bluuebunny/crossref_metadata_2025 huggingface dataset:
Application Research of Process Design Analysis based on Digital Technology
Authors: Fan Hongbin , Luo Yiheng
Published: July 2020

With the improvement of people’s aesthetic concept, simple bamboo-rattan knitting technology has been unable to meet the people’s design requirements for fur fabric, people hope that fur products have a sense of fashion, artistry and personalized characteristics. We study the development of bamboo-rattan knitting technology, adopting survey method, literature analysis method for data collection, mining the design methods of bamboo-rattan knitting technology in the field of packaging design. From the perspective of bamboo-rattan packaging, we analyze several common methods, but the designing efficiency is low, and the designing accuracy is not high. In order to further improve efficiency of designing, we introduce the digital technology, which can provide an interactive platform for designers, control the whole design process, monitor the production of design schemes and the effect of design schemes, and this technology can achieve standardized production, improve design accuracy, and adopt CAD, Photoshop and 3Dmax, which can be taken as digital technology platform to realize the simulation analysis of bamboo-rattan packaging design. We take digitalization technology as the main method, and integrate with the existing bamboo-rattan packaging methods, put forward the design process of bamboo-rattan fur knitting technology packaging based on digitalization technology, design the bamboo-rattan fur knitting packaging, therefore, get the design effect of bamboo-rattan packaging based on digitalization technology, and confirm that this method can improve the design efficiency of bamboo-rattan knitting products, but also meet the needs of people for bamboo-rattan fur knitting products.
Design and Implementation of SQL Injection Vulnerability Scanning Tool
Authors: Zhao Juanjuan , Liu Changhua
Published: July 2020

According to the “Top Ten Security Vulnerabilities List” (OWASPTop 10) released by OWASP in 2017, SQL injection attacks are still at the top of the list, and there are many ways of SQL injection attacks, which cause great harm. Although there are many vulnerability scanning tools, there is still a high rate of false negatives. Aiming at the current problems of SQL injection vulnerability detection, this paper proposes a scanning tool for SQL injection vulnerabilities. First, use the crawler framework scrapy to obtain the URL associated with the form and the a tag, and segment the URL based on the improved simhash algorithm. Deduplicate the link, then analyze the injection point to modify the URL parameter value injection test, and determine whether there is a vulnerability based on the response result of the server. The experimental results show that the detection method achieves a 96.50% URL deduplication rate in the crawler module, which greatly reduces the rate of false negatives. It is more suitable for detecting whether a website has a SQL injection vulnerability.
Design and Research of Omni-directional Moving AGV
Authors: Song Li , Ju Hong , Li Weixin , Sun Chongshu , Yuan Bing
Published: July 2020

Omni-directional mobile AGV can operate flexibly in a narrow space, which can replace heavy and dangerous labour to a greater extent and improve labour productivity. In this paper, the steering wheel integrated with walking and steering functions is taken as the driving unit, and the main research contents include: through digital structure design, the chassis structure and electrical control system of omnidirectional AGV are designed. Experiments show that the design realizes flexible operation of zero turning radius and 360-degree omnidirectional movement in narrow space, and meets the requirements of robot handling operation in complex environment.
On-line Defect Detection and Classification of Latex Gloves
Authors: Wang Xiangming , Zhang Zhongkai
Published: July 2020

At present, the detection of latex glove is mainly done manually. In order to realize the online detection of latex glove, this paper presents a method of defect detection and classification of latex glove based on multi-feature extraction to achieve online detection and classification of latex glove. Firstly, the target pixel and the background pixel were segmented using the OTSU method. Secondly, the image was pre-processed using median filtering, edge extraction and morphological closed arithmetic processing, and then the defect was framed using the minimum circumscribed rectangular frame selection method. Finally, the characteristics of three kinds of defects were proposed by analysis. Feature vectors were extracted using texture features and HOG features. The classification model selects SVM support vector machine to train the classifier to realize the classification of defects. When training the classifier, the Gaussian radial basis function was used as the kernel function. In view of the characteristics of the types of defects in latex glove, first classify the defects in a “one-to-one” manner, and then implement multi-classification. The experimental results show that the online defect detection and classification of latex glove based on multi-feature extraction has achieved good results.
RETRACTED: Research on Financial Management Innovation of Small and Medium Enterprises in the Context of Big Data
Authors: Jiang Lijun
Published: July 2020

The era of big data provides new vitality for the development of enterprises. And the traditional application pattern of financial management cannot come up with the development requirement of the era of big data. Financial management is the core work of enterprise operation and management, and good financial situation can support the sustainable development of enterprises. This paper launches the research on the innovation of enterprise financial management in the era of big data, which includes the analysis of the current situation of financial management in the era of big data and the the accordingly various impacts on enterprise financial management, the discussion of the advantages brought to enterprise financial management in the era of big data, and further discussion of the innovation of enterprise financial management in the era of big data, aiming to enable enterprises to correctly cope with the context of the era of big data, and make financial optimization management play an important role in the innovation and development of enterprises.
Load Balancing Mechanism Based on Linear Regression Partition Prediction in Spark
Authors: Huang Zichun , Wei Wenguo , Xie Guiyuan
Published: July 2020

