bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Effect of Dual-injector on Combustion Process of 396 Series Diesel Engine with Shallow Basin-shaped Combustion Chamber
Authors: Liang Yu , Zhou Liying , Huang Haomin 
Published: April 2020

Abstract
The 396 series diesel engine has high performance and reliability and long service life, and it has been widely used in many areas, especially in the field of military and industrial power plants. By applying shallow basin-shaped combustion chamber, the original fuel injection system of the 396 series diesel engine can be improved easily. With two symmetrical injectors in each cylinder, two injectors can be used to spray diesel at the same time, or one injector can be used to spray ignition diesel and the other injector can be used to spray biodiesel or alcohol fuel. A 3D combustion model of the 396 series diesel engine with shallow basin-shaped combustion chamber was established by using the computational fluid dynamics software FIRE. When 8-hole single-injector and 4-hole dual-injector were respectively adopted, the combustion process was simulated to compare and analyze the fuel spray, ignition start point, combustion pressure, combustion heat release rate, average temperature in cylinder and NO emission, and the impact of injection duration and fuel injection advance angle on the combustion process were discussed. By increasing fuel injection pressure, shortening fuel injection duration and increasing fuel injection advance angle properly, the combustion process of 396 series diesel engine can be improved when an 8-hole single-injector was adopted. When a dual-injector was applied, the fuel spray space distribution area was wide, combustion process was improved, cylinder pressure and temperature became high, combustion was relatively sufficient and thermal efficiency got high. Proper reduction of fuel injection advance angle and extension of injection duration can mitigate the condition of large NO emission and higher cylinder pressure when the dual-injector was adopted. The combustion process of the 396 series diesel engine with shallow basin-shaped combustion chamber can be improved obviously and the thermal efficiency can be improved by adopting the dual-injector and selecting proper injection duration and fuel injection advance angle. This research result is conductive to improve the combustion process of the 396 series diesel engine with shallow basin-shaped combustion chamber and provides a basis for using biodiesel and alcohol fuel in the diesel engine.
Prediction of Explosion Power of Fuel Air Mixture in Coal Mine by Improved BP Neural Network
Authors: Ma Shengxiang , Shi Xunxian , Yu Chenglong 
Published: April 2020

Abstract
In order to improve the feasibility and accuracy of predicting the explosion power of fuel air mixture, a method of BP neural network prediction is proposed by combining factor analysis method with BP neural network. Using factor analysis method, the original data of 9 fuel air mixture explosion power factors were processed by dimensionality reduction data, 2 common factors were obtained, and 2 common factors were substituted for 9 fuel air mixtures as input layer parameters of BP neural network. A prediction model of coal and gas outburst with the combination of factor analysis method and BP Neural network is established to predict the explosion power of fuel air mixture. The prediction model of the explosion power of the fuel air mixture is selected to verify the improved BP neural network prediction models, and the final results are as follows: The relative error range of four prediction samples is 0.16%-7.58%, all less than 10%. The improved BP neural network prediction method is used to solve the problem of the traditional BP neural network because of the excessive number of input layer parameters, low data processing efficiency, slow iteration rate and low precision, which provides a new research way for predicting the explosion power of fuel air mixture.
Research on The Current Situation and Development Measures of Rail-Water Intermodal Transport in Guangzhou Port Group
Authors: Hu Guojie , Sun Wanhua , Jiang Jian 
Published: April 2020

Abstract
The development of rail-water intermodal transport is not only the strategy of national development, but also the inevitable result of the adjustment of national transport structure. The development of rail-water intermodal transport will greatly reduce the logistics cost of the whole society and promote the development of social economy. In this paper, Guangzhou Port Group in Guangdong, Hong Kong, Macao and Pearl River Delta region is the main research object. The problems faced by the development of rail-water intermodal transport are analyzed, and corresponding countermeasures are put forward to promote the development of rail-water intermodal transport in Guangzhou Port Group and increase the proportion of container rail-water intermodal transport.
Research on the Relationship between Highway Trip Demand and Social Economy in the New Normal Economic stage of China Based on Panel Data Analysis
Authors: Sun Zhuoqun , Zhang Yi , Ji Wenbo , Li Shengli , Wang Chao , Ye Zhirui 
Published: April 2020

