bluuebunny/crossref_metadata_2025 huggingface dataset:
Medical waste treatment and electricity generation using pyrolyzer-rankine cycle for specialty hospitals in Quezon City, Philippines
Authors: Manegdeg F , Coronado L O , Paña R
Published: April 2020

Acquisition, treatment, and final disposal of health-care waste is a vital public concern. Improper disposal has heightened this concern as it could lead to a widened risk of transmission of agents associated with blood-borne diseases. One of the ways to address these concerns is waste disposal and waste-to-energy plant. This facility is envisioned not only to manage hazardous wastes from hospitals with the least emissions of toxic substances and greenhouse gases but also to generate electricity. This study investigated the feasibility of developing waste disposal and waste-to-energy plant which involved: the selection of hospital type and location, waste composition, energy conversion, and power plant technology, and financial viability of the plant. The sampling design process identified the hospitals to be surveyed. The criteria include proximity of the hospitals, number of beds, and type of hospitals. A survey of waste generation across the specialty hospitals was then conducted and determined the type of waste, the quantity of the wastes produced, the percentage by weight, bulk density, and composition of the wastes. A selection was done to determine the energy conversion technology. The electric power plant technology was then selected knowing the characterization of the synthetic gas. The average waste generation was found to be 579 kg waste per day which has 29,062 kJ/kg calorific value. The study shows that electricity could be generated from this waste by utilizing a Pyrolyzer - Rankine Cycle power plant and is viable with a payback period of 5 years, and a Benefit-to-Cost ratio of 4. A business plan and enabling environment for the establishment of the Pyrolyzer – Rankine Cycle power plant is recommended to be studied.
A Shallow Prediction Model with Enhanced Features for Video Time Series
Authors: Zhang Yifei , Bie Hongxia
Published: April 2020

Fast video time series prediction is an important part in video anomaly detection in deep learning framework. Time series deep learning models have good performance in time-series data prediction, such as traffic flow, rainfall and network traffic. The models, such as ConvLSTM, ConvGRU with complex structure and large amount of computation, are difficult to fit the video time series prediction. In this paper, we analyze data characteristics of video sequences and propose a shallow video series prediction model. We not only consider the spatial correlation in continuous video frames, but also investigate the interval video frames, which also maintain spatial correlation. We explore the gray scale pixel values of the interval frames which appear specific trend properties when we connect the context pixels together. Based on the enhanced features, we design a shallow 2D convolutional video time series prediction model with good prediction performance and much less total parameters.
Application Research of “Edge-Cloud Collaboration” Architecture in Security Protection of Ubiquitous Power Internet of Things
Authors: Song Hu , Chen Yuhang , Dong Qingquan , Wang Xiaolong
Published: April 2020

With the planning and construction of the ubiquitous power Internet of Things(UPIOT), how to achieve secure connection and interaction between the platform and the terminal becomes a crucial issue. Based on cloud computing and edge computing, this paper constructs the “edge-cloud collaboration” architecture of UPIOT to meet the functional requirements of grid-side intelligent services and core-side data analysis and low-latency, high-bandwidth, and large-access performance. According to the actual deployment situation of Jiangsu electric power, the firewall and VPN application scenario security protection scheme is proposed to provide a theoretical basis for the UPIOT security protection.
A Novel Multiuser Detector for LDPC-Coded DS-UWB Space Formation Flying
Authors: Ma Bo , Liu Qingzhi , Wu Zhilu , Jiang Xu
Published: April 2020

Space formation flying has attracted a lot of attention recently. In this paper, we using direct-sequence ultra-wideband (DS-UWB) as the physical layer of inter-spacecraft communications. The traditional multiuser detection method like soft-input soft-output (SISO) cost too much computation. The proposed multiuser detector no longer uses interleaving, and the computational complexity has a linear relationship with the number of users. The bit error ratio (BER) simulation result shows that the proposed method approaches the single-user system with increasing signal-to-noise ratios (SNRs).
Research and Design of LED Light Suppression Flicker Technology in Visible Light Communication Technology
Authors: Si Yuncheng , Pan Yu , Li Tao , Dong Guangzhi
Published: April 2020

“Lighting communication integration” is a key technology research for the future application of visible light communication(VLC). However, the bandwidth characteristics, dynamic modulation range and linear modulation performance of existing white LED still do not meet the requirements of high-speed communication. After adding the dimming function, the naked eye It is noticeable that flicker is felt. In order to solve the problem of LED flicker caused by high-speed communication, this paper proposes a “lighting and communication integration” technology scheme based on visible light communication(VLC), which studies from the aspects of suppressing flickering VLC scheme, LED communication dimming, and high-efficiency modulation driving circuit design. A PWM dimming control technology based on optical OFDM system is used for VLC and LED dimming scheme. Finally, the technology is applied to the typical application scenario of the power grid—cable tunnel, which realizes the two-way real-time voice communication of cable tunnel inspection personnel. And accurate positioning to ensure the personal safety of the inspectors and the safety of the grid production.
Software Practice of Orderly Charging Information Communication System
Authors: Wang Weiguo , Li Tao , Pan Yu
Published: April 2020