With the rise of cloud computing, the internet of things, social networks and other technologies, information data is expanding rapidly, and traditional processing and storage systems have been difficult to deal with massive data. Spark is a fast and efficient MapReduce implementation developed after Hadoop. However, the shuffle operation in spark will cause the data set on some working nodes to be too large, while other nodes may be idle, which will affect the performance of spark jobs. This phenomenon is called data skew. Aiming at the problem of data skew in spark platform, this paper proposes a load balancing mechanism based on linear regression partition prediction: SP-LRP (Spark load balancing mechanism based on Linear Regression Partition), SP-LRP predicts the partition size of the reduce tasks at run-time, leverages the skew detection algorithm to identify the skew partition and adjusts the task resource allocation according to the fine-grained resource allocation algorithm. We use the benchmark dataset to evaluate SP-LRP, and compare the average execution time of two algorithms and the load balancing degree of reducers in different situations. The experimental confirmed the efficiency of SP-LRP in their respective usage scenarios.
Blind Super-Resolution for Single Remote Sensing Image via Sparse Representation and Transformed Self-Similarity
Authors: Liu Yuhang , Sun Weidong
Published: July 2020

Super-resolution (SR) reconstruction is one of the effective ways to improve the spatial resolution of remote sensing images, but the blur kernel estimation without any additional prior information is the key to the quality of SR reconstruction. Facing the above problem, a blind super-resolution method via sparse representation and transformed self-similarity is proposed in this paper. In this method, the blur kernel as well as the reconstructed high-resolution image are estimated at the same time using the structural self-similarity from a single image, a down-sampled version of the observed image is used as the training samples for the dictionary learning, and the internal patch search space is expanded using the transformed self-similarity to improve the quality of estimation. Experiment results show that, our method performs well both in quality of kernel estimation and SR reconstruction.
Logistics Support Path Planning Model of Forest Fire Based on Ant Colony Algorithm
Authors: Tian Shuchao , Zhou Ziqing , Wang Tiejun , Xia Qing , Wen Zhehua , Wang Baoxue , Liu Ling
Published: July 2020

The problem of the network node and the complex constrain in the path planning has become a difficulty in forest fire logistics support. The traditional ant colony algorithm is improved. We establish two objective functions for the distance between nodes and the time required to finish task. We optimize the two objective functions. We redesigned the calculation method of heuristic information and the update function of pheromone. We set a time window to limit the time to complete urgent tasks. Finally, an example is given for verification. The results show that the improved algorithm can solve the problem of logistics support path planning model of forest fire. The results are more close to the actual situation.
Research on Target-Driven Navigation of Mobile Robot Based on Deep Reinforcement Learning and Preprocessing Layer
Authors: Yu Gang , Zhang Chang , Xu Jiexiong , Sun Tongda
Published: July 2020

Recently, with the rise of deep reinforcement learning model, robot navigation based on this method has a huge advantage compared with traditional slam method, which has attracted extensive attention. However, when the navigation algorithm trained in the virtual environment is transferred to the real environment, the navigation performance of the robot will decline sharply because of the great difference between the virtual environment and the real environment. In order to improve the navigation ability of mobile robot, this paper implements a mobile robot navigation system based on deep reinforcement learning without environment map and only visual input. At the same time, in order to solve the problem of poor generalization ability of deep reinforcement learning from virtual environment to real environment, this paper proposes a preprocessing layer with knowledge and combines it with deep reinforcement learning module. The combined algorithm model alleviates the performance fault problem caused by the migration algorithm and the performance difference between virtual sensor and real sensor. At the end of this paper, a navigation experiment based on the turtlebot is designed, which proves that the deep reinforcement learning algorithm with the preprocessing layer can alleviate the performance fault problem caused by the migration algorithm, and have a certain ability of obstacle avoidance and avoidance without the environment map.
X-DenseNet: Deep Learning for Garbage Classification Based on Visual Images
Authors: Meng Sha , Zhang Ning , Ren Yunwen
Published: July 2020

In order to effectively solve the problem of garbage classification, this paper designs a garbage classification model based on deep convolutional neural network. Based on Xception network, combined with the idea of dense connections and multi-scale feature fusion in DenseNet, the X-DenseNet is constructed to classify the garbage images obtained by visual sensors. This paper conducts experiments through the process of “obtaining dataset-preprocessing data-building X-DenseNet model-training and testing model” and the accuracy of the model on the testing set is up to 94.1%, which exceeds some classic classification networks. The X-DenseNet automatic garbage classification model based on visual images proposed in this paper can effectively reduce manual investment and improve the garbage recovery rate. It has the vital scientific significance and application value.
Three-branch Semantic Segmentation Network
Authors: Wei Lihua , Ma Yingdong
Published: July 2020

