bluuebunny/crossref_metadata_2025 huggingface dataset:
Traditional Chinese Medicine (TCM) Diagnosis Model Building Based on Multi-label Classification
Authors: Zhou Lu , Li Guang-geng , Zhou Yu-mei , Yin Dan , Sun Yan , Zheng Yan , Li Yu-hang
Published: November 2018

In the study, we propose a TCM diagnosis model that can be used for multi-label classification and give clear diagnosis, as well as the basis for diagnosis and differentiation when the symptoms correspond to multiple diseases or syndromes. The implementation of the model is divided into three steps. Firstly, choose the machine learning algorithm to train the TCM diagnosis model. The features of the training data are symptoms and the labels are diseases or syndromes. Secondly, give the number α (α>1, α∈Z+), the model will output the diagnoses with the top α highest probability according to the input symptoms as candidate diagnoses. Finally, the rules of differential diagnosis are designed to determine which candidate diagnoses should be reserved, thereby complete the multi-label classification. In our test dataset, by 10-fold cross-validation, the average accuracy of the single label classification was 0.882; the average precision was 0.974; the average recall was 1.000; the average f1 score was 0.967; the average accuracy of the multi-label classification was 0.706; the average micro precision was 0.934; the average micro recall was 0.941 and the average hamming loss was 0.060. Through the test we can know that this model had a good potential for auxiliary decision making in clinical diagnosis and treatment.
Remote Sensing Image Super-resolution Based on Sparse Representation
Authors: Zhu Fuzhen , Liu Yue , Huang Xin , Zhu Haitao
Published: November 2018

In order to obtain higher resolution remote sensing images with more details, an improved sparse representation remote sensing image super-resolution reconstruction(SRR) algorithm is proposed. First, remote sensing image is preprocessed to obtain the required training sample image; then, the KSVD algorithm is used for dictionary training to obtain the high-low resolution dictionary pairs; finally, the image feature extraction block is represented, which is improved by using adaptive filtering method. At the same time, the mean value filtering method is used to improve the super-resolution reconstruction iterative calculation. Experiment results show that, compared with the most advanced sparse representation super-resolution algorithm, the improved sparse representation super-resolution method can effectively avoid the loss of edge information of SRR image and obtain a better super-resolution reconstruction effect. The texture details are more abundant in subjective vision, the PSNR is increased about 1 dB, and the structure similarity (SSIM) is increased about 0.01.
Determine Frequency Adjustment Reserve Based on AGC Regulation Capacity Demand’s Random Fuzzy Model
Authors: Pan Liqiang , Zhu Zhixuan , Yu Haifeng , Luo Leixin , Jiang Xing , Wu Zhenyu
Published: November 2018

The uncertainty of wind power has a negative impact on the frequency adjustment of the system, so the frequency fluctuation caused by wind power can be suppressed only when the system has sufficient frequency adjustment reserve. Only considering randomness or fuzziness cannot describe the uncertainty of wind power, and it is impossible to determine the frequency adjustment requirement of the system. The random fuzzy uncertainty model of AGC regulating capacity demand is proposed, established and verified in this paper, And based on the model, the frequency adjustment reserve can be detemined.
3D recognition based on ordered images reconstruction
Authors: Zhang Ning , Zhao YongJia
Published: November 2018

Nowadays, more and more applications require precise and quickly 3D recognition, such as augmented reality and robot navigation. In recent years, model-based methods can get accurate object or scene recognition, but it takes a lot of time to reconstruct the model. Therefore, we propose a fast 3D reconstruction method based on ordered images for robust and accurate 3D recognition. The proposed algorithm consists of two parts, the offline processing stage, and the online processing stage. First, in the offline processing stage, the sparse point cloud model of the scene or object is reconstructed based on the sequential images, optimized using the BA algorithm based on the local correlation frame, and then the local descriptor of the resulting model points is stored. Secondly, in the online processing stage, for each image frame of the camera video, a matching relationship between the stored point cloud and the 2D feature points on the image frame is established, based on which the pose of the camera can be solved accurately.
Anomaly targets detection of hyperspectral imagery based on wavelet transform and sparse representation
Authors: Baozhi Cheng
Published: November 2018

The research of anomaly target detection algorithm in hyperspectral imagery is a hot issue, which has important research value. In order to overcome low efficiency of current anomaly target detection in hyperspectral image, an anomaly detection algorithm for hyperspectral images based on wavelet transform and sparse representation was proposed. Firstly, two-dimensional discrete wavelet transform is used to denoise the hyperspectral image, and the new hyperspectral image data are obtained. Then, the results of anomaly target detection are obtained by using sparse representation theory. The real AVIRIS hyperspectral imagery data sets are used in the experiments. The results show that the detection accuracy and false alarm rate of the propoesd algorithm are better than RX and KRX algorithm.
A Comparative Study of Cuckoo Algorithm and Ant Colony Algorithm in Optimal Path Problems
Authors: Wang Guanyu
Published: November 2018