At present, SGCC actively implements the national New Energy Strategic Policy, vigorously promotes the construction of electric vehicle charging piles, and actively guides electric vehicles to participate in orderly charging through multiple ways. Combined with the construction objectives and requirements of SGCC for orderly charging business, based on the functions of the original charging pile operation management system, our company(Beijing Smart-chip Microelectronics Technology Ltd.) has realized the orderly charging system of charging pile through structural transformation and function upgrading. The system is realized by distributed and microservice architecture mode, which can support large-scale charging piles fast access. This paper describes the orderly charging system of charging pile and the practice of distributed and microservice architecture in the system.
Design, Simulation and Failure Influence of Tape Spring Hinges in a Large Deployable Antenna
Authors: Wang Pengpeng , Zheng Shikun , Wang Feng
Published: April 2020

The design, simulation and failure influence of tape spring hinges in a large deployable antenna is studied. By sensitivity analysis between modal frequencies of the large deployable antenna and stiffness coefficients of the tape spring hinge, it is found that compression stiffness along longitudinal axis and bending stiffness about transverse axis are the key points of tape spring design. Stiffness coefficients, buckling loads and bending moments of the tape spring hinge are obtained by mechanical simulation. By in orbit disturbance analysis, disturbance loads applied on the tape spring hinge result from satellite attitude control and scanning mechanism operation are presented. Finally, failure influences of the tape spring hinges on both antenna modal frequencies and pointing accuracy are studied.
A New Dynamic Parameters V-RC Model of Battery Parameter Identification
Authors: Zhang Liguo , Gao Jing , Liu Le , Miao Guangxuan , Qi Jintao , Xu Haichao , Luan Jiacui
Published: April 2020

Different state of charge (SOC), batteries have different model parameters. This paper proposes a dynamic parameter identification method for battery models under different SOC. Firstly, dynamic parameter V-RC model of battery was designed according to the hysteresis loops characteristics and the polarization characteristics of the battery voltage during the charge-discharge process. Next, the test program was designed which can complete the lithium battery charge and discharge data acquisition, including identification of battery model parameters for AC signal injection. The relationship between OCV and SOC are obtained by using the least squares curve fitting method, which realizes the function fitting of the model’s parameters. Then, battery transient response experiment indicating that have different parameters under different SOC. Finally, test results can show that open-circuit voltage (OCV) error of the new model is lower than constant parameter model OCV error. The error of the fixed parameter model OCV is 2.6%, while the OCV error of the dynamic parameter model is 1.6%. Dynamic parameter VRC model can more accurately reflect the actual state of the battery.
The Application of FTA and FCE on Navigation Safety Assessment
Authors: Yan Langtao , Tan Jiawan , Ai Jian , Zhang Shuang
Published: April 2020

In order to analysis the impact of ship state on the navigational safety, the fuzzy comprehensive evaluation method based on fault tree of ship safety state is to be present in this paper. The fault tree of ship navigation state to be established using the software named Easydraw, after analyzing systematically influence factors of ship safety navigation, and the structure important degree of the basic event is calculated based on the fault tree, which made the main factors influencing the ship navigation safety clear.. With the analyzing results of the navigation state fault tree, several important factors such as speed, channel and visibility, to be regard as the main correlation factor evaluating ship safety state, and the mathematical model of fuzzy comprehensive evaluation on ship safety state to be established. The experiment is conducted in the YouShui river, the relevant parameters is obtained, using the GPS navigation system on board, and the navigation state is to be analyzed and evaluated by the mathematical model. The evaluation results shows that the evaluation model applied to the ship safety state is reliable and effective.
Research on the Influence of Torque, Speed and Allowable Loss Deviation on the Optimized Current in the Efficiency Optimization Control of IPMSM
Authors: Pang Likun , Wu Qinmu , Ma Senquan , Li Jiahao
Published: April 2020

In the efficiency optimization control of IPMSM, the working state of the search should be determined by using the search method to obtain the initial optimized current set. For any system, it is expected that the working state of the search should be as little as possible. Meanwhile, according to the initial optimized current set, the interpolation method can be used accurately to realize the efficiency optimization of the whole state. Based on the total loss model of IPMSM, various constraints of running and optimization theory, the equation satisfying the optimization current was obtained, and the influence of motor speed and torque on the optimization current was theoretically analyzed. Through the simulation test of electric drive system of electric vehicle, the optimization current of motor in various states is searched. The simulation results verify the correctness of the theoretical analysis results. Then the number of states to be searched under different allowable loss deviations is analyzed to obtain the initial optimized current set.
Research on Server Health State Prediction Model Based on Support Vector Machine
Authors: Jin Dan , Li Ce , Wang Qiong , Chen Yuhang
Published: April 2020