Effective Semantic segmentation requires both spatial details and object-level semantic information. Meanwhile, context information is also important for complex scene understanding. However, it is hard to meet these demands simultaneously in the top-down CNN structure. In this paper, we tackle this problem with a Three-branch Semantic Segmentation Network (TSS Net). The proposed TSS Net consists of three parts, including a spatial network, a semantic network and a context network. The spatial network utilizes convolutional layers with small stride and a spatial pyramid pooling module to extract multi-scale spatial features. In the semantic network, multiple level features are combined to enhance semantic information. The context network integrates different scales contextual information to facilitate objects localization in complex scene. The proposed semantic segmentation framework has been evaluated on the CamVid and the Cityscapes datasets. Experimental results demonstrate that the TSS Net achieves state-of-the-art performance.
Design of Trajectory Planning System for River Crab Farming with Automatic Feeding Boat
Authors: Wang Xiaoyu , Hong Jianqing , Sun Yueping , Zhao Dean
Published: July 2020

The bait feeding of river crab farming needs to be covered evenly on the whole pond. At present, feeding is mainly carried out by manual driving or remote control ship-borne feeding machine on the pond. The feeding accuracy and efficiency are relatively low, and it is difficult to guarantee feeding effect. In view of the above situation, based on the mobile automatic feeding boat equipped with GPS, this paper proposes a complete coverage trajectory planning method with irregular quadrilateral pond, and a trajectory planning system based on SuperMap Objects is designed to generate reciprocating traverse feeding trajectory automatically. The simulation is performed to verify the feasibility of the trajectory planning method. The results show that the trajectory planning system can meet the requirements of automatic and uniform feeding on the crab pond.
An Evaluation Model for Authors’ Academic Influence Based on Multi-source Heterogeneous Database in Bilingual Environment
Authors: Deng Zhijian , Zhang Zhenhua , Xiong Chun , Chen Mingqin , Huang Yanting , Li Junran , Shen Jiawen
Published: July 2020

As the internationalization of academic rise up, it is insufficient to evaluate a scholar’s influence only taking domestic academic contribution as reference. To have a better understanding of scholars’ academic contribution in an international scale, this paper proposes a new evaluation system of academic influence based on the optimal dataset of entity recognition in bilingual environment. The new evaluation system has been experimented on a real literature dataset of DBLP. The research is conducted by the following steps. First, handle bilingual data. Second, optimize the literature data with entity recognition technology. Third, make an academic influence evaluation. Experiment results show that the new evaluation system is feasible and reasonable.
Left and Right Consistent Stereo Image Detection and Classification Based on Deep Learning
Authors: Tang Lijuan , Wang Qing , Chen Guannan
Published: July 2020

With the development of stereo camera technology, the increasing of the data volume of binocular image makes the target detection and classification of binocular image become one of the research directions in the field of computer vision. Compared with monocular image, binocular image contains the depth information of the image. For using the depth information of the image to improve the target detection and classification accuracy of image, this text puts forward a method of detecting and classifying left and right consistent objects in stereo images based on deep learning, which is based on the Mask R-CNN network and adds the binocular matching algorithm to improve the accuracy of image target detection and classification. The experiment compares the evaluation indexes of monocular and binocular.
Research on Vehicle Object Detection Algorithm Based on Improved YOLOv3 Algorithm
Authors: Liu Jin , Zhang Dongquan
Published: July 2020

Vehicle object detection is one of the important research directions in the field of computer vision. Aiming at solving the problems of low accuracy, slow speed, and unsatisfactory results of using traditional methods to detect the object of the vehicle in front of the driverless car on the road, this paper proposes an improved YOLOv3 vehicle target detection algorithm which we name it F-YOLOv3. First the multi-scale prediction network model is improved according to actual traffic conditions and efficiency requirements based on the original general object detection YOLOv3 algorithm. Then a scale prediction layer is added to improve the detection accuracy of large vehicles and improved k-means++ the algorithm is used to improve the effect of anchor box dimensional clustering and the detection speed. At last an experiment was conducted on a self-made dataset and compared with YOLOv3 in order to test the effectiveness of the F-YOLOv3 algorithm. The test results show that the improved F-YOLOv3 model has a precision mAP of 91.12% and a speed of 59FPS, which are better than the traditional general object detection YOLOv3 algorithm. Therefore, the algorithm has better performance and popularization prospect in vehicle object detection.
Crane Hook Detection Based on Mask R-CNN in Steel-making Plant
Authors: Kang Shuai , Wang Hongbing
Published: July 2020

