bluuebunny/crossref_metadata_2025 huggingface dataset:
An Analysis on Urban Land Use Efficiency Based on Super-efficiency DEA
Authors: Qiu Yingying , Sheng Jia , He Xiaoyu
Published: April 2021

The purpose of this research is to, by taking Wuhan city as an example, build the super-efficiency DEA to calculate and analysis the urban land use efficiency so as to provide reference for improving urban land use efficiency. Methods employed include super-efficiency DEA. The results show that: 1) the overall land use efficiency of Wuhan city in 2010-2016 is relatively high, most of the regional land use efficiency is relatively effective, but the difference of land use efficiency is relatively large, 2) super-efficiency DEA model can effectively measure and distinguish the urban land use efficiency from the quantitative point of view.
A novel linguistic steganalysis method for hybrid steganographic texts
Authors: Xu Yimin , Yang Liran , Zhao Tengyun , Zhong Ping
Published: April 2021

Most of the existing linguistic steganalysis methods mainly focus on detecting steganographic texts which are generated by embedding secret information into a type of text medium using one steganographic algorithm. But in practical applications, a large number of the steganographic texts may be hybrid ones which are generated by embedding secret information into different types of text media using different steganographic algorithms. In this paper, inspired by transfer learning, a novel linguistic steganalysis method is proposed to detect hybrid steganographic texts. The proposed method first uses the pre-trained BERT language model to obtain initial context-dependent word representations. Then the extracted features are fed into attentional Long Short-Term Memory (LSTM) to get the final contextual representations of sentences. The experimental results show that the proposed method can better satisfy the practical application demands than the existing linguistic steganalysis methods.
Research on Data Security Encryption Based on Extracting Evaluation Index from Multiple Angles
Authors: Hu Pan , Hu Nan , Jiao Chuanming , Zhang Fuliang , Qu Ruiting
Published: April 2021

In order to solve the problem of low accuracy of ciphertext analysis in traditional power system data encryption methods, this paper presents and designs a power system data encryption method based on multi-angle evaluation index. Firstly, the C/S architecture of security protection is established, and the information node of the management information database is supplemented with the multi-level security management system. Then the 3DES encryption algorithm is introduced to balance the weights of the two factors according to the scaling assignment, to increase the data confidentiality, and the embedded terminal is used to assist decryption. The experimental results show that the decryption result of the design method has a high precision, which verifies the effectiveness of the design method in improving the precision of ciphertext.
A 3D trajectory tracking algorithm for AUV
Authors: Li Wenkui , Zhou Zhu , Lou Jianlu , Zhang Xuguang
Published: April 2021

This paper mainly studies the trajectory tracking problem of six-degree-of-freedom AUV in seafloor three-dimensional space. The mathematical model of AUV is established, the trajectory guidance law is designed by LOS method, the speed and rudder force are compensated by adding PID controller, and the stability of the system is proved by Lyapunov stability criterion. Taking Remus100 as an example, the trajectory tracking simulation of straight line and helix in space is carried out. The simulation results show that the trajectory tracking algorithm can realize the trajectory tracking of AUV.
Application of Bioinformatics in the Internet of Things-Construction of Mushroom Cloud Digital Learning Platform
Authors: Lin Yu-Feng , Lin Chia-Hui , Tsai Sheng-Hsien , Lin M-F(Fanny)
Published: April 2021