With the development of artificial intelligence, machine learning methods have been widely applied to predictive modelling in various fields. Support vector machine is a linear classifier with the largest interval defined on the feature space. In order to improve the current status of server operation and maintenance, and improve the accuracy and efficiency of server health prediction, this paper studies the feature quantity selection based on grey relational analysis, studies the support vector machine applied to data generalization and classification, and establishes a health prediction model. The simulation training of historical data shows that the method has fast learning, high prediction speed, high efficiency, high accuracy and wide application prospects.
An Intrusion Prevention Scheme for Malicious Network Traffic Based on SDN
Authors: Xu Xiaofeng , Dai Jiahao , Zhi Yifang
Published: April 2020

In recent years, SDN technology has developed rapidly, and the security of SDN is the key to its further development and application. Intrusion prevention system possesses both the features of intrusion detection and protection, which is one of the important methods to ensure the security of SDN network. In this paper, we proposed a SDN-based intrusion prevention scheme for SDN security. The scheme utilizes the programmability of SDN to create four modules on the application plane of the controller, including the network monitoring module, IP address detection module, destructive packets detection and Snort linkage module. The scheme also provides users with Web UI and manual/automatic operation mode. Finally, we deployed the scheme on the Mininet platform with the Floodlight controller.
Design and Development of Campus Environment Display System Based on Augmented Reality Technology
Authors: Wang Shijie , Liu Huaqun , Shu Hou , Zhang Xinzhe , Zhang Yu
Published: April 2020

With the rapid development of augmented reality technology and the continuous improvement of people’s needs in various aspects, people are more looking forward to interactive, real-time augmented reality systems. In the field of physical display, Augmented Reality Technology provides a more convenient channel for people to experience various objects at zero distance, and reforms a new form of physical display. Including campus display, AR augmented reality technology creates a new display experience for users. This project uses Beijing Institute of Graphic Communication as the research model. In the early stage, the scene was modeled using Cinema 4D software. In the later stage, the scene was interactively designed using Unity 3D. The Vuforia engine was used to detect and track feature points and match them. After superimposing on the scene, we explored the optimization strategy of AR augmented reality technology in campus display applications.
A Scheme of Anomalous Detection Based on Reinforcement Learning for Load Balancing
Authors: Kim Hye-Young
Published: April 2020

In recent, both researchers and developers have great interests in anomalous detection. However, it is still difficult to implement a uniform framework for anomalous detection. Also, the network anomalous detection using deep learning methods has been discussed with potential limitations and interests. An anomalous detection in wireless or wired network is extremely important because it is caused by flood traffic of network and intrusion. Patterns of malicious network loads are defined, while anomalous detections is more suitable for detecting normal and anomalous network loads by means of deep learning. The important goal of these issues is to recognize the anomalous detections for better preparation against future load balancing of networks. In this paper, we propose an agent Detectbot that processes anomalous detection for load balancing based on reinforcement learning. Our simulation results show that the reinforcement learning scheme is effective for anomalous detection in load balancing.
Accelerating k-Means on GPU with CUDA Programming
Authors: Yang Can , Li Yin , Cheng Fenhua
Published: April 2020

We accelerate basic k-Means algorithm using CUDA GPU, a new programming model by NVIDIA, and experiment data shows we achieve a maximum speedup of 67.752, while other teams claim 20 to 40. Also we find that the basic k-Means algorithm is most sensitive to the cluster size k, and less to the datasets size b and least to the dimension d. In addition, we find the CUDA shared memory improves the performance, but also depends on which factor we scale.
Analysis and Implementation of Improved Software Phase-Locked Loop for Single-phase Grid-connected Inverter
Authors: Zhou Defang , Fang Yu , Cao Songyin , Yao Yong
Published: April 2020

For single-phase grid connected inverter, based on the traditional closed-loop structure of three-phase phase-locked loop (PLL), an improved software PLL was proposed. The basic principle of the phase-locked loop was analyzed and its mathematical model was deduced. In addition, the software implementation method of the phase-locked loop was presented. Then, the influence resulted from the change of amplitude, frequency and phase on the grid voltage was simulated with PSIM software. The results show that the software phase-locked loop can realize the phase tracking at any time in the cycle effectively and quickly, without waiting for the zero crossing of the grid. Finally, the software phase-locked loop proposed in this paper was implemented respectively by using TI’s DSP TMS320F28035 and TMS320F2808 and applied to the 500W dual-channel single-phase grid-connected micro-inverter and 5kW single-phase grid-connected inverter. The simulation and experiment results verify the proposed software phase-locked loop.
Convergence of IT and SCADA: Associated Security Threats and Vulnerabilities
Authors: Smurthwaite Michael , Bhattacharya Maumita
Published: April 2020

As many industries shift towards centralised controlled information systems for monitoring and control, more importance is being placed upon technologies such as Supervisory Control and Data Acquisitions industrial systems (SCADA). This focus on integration and interoperability presents numerous challenges for security personnel and organisational management alike. It becomes paramount therefore to reciprocate this new direction within an organisation with adequate plans and frameworks that ensure protection and security of its SCADA architecture. A clear understanding of the relevant threats and vulnerabilities is critical for adopting/developing appropriate policy and frameworks. To this end, in this research we identify and analyse relevant SCADA security threats and vulnerabilities and present a simple scheme to classify them for better understanding.
Research of E-map System Based on Baidu Map API for University Campus
Authors: Cai Yingjian , Hu Lishuan , Xiang Caihong
Published: April 2020