This paper proposes a solution based on machine vision and deep learning for the hidden safety problems that the hook does not match the ladle trunnion correctly, which is one of the hidden dangers during the crane lifting the ladle. Mask Region Convolutional Neural Network (Mask-RCNN) was introduced to segment the crane hook and find the bottom point of the hook contour. The trunnion center point can be directly located in image by painting a special color on it. Then determine whether the hook and trunnion match correctly by calculating the angle between the horizontal line and the line connecting the bottom point of the hook and the trunnion center point. According to the experimental rsulrs of 100 test images, that the average accuracy (AP) of our methods for hook segmentation can reach 92%. And the accuary of the safety judgment algorithm has reached 96%.
Determination of Aquatic Product Growth Factors Based on PCA with Stepwise Regression Test
Authors: Zheng Yingkun , Hua Xufeng , Zhang Yu , Tian Yunchen , Xue Yangyang , Wang Manjiang
Published: July 2020

For the information contained in the growth data of the pearl gentian grouper, there is overlap and inclusion. When establishing the growth model of the pearl gentian grouper, it is difficult to grasp the inherent laws of the growth factors to affect the establishment of the research target model and the operation efficiency. The data dimensionality reduction method is often used in the data preprocessing stage. The Principal Components Analysis (PCA) method was used to analyze and influence the growth factors of the pearl gentian grouper The method of regression fitting optimizes the results of selecting principal components under different criteria. Experimental results show that the main growth factors of the pearl gentian grouper selected by this method can meet the needs of the construction of aquaculture growth models, and can provide a reference for reducing the dimensions of aquaculture fish growth data and the complexity of the modeling process.
The Scheduling Technology Development of Multi-AGV System in AI Era
Authors: Huo Dengya , Wu Yaohua , Wu Shasha
Published: July 2020

As an important intelligent transportation equipment of logistics, Multi-AGV scheduling is a key problem that restricts the operation efficiency and large-scale expansion of AGV system. This paper analyzes and elaborates three key technologies of AGV scheduling, namely Path Planning, Task Scheduling and Traffic Control Management. The method of Time Window modeling based on physical entity is superior to that based on particle motion. Finally, the trend of AGV scheduling intelligentization is illustrated by combining with the current advanced technology.
Research on Intrusion Detection Algorithm of JRNB Nework Based on Feature Weighting
Authors: Wang Kunfu , Xu Shijun , Zhang Pengyi
Published: July 2020

With the development of the Internet Era, the network attacks are on the rise. To some extent, the conditional independence assumption of Naive Bayes (NB) algorithm sacrifices the accuracy of classification, especially in dealing with complex network intrusion data. Aiming to solve this problem, this paper proposes a feature weighted JRNB intrusion detection algorithm. First, in order to remed for the deficiency of the equal analysis of all feature terms in Naive Bayesian algorithm, JS divergence method is introduced to measure the weight of each feature term to highlight the difference between different feature terms; Then, take into consideration of the impact of class frequency on sample classification, the reverse class frequency (RCF) is proposed to improve the calculation of feature weight and further reducing the impact of conditional independence. Compared with the traditional Naive Bayes algorithm and other popular classification algorithms, this algorithm in this paper has some improvement in detection performance.
OBD Quality Evaluation System and Control
Authors: Xue Hongshuai , Liu Zhili , Yu Xiangyang , Wei Xinmei
Published: July 2020

Based on the characteristics of OBD data and its role in detecting automobile exhaust emissions, the data from January to August was selected from 368 vehicles of 12 companies to establish an OBD data quality evaluation system. Based on the results of quality evaluation, a method of controlling variables was adopted in order to compare the factors that affect data quality and quantitatively analyse the relationship between different factors and data quality results, which can provide technical support for law enforcement supervision and policy development.
Synthesis of pH-Sensitive Macromolecular Micelles from Amphiphilic Star Copolymers for Drug Delivery
Authors: Yao Lin , Yu Lili , Li Li , Kou Jiahui
Published: July 2020

Stimuli-responsive copolymers are a significant class of smart materials extensively studied for drug delivery systems. Two novel amphiphilic four-arm star copolymers poly(ε-caprolactone)-b-poly(hydroxyethyl methacrylate) (4sPCL-b-PHMEA) and poly(ε-caprolactone)-b-poly(diethylaminoethyl methacrylate)-b-poly(hydroxyethyl methacrylate (4sPCL-b-PDEAM-b-PHEMA) with pH-responsive were designed and synthesized by a combination of ring-opening polymerization (ROP) and atom transfer radical polymerization (ATRP). The structure of the copolymers and the particle size of macromolecular micelles were investigated by FT-IR and DLS, and the controlled release kinetics of two copolymer micelles was detected using adriamycin (DOX), a hydrophobic antitumor drug. The results showed that, the both micelles have appropriate particle size and can be used for DOX carrier, the DLC of 4sPCL-b-PHEMA and 4sPCL-b-PDEAM-b-PHEMA micelles were 21.30% and 27.25%, respectively. The release process showed that, comparing to the diblock star copolymer, triblock star copolymer had more significant pH-sensitivity. The cumulative release percentage of DOX in triblock micelles gradually increased with the decrease of pH. The cumulative release percentage of 14 h at pH 2.2 was about 80%, which had significant pH-sensitivity. A pH-sensitive four-arm star copolymer was synthesized, which can be used as drug delivery system for further research.
Study on the Sustainable Development of Space in Post International Horticultural Exhibition Age from Urban Perspective
Authors: Gao Chenglin
Published: July 2020

