract
Deformable image registration (DIR) is crucial in adaptive radiation therapy. However, the validation is a challenging work due to the lack of gold-standard. This study proposed an evaluation framework by using point-to-point displacement vector field (DVF). Three DIR algorithms including original flow, active Demons and symmetric force Demons were validated for ten lung 4D CT images with landmarks. DVFs derived from DIR algorithms (dDVF) and manually measured according to landmarks (mDVF) were analyzed and compared. Their target registration errors (TRE) and the relationship of lung motion and three-dimensional TRE were explored. The distance discordance metric (DDM) values were calculated. For all cases, the active Demons algorithm had the smallest TRE value and DDM values and it showed the poor correlation between 3D TRE and lung motion, which indicated that this algorithm outperformed other DIR algorithms enrolled in this study. Preliminary results demonstrated that the proposed evaluation framework had a potential ability of providing clinical guidance for the selection of appropriate algorithm in radiation therapy.
Adaptive tracking algorithm based on target moving speed
Authors: Liu K W , Wu D W , Xie Q S , An Z Y 
Published: March 2020

Abstract
To solve the problem of tracking failure caused by fast object movement, we proposed an adaptive tracking algorithm based on object movement speed on the basis of ECO-HC (ECO for hand-crafted feature version). First, correlation filtering method was used to obtain the distance of the maximum response point of adjacent frames. Then the speed of the object was judged by the distance of the maximum response point of the adjacent frame. Then the number of scale filter factors and interval frames updated by the template were adjusted on the basis of the object’s speed. The comparative experiment on the VOT2016 benchmarks showed that our tracker improved the accuracy and robustness of object tracking.
Innovation and Practice of Teaching Reform in Higher Vocational Colleges under Artificial Intelligence Environment
Authors: Cheng Yunli , Bu Xu 
Published: March 2020

Abstract
With the great success of machine learning algorithms represented by deep learning in the fields of machine vision and speech recognition, as well as the abundant and continuous data resources provided by cloud computing and big data, artificial intelligence has entered an unprecedented period of rapid development. Deeply changing all walks of life, the state requires corresponding intelligent education, but the artificial intelligence + education road is how to go, there is still no systematic discussion. In view of this article, artificial intelligence is used to promote the research of teaching reform, in order to enlighten the application of artificial intelligence teaching and promote education. The intelligent development of teaching.
Redis rehash optimization based on machine learning
Authors: Zhang Juan , Jia Yunwei 
Published: March 2020

Abstract
This paper proposed an optimization for Redis rehash based on machine learning. Since Redis involves numbers of dimensions, only the process of Redis rehash was studied. In order to use Redis correctly, the principle of Redis rehash was analyzed firstly and then pointed out a feasible optimization scheme. Aiming at solving the problems that might exist in the rehash process, the scheme could predict the number of keys based on the time series model ARIMA. The result showed that the scheme was feasible in practice.
Cattle Face Recognition Method Based on Parameter Transfer and Deep Learning
Authors: Wang Hongyu , Qin Junping , Hou Qinqin , Gong Shaofei 
Published: March 2020

Abstract
In order to accurately identify cattle, help insurance companies to deremine claim of Cattle Insurance, or realize inteligent breeding. We need a cattle face recognition technology. Due to the difficulty in data collection of cattle face and the small amount of data, it is difficult to apply deep learning method to cattle face recognition. So there is a method combined with tarnsfer learning effectively trains the model,or initializes the network weights by parametric transfer. This paper proposed using VGGFace dataset pre-training network to solve the problem of small sample face recognition. The VGG-16 deep convolutional neural network model was used to extract the cattle’s face features. The model parameters obtained by training the VGGFace face dataset were used to initialize the network weights, and then the network was trained on the cattle face dataset. The experimental results show that the method can obtain 93% recognition accuracy under small sample data.
Optimization analysis of autonomous obstacle avoidance path for self-driving vehicles based on improved ant colony algorithm
Authors: Li Shixuan 
Published: March 2020

Abstract
In order to further improve the accurate response and fast response ability of autonomous obstacle avoidance in real dynamic environment, an improved AC (ant colony algorithm) model based on PSO (Particle Swarm Optimization) is proposed to realize the global and fast optimization analysis of autonomous obstacle avoidance path planning for self-driving vehicles. Firstly, an autonomous obstacle avoidance path planning model for self-driving vehicles is established; secondly, the global pheromone is searched by using the cooperation and information sharing mode between particles in PSO; thirdly, the global pheromone updating strategy is used to optimize the path searching ability of AC; finally, an innovative way of integrating PSO and AC is used to obtain the optimal path of autonomous obstacle avoidance for self-driving vehicles. The simulation results show that the AC model is improved by PSO to realize the fast and accurate planning of autonomous obstacle avoidance path for self-driving vehicles.
Design and Research of Control System of the UAV Photodetector Stabilized Platform
Authors: Zhao Xinglong , Liang Shaojun , Liu Fulin , Ding Fangzheng , Zhao Jingshan , Zhuo Jiajing , Xu Luoting , YunLiu  
Published: March 2020