Abstract
As China entered the new normal of economy, the economic growth rate and industrial structure are undergoing huge changes, which has also profoundly affected the traffic volume of expressways. Therefore, analyzing the relationship between socio-economic and transportation demand is crucial for transportation planning and demand management. This study analyzed the interaction of socio-economic and trip demand from 2008 to 2017, which was a crucial period for Shandong’s industrial transformation and economic development. To achieve this goal, principal component analysis and panel data analysis methods were applied to our issue.
Realization of the Airborne System for Moving Target Detection and Tracking Based on Quadrotor
Authors: Ding Yongfei , Wei Chunyan , Wang Xinhua , Li Jiahuan 
Published: April 2020

Abstract
In this paper, taking quadrotor as the research object, a kind of airborne vision system is presented to detect and track the moving target. Lower cost and better performance are the remarkable characteristics of the system. Firstly, the overall scheme of the detection and tracking system is designed. Secondly, a new image detection algorithm based on HSV color model and template matching is proposed, then according to image principle, the relative distance from quadrotor to target is calculated. In order to solve the time delay caused by image processing, the target position prediction is made by adding Kalman filter. Then, according to the position information of quadrotor and target, a segmented PID controller is designed to improve the tracking effect. Finally, the algorithm is applied to the actual flight of the quadrotor to verify its feasibility.
Population migration and environment reconstruction of Bay Area Urban Agglomeration——Evidence from the Beibu Gulf Megalopolis
Authors: Hu Zhaolian 
Published: April 2020

Abstract
Bay area construction is an important part of regional energy and environment construction and high-quality economic development, and people-oriented is the core of high-quality development, so it is of great significance to re-examine the development of Bay Area Urban Agglomeration and energy and environment structure from the perspective of population migration. Based on the gravity data of Beibu Gulf Urban Agglomerations, this paper uses the social network analysis method to deconstruct the population migration and spatial network structure of urban agglomerations. The results show that the network strength of the Beibu Gulf Urban Agglomeration is gradually increasing, and the network integrity is significantly enhanced; the external radiation effect of the central city is enhanced, showing the spatial characteristics of “gathering and diffusion in one”. The conclusion of this paper is of great significance to the formulation of energy and environmental policies and the promotion of high-quality development of bay area integration.
Autonomous evasion method for drones under static threat
Authors: Dai Chao , He Qian , Liu Yang , Yan Nan 
Published: April 2020

Abstract
In the flight area, it is difficult for drones to have a clear understanding of all threats in advance, that is, there are some sudden static threats, which requires real-time detection and avoidance of drones during flight. This paper proposes an improved RPG method for UAV threat evasion guidance control, and gives the UAV threat evasion guidance law.
Research on Highway Tunnel Safe Speed Limit Setting Method Considering Energy Conservation and Emission Reduction
Authors: Li Hao , Wen Yuanyong 
Published: April 2020

Abstract
Highway tunnel sections are prone to accidents. In order to reduce safety risk factors generated by tunnels, strict speed limit is implemented in highway tunnels. At present, there is still a lack of research on speed limit standards for expressway tunnel sections.Firstly, this paper analyzes the general situation of highway speed limit in China and abroad, the influencing factors of highway tunnel speed limit settingf, and the driving process into the tunnel.Then a speed limit setting model of highway tunnel considering the constraint conditions of energy saving and emission reduction is proposed, based on the serial influencing factor model, the highway tunnel speed limit setting model is determined by taking the road conditions, traffic conditions, energy consumption and emission factors and environmental conditions into comprehensive consideration and combining with the analytic hierarchy process.Finally, the speed limit scheme of highway tunnel section with the consideration of energy consumption conservation and carbon emmission redectuon is put forward, and some suggestions for setting conditions and constraints of the speed limit scheme are put forward.The results show that the method can be operated and the results obtained are reliable, which can be used as an effective method for the implementation of energy conservation, emission reduction and safety scheme in the field of highway.
Studies of Phytoremediation on Sasa argenteastriatus for Soil Cadmuium Pollution
Authors: Hu Xia , Yin Peng , Liu Xiaojie 
Published: April 2020