International Horticultural Exposition is regarded as the “Olympic” event of horticultural culture and garden science around the world, moreover, the “harmonious symbiosis between city and nature” advocated by the Expo is the important embodiment of urban ecologicalization and also the harmonious link between city and nature. In this study, the environment landscape of International Horticultural Exposition is put under the background of city and nature, then combing and summarizing the effect of Expo development on the construction of green human habitation. At the same time, combined with the current situation of the developing experience of Beijing International Horticultural Exposition in 2019, this paper proposes that promoting regional value in natural resources of city plays a leading role in the sustainable development of space during the Post-International Horticultural Exposition Age, the construction of ecological community environment after the Expo will be a platform to alleviate and coordinate the contradiction between city and nature and it also can promote the integration of these two parts.
Research on Optimization of Rendering Efficiency of Point Cloud Data of Transmission Lines in Three-Dimensional GIS
Authors: Zou Biao , Wang Heping , Zhou Xiangxian , Jiang Wendong , Du Wei
Published: July 2020

In recent decades, computer graphics have developed rapidly. With the development of computer graphics, some related technologies have also appeared one after another or have made great progress on the basis of the original. 3d laser scanner obtains the point cloud data of objects in a non-contact way, and the modelling can truly restore the original appearance of objects, so it has a great impact on urban architecture, power grid design and manufacturing. This paper introduces the collection and processing of point cloud data, and optimizes the processing efficiency of point cloud data, which greatly improves the processing speed of point cloud data and the accuracy of data display. Promote the application of point cloud data in various professional directions.
An Assessment of GF-1 Fused Multispectral Images in Different Months of Spring for Mapping Quasi-Circular Vegetation Patch
Authors: Liu Qingsheng
Published: July 2020

The vegetation phenological information derived from multi-seasonal imagery is helpful for mapping vegetation dynamics. The previous studies indicate that the spring imagery is considered as an optimal data to map the quasi-circular vegetation patches (QVPs) in the Yellow River Delta, China. In this work, the GF-1 images acquired in different months of spring was compared for mapping the QVPs using the decision tree classifier and watershed image segmentation technique based on the brightness and greenness components of tasselled cap transformation. The result of this study recommended that the April GF-1 image with only circle-like detection rules could result in higher detection accuracy compared with that of the March and May images. In the future, more effective image segmentation algorithms and quantitative influence of image quality on detection accuracy should be considered.
Research on the Ways to Protect and Inherit Intangible Cultural Heritage in the Information Age
Authors: Guo Qinghui
Published: July 2020

Intangible cultural heritage is an important part of Chinese culture. With the development of the times, some problems gradually appear in the process of protecting and inheriting intangible cultural heritage, and the government and society also pay more attention to the protection and inheritance of intangible cultural heritage. In this paper, two ways are proposed to strengthen the protection and inheritance of intangible cultural heritage in the information age, that is, to strengthen the development of intangible cultural heritage tourism based on smart tourism and intangible cultural heritage campus education inheritance based on intelligent education, by expounding the significance of protecting and inheriting intangible cultural heritage and analyzing the methods and existing problems of protecting and inheriting intangible cultural heritage.
Research Hotspot and Evolution Analysis of ECG from the Perspective of Knowledge Map
Authors: Zhao Lili
Published: July 2020

In this paper, knowledge mapping technology is used to analyze the relevant literature of ECG research in China, and the research status, research hotspot and trend in this field are statistically analyzed. CiteSpace V is used to carry out data visualization analysis on the literature retrieved from CNKI database. Through the analysis, we can see that the research of ECG based disease diagnosis has achieved sustainable development in recent years, but the high influential authors pay less attention to the research in this field. The core of the research is mainly focused on wavelet transform, feature extraction, classification and recognition, and the research strength in this field still needs to be strengthened.
Research on the Development and Practice of Confucius Research and Study Travels in the Internet Plus
Authors: Zhang Lixia , Sun Zhongli
Published: July 2020

As a new mode of education, research and study travel skillfully combines the school education with the external education, and the development of practical education can quickly improve the comprehensive quality of students. It is an effective way to foster the comprehensive development of students. Built on the product of Confucius culture in the era of Internet +, it provides the possibility for the intelligent development of research and learning travel. This paper analyzes the development of Confucius research and learning travel from the aspects of “education + tourism” and “Internet +”, and the benefits it gives to students, schools and tourism enterprises. The Confucius culture-themed study tour further expands students’ learning space and improves students’ comprehensive quality in many aspects.
Research on Technical Characteristics of CDPF + SCR for China-III Heavy-Duty Diesel Vehicles Emission Retrofit Based on Remote Monitoring Method
Authors: Wang Jiguang , Xie Zhenkai , Chen Hao , Zhang Xiaowen
Published: July 2020