In recent three years, the practical spirit of “DIY(Do-It-Yourself)”advocated in European and American education to combine the value of creativity and innovation is developed to a word “Maker” after integrating into the education system, which comes from the idea of “Hacker” and “Self-creator”. The Maker transforms one-way learning model of “listening” and “writing” in the past to school curriculum of “image” and “practice”, causing a reversal of traditional educational concepts. Educational policy in Taiwan naturally moves with the tide of the world. What characteristics of DIY, trouble-shooting, creativity sharing and community link emphasized by the Maker is in consistent with the transformation of technical and vocational education and the innovation of higher education that focus on the spirit of exploration and practice as well as innovation? The school used to participate in High Scope Program Phase II, including the development of “eco-art” course module for the first three years focused on plant observation along with the use of photography, presenting the idea of truth, goodness and beauty with the practice of “scientific drawing” in Fine Art Department; and, elaboration and promotion stage for the following two years focused on the reinforcement of introduction to biological course and the function of “online plants learning platform”, expanding to university and senior high schools, including of the Affiliated Chongli Senior High School of National Central University, Taishan and Sanming Senior High School for the development of more functions. As the theme of mushroom nutrition & health care, the school continues the spirit of exploration and practice by integrating Dept. of Home Economics’ food safety issues, Dept. of Chemistry’s extraction analysis, Dept. of Physics’ spectrograph analysis and Dept. of Computer Science’s internet of things(IoT) into curriculum framework to develop courses module for additional learning platform of mushroom classification based on “online learning platform” within application of bioinformatics in the IoT. The content for logic concept of plant retrieval classification and feature concept of fungi classification is processed in our Mushroom Digital Learning Platform by combining tablet PC and interactive web pages of “Online plants and herbs(mushroom) learning platform” for multiple assessment, in order for teachers to understand the learning effect of each student and analyze the data through the cloud platform.
Modeling for geometry-based massive MIMO V2V channels and analysis of space-time correlation
Authors: Xing Kexin , Guo Aihuang , Song Chunlin
Published: April 2021

This paper proposed a three-dimensional dual-spheres confocal ellipsoid geometry-based model for massive MIMO vehicle-to-vehicle (V2V) communication. In this proposed model, the received signal is composed of non-line-of-sight propagation components generated via effective scatterers and line-of-sight propagation components. According to the geometric relationships in the model, the information of angle and distance can be derived, and then the space-time correlation function expression is obtained. To calculate parameters, modified method of equal areas is employed, and the influence on space-time correlation of scatters in different environments is analyzed. Channel characteristics in different scenarios such as highway scenario, urban road scenario and tunnel scenario are compared and studied. Simulation results show that the scatterers distribution and angle information of antenna arrays make a joint contribution on spatial cross-correlation, and moreover, the degree of anisotropy of scatterers and multipath components have distinct impacts on temporal auto-correlation. Compared with the results of 2D model, the proposed 3D model in this paper is more appropriate to characterize V2V communication in various scenarios.
Towards Discovery of Differences of Source Code Through Semantic Difference Checking
Authors: Han Qingdi , Gao Wu
Published: April 2021

Source code difference analysis plays an important role in software development, maintenance and regression testing. Many existing research methods are text-based, however, they are subject to code movement and alignment limitations, resulting in imprecise difference analysis. In addition, some methods are lexical and syntax-based, which ignore the key semantic information of the code and make the analysis results imprecise. In this paper, we propose a source code difference analysis technique based on semantic difference checking to improve the problem of inaccurate difference analysis. We implement the prototype, and exploit static analysis and textual difference detection tools to pro-process the programs, then perform semantic difference checking on the code with textual differences, and define the semantic differences. We conduct experiments on two C programs with differences and the results show that our approach can effectively and accurately detect code differences.
Unified SQL Query Middleware for Heterogeneous Databases
Authors: Zhang Huiran , Zhang Cheng , Hu Rui , Liu Xi , Dai Dongbo
Published: April 2021

With the development of modern computer technology, the data which needs to be stored and processed by modern application systems becomes more and more varied. While traditional relational databases still dominate, NoSQL databases are developing rapidly and occupy a place in the entire industry. Therefore, more and more applications need to connect to multiple database systems at the same time. However, the different characteristics supported by different database systems and the differences in query syntax rules make multi-database application development very complicated. This paper talks about a unified query middleware system that supports federated analytical queries with standard SQL syntax for various data sources and can perform joins, aggregates and filter on data from different data sources in a single query.
Research on Intelligent Control Method of Fire Emergency Lighting Distribution in High Rise Buildings
Authors: Zhong Yi
Published: April 2021

Aiming at the problem of high energy consumption in the traditional intelligent control method of fire emergency lighting distribution in high-rise buildings, the intelligent control method of fire emergency lighting distribution in high-rise buildings is proposed. By using the data processing model of fire emergency lighting light environment of high-rise buildings, the data of fire emergency lighting light environment of high-rise buildings are normalized. By calculating the distance between lights and using the optimal mathematical model, the intelligent control algorithm of fire emergency lighting power distribution of high-rise buildings is designed. Finally, through the development of high-rise building fire emergency lighting power distribution intelligent control scheme, to achieve high-rise building fire emergency lighting power distribution intelligent control. Dialux is used to simulate the lighting system with dimming control. The simulation results show that the minimum illumination, total illumination uniformity and longitudinal illumination uniformity of fire emergency passage of high-rise buildings meet the lighting requirements under different walking speed and traffic flow conditions.
Time series forecast of sales volume based on XGBoost
Authors: Zhang Lingyu , Bian Wenjie , Qu Wenyi , Tuo Liheng , Wang Yunhai
Published: April 2021