Abstract
In order to explore the Phytoremediation effect of Sasa argenteastriatus on cadmium-contaminated soil, pot experiments were conducted to study the growth and enrichment efficiency of Sasa argenteastriatus on cadmium-contaminated soil. The results showed that cadmium had a significant inhibitory effect on the growth of Sasa argenteastriatus, and the inhibitory effect increased with the increase of cadmium concentration. Cadmium content in roots, stems and leaves of Sasa argenteastriatus increased with the increase of exogenous cadmium, especially in roots. The order of cadmium enrichment efficiency was the same in different cadmium contaminated soils, all of them were leaves < stems < roots. And the cadmium enrichment coefficient in root was obviously higher than that in other organs. The research on growth and enrichment of Sasa argenteastriatus under cadmium stress provides theoretical basis and data support for its application in cadmium-contaminated areas.
Application of a Wavelet Packet and SOM Neural Network in Wastewater Treatment Fault
Authors: Lu Ming 
Published: April 2020

Abstract
In order to solve the problem of fault diagnosis in sewage treatment, a fault diagnosis method combining wavelet packet and improved self-organization mapping (SOM) neural network was proposed. In this method, the fault of sewage treatment is decomposed into three types by wavelet packet, and then decomposed into several frequency bands to calculate the energy of different frequency bands. By using the ratio of these energy values to the energy values of normal operating frequency bands, the feature vector of fault diagnosis of sewage treatment fault is constructed to extract fault features. SOM neural network of 3 x 3 was designed, and the neural network training was carried out using the energy fault feature vector [1], so as to determine the network parameters and achieve the purpose of fault diagnosis. The simulation results show that the fault diagnosis method is effective and accurate.
Design and Implementation of Wireless Communication System Based on CC1100
Authors: Gao Jianhua , Zhu Yuanjing 
Published: April 2020

Abstract
As one of the most promising information technologies in this century, radio frequency technology has been highly valued. The technology utilizes the radio frequency method for non-contact two-way communication, it can automatically identify the target object and acquire relevant data, and it has many advantages such as high precision, strong adaptability to the environment, strong anti-interference ability, and fast operation. The radio remote control uses radio frequency signals to control remote devices of remote control devices. For modern homes, various home appliances are designed to control multiple devices and wireless remote control switches. This paper designs a simple wireless remote control system based on CC1101 communication module. Based on the theory of wireless transceiver technology, the system realizes the transceiver and status display of wireless data.
Development and Optimization of Check-in System Based on Face Recognition Technology
Authors: Chen Pingping , Geng Xiaoran , Zou Min , Xu Qingming , Tan Dingying 
Published: April 2020

Abstract
Face recognition technology is widely used. By comparing the speed and accuracy of Face++ and Baidu AI face recognition, the face sign-in service was collected in the mobile phone or pad APP, which realized the mobile check-in attendance that can be used for college students or training institutions. The system was characterized by accuracy, fast and anti-cheating ability. The experimental results show that Baidu AI’s face detection and recognition performance is better, its speed is more than twice faster than Face++, the recognition score is higher than Face++, and includes live detection, which can effectively prevent static picture cheats. However, Baidu AI’s face detection time (about 271.2ms) was much higher than the commercial face detection algorithm (about 25ms), so the Adaboost face detection algorithm was studied, and the Adaboost algorithm based on OpenCV was transplanted to Android. The platform enables real-time detection of faces. After the system optimization, the face detection time is about 10ms, which effectively improves the face detection speed.
Organization Structure Design of Greenization Transformation of Old Districts—Taking the Elevator Installation Project as an Example
Authors: He Weiyi , Li Tianyi 
Published: April 2020