In order to study the technology of reducing heavy-duty diesel vehicles PM and Nox emission, a China-III sprinkler driving on Tianjin expressway was selected to equip with CDPF+SCR for demonstration of PM and NOx emission retrofit. By using the remote monitoring method, the vehicle speed, engine speed, exhaust temperature and pressure drop of upstream and downstream CDPF, NOx concentration upstream and downstream SCR, geographical location and other data were collected and analyzed in real time, and analyze the characteristics of CDPF passive regeneration, SCR conversion efficiency and DPF matching with SCR. The results show that :the idling speed and the middle and low speed operating conditions of the sprinkler are evenly distributed, exhaust temperature at 175∼275 °C accounts for 74%, and CDPF started passive regenerative emission retrofit at 220°C, NOx concentration after installing SCR was mainly concentrated below 800ppm,the average NOx concentration was 620ppm, and the reduction rate of NOx concentration was 51.6%.
Research on Evaluation Index of Mine Environment Rehabilitation
Authors: Wang Haiqing , Li Li , Wang Jie
Published: July 2020

Mine environmental rehabilitation is an essential part of the construction of ecological civilization in the new era. Effective evaluation of the degree of regional mine environmental rehabilitation can provide decision-making reference information for the corresponding work planning. A method to calculate the index of mine environmental rehabilitation was put forward in this article. It was the value of “the area of mine environmental rehabilitation” divided “the area of mine land which should be urgent rehabilitation”. The index of mine environmental rehabilitation by using the data of national remote sensing survey in 2016-2017 was calculated. The results show that the proposed evaluation method and the research results can provide a reference for mine environmental rehabilitation planning.
Research on Artificial Intelligence Customer Service on Consumer Attitude and Its Impact during Online Shopping
Authors: Li Chenzhuoer , Pan Runjie , Xin Huiyu , Deng Zhiwen
Published: July 2020

Currently, AI customer service is gaining popularity at a high rate, with over 92% of online shoppers having experience with AI customer service. The question is: what attitudes do consumers have towards AI customer service? A randomly selected sample of 670 consumers was surveyed and the study found that 71.5% of consumers accept or at least do not resist AI customer service. The main reasons AI customer service is so popular are that it is fulltime responsive, absolutely neutral, more objective, and represents a future trend. Nevertheless, 28.5% of consumers are still resistant to AI chatbot, mainly because they are not as relevant, effective, and smooth as a human customer service agent. Besides, there are prevalent obstacles to seamlessly bridge AI chatbots with human agents. In terms of explicitly specified AI chatbots versus concealed AI chatbots, merchants should have them specified since consumers have strong antipathy with AI chatbots disguising as human agents. Furthermore, there are differences in attitudes towards AI customer service across age and educational background. Accordingly, we recommend that, in the context of the overall improvement of service quality, to slow down the pace of AI replacing human agents, to do so in a step-by-step and orderly manner, and to give consumers adequate choice for human agents versus AI chatbots. Finally, to fully promote AI customer service, it is an essential measure to increase its media coverage and publicity.
Study on Periodic Solutions for a Kind of Predator-Prey Model with Age-Dependent and Stock
Authors: Wang Hui
Published: July 2020

In this paper, we consider the predator-prey model with age-dependent and stock because of human intervention. The original model is transformed into an equivalent model through a homeomorphism. The existence of a positive periodic solution is proved by using coincidence degree theory and Mawhin continuation theorem.
Comprehensive Teaching Quality Assurance with Artificial Intelligence Applications
Authors: Yuan Ye
Published: July 2020

Establishing the teaching quality assurance system is a key aspect to realize the cultivation objectives of talents of higher education. This paper first discusses the composition, function and evaluation subjects of the comprehensive teaching quality assurance system. Secondly, the novel techniques of applying artificial intelligence to the diagnosis and mining of teaching state information is explored in detail, which constitutes scientific evidence for continual improvement of teaching.
System Fault Diagnosis Method Based on OSDG Model
Authors: Cong Wei , Yu Hongkun , Liu Jing
Published: July 2020

For the difficulties of cross-link fault diagnosis in complex systems, a fault diagnosis method based on optimised signed directed graph model is proposed. First, the system structure is layered and the control bridge is used to implement a top-down hierarchical structure. The SDG is used to describe the hierarchical structure of the system, and the SDG model is also layered so the fault information is propagated unidirectionally according to the layer. The reverse search strategy based on the fault propagation matrix is used to judge the compatible path, obtain the set of candidate fault sources, use the use availability to objectively evaluate the impact of multiple fault sources to improve the efficiency of troubleshooting. The example analysis shows that the method in this paper can adapt to the fault diagnosis needs of complex systems, and has practical application value for shortening the time of system fault determination and improving the accuracy of troubleshooting.
Temporal and Spatial Pattern Characteristics of Vegetation in Qaidam Basin and Its Response to Climate Change
Authors: Du Yu’e , Liu Baokang , He Weiguo , Zhou Jianping
Published: July 2020