With the rapid growing of universities, the campus infrastructure continues to expand. Visitors are not clear the position of their destination. Traditional online mapping service updating not timely can only supports customers to browse and query incomplete description of the destination. In this paper, a spatial information inquiry system of campus is designed based on Baidu map API with JavaEE technologies. The system can provide the basic map function for almost all important things on campus. Based on this method, Beijing Union University campus E-map has been developed successfully, which demonstrates the feasibility of this solution.
Natural Scene Text Detection Based On Multi-level Fusion Proposal Network
Authors: Li Tong , Li Wanggen , Zhu Nannan , Gong Xuecheng , Chen Jiajia
Published: April 2020

Natural scene text detection is a challenging issues. In this work, a multi-level features fusion two-stage text detection network was developed to solve the problem of the insufficient use for feature map and the difference between text and common target. In order to obtain deep semantic feature, the network framework of VGG-16 was improved, and different levels of convolution feature map were confused, meanwhile the fusion approach was partially adjusted. Also, vertical proposal network was used to classify and regress bounding box. Results indicated the accuracy and recall rate of this method are 85.4% and 81.0%, respectively, by evaluating the net on ICDAR2013 dataset. The experimental results suggest that the multi-level features fusion method can improve the efficiency of feature map in natural scene text detection.
2D Extreme–Point Symmetric Mode Decomposition Method
Authors: Gao Feng , Chi Chunmei
Published: April 2020

This paper proposes a kind of 2D extension of Extreme–Point Symmetric Mode Decomposition Method. The 2D-sifting process is performed by 4 steps: 1 Extrema points detection (by neighboring window). 2 Delaunay triangulation is done over the grid of all extrema points. 3 Mid points of the triangulation are obtained. 4 Thin plate splines are used to interpolate the mid points. 5 Sifting processing is carried out. Finally, experiments are done with real images to show the efficiency of this 2D Extreme–Point Symmetric Mode Decomposition Method.
A Hybrid Collaborative Filtering Recommendation Algorithm Based on User Attributes and Matrix Completion
Authors: Yi Jie , Zhong Maosheng , Chen Yinfen , Jie Anquan
Published: April 2020

Collaborative filtering is a popular strategy in recommendation system. Traditional collaborative filtering relies on the user-item rating matrix that encodes the individual ratings of users for items to make recommendations. However, in the real-world, the rating matrix is highly sparse, and many new users do not have rating records, thus traditional collaborative filtering could not provide satisfactory recommendations. To alleviate this issue, we propose a hybrid algorithm that utilizes LMaFit to complete rating matrix, reducing the degree of sparsity, and provides a hybrid user-similarity to supply a good support for recommending to new users in the condition of cold start. Extensive experiment results on real-world datasets show the proposed algorithm has a better performance than other methods.
Distributed Cloud Platform Access Collaborative Selection Algorithm based on Multi-objective Optimization
Authors: Zhao Wei , Li Huiqin , Wang Chenfei , Wang Yajuan , Xu Liyang , Liu Juan
Published: April 2020

Decentralization is the mainstream trend of large-scale center construction. Based on the requirements of mass service access, big data processing and high reliability of State Grid 95598 cloud platform, a distributed cloud platform access collaboration selection algorithm based on multi-objective optimization is proposed. The algorithm considers load balance of distributed cloud platform and average user experience quality. In addition, it measures the comprehensive performance of the cloud platform from users and load balance of distributed cloud platform based on the synergy degree in the selection process in order to avoid “cask effect”. The simulation results show that the algorithm can adjust the access cloud centers of users in real time and balance loads of cloud centers, which can provide technical support for cloud platform construction in the era of big data.
Object Detection Algorithm for Improving Non-Maximum Suppression Using GIoU
Authors: Hou Zhiqiang , Liu Xiaoyi , Chen Lilin
Published: April 2020

To address the problem of object miss detection and object false detection in single threshold-Non-Maximum Suppression algorithm, this paper proposed a GDT-NMS (Generalized Intersection over Union Dual Threshold NMS, GDT-NMS)) algorithm which using GIoU(Generalized Intersection over Union). Using the GIoU indicator computing the similarity between objects, can better describe the relative position and overlap between the objects. And we proposed the dual-threshold NMS algorithm, which can balance the relationship between the object missed detection problem and the object false detection problem, reduce “false positive example” problem. By nonlinearly processing the weight function, the object is better distinguished. The algorithm uses Faster R-CNN as the detector. The experimental results show that the improved algorithm has outstanding performance.
Visual Tracking Algorithm Based on Color Name Histogram
Authors: Yue Chenchen , Yu Wangsheng , Hou Zhiqiang , Ma Sugang
Published: April 2020