Abstract
Taking the “village collective” in the old suburbs of Tianjin’ s suburbs as an example to upgrade existing residential elevators, using organizational design theory and business process theory, and using traditional organizational design methods, the village collectively funded elevators are retrofitted. Conduct organizational structure design and process design to form the project organization task-resource allocation relationship and the cooperation relationship between the subjects. From the operational level, we provide design solutions for the implementation of specific projects, making them more targeted and operable. Enriched the research field and content of organizational structure design issues.
ATLA: A novel metaheuristic optimization algorithm inspired by the mating search behavior of longicorn beetles in the nature
Authors: Han Xiaokuang , Du Xianjun , Yu Ping 
Published: April 2020

Abstract
Compared with the traditional optimization algorithms, metaheuristic optimization algorithm has more powerful performance in the optimization problem, which has attracted more and more scholars’ attention. In this paper, a novel metaheuristic optimization algorithm, named artificial transgender longicorn algorithm (ATLA), is proposed, which is inspired by the mating search behavior of longicorn in the nature. ATLA simulates the mechanism of sex pheromone emission and attraction between female and male longicorn beetles, and realizes the process of local search and global search of an optimization problem. Simulation results based on three standard benchmark functions show the good search performance of optimal solution and the effectiveness of the proposed ATLA.
Data Analysis and Application of Retail Enterprises Based on Knime
Authors: Pu Xiaochuan , Qi Ning , Huang Junli 
Published: April 2020

Abstract
With the rapid development of information technology, the application of cross-discipline has shown explosive growth. Data mining, big data and other technologies are rapidly entering all walks of life. Research on data mining technology and its application in data analysis of related enterprises have certain theoretical significance and practical value. This paper starts with a cross-border sales data set and uses Knime visual data analysis tool to illustrate that the widespread application of visual data mining technology in small and medium-sized enterprises is a feasible way to improve the decision-making ability of enterprises.
Application of BP Neural Network for Pre-Dehumidification Time Prediction of Capillary Ceiling Radiant Cooling Panel Air Conditioning System
Authors: Ye Qiming , Shi Wei , Xu Linghong , Hu Pingfang 
Published: April 2020

Abstract
Pre-dehumidifying the room is generally needed before the capillary ceiling radiant cooling panel (CCRCP) air condition system is turned on. Accurate pre- dehumidification time is critical for condensation prevention and energy usage. The pre- dehumidification time, which is related to multiple variables with complicated correlation relationship, is difficult to be calculated by conventional methods. Therefore, BP neural network is considered to be applied to predict the pre-dehumidification time. In this study, a dynamic model of CCRCP + displacement ventilation air conditioning system was built to simulate the pre-dehumidification process in TRANSYS. And then BP neural network was established, it takes the indoor and outdoor temperature and humidity conditions at 7:00 in every morning as the influencing factors and predict the optimal pre-dehumidification time for each day. The results show that the mean square error (MSE) of the BP neural network training process is 1.90958×10−4, the correlation coefficient R between the training data and the sample data reaches 0.99906, and the correlation coefficient R between the predicted data and the sample data reaches 0.99897. The BP neural network can reflect the intrinsic relationship between optimal pre-dehumidification time and input variables, and has high accuracy in predicting optimal pre-dehumidification time of CCRCP air conditioning system.
Parallel Residual Attention Network for Image Super-Resolution
Authors: Duan Yongsheng , Su Yang , Xu Jiahao , Wu Wei 
Published: April 2020