Abstract
Based on use conditions and functional requirements of the UAV photodetector stabilized platform, an overall design scheme of its control system is given. This system is studied from hardware and software. Development of the platform is prospected.
Topology optimization method and lightweight design of anthropomorphic manipulator
Authors: Wu Haoting , Yin Meng , Zhao Zhiliang , Xu Zhigang 
Published: March 2020

Abstract
The topology optimization method is adopted to realize the weight reduction of the mechanical arm under the rigidity condition. The typical configuration and load conditions of the manipulator are analyzed. The stiffness mass model of the part is established by the finite element analysis method, and the topology optimization of the part is carried out. On this basis, the optimization of the manipulator system is completed. The optimized art quality is reduced by 6.2% compared with the original model, and the stiffness meets the standard requirements. The method of combining virtual joint method with working space of the manipulator is proposed. The amount of end deformation after optimization of the manipulator is analyzed. The maximum deformation is 0.27mm, which meets the requirements. The optimization process provides a reference for the selection of the drive joint parts of the mechanical arm. According to this, the physical design of the mechanical arm is completed and the load test is carried out. The experiment shows that the mechanical arm can still achieve rapid response under the condition of a 2kg end load.
A New Method of Gene Information Vectorization and its Application in Similarity Search
Authors: Dong Qian , Zhang Zhaogong , Zheng Dayuan , Zhang Zhiliang 
Published: March 2020

Abstract
With the development of the Human Genome Project, more and more biological sequence data are generated, and the analysis and processing of these sequence data have promoted the development of bioinformatics. Sequence similarity analysis is the basis of bioinformatics, through which we can use the information of known sequences to study the structure, function and evolutionary relationship of unknown new sequences. This paper performs data compression and retrieval on the genome database based on the dbSNP information of DNA. According to the rule of determining a protein by three bases, the amino acid characters are determined, and the redundant information is removed by using the dbSNP information. It is the first time to propose the construction of a new compressed form of biological sequence structure, which can reflect the strong correlation between the SNP location information and SNP in each sample in the genome. Finally, this paper constructs a complete biological sequence approximate neighbor query system, which can not only greatly reduce the storage and computing overhead, but also improve the query efficiency under the condition of ensuring the retrieval accuracy. The accuracy and scalability of this method are verified by experiments on a large data set of gene database.
Simulation Research on Optimal Installation Position of partially-filled pipe Electromagnetic Flowmeter sensor
Authors: Jiang Yulin , Jiang Wuzhi , Zhang Chao 
Published: March 2020

Abstract
The measurement sensor of the partially-filled pipe electromagnetic flowmeter must be installed where the fluid is fully developed. For partially-filled pipe electromagnetic flowmeters, the boundary conditions vary with the fullness of the pipe, and the distance from the pipe inlet to the fully developed is not the same as the distance of the full-filled pipe flowmeter. Therefore, in the partially-filled pipe state, the mounting position of the electrode sensor is also different from the mounting position at full-filled pipe state. Based on the measurement principle of electromagnetic flowmeter, the finite element simulation method is used to simulate the flow field development of partially-filled pipe electromagnetic flowmeter. First, according to the knowledge of hydraulics, the variable boundary constraint is established, and then the simulation model of flowmeter fluid development process is established. Second, the Comsol Multiphysics finite element simulation software is adopted to solve the fluid development process, and the required distance for the full development of the partially-filled pipe fluid is obtained. Finally, the optimal installation position of the partially-filled pipe electromagnetic flowmeter sensor was determined based on the distance. The simulation results prove the feasibility of the proposed method, which can provide powerful theoretical support for the fabrication of partially-filled pipe electromagnetic flowmeters.
Warships Formation Identification Based on Neural Network
Authors: Tian Liye , Wu Jinping , Wang Yongjie 
Published: March 2020

Abstract
Submarine tactical software should be able to identify warships formation. Neural network based pattern recognition method is introduced in submarine tactical software to improve accuracy. This paper discussed how to transform sensor data into training samples by using Matlab, and how to choose training samples. Experiments indicate that GRNN network is capable of this work and suitable for actualizing.
Application of Artificial Bee Colony Algorithms in Smart Grid
Authors: jie YU 
Published: March 2020