Aimed at the problem that traditional histogram is sensitive to illumination changes in visual tracking, combined with the CN(Color Name) feature, we proposed a new feature(denotes CNH, Color Name Histogram) based on color name. Firstly, the method projected the original RGB image to CN space to obtain robust 11 feature layers. Then, we counted the each pixel numbers of feature layers. Finally, normalizing the amount of pixels in each layer. In addition, we adopted a feature adaptive fusion method to combine CNH and HOG(Histogram of Oriented Gradient). In order to prove validity of the proposed algorithm, we use Staple(Sum of Template And Pixel-wise Learners) algorithm frame to make a controlled trial. In contrast with the reference algorithms, the success of our algorithm increases by 1.5% and the precision increases by 1.7%. The results show that this method retains the advantages of traditional histogram which is insensitive to target deformation, but also enhances the robustness to illumination change.
Research on User Clustering Algorithm Based on Improved ROCK Algorithm
Authors: Wang Rong , Sun Aimin
Published: April 2020

This paper analyzes the merits and demerits of the ROCK algorithm firstly, then indicates that the merits of Rock is easy to cluster categorical database such as Mushroom, and the demerits is that the similarity formula sim of this algorithm depends on the intuition of domain experts. The improved ROCK gets the result of clustering by calculating the similarity using Jaccard coefficient based on the reason which is that the bigger figure of the similarity is, the more alike the object is. Then we can implement personality recommendation according to the result.
Scheduling Problems of Automated Guided Vehicles in Automated Container Terminals Using a Genetic Algorithm
Authors: Gan Yufan , Ji Shouwen , Zhao Qianru , Guo Dong
Published: April 2020

The automated guided vehicle (AGV) is adopted as horizontal transport equipment in automated container terminals. In order to improve the operation efficiency of the AGV, we constructed a mixed integer programming model for AGV scheduling optimization in unloading operations in an automated container terminal with a vertical layout. The model aimed at minimizing the end time of the last task and the time of AGV invalid operation. The constraints included the operation limit and the time window. We also designed a genetic algorithm to solve the model, and set three experiments to prove the superiority of the method. The experimental results show that the genetic algorithm can significantly improve the calculation efficiency in large-scale AGV scheduling problem, and the scheduling model we constructed can better improve the operation efficiency of the AGV. We also simply studied the problem of the optimal number of AGV configurations.
Research on Flight Time Optimization of Short-term Airport Group Based on Weather Conditions
Authors: Ji Shouwen , Zhang Dan , Liu Huaiyuan , Guo Dong
Published: April 2020

Flight schedule optimization is critical to improving air traffic flow management. This paper considered the impact of weather conditions on the capacity of the airport and airspace, and combined ground-holding and air-holding strategies to establish a multi-objective short-term airport group flight schedule optimization model. At the same time, this paper designed a non-dominated sorting genetic algorithm (NSGA-II algorithm) with an elite strategy, and verified the case with the Yangtze River Delta airport group. The results show that the model can reduce the delay time and delays of the airport group by nearly 25%. The innovation point of this paper is to further consider the impact of weather factors on flights in reality, and improve the traditional genetic algorithm for better solution, which has practical significance. The method can effectively improve the level of air traffic flow management.
A Novel Arc-length Numerical Method for Shock Interruption Problems
Authors: Xu Hui
Published: April 2020

Accurately tracking the propagation process of a wave front is important for studying the propagation law of shock waves. In this study, a novel arc-length numerical algorithm to effectively calculate the interruption of shock waves is proposed, and a systematic theoretical analysis and application of this research are conducted. First, the arc-length numerical method is proposed based on the hyperbolic conservation model equation, and the basic concept of the arc-length numerical method of hyperbolic problems is provided. Then, an introduction method for arc-length in multidimensional space is described from the perspective of tensor analysis, and the mathematical model of shock wave propagation problems in arc-length space is established. The discrete solution of the spatial mathematical model of arc length is given, and control and smoothing factors are added to ensure shock wave propagation without oscillation. Finally, the numerical calculation of the Lax and double Mach reflection problems shows that the arc-length numerical algorithm can be widely used as a new calculation method for shock interruption problems.
Time-window-based Scheduling Strategy and Optimization for Maximizing the Income of Drop and Pull Transport
Authors: Xu Linlong , Qiu Zheyong , Kang Zibo , Ma Xiaojuan , Xiong Huilin , Yang Lei
Published: April 2020

As an intensive and efficient way of transportation, drop and pull transport has become the mainstream transportation organization of foreign developed countries and regions. Based on the freight demand vector and aging of a given initial state, this paper established a goal planning and scheduling model based on the maximization of time window revenue to get the most efficient deployment plan under the condition of high customer satisfaction. The genetic algorithm based on task urgency was used to solve this model to obtain the optimal allocation scheme of total income. Finally, the number of algorithm iterations was analyzed, which proved the effectiveness of the algorithm performance. Through the sensitivity analysis of the number of tractors, this paper gave suggestions for more efficient tractor configuration.
A Case Study of Finite Element Check for the Strength and Rigidity of the Escalator Truss
Authors: Shu Wenhua , Ouyang Huiqing , Jin Mingdi , Kuang Lin , Wang Dongmei
Published: April 2020