vegetation is a sensitive indicator of climate change. The spatial-temporal dynamic changes of vegetation cover and aboveground biomass and their relationship with climate factors in Qaidam Basin in recent 13 years were studied by using vegetation index. The results are as follows: (1) the total area of vegetation in Qaidam Basin increased from 2002 to 2015, with a growth rate of 644.11km2/a (R2 = 0.4919). In recent 14 years, the change of vegetation area has been increasing → decreasing → increasing → decreasing, among which the vegetation area has been increasing continuously from 2009 to 2012; (2) During the period of 2002-2015, the vegetation area of each level of vegetation coverage showed an increasing trend, and the increasing rates were 300.2km2/a, 242.8km2/a and 101.2km2/a, respectively, which indicated that the vegetation ecology in Qaidam Basin was developing to a benign trend; (3) the aboveground biomass of vegetation was mainly low-yield vegetation less than 1500kg/hm2, followed by vegetation of 1500-3000kg/hm2, accounting for the total area of vegetation The proportion is less than 10%, and the vegetation area of other grades is very small, only scattered, while the high-yield vegetation larger than 6000kg/hm2 is distributed in the southeast of the basin and the alpine mountains around the basin; (4) there is a certain coupling relationship between the climate and vegetation change in Qaidam basin, which is reflected in the positive correlation between the total vegetation area and the annual precipitation, the precipitation from May to September and the precipitation in summer, and the correlation significance of summer precipitation > may September precipitation>annual precipitation. However, it was negatively correlated with winter precipitation, but not with autumn precipitation and annual average temperature (P > 0.5).
An Optimization Control Method for Heat Transfer Model during Slab Continuous Casting
Authors: Wang Zhaofeng , Zhang Yichi , Jiang Yuting , Zhang Jiahui , Zhang Shuai
Published: July 2020

Solidification of continuous casting slab is a complex process including a series of phenomena such as heat transfer, mass transfer and flow. The secondary cooling process plays an important role in the production quality of continuous casting slab. In this paper, an improved particle swarm optimization algorithm has been proposed. The simulation results show that the optimized slab temperatures have more reasonable and uniform distribution. The purpose of slab quality improving is achieved and the feasibility of secondary cooling water distribution scheme is verified.
Application Analysis of Artificial Intelligence in Port Shore Power
Authors: Wu Jiangpeng , Yin Hongxu , Huang Dan , Shao Yang
Published: July 2020

By studying the development status, application scenarios and development needs of port electricity application and operation at home and abroad, this paper analyzes the significance of building a port artificial intelligence power business support platform for shore power operation. In view of the diversified demand of electric equipment and the emerging demand of operation service under the condition of port power grid, this paper puts forward a scheme of electric business support platform system for port power and other artificial intelligence electric equipment, focusing on the platform system architecture, external interface of the system and future expansion function, and based on the development trend of China’s ports, it will support the future port intelligent electric business The application of the platform is prospected.
Research on Innovation and Application of Multi-dimensional Interactive Teaching Mode in Smart Classroom: Taking Junior Physics Applied Research as an Example
Authors: Dai Yi , Liu Zhen , Luo Dan
Published: July 2020

There are many phenomena such as the interaction between teachers and students is not smooth and rich in the current physics teaching of junior high school. With the help of “Guangdong Education Cloud” platform and the Digital Textbook, this paper mainly discussed multi-dimensional interactive and collaborative learning strategies, and built a multi-dimensional interactive cloud classroom model and application model. The implementation process of cloud interactive classroom teaching of junior middle school in physics was introduced as an example, and the validity of the model was verified according to the contrastive analysis of the data before and after the implementation of the multi-dimensional interactive cloud classroom.
Allometric Growth Patterns of Taimen Larvae and Its Ecological Significance
Authors: Yang Guiqiang , Wang Zhanquan , He Jie , Li Wentong , Yuan Ding
Published: July 2020

Ecological experiment was conducted to study the allometric growth of taimen yolk-sac larvae and its significance in adaptation in early life stage. The results indicated organs such as feeding, breathing and swimming of larvae in the yolk sac stage are rapidly differentiated, and all key organs are allomorphic. In all parts of the body, the head length and body height are growing at a positive allometric speed, the trunk and tail fin length are growing at a slow speed; in the head organs, the rostrum length, eye diameter and head length are growing at a positive allometric speed; in the swimming organs, tail fin length is negative allometric growth; yolk sac length, yolk sac width and yolk sac height are negative allometric growth consumption. The fast development of feeding, breathing, swimming and other organs in yolk-sac larvae of taimen, increases larval survival ability at the early stage in the shortest possible time, and there were important ecological significance to adapt the complex and changing external environment.
State of Charge Estimation for Lithium-ion Battery Based on Cubature Kalman Filter with Fading Square-foot Factor
Authors: Zhang Yulong , Zhou Sida , Hua Yang , Zhou Xinan , Yang Shichun , Liu Xinhua
Published: July 2020