Some problems such as the decline of new labor force, the increase of retired labor force emerge because of the complex and changeable market environment, consequently exacerbating the staffing problem in the retail industry. Also, the unreasonable distribution of personnel, there are few people in busy hours and too many people in idle hours, which causes waste of labor. To address this issue, we analyzed the time series of sales volume in the retail industry in detail, and processed the data with feature engineering for predicting the in-store sales volume in the future. At the same time, other features such as weather and temperature are added to improve the accuracy of the model. Considering the characteristics of the data, we choose XGBoost as the prediction model. The experiments on real-world datasets verified better performance of proposed model compared with other state-of-art models.
Lane Detection of Smart Car based on Deep Learning
Authors: Yang Dongdong , Bao Wenzhi , Zheng Kai
Published: April 2021

Deep learning brings higher accuracy to lane detection, and the speed of the model is becoming faster and faster. The lane detection is regarded as the classification task after image gridding, and a simplified lane structure loss function is proposed, which is more suitable for the car track. The lightweight SqueezeNet is used as the backbone network, and the deep learning model is applied to the intelligent car of raspberry pie. Through the experiment, the real-time detection speed reaches 23FPS, which can complete the task of lane tracking. Compared with traditional methods, deep learning model has better robustness.
Overview of Generative Adversarial Networks
Authors: Songyuan Li , Fan Mengxuan , Chen Renqiu
Published: April 2021

The study of generative adversarial networks (GAN) provides a new approach and framework for computer vision and makes an outstanding choice for cross-domain image translation problems. In this work, the basic framework structure of GAN as well as the evolution of GAN are summarized. It is known that the unsupervised domain adaptation algorithms attempt to map representations between the two domains, or learn to extract features that are domain–invariant. An approach that learns in an unsupervised manner can be a transformation in the pixel space from one domain to the other. Finally, some existing problems of GAN and its potential future are also summarized and discussed.
Application of simulated annealing particle swarm optimization in complex three-dimensional path planning
Authors: Wangsheng Fang , Chong Wang , Ruhua Zhao
Published: April 2021

Particle Swarm Optimization (PSO) has achieved good results in UAV path planning, but there is still the phenomenon of abandoning the global optimal path and choosing the local optimal one. In order to improve the ability of particle swarm in path planning, a simulated annealing particle swarm algorithm is proposed. First, tent reverse learning is used to initialize the population so that the algorithm is evenly distributed in space. Then annealing operation is performed after iteration once, which has better local path judgment ability and avoids the phenomenon of local optimum to some extent, so as to find a more satisfactory path. Simulated annealing particle swarms can find a clear and satisfactory path with high stability through the complex three-dimensional path planning simulation of UAV.
Multi level Recommendation System of College Online Learning Resources Based on Multi Intelligence Algorithm
Authors: Zheng HU
Published: April 2021

In order to accurately grasp the actual search habits of online learning objects and establish a more reasonable multi-level recommendation scheme, a multi-level recommendation system of online learning resources in Colleges and Universities Based on multi intelligent algorithm is designed. With the help of the given topology, the multi-level recommendation behavior in the system is analyzed. Then combined with various types of Resource Recommendation application units, the hardware execution environment of the system is built. On this basis, a multiple intelligent neural network model is established. Combined with multi intelligent recommendation technology, the actual Resource Recommendation behavior related to learning objects is determined, and the software execution environment of the system is built. Combined with the structure of relevant hardware equipment, the design of multi-level recommendation system for online learning resources in colleges and universities based on multiple intelligent algorithms is completed. The experimental results show that the system designed in this paper records a larger number of learning objects, but the recommended waiting time is relatively shorter. The system can accurately grasp the actual search habits of online learning objects and establish a more reasonable multi-level recommendation implementation scheme.
Automotive Parking Assistant Testing Scene analysis and evaluation research
Authors: Xue Liang , Leng Yue , Lian Xin
Published: April 2021