As an important part of escalator, the truss must be checked for strength and rigidity after design. In this paper, the finite element method is used to check the strength and rigidity of an escalator truss under various working conditions. Compared with the traditional design method, the finite element analysis can obtain the mechanical properties of the object quickly and accurately, shorten the project development time, and thus reduce the design and test cost greatly.
An Adaptive High-Resolution and Low-Dissipation Hybrid Energy Consistent/WENOCU Scheme
Authors: Li Liang , Wang Hongbo , Xiong Dapeng , Sun Mingbo , Tang Tao , Zhao Guoyan , Wang Xinxin
Published: April 2020

We investigate the performance of the hybrid energy consistent/WENOCU4 scheme compared to the classical WENOCU4 scheme. It is borne out that the hybrid scheme preserves excellent shock-capturing ability without numerical oscillations. In the meantime, the hybrid scheme can achieve more accurate representations of smooth flow features which indicates its low-dissipation capacities. Moreover, hybrid scheme significantly outperforms WENOCU4 for its superior computational efficiency. Therefore, employing hybrid scheme is a much more cost-effective choice for the simulation of shock/turbulence interaction.
Fractal Effect of Random Disturbance on Reaction-diffusion Equation
Authors: Zhang Li
Published: April 2020

Fractal dimension is the main feature of many nonlinear phenomena like the coastline, stock indexes and surface growth. Reaction-diffusion equation which is used mainly in different fields such as physics and medicine has complicated characteristics as its components are nonlinear. In this paper, the fractal effect of the external disturbance on the reaction-diffusion equation which is a partial differential equation is studied. The relationship of the disturbance between the fractal dimension of the output variable has been obtained by finite difference method simutanously. Even there exists random term in the disturbance, the fractal dimension is also stable characteristics of the output variable of the reaction-diffusion equation.
Anomaly Location Method for QAR Data Based on Principal Component Analysis Hierarchical Clustering
Authors: Gao Xiaoxia , Cheng Zhen , Huo Weigang
Published: April 2020

The existing QAR (Quick Access Recorder) data anomaly detection algorithm can detect abnormal flights, but it cannot effectively locate the abnormal QAR data of abnormal flights. In order to address the issue, QAR data of abnormal flights are smoothed and pre-processed based on k-medoids algorithm. Pre-processed QAR data are transformed into a one-dimensional time series represented by angle cosine, and a subsequence feature matrix is generated from the angle cosine sequence by sliding window mechanism. Then, the dimension of the matrix is reduced based on principal component analysis, and the top-down hierarchical clustering is performed on row vectors of the reduced matrix according to the amount of information within each column. The anomaly nodes are detected according to the number of vectors contained in the clustering tree nodes. The abnormal data segments of QAR data of abnormal flights are located by the positions of vectors generated in the cosine angle sequence in the abnormal nodes. The experimental results on real flight data sets show that the proposed method can locate not only the known exceedance events, but also the abnormal fragments besides the monitoring items.
Dynamic Assessment of Water Resources Carrying Capacity in Heze Using Fuzzy Sets Methods
Authors: Xin Shuai , Li Wanwan , Jin Hua , Li Qingguo
Published: April 2020

It’s necessary to assessment the regional water resources carrying capacity for water resources long-term plan and projects. In this paper, the water supply and water utilization of Heze City in the past 10 years are analyzed firstly, and then figured out the current situation and existing problems of water resources in this study area. Thirdly, on the basis of constructing the comprehensive evaluation index system of water resources carrying capacity of Heze City, we introduced a fuzzy comprehensive evaluation model of water resources carrying capacity of Heze City. The purpose is tantamount to dynamically evaluate and analyze the water resources carrying capacity of the current level year and the planning level year of Heze City. The result showed that the water resources carrying capacity level of Heze City are changing to a positive direction, but the trend is weak and the prospect is not optimistic. At the same time, the validity and feasibility of the model and method are verified.
Study on the Calculation Method of Energy Saving Potential of the Whole Society during the 14th Five Year Plan Period
Authors: Tang Wei , Wu Peng , Duan Jinhui
Published: April 2020

This paper studies the calculation method of the energy-saving potential of key industries, then calculates the structural energy-saving potential, and finally puts forward a method to calculate the energy-saving potential of the whole society during the 14th Five Year Plan period. It is estimated that during the period of the 14th five year plan, the whole society will save about 300-400 million tons of standard coal.
Time-change Reliability Assessment and Analysis of Cryogenic Pneumatic Valve Based on Dynamic Bayesian Network Theory
Authors: Qin Yongtao , Sun Le , Tang Liping , Wang Jianfang
Published: April 2020