The state of charge (SOC) is the key issue to ensure the safe operation of the battery, but the battery system’s state estimation often has low accuracy and robustness under complex conditions or uneven measurement problem. To solve this problem, this paper proposes an SOC estimation method based on the combination of cubature Kalman filtering, fading factor and square root filtering. In addition, the second-order equivalent model is adopted, and parameters are identified. To verify the success of the algorithm, various operation tests were conducted. The simulation results agree well with the experimental results, and the maximum error can reach 3%. Numerical analysis shows that the method has good convergence and robustness under the initial error disturbance.
Design of Equipment Online Monitoring and Fault Diagnosis Platform Based on IOT
Authors: Yang Luxia , Zhang Guihua , Wu Peng
Published: July 2020

Complex equipment in the process industry is the core productivity of automated manufacturing. Fault prediction, diagnosis, and health maintenance of such equipment are important factors to ensure continuous and reliable operation of production. However, how to adjust the fault judgment rules in time according to the changes in the operating conditions and process of the equipment is the core design content of the fault diagnosis platform. The platform of this paper presented is mainly based on stress wave condition monitoring technology, which combined with process monitoring to form an online monitoring data set of the equipment; Then use the data fusion technology to fuse the collected signals at the decision-making level, and finally combine principal component analysis and the BP neural network to predict the equipment’s health trend and fault type.
Structural Design and Vibration Simulation of A New Type of Hollow High Precision Reducer with Integrated Structure
Authors: Zhao Honghua , Lin Yifei , Lu Shouyin
Published: July 2020

A new type of hollow and high precision reducer for robot is designed. By machining the track in the outer ring of input shaft and cycloid wheel, the traditional structure of crankshaft and bearing is replaced. The 4-DOF dynamic model is used for modeling, and the fixed step and 4-order Runge Kutta method of MATLAB software is used for solving, and the accuracy simulation of the reducer is completed. Compared with the existing reducer, the vibration and comprehensive performance of the new hollow high-precision reducer with integrated structure is better than the existing reducer.
Application of Artificial Intelligence in Civil Engineering Education
Authors: Xie Ming , Meng Fanbing , Zou Jingya , Feng Wei , Ma Shaohua
Published: July 2020

Artificial intelligence technology plays a very critical role in many fields in China. The technology can also realize its due value in the field of education. Taking civil engineering as an example, teachers can use artificial intelligence technology and civil engineering. The combination of professional course content helps students’ in-depth understanding of the actual construction of civil engineering projects and the application of some professional mechanical equipment in the classroom. This is also the main content that the author will discuss in the paper.
Quasi-Convex Functions and Their Inequalities Based on Fractional Integrals
Authors: Yin Hongping , Wang Jingyu
Published: July 2020

In the article, on the basis of Katugampola fractional integrals

K

ρ

u
+

α

h

and

K

ρ

ν
−

α

h

with

h
∈

X
c
p

(

u
,
v

)

, the quasi-convex function is discussed and a few inequalities are derived.
SSM-Seq2Seq: A Novel Speaking Style Neural Conversation Model
Authors: Wang Boran , Sun Yingxiang
Published: July 2020

Open domain personalized dialogue system has attracted more and more attention because of the ability of generating interesting and personalized responses. To incorporate speaking style, the existing methods first train respectively a response generator over a non-personalized conversational dataset and a speaking style extractor over a personalized non-conversational dataset, and then generate personalized responses by the parameter sharing mechanism. However, the training datasets’ speaking styles of the response generator and speaking style extractor is totally different, which makes the performance of the existing methods be not optimal. Intuitively, it will improve the performance by decreasing the gap between two training datasets’ speaking styles. Thus, in this paper, we propose a novel speaking style memory sequence-to-sequence (SSM-Seq2Seq) model, which incorporates the speaking style information from personalized non-conversational dataset into the training dataset of response generator to eliminate the gap. Extensive experiments show that the proposed approach yields great improvement over competitive baselines.
Deep Hashing with Attribute Guidance for Image Retrieval
Authors: Lu Yao , Huang Heyan
Published: July 2020

Similarity-preserving hashing is an important method to solve approximate nearest neighbour search problem for image retrieval. Lots of works have been proposed for supervised hashing and image category labels are utilized as supervised information. However, current works ignore a fact that images can be described by a set of attributes. Intuitively, images of different categories with close visual features can be separated by their attribute features because attributes keep more detailed information. In this paper, we propose a novel supervised deep hashing method with image attribute guidance. Specifically, hash codes are learnt through image visual features and guided by image attributes by maintaining pair wise similarities between images as well as the corresponding attribute descriptions. Extensive experimental results on two benchmark datasets show that our proposed method achieves better performance compared with the state of the art hashing methods.