Abstract
The operation of modern society cannot be separated from the power network. The power output from power stations is transmitted to all walks of life through the power network. The same people’s activities are inseparable from electricity. In recent years, the scale of the power grid has become larger and larger, and communication technology and control technology have also developed rapidly. The emergence of smart grid is to meet the needs of users, optimize resources, balance supply and demand relations, etc. The development of artificial bee colony algorithm also provides a new dispatching method for smart grid. This paper studies the application of artificial bee colony algorithm in fault location of distribution network, so as to make the smart grid develop better.
SoC Implementation of Visual-inertial Odometry for Low-cost Ground Robots
Authors: Liu Bo , Li Lin , Liu Hengzhu 
Published: March 2020

Abstract
Simultaneous localization and mapping (SLAM) is a key technique for autonomous navigation of a robot in unknown environments. Recently, many researchers focus on the algorithm optimization of visual-inertial odometry (VIO) as a real-time SLAM method. In this paper, different from pure algorithm research, we propose a novel low-cost hardware solution based on the system on a chip (SoC) to achieve real-time performance and low power consumption of VIO. We design a novel hardware architecture to accelerate a popular VIO algorithm, with the time-costly image feature processing computed on FPGA and floating-point numerical computation been done on ARM. On the algorithm side, we fuse odometry information from the two wheels of the ground robot in a unified optimization method, which results in accurate metric scale estimation of the VIO. The experimental results show that our design and implementation have superior performance for ground robot applications, allowing real-time localization of a robot with a very low-cost hardware for computation in complex environments.
Distributed System Based on Publish-Subscribe Middleware Automated Testing Method
Authors: Wang Xingmin , Yang Meng , Han Peng 
Published: March 2020

Abstract
Publish-subscribe middleware has been widely used in military, medical and other important industries because of its good characteristics of time and space decoupling. With the continuous expansion of the scale of distributed system application, the problems in distributed system testing, such as low efficiency and difficulty in fault positioning, are more prominent. In this paper, an automatic testing method is proposed, which is based on the characteristics of the publish-subscribe middleware systems. Based on an independent designed and implemented publish-subscribe system named BlueDCS, a corresponding automatic testing tool is developed. Application verification shows that the tool can well solve the aforementioned problems in distributed system testing.
Automatic Target Recognition for CT-based Airport Screening System
Authors: Gu Chen , Dong Zhen 
Published: March 2020

Abstract
To construct an automatic target recognition CT-based screening system for airport, this paper introduces a method by combining two hot technology, CT Image Processing and Machine Learning together. With the grey-scale features and the Histogram of Oriented Gradient (HOG) features extracted from the CT images, we can train different classifier (SVM, KNN) to recognize the targets (saline, rubber, clay) we want. By comparing the recall rate and precision rate of each classifier, we may find the best classifier for this project.
Wireless Sensor Network Node Deployment Based On Regular Tetrahedron
Authors: Zhang Yunfei , Zhang Zhaogong 
Published: March 2020

Abstract
The deployment of nodes in 3D wireless sensor networks has always been the focus of research. In this paper, two algorithms for achieving full coverage are proposed, which are applicable to the even distribution and the uneven distribution of target points. Among them, the characteristics of the spherical and regular tetrahedrons are rationally utilized to achieve the purpose of covering more space with the same nodes. For the three-dimensional space with uneven target distribution, it is proposed to use the DBSCAN clustering method for target point processing, and then perform the same processing in each cluster to avoid wasting more sensor nodes and increasing energy consumption. Finally, considering the problem of energy saving, some nodes are put to sleep and waiting for the next call to reduce energy consumption and extend the working time of the network. Simulation experiments show that the algorithm has improved the number of nodes used and energy consumption.
Non-contact sensing and modelling on the voltage and electric field for powered transmission line
Authors: Fuqing Yuan , Lu Jinmei 
Published: March 2020

Abstract
From environmental, ecological or technical perspectives, the measurement of the potential voltage, electric field near the power transmission line is essential to ensure the exposure level does not exceed the limits of the government specified. This paper develops a potential voltage model, designs experiments to verify the developed model and to evaluate the parameters in the model. An electric field model is derived from the voltage model further, which can be used to estimate the electric field strength numerically. The models are found consistent with the observed data in the experiment.
Electric Tower Target Identification Based on High-resolution SAR Image and Deep Learning
Authors: Tian Guishen , Meng Song , Bai Xuejiao , Liu lijuan , Zhi Yang , Ou Wenhao , Fei Xiangze , Tan Yuanpeng 
Published: March 2020