Since the existing automatic parking testing procedure scene is way too simple and idealized, it’s necessary to explore a set of effective verification procedure for the complex scene of Automatic Parking Assistant, which can evaluate the overall performance of the automatic parking function of different vehicles comprehensively, objectively and accurately. In the actual vehicle parking process, there are a lot of harsh and complex scenes which cannot be covered by the current verification system. This paper aims to build a set of effective verification system for the complex scene of automatic parking based on Artificial Intelligence technology. It can comprehensively, objectively and accurately evaluate the comprehensive performance of the automatic parking function of different vehicles.
A Toxic Comment Classification Model Based on Ensemble
Authors: Xu Jian , Zhai Yuqing
Published: April 2021

Accurate classification of toxic comments in different languages is an important task in today’s international social networking platforms. In order to improve the classification of toxic comments in different languages, this paper combines the advantages of high accuracy of monolingual model and strong generalization ability of multi-language model, and adopts the ensemble of multilingual model and monolingual model to classify toxic comments. For the monolingual model, the monolingual pre-training model is fine-tuned with labeled task data; for the multilingual model, before fine-tuning the model with labeled task data, a further pre-training is applied to train model on unlabeled data, which aims to make full use of the large amount of unlabeled data and reduce the dependency of amount of labeled comment data while improving the classification effect. Comparative experiments on Conversasion AI’s multilingual toxic comment dataset show that the model in this paper has improved results on different evaluation metrics compared to the XLM-RoBERTa multilingual fine-tuning model, illustrating the validity of the model.
Research on students’ classroom behavior based on big data analysis and hidden Markov model
Authors: Tang Mingwei , Chen Xiaoliang , Mao Hongyun , Yang Tian , Xie Jianhua , Zhu Lin , Zhong Shifen
Published: April 2021

Under the traditional mode of classroom teaching, there is a problem that students’ classroom behaviours are inconsistent with their classroom results. In view of the above problems, this paper analyses students’ classroom behaviours through big data, and gives a hidden Markov model. The model can establish the organic relationship between classroom behaviours and students’ results, and adjust the contents that affect classroom behaviours in real time in the process of teaching. The results show that the model is effective, and big data analysis plays an important role in the analysis of curriculum behaviours.
Research on the application of animation design based on digital media technology
Authors: Liu Ying , Zhang Xinyue
Published: April 2021

The continuous development of science and technology is making digital media technology widely used. In the field of animation design, the application of digital media technology shows great advantages; it not only improves the efficiency of animation design, but also promotes the healthy development of China’s animation industry. The article firstly draws attention to this industry by the sharp increase of digital media practitioners, analyses the combination of digital media technology into animation design and the advantages of the combination development, and puts forward the view that digital media technology is conducive to improving the efficiency of animation design and the more skilled digital media technology is, the higher the efficiency of animation design is, and puts forward strategies to optimize the application of digital technology in animation design in the case practice. It also proposes strategies to optimise the application of digital technology in animation design in the case practice, hoping to provide reference for improving the technology of animation design.
Design of Plant Breeding System Based on one M2M Standard
Authors: Liu Zeyu , Bu Fanru , Yin Xinyu , Wang Xiuxiu , Zhang Zhongjie
Published: April 2021

With the continuous upgrading of the Internet of Things, cloud platform and intelligent control technology, the development of plant cultivation has become intelligent. Aiming at the problems of low intelligent degree of environmental monitoring, in this paper, combined with agricultural Internet of Things, a plant cultivation system based on one M2M platform was designed and developed. In addition, this paper takes succulent seedlings as the experimental object and designs a succulent seedling cultivation system to achieve the control expectation of this plant cultivation system.
NAUI : Neural Attentive User Interest Model for Cross-Domain CTR Prediction
Authors: Wang Ren , Xie Zhihong , Qi Gaofeng , Li Ping
Published: April 2021