Finding the optimal path can be realized through a wide range of algorithms, which is demanded in many fields. Among countless algorithms that are used for solving the optimal path problem, the ant colony optimization (ACO) is one of the algorithms used to solve the approximate optimal path solution, while the cuckoo search (CS) algorithm is a swarm intelligence algorithm featuring Levy flight, whose core idea is derived from the cuckoo nesting property. In order to provide more ideas and directions for future research on optimal path problems, this paper discusses in detail the advantages and disadvantages of the two algorithms for solving the optimal path problem and their scopes of application by comparing principles and flows of the two algorithms.
The application of Randomized HITS algorithm in the fund trading network
Authors: Xu Xingyu , Wang Zhen , Tao Chunhe , He Haifeng
Published: November 2018

For the economic crime investigation, it is very important for the rapid detection of the case to determine the key suspects efficiently and accurately in the fund trading network. In this paper, the design idea of Randomized HITS algorithm, combined with the fund flow characteristics of the personnel in the fund trading network , is used to study the key suspects. Based on the characteristics of the amount of funds and the frequency of transactions in the personnel relationship of the fund trading network, this paper expounds in detail how to construct the probability transfer matrix. In the end, the method is applied to a really case. From the final result, the algorithm can find the key suspects quickly from the large amount of fund trading data, improve the efficiency of information analysis. It provides a new alternative method of fund network analysis.
A segmentation of pulmonary nodules based on improved fuzzy C-means clustering algorithm
Authors: Yang Tiejun , Cheng Jinfeng , Zhu Chunhua
Published: November 2018

According to reports, lung cancer is gradually becoming the first cancer that threatens human life. The early stage of lung cancer is in the form of pulmonary nodules. The key issue in computer-aided diagnosis of lung tumors is to correct and accelerate rapid segmentation of diseased tissue. Therefore, this paper proposes a robust fuzzy c-mean clustering algorithm for pulmonary nodules segmentation, which can effectively improve the adaptive degree of local domain pixels. Since the information of the domain pixels does not necessarily have a positive correlation with the central pixels, the reference mechanism of domain window pixel information needs to be redefined. The robust fuzzy c-means clustering algorithm redefines the grayscale of the spatial pixel points in the domain and selects different fuzzy factors according to the reference standard. Based on this, the weights of different fuzzy factors are updated according to the characteristics of pixel points and gray fluctuation in pixel domain. The experimental results show that this method is superior to other typical algorithms in the segmentation of pulmonary nodules.
Research on An Improved RFID Collision Algorithm
Authors: Zhang Qing-hui , Wang Qi-ming , Qin Shuying
Published: November 2018

Radio Frequency Identification (RFID) is a kind of information that using radio Identification technology. Anti-collision algorithm has always been a research topic for researchers. The anti-collision algorithm of labels is mainly divided into two major categories: ALOHA-Based Anti-Collision Algorithms and Anti-collision algorithm based on binary search. Both algorithms have their own advantages and disadvantages, Anti-collision algorithm that based on ALOHA is simple and fast, but it will lose labels. Binary-based anti-collision algorithm can be searched for every tag, and it is not easy to lose tags, but it is relatively complicated and has poor security. Therefore, this paper proposes an Anti-collision algorithm which combines the dynamic frame slot Anti-collision algorithm with the return binary search algorithm.
An Efficient Algorithm of the Planar 3-Center Problem for a set of the convex position points
Authors: Bian Donglai , Jiang Bo , Cao Zhiying
Published: November 2018

The planar 3-center problem for a set S of points given in the plane asks for three congruent circular disks with the minimum radius, whose union can cover all points of S completely. In this paper, we present an O(n2 log3n) time algorithm for a restricted planar 3-center problem in which the given points are in the convex positions , i.e. The given points are the vertices of a convex polygon exactly.
Dynamic Online learning Algorithm For Three-way decision
Authors: Cheng Gaojie , Liu Jianmo , Xu Jianfeng , Wang Xiqiu
Published: November 2018

Three-way decision is an important theory for solving uncertain problems. Online computing is a new dynamic Stream computing form. How to execute three-way decision quickly in online computing is a challenging topic. In this paper, Online computing process is divided into incremental computing portion and decreasing computing portion. And a three-way decision dynamic incremental and decreasing learning algorithm for online computing is proposed. Firstly, the dynamic incremental and decreasing learning models is studied for stream computing based on probabilistic rough set . Then, the logical reasoning for three-way decision regions changing are discussed based on the dynamic incremental and decreasing learning models. And a novel dynamic online learning algorithm for three-way decision online computing is proposed based on the above theory. Finally, the experiment by UCI data set show that the proposed algorithms are superior than classical static three-way decision method in time efficiency.
Overview of image noise reduction based on non-local mean algorithm
Authors: LIU Baozhong , LIU Jianbin
Published: November 2018

The system introduces the extensive application and development process of image denoising based on non-local mean. The principle and specific theoretical model of the non-local mean algorithm are described. The process of improving the non-local mean algorithm after being proposed and how to improve it is elaborated and the shortcomings of the algorithm are pointed out. The noise reduction algorithm is experimentally described in detail from the aspects of peak signal-to-noise ratio, mean square error and structural similarity under different noise environment conditions.
Predicting China's Economic Running State Using Machine Learning
Authors: Luo Jianxiang , Fu Yonggang
Published: November 2018