Abstract
With regard to the electric tower identification problem in the high-resolution SAR image under complicated background, it is difficult for the existing target detection algorithm to reach balance in identification precision and efficiency. Therefore, this paper combines the advantages of high YOLOv2 calculation efficiency and high VGG classification precision, and proposes a kind of two-stage target detection algorithm of YOLOv2 and VGG cascade connection by virtue of transfer learning. At the Stage-1, the sliding window and the non-maximum suppression algorithms are combined, and the YOLOv2 is utilized to conduct rapid electric power detection to the whole SAR image, thus obtaining the target detection result of high recall rate; at the Stage-2, the VGG classification model is utilized to conduct secondary classification to the target and background with regard to the target detection result at the Stag-1, thus further eliminating the false positive. This algorithm can be used to enhance the accuracy of only using YOLO v2 f or target identification, thus reducing the false alarm rate of model effectively. The electric towers in the mountainous belt and the plain belt are used as samples for training, thus enhancing the robustness of algorithm. After conducting algorithm testing to the COSMO image in Zhijiang City, Hubei Province, the result shows that the electric tower recall rate can reach 73.8%. The method adopted in this paper can identify the electric tower target of the whole SAR image more accurately through model transfer and two-stage deep learning, thus being further promoted into actual application scene.
Overview Of Serverless Architecture Research
Authors: Jiang Lizheng , Pei Yunman , Zhao Jiantao 
Published: March 2020

Abstract
With the development of cloud computing, serverless computing, that is, function as a service (FaaS) is considered to be the next stage of cloud computing development. Serverless computing can be seen as a logical extension of cloud computing, a disruptive approach to application development. It is based on the code written by the developer for accurate resource allocation, and the resources on the platform are started when a predefined event is triggered. By comparing with the traditional architecture, the advantages of serverless architecture are highlighted. Although serverless is a relatively new concept in the field of software architecture, it is also a technological innovation with great influence.
Spectral efficiency analysis of millimeter-wave heterogeneous cellular networks based on PCP
Authors: Lu Yi , Jia Xiangdong , Chen Yuwan 
Published: March 2020

Abstract
To solve the interference problem in densely populated areas, this paper proposes a new scheme that taking user equipment (UE) as the center of millimeter-wave heterogeneous networks based on Poisson cluster process (PCP) model. Under the network model, the UE is divided into cluster-center UE or cluster-edge UE by using the ratio of the first and second closest distances of the UE from pico base stations. The random geometry and PCP methods are used to study the downlink spectral efficiency and the correct derivation results are verified. At last, the influence of relevant parameters about system performance is analyzed.
Research on precise organization of operational network based on “Chains in Network” model
Authors: Li Fangsheng , Hou Jianfeng , Qu Lianzheng , Fan Binbin 
Published: March 2020

Abstract
Aiming at the network organization requirements of precise operation, this paper proposes a precise network organization method based on the “network in the chain” model: starting from the command perspective, setting the intelligence chain, C2 chain, strike chain and service chain as the entry points, the organizing and planning of operation network is classified and carried out. The model of “chain in net” is formally described, and the evaluation index system of “chain” to “net” is established. This kind of precise network organization based on command perspective is of great significance to improve the ability of joint operation based on network information system.
Research on the Formulation of the Motion Angle of Human Lower Limb Joints
Authors: Wang Kaiyuan , Dai Zongmiao 
Published: March 2020

Abstract
In order to make the exoskeleton recognize and predict human gait after walking for a period of time, the control system of the exoskeleton must establish the human gait database in real time. The traditional method is to collect the discrete point data of the angle of each lower limb joint changing over time and then store it in the database. There are two main disadvantages: first, the data volume is too big to store everyone’s gait data which is unrealistic; second, it is slow to find the optimal matching of gait process one by one from the database, and it will affect the speed of the gait recognition and prediction, so the exoskeleton is slow to respond. Therefore, it is necessary to find a method dividing human gait data and fitting the function of each piece of data, namely, the formulation of joint motion angle. This paper presents a research on the formulation of the motion angle of human lower limb joints.
Mosaic Method for Insulator Images Based on Region Characteristics
Authors: Wang Zhihui , Zhang Licai , Yao Chenhong , Sun Xiaoyan 
Published: March 2020

Abstract
Based on the analysis of image registration methods based on region and feature, an image mosaic method based on edge statistical features is proposed. By using the mean and mean square deviation of RGB parameters of edge region pixels as matching criteria, this method improves the shortcomings of general region registration algorithm, such as large computational complexity, sensitivity to brightness and scale changes, poor real-time performance and adaptability, and simplifies the calculation of global region features of images to that of local region features. This method makes full use of the relevant information of the RGB parameters of the pixels. Compared with the registration calculation based on gray level, it has the characteristics of abundant optional features and high practicability.
Clustering with Fuzzy C-means and Common Challenges
Authors: Deng Songyin 
Published: March 2020

Abstract
Clustering algorithm is massively used in various fields such as computer vision and so do FCM. One of the purpose of this paper is to generate new insight into improvement on general clustering algorithms through this inspection of one specific clustering algorithm (FCM) help. Three common challenges of clustering (Noise problem, long operational time, and initial bias) in Fuzzy C-Means algorithm and corresponding solutions to each of these problems are introduced. Further potential of meta learning and adversarial learning to solve the clustering problems are recognized in the end.