In the existing works for recommender systems, the design of Cross-Domain CTR prediction is less mentioned. In order to solve the data sparsity problem in CTR prediction, Cross-Domain Recommendation (CDR) leverages a wealth of information from a source domain to improve the CTR prediction performance on a target domain with sparse information, which is better than Single-Domain CTR prediction. Ads are usually displayed with natural content, which gives Cross-Domain CTR prediction the opportunity for problemsolving. In this paper, we propose a CDR novel named NAUI which can leverage auxiliary data information to improve the CTR prediction performance. NAUI utilizes an extracting user interest method which reduces excessive punishment for active users, and jointly training Cross Net and MLP components together on CDR. NAUI can capture more information about nonlinear features and combined features efficiently capture implicit and explicit high-order features interactions, and greatly improve the expression ability of the model on Cross-Domain CTR recommendation. Furthermore, we add an auxiliary classifier to the deep neural network to improve recommendation performance. Our experiment results has demonstrated that NAUI outperforms several frequently state-of-the-art methods of CTR prediction.
Carbamoylated chitosan hydrogels with improved viscoelastic properties and stability for potential 3D cell culture applications
Authors: Marapureddy Sai Geetha , Hivare Pravin , Kumar Siddhant , Gupta Sharad , Thareja Prachi
Published: April 2021

We demonstrate a benign and straightforward method to modify the chitosan (CH) by carbamoylation. The free amines on CH are converted into carbamyl functionalities by reacting with potassium cyanate (KCNO). One wt% CH solution, when reacted with KCNO ⩾ 0.1 M, leads to the sol–gel transition of CH through the hydrogen bonding to form carbamoylated chitosan (CCH) hydrogel. Gelation time of CCH decreases with an increase in the KCNO concentration and an interconnected porous network is formed as observed under SEM. Rheological studies show that while one wt% CH solution is a viscous liquid, the CCH hydrogel with 0.5 M KCNO has a storage modulus (G') of 104 Pa. The CCH hydrogel is proved to be non-cytotoxic and promotes the attachment and growth of the small lung cancer model A549, and the neuroblastoma SH-SY5Y cell lines. CCH hydrogel also promotes the differentiation of SH-SY5Y cells into neuronal cells, as supported by immunostaining and thus demonstrating its utility as a versatile scaffold for three-dimensional cell-culture systems.
Crop-specific exposure to extreme temperature and moisture for the globe for the last half century
Authors: Jackson Nicole D , Konar Megan , Debaere Peter , Sheffield Justin
Published: April 2021

Global assessments of climate extremes typically do not account for the unique characteristics of individual crops. A consistent definition of the exposure of specific crops to extreme weather would enable agriculturally-relevant hazard quantification. To this end, we develop a database of both the temperature and moisture extremes facing individual crops by explicitly accounting for crop characteristics. To do this, we collate crop-specific temperature and moisture parameters from the agronomy literature, which are then combined with time-varying crop locations and high-resolution climate information to quantify crop-specific exposure to extreme weather. Specifically, we estimate crop-specific temperature and moisture shocks during the growing season for a 0.25∘ spatial grid and daily time scale from 1961 to 2014 globally. We call this the Agriculturally-Relevant Exposure to Shocks (ARES) model and make all ARES output available with this paper. Our crop-specific approach leads to a smaller average value of the exposure rate and spatial extent than does a crop-agnostic approach. Of the 17 crops included in this study, 13 had an increase in exposure to extreme heat, while 9 were more exposed to extreme cold over the past half century. All crops in this study show a statistically significant increase in exposure to both extreme wetness and dryness. Cassava, sunflowers, soybeans, and oats had the greatest increase in hot, cold, dry, and wet exposure, respectively. We compare ARES model results with the EM-DAT disaster database. Our results highlight the importance of crop-specific characteristics in defining weather shocks in agriculture.
Global perspective on CO2 emissions of electric vehicles
Authors: Märtz Alexandra , Plötz Patrick , Jochem Patrick
Published: April 2021