China's business index of macro-economic includes early warning index, coincidence index, leading index and lagging index, among which early warning index reflects the economic running state. However, obtaining these indexes is a complex and daunting task. To simplify the task, this article mainly explores how to use machine learning algorithms including multiple linear regression (MLR), support vector machine regression (SVM), random forest (RF), artificial neural network (ANN) and extreme learning machine (ELM) to accurately predict early warning index. Finally, it can be found that the warning index can be well predicted by above machine learning algorithms with coincidence index, leading index and lagging index to be variables, furthermore, extreme learning machine and random forest are superior to other methods.
Application of Improved EMD Threshold Algorithm in the Study of the Electric Life State of the AC Contactor
Authors: Bo Yiping , Zhang Liang , Liu Shuxin , Zhang Yanjun , Cao Yundong
Published: November 2018

The condition monitoring signal of electrical life of AC contactors has characteristics such as non-linear, non-stationary and strong background noise. The premise and basis for the accurate establishment of the assessment model of the electrical life of AC contactors is how to accurately extract the characteristic parameters of electrical life signals. Therefore, it is of great significance for the study of AC contactors’ electrical life to preproccess its characteristic parameters of electrical life signals. Adopting traditional soft and hard methods cannot remove the noise effectively, therefore, a new threshold function can be proposed, and further model the wavelet threshold denoising theory to research the threshold denoising method of empirical mode decomposition (EMD), denoise the main parameters which can influence the state of AC contactors. The experimental results show that adopting the improved EMD threshold algorithm can effectively remove the noise, and it is better than adopting wavelet threshold method or empirical mode decomposition alone
Research on Gesture Recognition Method Based on Computer Vision
Authors: Wang Xianghan , Jiang Jie , Wei Yingmei , Kang Lai , Gao Yingying
Published: November 2018

Gesture recognition is an important way of human-computer interaction. With time going on, people are no longer satisfied with gesture recognition based on wearable devices, but hope to perform gesture recognition in a more natural way. Computer vision-based gesture recognition can transfer human feelings and instructions to computers conveniently and efficiently, and improve the efficiency of human-computer interaction significantly. The gesture recognition based on computer vision is mainly based on hidden Markov, dynamic time rounding algorithm and neural network algorithm. The process is roughly divided into three steps: image collection, hand segmentation, gesture recognition and classification. This paper reviews the computer vision-based gesture recognition methods in the past 20 years, analyses the research status at home and abroad, summarizes its current development, the advantages and disadvantages of different gesture recognition methods, and looks forward to the development trend of gesture recognition technology in the next stage.
The Research of a new Software Framework for cross-platform development Field
Authors: Lin Wenfeng , Zhang Gaoxuan , He Zhoucan , Liu Xinyu , Dang Wenchao
Published: November 2018

Software framework is a very important approach to realize software reuse and improve the software quality. In this paper, we firstly introduce a new software framework named QFusion to complete cross-platform desktop software development, which is based on function plug-in module. The QFusion framework can realize information interaction by use of event bus, data bus and service, which can separate the graphical user interfaces (GUI) from data processing completely. Based on the framework-related develop process, the complexity is largely reduced. Secondly, we give the practice of QFusion framework in modern military field to implement the feature extraction and data processing algorithm. Benefit from the QFusion framework, the signal processing task is completed by the collaboration among three groups, including data generation plug-in development group, data processing plug-in development group and GUI plug-in development group, respectively. Finally, the signal processing results are presented to prove the validity of the QFusion framework, which lays a solid foundation for solving the practical problem in engineering application.
CFD-Based Selection of Dispersion Plates
Authors: Chen Jing , Deng Ning , Wu Guoyong , Zhou Jinqing
Published: November 2018

Computational Fluid Dynamics (CFD) technology was used to analyse dispersion effects of 3 plates of different structures during adhesives production. Three models of the dispersion plates were designed: (1) Project 1: a plate with sharp and short teeth, (2) Project 2: a plate with sharp and long teeth, (3) Project 3: a plate with blunt and long teeth. Pictures of velocity flow contours and flow trajectories in the CFD analysis were obtained to show the flow conditions inside the Reactor. Particle studies were also run to predict adhesive particles dispersion effects of these 3 kinds of plates, so that the best structure of the plate would be chosen.
Statics Analyses of a Riveting Robot based on 6-SPU Parallel Mechanism
Authors: Liang Zheng , Xu Yong , Lv Yeping , Xu Yong
Published: November 2018

A new walking riveting robot based on 6-SPU parallel mechanism is designed to meet the needs of high precision and high efficiency machining for large, thin-walled and complex curved surface workpieces in aviation industry and automotive industry. After modeling and solving the position inverse solution of the robot, the riveting trajectory planning is carried out, and the correct positions and orientations of riveting holes are determined. For the workpiece with large thin-walled cylindrical surface, the riveting hole process of the robot is simulated by finite element analysis software, the maximum deformations in all orientations and the maximum equivalent stresses of the moving platform corresponding to riveting points are obtained. The above results provide the necessary theoretical basis for the structure optimization and performance analyses of the automatic riveting robot.
Development of Automated Warehouse Management System
Authors: Deng Mingxing , Mao Jian , Gan Xingwen
Published: November 2018