Abstract
The application of convolution neural networks (CNN) to image super-resolution has achieved excellent results. Inspired by these excellent results, we find that most models only increase the depth of the network in order to obtain deeper features. However, these models often cannot take full advantage of the original feature information from the low-resolution (LR) images. Moreover, the image information is mainly divided into high frequency information and low frequency information, and the existing image super resolution network models are mostly single-branch models, which limits the performance of extracting various aspects of image information. To resolve the problem, we proposed a parallel net work model. About the network, we proposed the LR residual block (LRB) and attention block (AB). LRB allows constantly replenishing original LR features in the process of extracting deep features, thus it can effectively extract more information from LR image. The AB contains the attention mechanism, it will ad just their weights based on the importance of the image features to extract more efficient features between low- resolution (LR) images and high-resolution (HR) images. Experiments on benchmark datasets show that our model performs better. We achieve higher accuracy and visual improvements against state-of-the-art methods.
A Review on the Effect of Microstructure Surface on the Adhesion of Marine Fouling Organisms
Authors: Yang Hongyue , Wang Songling 
Published: April 2020

AbstractMarine anti-pollution is a difficult issue in marine development. At present, marine anti-fouling researches mainly focus on three aspects: chemical, physical and biological. With the spread of the concept of environmental protection, the development of environmentally friendly, bio-adaptive anti-fouling technology has become a new development trend, and micro-structure surface anti-fouling technology has become a research hotspot. This paper introduces the profile and impact of biofouling, highlights the antifouling mechanism and research progress of microstructure technology, and describes the adhesion characteristics of the three main fouling organisms on the microstructure surface.
Visibility Tagging of nouns in Text-to-Scene Conversion
Authors: Yang Fuping , Cheng Xi , Chen Qi 
Published: April 2020

Abstract
The recognition and extraction of visual text information is the basis of the realization of Text-to-Scene Conversion, while nouns are the main expression form of entity, event, orientation, action and other information in text, but not all nouns are suitable for visualization, so how to recognize the visibility of nouns is the key problem of Text-to-Scene Conversion. Based on the definition and classification of noun visualization, this paper establishes a keyword visibility dictionary. Furthermore, in view of the static limitations of the dictionary, a dynamic expansion method based on semantic similarity is studied, and an optimization method for the visibility annotation of nouns is proposed in combination with unsupervised clustering. The experimental results show that the proposed method is effective and feasible for nominal visibility annotation of common texts, and the accuracy of the optimized method is 16% higher than that of the simple semantic similarity method.
Research on Spatial Spectrum Constraint of Distributed Passive Radar Imaging
Authors: Zhang Yanhou , Wang Shuo , Zhai Hao , Han Yusheng 
Published: April 2020

Abstract
Spatial spectrum is an important tool for radar imaging performance analysis. In order to analyze the effect of spatial spectrum filling on the imaging quality of distributed passive radar, the constraints of spatial spectrum filling are studied. The imaging model of distributed passive radar is established, the imaging resolution characteristics are analyzed, and the influencing factors of spatial spectrum filling are obtained. The filling rule of spatial spectrum is analyzed, and the constraint conditions for the critical azimuth and arc of filling are given. The validity of the constraint conditions is verified by simulation, which has guiding significance for optimization of radar station layout and imaging quality improvement.
Mixnet Face Recognition How Combing 2D and 3D Data Can Increase the Precision
Authors: Zhang Xinyu , Zhao Yang , Zhang Hao 
Published: April 2020

Abstract
Great breakthrough has been made on Classic 2-D face recognition in normal environment. The facenet [1] proposed by Google in 2015 has 99.65% accuracy on LFW dataset. It can be considered that the performance of traditional 2-D network in normalized environment such as security check and bank is reliable enough. However, the accuracy of 2-D face recognition will significantly reduce when processing angular faces or occluded face. This paper claims that the lack of depth information is the reason why the recognition ability of neural network is inferior to that of human beings under complex conditions. Furthermore, we have proposed a method, which can obtain 100% accuracy on both Texas and Bosphorus dataset by using both 3-D deepmap and 2-D rgb picture as input.