In order to fully identify the root cause of cryogenic pneumatic valve failure in the process of liquid rocket engine test, and to analyze the dynamic time change of the process of cryogenic pneumatic valve reliability analysis, this paper first analyzes the failure factors of low temperature pneumatic valve in the test process of liquid rocket engine according to the human-machine environment system engineering. By introducing the dynamic Bayesian network theory, and by means of analyzing the time-change failure failure mode of cryogenic pneumatic valve, constructing the time-change reliability model of cryogenic pneumatic valve was constructed in the test process of liquid rocket engine, and the reliability growth technology of cryogenic pneumatic valve was researched by the optimal failure search strategy. Finally, the validity and accuracy of this method are verified by the example. This method can provide a method guide for quantitative analysis and improvement of the reliability of cryogenic pneumatic valve, and provide support for the accurate and objective evaluation and development of liquid rocket engine performance.
Study on Enterprise Competitive Intelligence Evaluation Based on Mixed Uncertain Attribute Group Decision-making
Authors: Song Jiekun , Zhao Zhihao , Zhang Yemeng
Published: April 2020

Enterprise competitive intelligence evaluation has the characteristics of uncertainty and group decision. It is significant to construct the evaluation model based on the mixed uncertain attribute group decision-making. In this paper, we reviewed the algorithms, order relations and distance measures of the main uncertain parameters. Based on mixed uncertain attribute group decision-making, prospect theory and VIKOR theory, we constructed the evaluation model. We put forward the processes including standardization, group integration, value measurement and ranking. An example analysis shows that the evaluation model can integrate a variety of uncertain indicators, comprehensively reflect the evaluation opinions of each expert, and reflect the decision-maker’s risk psychology and preferences. The proposed model can provide more scientific and consistent conclusions for the evaluation and selection of competitive intelligence of enterprises.
Structure Oriented Local Image Feature Description
Authors: Yu Wangsheng , Qin Xianxiang , Wang Peng , Hou Zhiqiang , Ma Sugang
Published: April 2020

In this paper, we proposed a structure oriented descriptor (SOD) for local image feature description. Different from the traditional methods, we explored the structure information via hierarchical strategy and structure coding elements. Firstly, the support region is partitioned into hierarchical sub-regions according to the intensity orders. Secondly, a pre-designed structure coding image is explored to pooling the features according to the hierarchical sub-regions. The final descriptor is a conjunction of the feature of each sub-region. We evaluated the proposed descriptor on the public dataset and compared it with the state-of-the-art works. The experimental results indicate that the proposed descriptor is robust to image appearance change and outperform the state-of-the-art works in most cases.
Research of Stock Price Prediction Based on PCA-LSTM Model
Authors: Wen Yulian , Lin Peiguang , Nie Xiushan
Published: April 2020

At present, there are some problems in domestic stock market, such as difficulty in extracting effective features and inaccuracy in stock price forecast. This paper proposes a stock price prediction model based on Principal Component Analysis (PCA) and Long Short-Term Memory (LSTM). Firstly, PCA is used to extract the principal components of the technical indicators affecting stock prices, so as to reduce the data correlation and realize data dimensionality reduction. Then, LSTM is used to model and predict the stock price. According to the experimental results of Pingan Bank, compared with the traditional stock price prediction models, the stock price prediction model based on PCA and LSTM can accurately predict the stock price fluctuation trend.
Research on Digital Watermarking Technology Based on Discrete Wavelet Transform
Authors: Tan Dingying , Liu Huiling , Wang Huili , Zou Min , Chen Pingping
Published: April 2020

By using the advantages of discrete wavelet transform in digital watermark embedding, extraction and detection, a corresponding basic model was established. Using MATLAB as a tool for simulation experiments, the experimental results show that the discrete wavelet transform can extract the watermark signal under the common JPEG compression, noise, shear and rotation, filtering and other attacks, and has high robustness.
Simulation and Optimization Design of CRH380A EMU Bogie Frame
Authors: Xing Bangsheng , Zhang Jialu , Xu Yongjie
Published: April 2020

Taking SKMB-200 power bogie frame applied to CRH380A EMU as the research object, based on UIC615-4 standard, four kinds of simulated operating conditions load and one kind of supernormal load are calculated, and then constraints and loads required for ABAQUS simulation analysis are determined. The results of static strength simulation show that the maximum stress of the frame under simulated operation conditions, and under abnormal load conditions are lower than the allowable stress of the main material SMA490BW weathering steel. The static strength of the frame meets the standard. Then, through setting design variables, selecting constraints and determining the objective function, the structural optimization analysis of the selected abnormal load cases is carried out. The optimization results show that the total mass is reduced by 109 kg, which is 6.8% lower than that before optimization, and the maximum equivalent stress value of the frame is 329.98 MPa, which still meets the strength requirements. By optimizing the structural parameters of the frame, the under-spring mass of SKMB-200 bogie can be effectively reduced, and its dynamic performance can be improved, which can provide reference for the optimum design of the bogie structure of EMU.
Numerical Simulation of Pressure Control in High Pressure Pipe
Authors: Xiong Mei , Chen Longwei , Sun Yang
Published: April 2020