With the rapid development of the logistics industry, high-speed, high-efficiency and accurate delivery have become the new pursuit goals of the logistics industry, and intelligent logistics has been favored by enterprises. Aiming at the current situation that the offline products must be manually moved, sorted and discharged, the scheme of fully automated three-dimensional warehouse is proposed. Through the design of the whole three-dimensional warehouse, the whole process of the offline products can be realized by AGV, AGV management system, warehouse management system and roller. Lines, palletizers, etc. are completed. As the core part of the whole solution, the warehouse management system plays a vital role in achieving point-to-point tracking of offline products, and can perform regular statistical analysis on the inbound and outbound products to achieve digital management, improve the competitiveness of enterprises and bring considerable economic benefits.
A novel ML DOA estimation algorithm for array signal processing
Authors: Shi Pengfei , Fan Xinnan , Ni Jianjun , Yang Dewei
Published: November 2018

A novel algorithm for finding the optimal solution of nonlinear function in maximum likelihood DOA estimation is proposed to reduce the calculation in multi-dimensional nonlinear search of the estimation. In the proposed method, firstly, the mode of population initialization mode is modified to improve the stability of population evolution. Secondly, the crossover operator is also improved to enlarge the range of new generated individual. Thirdly, parameters adaptive adjustment strategy is designed to accelerate convergence. The simulation shows that the proposed algorithm can greatly reduce the calculation time.
Short-term Power Forecasting Method and Application of Wind Farm
Authors: Yang Xiaohu , Ju Rong , Yuan Zhe , Zhang Zhenya
Published: November 2018

The prediction of output power of wind farm has important value and significance to the normal operation of some large-scale wind power system. In this paper, the related prediction methods and practical application are studied, and the short-term power forecasting method of the wind power of the vector machine-Markov chain is proposed.
Analysis and Optimization of Impact Condition of Power Conditioning Inverter Based on ANSYS
Authors: Chen Guilin , Wu Yong , Pan Qijun , Ning Fuli , Jiang Peng
Published: November 2018

This paper uses the professional finite element analysis software ANSYS to process a certain type of power regulating inverter. The overall finite element model of the inverter is established then the three-way impact condition is analysed according to the requirements of GJB 1060.1-91. Through the modal analysis in ANSYS software, the natural frequency and natural vibration mode of the inverter are calculated. Based on modal analysis of the inverter, the DDAM shock spectrum analysis function is used to analyse the impact condition of the inverter. Through the calculation of the impact condition, the deformation and stress state of the inverter structure under various working conditions are obtained. By analysing the calculation results, the weak position of the inverter structure is found and the corresponding optimization scheme is proposed to improve the dynamic performance and improve the electron. The overall dynamic performance of the inverter cabinet also provides an important reference for the design of subsequent electronic cabinets.
Dynamic load balancing scheme on massive file transfer system
Authors: Hou Weiguang , He Gang , Liu Xinwen
Published: November 2018

In this paper, a dynamic load balancing scheme applied to massive file transfer system is proposed. The scheme is designed to load balance FTP server cluster. Instead of recording connection number, runtime load information of each server is periodically collected and used in combination of static performance parameters collected on server startup to calculate the weight of servers. Improved Weighted Round-Robin algorithm is adopted in this scheme. Importantly, the weight of each server is initialized with static performance parameters and dynamically modified according to the runtime load. Apache Zookeeper cluster is used to receive all information and it will inform director of the runtime load variation and offline behavior of any server. In order to evaluate the effect of this scheme, a contrast experiment with LVS is also conducted.
Research on Performance Test Characteristics of Solar Energy ORC Generator Set
Authors: Zhang Yongkang , Song Jinghui , Xia Yunfeng
Published: November 2018

In order to study the performance of low-temperature solar-powered ORC generator sets, a solar-powered ORC power generation test bench was designed and built. In the experiment, R-123 was used as the organic Rankine cycle working fluid, and the solar ORC power generation system was experimentally studied. The research results show that when the direct solar radiation intensity is about 400W, the temperature of the heat transfer oil at the outlet of the collector can reach 140 °C. When the temperature of the heat transfer oil at the outlet of the collector is around 110°C, the collector efficiency of the collector can reach about 60%. Under the heat source condition, when the power cycle part is switched from the basic cycle to the regenerative cycle mode, the collector heat collection efficiency can reach about 60%. Under the heat source condition, when the power cycle part is switched from the basic cycle mode to the regenerative cycle mode, the measured efficiency is increased from 9.3% to 10.8%, and the measured cycle efficiency is increased from 1.57% to 1.67%, which is an increase of 6.07%. The measured cycle system efficiency is about 10%, and the heat recovery mode is slightly higher than the basic cycle mode. The organic Rankine cycle performance under different working fluid flows was also investigated in the experiment. The maximum measured average power was 386.27 W when the working fluid flow was 6.88 kg·s. At a certain heat source temperature, as the flow rate of the working fluid increases, the inlet pressure of the expander increases, and the circulating output work also increases. Under a certain working fluid flow rate, as the temperature of the heat source increases, the temperature of the inlet of the expander increases, and the inlet pressure increases. the cycle output work also increased.
Generator flow field and temperature field analysis
Authors: Li Bang , Liu Xiaozhu , Liu Dinghao
Published: November 2018