Plug-in electric vehicles (PEVs) are a promising option for greenhouse gas (GHG) mitigation in the transport sector - especially when the fast decrease in carbon emissions from electricity provision is considered. The rapid uptake of renewable electricity generation worldwide implies an unprecedented change that affects the carbon content of electricity for battery production as well as charging and thus the GHG mitigation potential of PEV. However, most studies assume fixed carbon content of the electricity in the environmental assessment of PEV and the fast change of the generation mix has not been studied on a global scale yet. Furthermore, the inclusion of up-stream emissions remains an open policy problem. Here, we apply a reduced life cycle assessment approach including the well-to-wheel emissions of PEV and taking into account future changes in the electricity mix. We compare future global energy scenarios and combine them with PEV diffusion scenarios. Our results show that the remaining carbon budget is best used with a very early PEV market diffusion; waiting for cleaner PEV battery production cannot compensate for the lost carbon budget in combustion vehicle usage.
Development Status and Application of Under Pressure Operation Equipment Technology
Authors: Tang Shiguo , Qin Fang , Dong Liangliang , Sun Hanwen , Zheng Li , Luo Hong , Wu Ke , Luo Wei
Published: April 2021

With the development and development of unconventional oil and gas reservoirs, the problem of difficult completion and workover has gradually become apparent, and pressured operations have gradually been valued by major oilfields and enterprises. In order to promote the development of pressure-related workover related equipment and technology in our country, and overcome the difficulties of late start and little experience, this article focuses on the development status of pressured operation. The main contents include: a brief introduction to the dangers of annulus pressure and the distribution statistics of annulus pressure wells at home and abroad; introduction to the development process of annulus operations; and introduction of a series of pressure equipment products that have matured or formed an annulus at home and abroad, and The research status of the key components of the pressure-proof operating equipment, such as the blowout preventer and the floating slip, is summarized. Finally, China’s domestically developed independent research and development of pressure-operating equipment is analyzed and considered. Based on the operating concept, enhance the trust and confidence of enterprises and oilfields in pressured operations; technical development should be oriented towards integration, characterization, and digitization, and systemized and serialized pressured operating equipment and process technology. The combination of pressure operation technology and equipment with repair and drill forms a drill-finish-repair integrated pressure operation system.
Numerical Analysis of Casing Damage in Heavy Oil Thermal Recovery Wells
Authors: Geng Lijun , Liu De , Han Liang , Feng Shuo
Published: April 2021

With the decrease in the world’s thin oil resources, heavy oil resources gradually become the main resources in the current and coming period. However, the casing damage of thermal recovery wells seriously restricts the development and exploitation of heavy oil. By investigating geological conditions, production status, and casing damage from in Liaohe Oilfield, the mechanism of casing damage in heavy oil thermal recovery wells was analyzed. Through establishing a casing-cement sheath-formation model and using a thermosetting coupling model of transient heat transfer, the temperature field and stress field of casing in the perforation section were simulated and studied, and the influence law of thermal stress generated by high temperature on the casing was analyzed. The damage of perforated casing is mainly caused by thermal stress, making the casing bear the alternating load of high temperature and high pressure, research shows. After multiple rounds of steam huff and puff, the residual stress of casing increases with the period, resulting in casing fatigue failure. Meanwhile, sand production seriously abrades casing, causing stress concentration of casing and then accelerating casing damage. By studying the casing optimization design, the occurrence of casing damage in heavy oil thermal recovery wells can be reduced and even prevented.
A Landslide Displacement Calculation Method Based on Correlation Analysis of Point Cloud Intensity Images
Authors: Xie Mowen , Liu Weinan , Wang Hongfei , Li Qingbo
Published: April 2021

This article proposes a new point cloud data analysis method to expand the applicability of 3D laser scanning technology for landslide deformation monitoring. First, the laser intensity value of the point cloud needs to be corrected. The corrected, discrete point cloud data is converted into a two-dimensional false color image based on its laser intensity. Then, a digital image correlation algorithm is introduced to analyse the point cloud intensity raster images. The displacement field of the landslide on a specific projection plane is calculated. Finally, the calculated landslide displacement field is matched with the digital elevation model of the landslide. The spatial displacement field of the landslide surface was calculated by comparing the elevations before and after the deformation. Laboratory experiments show that this method can monitor the deformation and failure of the landslide model as well as calculate the spatial displacement of the landslide surface.
Product Information Units Modeling Oriented to Digital Twin
Authors: Bao Qiangwei , Zhao Gang , Yu Yong , Dai Sheng
Published: April 2021