When the injector works, how to control the fuel inlet valve so that the fuel pressure in the high-pressure fuel pipe is kept at a constant value. The method of calculation and numerical simulation is presented.
Existence of Global Solutions for Stochastic Population Models with Time Delays
Authors: Wang Changyou , Yang Kaixiang , Jia Lili
Published: April 2020

In this work, we study a class of stochastic multi-species predator-prey model with time delays. By constructing a appropriate Lyapunov functions, the existence of global positive solution for the models is proved, and some known results are generalized.
Design and Construction of Virtual Simulation Experiment Platform Based on Cloud Computing
Authors: Xing Zhihuan , Yao Ning , Lu Xinxi
Published: April 2020

This paper provides a new method to build a virtual simulation experiment platform. The platform is based on cloud computing, which has the ability to support elastic demands on different numbers of students or different experiments. Compared with traditional similar platforms, the platform raises resource utilization rate, requires less hardware, needs less management and has a better performance. The platform also provides many other functions related to virtual simulation experiments, such as course management, reports management, reports assessment, student management and so on, which means one single platform can satisfy almost all demands during the experiment teaching process.
Mesh Coarsening for Fast Simulation on Low Resource Machine
Authors: Luo Gan , Zhang Zhiguo
Published: April 2020

Mesh-based application uses a mesh to discretely represent a real physical system and then calls appropriate algorithm over the mesh to solve equation for simulation. Mesh-based application is usually developed by domain programmers and it runs with very large mesh on super computer. It takes a long time to run with such a large mesh on low resource machine. In this paper, we propose an algorithm designed for coarsening two-dimensional quadrilateral mesh aiming to reduce the size of the mesh so that the application could run with the smaller coarse mesh on low resource machine in a short time. This makes it more convenient for domain programmers to develop and debug the application on low resource machine. The algorithm first generates cells of the coarse mesh by agglomerating cells of the original mesh. Then it constructs internal edges, boundary edges, nodes and all mappings of the coarse mesh. At last, the algorithm constructs datasets of the coarse mesh according to the datasets of the original mesh. The experimental result shows that it takes much less time to run application over the coarse mesh produced by our algorithm, and the error of fast simulation results is within the acceptable range.
An Improved Non-coupled PCNN Model for Image Segmentation
Authors: Deng Xiangyu , Yang Yahan , Qin Wenjuan
Published: April 2020

Pulse-coupled neural network (PCNN) model is widely used in digital image processing, but it is always a difficult problem to set network parameters and determine the optimal segmentation. By analyzing the firing characteristics and network parameters setting for the non-coupled linking PCNN, we propose an improved non-coupled linking PCNN for image segmentation. The model introduce the coupling effect of neighboring neurons into the dynamic threshold subsystem, and using a combination of DNN network, manual adjusting on step length for setting the dynamic threshold initial value. When the dynamic threshold initial value is adjusted properly, the optimal segmentation for the image can be obtained. Using the proposed algorithm in image segmentation of Lena and mammographic images, the segmentation effect similar to that of the traditional model can be obtained by less iteration, and it shows faster speed and better robustness.
Structural Simulation and Fatigue Life Analysis of the Step Attenuator
Authors: Kong Zhigang , Liu Peng
Published: April 2020

In this paper, the internal reed of a type of wideband coaxial step attenuator was studied. The research unit was modeled, and the finite element ANSYS-Workbench simulation software was used for simulation analysis to clarify the stress status of the reed and determine the dangerous position. Based on the theory of structural fatigue damage, the nominal stress method is used to predict the theoretical life of the reed, and N-code fatigue simulation software is used for fatigue simulation. The result shows that the maximum stress of reed connector occurs at the fixed end of the reed, which is the dangerous part. The theoretical calculation value of maximum stress is 318.54MPa, the simulation value of finite element is 395.53MPa. The theoretical prediction of fatigue life is 8.65e6, and the simulation life of N-code is 7.003e6.
Transient Simulation Model for Electric Field Distribution in Cable Joint
Authors: Liao Lei , Zhang Ruxin , Du Gang , Wu Mingyan , Wu Zheng , Huang Xueyou , Li Haiming , Zhang Jian , Lu Binxian
Published: April 2020

The analysis of the impact of the switching impulse voltage on the internal electric field of the cable joint plays a key role in studying the breakdown of the joint. In this paper, the finite element method is used to simulate the transient electric field of the axisymmetric model of the cable joint. By changing the closing moment, the influence of different closing moments on the electric field intensity distribution is studied and analyzed. The results show that under the switching voltage excitation, when the closing moment at t
0=nT, the electric field distribution in the cable joint is consistent with the steady state without distortion. Others, the point near the root of the stress cone will distort when the switch is closed, the closing moment is at 7.5ms, which is the most serious. The closing time is at 10ms, has the greatest influence on the electric field intensity distribution in the cable joint, especially the stress cone end, the bottom of the high voltage shield and the position near the high voltage conductor in the air domain.