In this paper, the flow area of the generator and the solid area of the generator are taken as the research object. According to the theory of fluid mechanics and heat transfer, the CFD software Fluent is selected as the calculation tool, and the direct coupling simulation analysis method is adopted to determine the boundary conditions and carry out the ship power generation. Numerical simulation of fluid-solid coupling. The 1/8 circumference of the motor is intercepted as a simulation model. Firstly, the simulation is carried out for the fluid field. According to the simulation results, the wind resistance of each air path in the motor and the total pressure drop of the motor are adjusted, and then the coupling simulation calculation of the fluid field and the temperature field is performed. The calculation results of the temperature field are evaluated.
Study On The Remote Monitoring System For Medical Insurance Prescription Of Chinese Patent Medicine
Authors: Pan Wangping , Du Jianqiang , Nie Bin , Zhou Xian
Published: November 2018

Chinese patent medicine was the preparation and integration of traditional Chinese medicine in traditional Chinese medicine. It was a continuation of traditional Chinese medicine in modern society. China's hospital information construction was at a stage of development. The implementation of the medical insurance prescription monitoring system had significantly improved the level of medical insurance service management in hospitals. Based on the Eclipse platform and MYSQL database, this paper constructed a prescription insurance monitoring system for Chinese patent medicines. A visual graph of drug monitoring and medication recording was formed to determine whether there is any unreasonable phenomenon. At the same time, auxiliary diagnosis needed to input common symptoms of disease into database. According to the search, it could respond quickly, assist doctors to diagnose and improve the speed of seeking medical treatment. Prescription management recorded the prescribed prescriptions to achieve the visualization of prescription management, and achieved maximum maintainability and operability.
Research on the performance of multi-base buoy arrays under the condition of on-called anti-submarine and warship-helicopter cooperation
Authors: Zhang Yuhang , Ju Jianbo , Wang Siqing
Published: November 2018

In order to improve the performance of traditional on-called Anti-submarine, the method of combining the towed sonar and helicopter deployment with traditional buoy arrays for multi-base searching is proposed. Combining the acoustics principle and the actual movement characteristics of warships and helicopters, model of naval movement and multi-base passive circular buoy arrays,square buoy arrays, and triangle buoy arrays deployed by a helicopter were established. The Monte Carlo method was used to simulate and analyse the effect of the initial distance from the call point, the initial position of the submarine, the speed of the submarine economy, the size parameters of the float array and the number of deployments on the multi-base search performance under each formation. The simulation results show that the search performance of the three multi-base arrays decreases with the increase of the initial distance, the initial position of the submarine, and the speed of the submarine economy; the circular multi-base array has the best search performance, and the appropriate deployment radius and the number of passive buoys to be deployed can be selected according to different search requirements and actual operational conditions. This method is suitable for on-called anti-submarine within a certain distance, and has certain military significance for anti-submarine warfare.
A Fast Orientation Invariant Detector Based on the One-stage Method
Authors: Yin Jun , Pan Huadong , Su Hui , Liu Zhonggeng , Peng Zhirong
Published: November 2018

We propose an object detection method that predicts the orientation bounding boxes (OBB) to estimate objects locations, scales and orientations based on YOLO (You Only Look Once), which is one of the top detection algorithms performing well both in accuracy and speed. Horizontal bounding boxes(HBB), which are not robust to orientation variances, are used in the existing object detection methods to detect targets. The proposed orientation invariant YOLO (OIYOLO) detector can effectively deal with the bird’s eye viewpoint images where the orientation angles of the objects are arbitrary. In order to estimate the rotated angle of objects, we design a new angle loss function. Therefore, the training of OIYOLO forces the network to learn the annotated orientation angle of objects, making OIYOLO orientation invariances. The proposed approach that predicts OBB can be applied in other detection frameworks. In additional, to evaluate the proposed OIYOLO detector, we create an UAV-DAHUA datasets that annotated with objects locations, scales and orientation angles accurately. Extensive experiments conducted on UAV-DAHUA and DOTA datasets demonstrate that OIYOLO achieves state-of-the-art detection performance with high efficiency comparing with the baseline YOLO algorithms.
Research and Simulation of Electromagnetic Voltage-Regulated Soft Starter Based on Predictive Control
Authors: Chen Xiaoling , Li Haihua
Published: November 2018