To solve the problem of expression of multi-source heterogeneous data of product development and manufacture, a new concept of product information units (IUs) and a new method of product data modeling based on IUs are proposed. Firstly, the definition and composition of IUs are analysed according to the formation time and description object. Secondly, the geometric elements and their topological relationships of products are regarded as bases, depending on which the association methods of various IUs are expounded. Meanwhile, the role of IUs in the construction of digital twin models is pointed out. Finally, the ontology representation of the IUs is realized to prove the feasibility of the method proposed.
The Kozai-Lidov Mechanism in Binary Star Systems and the Stabilizing Effect of Binary Stars
Authors: Chen Zhifeng
Published: April 2021

This study used Python simulations to compare the orbits of planets in single-planet binary systems and two-planet binary systems with equivalent single star systems to examine the differences of the Kozai-Lidov mechanism in three-body single star systems and four-body binary star systems. The Python program simulated the forces between the stars and the planets, and produced inclination graphs and orbital diagrams. In the single-planet scenario, no Kozai-Lidov effect is observed as the additional star did not affect the planet’s inclination, but the orbit is considerably rotated. In the two-planet scenario, the Kozai-Lidov oscillation period decreases from 650 years to 370 years, and the maximum inclination decreases from 0.690 radians to 0.280 radians, indicating that the binary star system acts against the Kozai-Lidov Mechanism. Additional trials with modified initial configurations of the two-planet binary star system confirm the universality of the suppressive effect in varying initial conditions in binary star systems.
Suitability Analysis and Evaluation of GIMMS NDVI3g Product in Plateau Region
Authors: Zhao Jianyun , Ding Yuanyuan , Yang Jing
Published: April 2021

Quantitative Remote Sensing product have many challenges and uncertainties used in Tibet plateau, GIMMS NDVI3g is the longest NDVI time series products reflected the vegetation growing and changing at present. This paper takes Qinghai plateau as example, and using multi-source remote sensing data including SPOT, MODIS and Landsat to analyze its suitability and evaluate its accuracy. The results indicate that the value of GIMMS NDVI3g is bigger than others dataset, and there has no significant difference between the datasets according to the root mean square error, and the correlation coefficients are greater than 0.95. The vegetation phenology and changing characteristic reflected by the datasets is in line with each other. There have strong correlationship between NDVI3g and Landsat NDVI, and the root mean square error is 0.055, and the deviation is in accord with the Gaussian normal distribution. So NDVI3g dataset has favorable suitability and reliable accuracy used in vegetation change detection of plateau region.
Establishing a Cyclone Gyro Model to Study the Trajectory of Tornadoes
Authors: Zeng Yuanzhuo , Fu Yanjie , Lv Chenglin , Liu Wei
Published: April 2021

This paper attempts to study the rotation and advance characteristics of tornadoes by experiments and theoretical analysis. A cyclone generator that simulates the characteristics of tornado is completed, and put to experiments under different wind fields in the wind tunnel laboratory. The rotation pattern and advance pattern are analyzed from both the Bernoulli Principle and precession principle. Finally, this paper makes a summary of the research done so far and puts forward the prospect of the next experiment.
Remote Sensing Estimation for Aquacultural Algae Yield of Sea Area Based on Water Spectral Analysis
Authors: Cheng Yu , Zhang Lin , Li Kaiqiang , Zhu Hongchun
Published: April 2021

Mariculture yield estimation has an important significance in scientific planning and management of aquaculture scale. This study focused on the algae culture of sea area. The feasibility of constructing a remote sensing quantitative model for estimating the yield of algae culture was investigated through spectral characteristics analysis of sea water. Multi-source remote sensing data were used to analyse the spectral characteristics of sea water for coastal aquaculture. Low-pass filtering and threshold segmentation were used to classify algae culture areas. An estimation model was established based on trend yield and algae index for remote sensing quantitative estimation of the annual yield of algae culture. Results demonstrate that (1) the difference in spectral characteristics is mainly reflected in the blue-green band, the spectral reflectance of cultured shellfish is greater than that of cultured algae and the sensitive growth period is from February to April every year. (2) The total yield of algae culture estimated by counting the area of algae culture in Shandong Province is 520699 tons in 2019. This study shows the high accuracy and feasibility of remote sensing quantitative estimation model of algae culture yield.
Review of natural disasters in Yunnan Province of China
Authors: Yao Xiuyi , Fan Wenjie , Wang Wanqing
Published: April 2021