Aiming at the problems of large starting current and unsmooth starting of asynchronous motor, an electromagnetic voltage-regulated soft start control method based on predictive control is proposed. The model of motor soft starter based on predictive control algorithm is established. The control principle of predictive control algorithm is analyzed. The CARIMA model is used to adjust the parameters of motor starting process. With the help of MATLAB, the motor direct start model, the electromagnetic control soft starter model based on PID control algorithm and predictive control algorithm are simulated. The results show that the starting current waveform of the electromagnetic voltage regulator soft starter based on the predictive control algorithm is relatively flat, and the control algorithm can achieve a smooth start of the motor.
Generation Method Of Laser Beam Riding Guidance Information Field Based On Optical Phased Array
Authors: Wang Peiyang , Ai Jialin , Yan Wenbin , An Yudian
Published: November 2018

Laser beam riding guidance was a new concept of guidance technology put forward in 1970s. It is widely used in various laser guided weapon systems. The technology of generating information field in the laser beam riding guidance system is the key of the system. However, the traditional laser beam riding guidance technology needs complex mechanical devices for the generation of guidance information field, optical zoom control and so on. There are many problems, such as the complex structure and it is difficult to guarantee the precision. In this paper, Optical Phased Array (OPA) is used to explore a new method of generating laser beam riding information field, which can realize the non-inertia and rapid deflection control of the beam.
Proximity Effect Aware Detailed Placement in Electron Beam Lithography
Authors: Chen Yuhang , Huang Zhipeng , Chen Xiongfeng , Chen Jianli , Zhu Wenxing
Published: November 2018

Proximity effect is one of the most tremendous consequences that produces unacceptable exposures during electron beam lithography (EBL), and thus distorting the layout pattern. In this paper, we propose the first work which considers the proximity effect during layout stage. We first give an accurate evaluation scheme to estimate the proximity effect by fast Gauss transform. Then, we devote a proximity effect aware detailed placement objective function to simultaneously consider wirelength, density and proximity effect. Furthermore, cell swapping and cell matching based methods are used to optimize the objective function such that there is no overlap among cells. Compared with a state-of-the-art work, experimental result shows that our algorithm can efficiently reduce the proximity variations and maintain high wirelength quality at a reasonable runtime.
Dual-satellite integrated intelligent reconnaissance autonomous decision-making model
Authors: Jiang Haiyang , Liu Xiangyu , zhao Hongli
Published: November 2018

Aiming at aerospace remote sensing technology, this paper proposes a dualsatellite integrated intelligent reconnaissance decision-making model, and establishes a doublesatellite system. One satellite is used for “general investigation” and one satellite is used for “detailed investigation”. The target is carried out by general investigation load. Track identification provides guidance for detailed inspection loads, thereby improving the accuracy, real-time, flexibility and intelligence of space remote sensing. The focus is on three aspects: investigation model design, key algorithm research and semi-physical simulation verification. The reconnaissance model design completes the conceptual design and process demonstration of the model. The key algorithm research part completes the research of the fast detection based on deep learning and the key algorithm of load imaging strategy decision in the system. The satellite semi-physical simulation verification is carried out by constructing the semi-physical simulation verification system.
A High-precision Current Sense Circuit with Trimming for DC-DC Converts
Authors: Duan Ning , Liu Shulin , Zhu Xiangdong , Pei Jinjun , Zhu Haipeng
Published: November 2018

A high-precision current sense circuit with trimming is proposed to realize the over-current protection of the power management chip and improve its conversion efficiency. Based on solving the problem of voltage offset and current inrush caused by process deviation, this circuit can detect the value of the inductor current accurately. By designing the bandgap reference circuit and the reference voltage bias network, the required stable reference voltage and bias current can be obtained. The trimming bit selection circuit can realize the trimming function. This circuit is designed with TSMC 180nm 1P3M GEN2 process, and all circuits are verified by Cadence Spectre.
Ship Tracking with Static Electric Field Based on Adaptive Progressive Update Extended Kalman Filter
Authors: HU Shouwei , YAN Bing
Published: November 2018

An adaptive progressive update extended Kalman filter is introduced for unknown noise in ship tracking using static electric field. The corresponding state space model is established; the algorithm is introduced, and the simulation is designed. The simulation results show that the adaptive algorithm can effectively improve the performance of the algorithm, when the noise covariance deviates from the real value; the finite number of noise covariance estimation is beneficial to the stability of the filter.
Modeling and optimization of boiler combustion system in power station
Authors: Zhang Jiaying , Zhang Xuhan , Wang Zhe
Published: November 2018

This paper studies on researching the method of reducing NOx production and coal consumption of coal-fired power station boiler. It takes a power plant 600MW subcritical boiler as the research object, from the power plant Supervisory Information System (SIS) it gets the historical operation data as experimental data. Based on GA-GRNN (generalized regression neural network based on genetic optimization), a predictive model of boiler combustion system with 39 variables such as inlet and output of coal consumption and NOx production was established. Finally, coal consumption and NOx production were optimized based on the neural network model of boiler combustion system. In this paper, 29 adjustable thermal parameters of boiler combustion system model input are selected as optimization variables and the improved NSGA-II (non-dominated sorting genetic algorithm) is used to optimize multiple objective variables. The optimization study was carried out under the actual operating condition of 349.21 MW. After optimization, the coal consumption of power supply was reduced by 5.67% and the NOx production was reduced by 50%. Therefore, the optimization results provide guidance for adjusting the combustion of utility boilers.
Research on coal-rock recognition based on sound signal analysis
Authors: Chen Xihui , Yang Zenan , Cheng Gang
Published: November 2018

The recognition of the cutting state of shearer is the key technology to realize variable speed cutting and mining automation. It is of great significance for improving shearer reliability, ensuring personal safety and improving coal quality. This paper proposed a coal-rock recognition method based on sound signal analysis. The original sound signal produced during the cutting process of shearer is decomposed by variational mode decomposition (VMD), and the obtained IMFs can construct a signal matrix. The signal matrix is processed by singular value decomposition (SVD), and a series of singular values can be obtained and defined as the signal features. Finally, the coal-rock recognition is realized by extreme learning machine (ELM) based on the extracted signal features. The experiment results show that the overall recognition accuracy is 91.7% under the actual cutting condition, which verifies the effectiveness of the proposed method in coal-rock recognition, and lays a theoretical foundation for the automation and intellectualization of shearer mining.
Research on aerodynamic drag of a solid attitude control thruster based on PWM principle
Authors: Yang Zhong , Yan Hongwei , Sun Junlong , Li Wubin
Published: November 2018

Solid attitude control thrusters based on PWM principle are widely used in kinetic kill vehicle to control its attitude. In this paper, a kind of solid attitude control thruster is proposed and its piston’s motion model is established. One of the most important variables which has significant effect on the validity of the model is aerodynamic drag of rocker arm. We did research on the aerodynamic drag by throttle theory, numerical simulation and experiment. The results were consistent and proved to be valid by testing the pressure in the two control chambers. The result is expected to provide reference for the calculation and test of the aerodynamic drag and design of the solid attitude control.
A reference current source with a low temperature coefficient
Authors: Han DongYang , Xin XiaoNing , Liu GuoFeng
Published: November 2018

In view of the high demand for low temperature coefficient reference current sources in integrated circuits, the advantages and disadvantages of several typical reference current sources in circuit structure and temperature characteristics are compared. In this paper, a low temperature coefficient reference current source is designed. Based on Hua Hong HHNECGE 0.35um process, the output current is 0.4uA, the temperature range is -40°C-125°C, and the temperature coefficient is 7.6ppm/°C under typical process angle. Other processes The temperature coefficient under the corner is at 10ppm/°C.
Design of a Missile-borne Conformal Microstrip Navigation Antenna
Authors: Wu Junyan , Yu Jiaao , Tao Qin
Published: November 2018

A missile-borne conformal dual-fed circular polarized microstrip antenna array is designed and fabricated, which realized omnidirectional radiation in horizontal direction. Frequencies of the antenna include GPS L1 frequency (1.575GHz) and Beidou navigation system B1 frequency (1.562GHz). Based on the HFSS simulation, the influence of conformation is analyzed on S11, axial ratio and gain of antenna array. The size of microstrip patches is changed so that the influence of conformation on antenna can be reduced. The circular polarization performance and the circular polarization gain of the antenna are also improved. The antenna array prototype is fabricated and measured. The result shows that the S11 parameter of the antenna is less than -10dB in the 1.55~1.60GHz frequency band. At the GPS L1 frequency and the Beidou B1 frequency, the maximum of horizontal omnidirectional gain is 1.73dB, 1.25dB respectively. The out-of-roundness of the radiation pattern is less than 2.5dB. The antenna has a good horizontal omnidirectional circular polarization radiation performance.
Design of ultrasonic testing device for fatigue damage of pressure vessels
Authors: LU Wenchao , YANG Huibin , YAN Juan , KANG Chengbo
Published: November 2018

The container fatigue damage detection device is researched and designed for the fatigue damage detection requirements of pressure vessels. The hardware design of the detection device, the corresponding detection technology and the functions realized are introduced. The new test performs ultrasonic nondestructive testing by driving five DC servo motors to drive the mechanical part of the test device. Research on the detection system and technology to automate the detection of fatigue damage in pressure vessels.
Immunothérapie et thérapies ciblées, une combinaison d’avenir dans la lutte contre le cancer
Authors: Andrieu Nathan , Bendriss-Vermare Nathalie
Published: November 2018

Dans le cadre d’un partenariat avec médecine/sciences, et pour la seconde année, des étudiants du module d’immunologie virologie et cancer du Master de cancérologie de Lyon présentent une analyse d’articles scientifiques récents faisant état d’observations innovantes et importantes. Ce travail a été encadré par des chercheurs confirmés du département d’immunologie, virologie et inflammation du CRCL. Le master de cancérologie de Lyon (Lyon1-VetAgroSup) accueille chaque année 30 à 40 étudiants en M1 et en M2. Ce master dit « d’excellence » assure aux étudiants de M1 une formation à la cancérologie reposant sur un socle de base commun (biologie cellulaire, moléculaire, immunologie, bio-statistique...). En M2, les étudiants peuvent choisir l’une des trois spécialités suivantes : le Master recherche « Recherche en cancérologie », le Master recherche et professionnel « Technologie haut débit en cancérologie » et enfin le Master recherche et professionnel « Innovations thérapeutiques en cancérologie ». Le Master de cancérologie de Lyon repose sur une forte implication des chercheurs et enseignants-chercheurs du laboratoire d’excellence en développement et cancérologie (LabEx DEVweCAN), ainsi que sur un partenariat solide avec plusieurs instituts dont le MIT (Massachusetts Institute of Technology, Cambridge, États-Unis), l’université d’Harvard (Boston, États-Unis), l’université Johns Hopkins (Baltimore, États-Unis), l’Imperial College of London (Royaume-Uni), les universités de Jiao Tong (République Populaire de Chine) et de Tokyo (Japon), entre autres. Pour plus d’information : http://devwecan.universite-lyon.fr/formation/
La sénescence en passe d’être vaincue ?
Authors: Jordan Bertrand
Published: November 2018

Senescent cells are involved in many age-related diseases, and the effects of their elimination by “senolytic” drugs is an active research field. A recent paper describes a convenient murine model of induced senescence and uses it to convincingly demonstrate the positive effects of senolytics on performance and lifespan. Clinical studies have already been initiated; this approach hold promise to eventually improve human “healthspan”.
Association of Trunk Rotational Velocity with Spine Mobility and Curvatures in Para Table Tennis Players
Authors: Zemková Erika , Muyor José , Jeleň Michal
Published: November 2018

This study investigates the relationship of trunk rotational velocity with mobility and curvature of the spine in wheelchair table tennis players. Eleven para table tennis players and 13 able-bodied athletes performed 5 seated trunk rotations to each side with 1 kg barbell placed on the shoulders. Trunk rotational velocity and respective angular displacement were significantly lower in para table tennis players compared to able-bodied athletes. Both groups showed similar values of thoracic kyphosis. However, para table tennis players exhibited lower lumbar inversion and pelvic retroversion compared to able-bodied athletes. Peak and mean velocity in the acceleration phase of trunk rotation correlated with angular displacement in both para table tennis players (r=0.912, p=0.001; r=0.819, p=0.013) and able-bodied athletes (r=0.790, p=0.026; r=0.673, p=0.032). These velocity values were also associated with lumbar curvature (r=-0.787, p=0.003; r=− 0.713, p=0.009) and pelvic tilt angle (r=0.694, p=0.014; r=0.746, p=0.007) in para table tennis players. Findings indicate that slower velocity of trunk rotations in para table tennis players might be due to their limited range of trunk rotational motion. Decreased posterior concavity could also contribute to these lower values. However, other biomechanical factors may have an impact on the association between these variables and have yet to be documented.
Hybrid Arch for Acute Type A Aortic Dissection: When to Deploy the Endograft? Debate: Frozen versus Staged?
Authors: Appoo Jehangir , Fichadiya Akash , Smith Holly , Kotha Vamshi , Herget Eric , Gregory Alexander , Szeto Wilson
Published: November 2018

Advances in open and endovascular techniques have resulted in novel approaches to repair of acute Type A aortic dissection. Hybrid arch procedures involve open arch resection and stent grafting of the descending aorta with stent graft insertion in one of two ways: Frozen or Staged. In this article, pros and cons of the two different paradigms of emerging hybrid arch techniques for acute Type A aortic dissections are discussed.
Infertility Treatments and Long-Term Neurologic Morbidity of the Offspring
Authors: Levin Shai , Sheiner Eyal , Wainstock Tamar , Walfisch Asnat , Segal Idit , Landau Daniella , Sergienko Ruslan , Levitas Eliahu , Harlev Avi
Published: November 2018

Objective To determine the risk of long-term neurologic morbidity among children (up to 18 years) born following in vitro fertilization (IVF) or ovulation induction (OI) treatments as compared with spontaneously conceived.

Study Design A population-based cohort analysis was performed, including data from the perinatal computerized database on all singleton infants born at the Soroka University Medical Center (SUMC) between the years 1991 and 2014. This perinatal database was linked and cross-matched with the SUMC computerized dataset of all pediatric hospitalizations.

Results Neurologic morbidity was significantly more common in IVF (3.7%) and OI (4.1%) offspring as compared with those following spontaneous pregnancies (3.1%; p = 0.017). In particular, attention deficit/hyperactivity disorders and headaches were more common in the OI group and sleep disorders in the IVF group, whereas autism and cerebral palsy were comparable between the groups. In the Weibull multivariable analysis, while controlling for maternal age, preterm delivery, birthweight centile, maternal diabetes, and hypertensive disorders, IVF (adjusted hazard ratio [HR]: 1.40; 95% confidence interval [CI]: 1.14–1.71; p = 0.001), but not OI (adjusted HR: 1.17' 95% CI: 0.92–1.48; p = 0.196), was noted as an independent risk factor for long-term pediatric neurologic morbidity.

Conclusion IVF offspring appear to be at an increased risk of long-term neurologic morbidity up to 18 years of age.