Various natural disasters have brought great economic losses and huge social influence under the complex regional environment in Yunnan Province. In this paper, we developed a comprehensive review on variety of natural disasters in Yunnan Province including strong earthquakes, landslides, floods and droughts. Based on the statistical analysis, some important prevention measures and suggestions were provided. This review will provide some references on the comprehensive natural disaster studies and it is helpful for natural disaster prediction.
Study on the Influence and Correction of Spatial Heterogeneity of Air Temperature in Drought Remote Sensing Monitoring
Authors: Zhang Rui , Li Hongjun
Published: April 2021

Temperature Vegetation Dryness Index (TVDI) is one of the commonly used methods in remote sensing drought monitoring. Since this method requires the study area to be large enough to achieve the ideal fitting of the dry and wet edges of the temperature-vegetation feature space, the spatial heterogeneity of meteorological elements has a significant influence on the results. Taking Hebei Plain as an example, the air temperature data at the moment of satellite transit are used to modify the surface temperature retrieved by remote sensing, that is, the surface temperature subtracts the spatial heterogeneity of air temperature, to eliminate the influence of the spatial heterogeneity of air temperature on the TVDI index. TVDI index and surface temperature before and after correction are compared in this paper. The results show that the spatial heterogeneity of air temperature does have a significant effect on TVDI index, and the surface temperature distribution after temperature correction is more reasonable, and will not have great effect on the method of using TVDI to monitor the degree of drought. It can be seen that the correction of surface temperature is more helpful to improve the accuracy of agricultural drought monitoring.
Classification of Deep Sea Sound Speed Profiles in the Northwest Pacific Based on Cluster Analysis
Authors: Zhang Yu , Wang Hua , Yu Xiangjun , LI Qinghong
Published: April 2021

Sound speed profile in ocean has significant seasonal and sea area distribution characteristics. Different sound speed profiles have different effects on underwater acoustic propagation, which makes the detection performance of sonar have significant differences. In order to study the distribution characteristics of sound speed profile in the Northwest Pacific, using WOA13 data set, calculate the number of types by application hierarchical clustering method, using cluster fuzzy c-means method classify sound speed profile, calculate the distribution area of various types in different seasons and typical sound speed profile structure. It is concluded that there are 6 types of sound speed profiles in Northwest pacific: Subarctic category, subarctic transitional category, subtropical transitional category, subtropical category, tropical transitional category and equatorial tropical category. The distribution area of these categories is generally zonal distribution. Except for the tropical transitional category and equatorial tropical category, the other categories have significant seasonal changes.
Assessment of Submarine Landslide Susceptibility in the Sea Area of Zhoushan
Authors: Shan Zhigang , Guo Fenfen , Lai Xianghua , Xiao Jingjing
Published: April 2021

The research on the submarine landslide susceptibility has important guiding significance for the site selection and construction of marine engineering. The Zhoushan Archipelago New Area is dominated by the marine industry, and the marine engineering under its jurisdiction is densely covered. This research selected the surrounding sea area of Zhoushan island as the study area to evaluate submarine landslide susceptibility. The factors such as seismic peak acceleration, proximity to fault zone, average wave height, slope and sediment types were selected to construct the evaluation index system, all of which were considered to be influential in the occurrence of landslides. Meanwhile, the AHP method was used to calculate the weight of each index factor. In combination with geographical information system, the study area has been classified into five classes of relative landslide susceptibility, namely, extremely low, low, medium, medium-high and high. The research result showed that: (1) The high susceptibility zone in the evaluation result was consistent with the position of historical landslide. (2) The five classes in the result of submarine landslide susceptibility assessment for study area accounted for 1.17%, 1.97%, 9.08%, 56.05% and 31.74% of the total area from high to low, and the area with susceptibility above middle grade mainly distributed in the underwater bank slope around the islands or the slopes position of the tidal current scours. (3) This research was a preliminary study on the susceptibility assessment of regional submarine landslides. It was limited by the availability of evaluation index data and submarine landslide data accumulation in the region. Besides that, the evaluation model was influenced by experience greatly, so the evaluation result had certain subjectivity.
Development of an unmanned device with picric acid strip for on-site rapid detections of sodium cyanide in marine water
Authors: Wang Ze , Yuan Tao , Yao Jingfang , Li Jiafan , Jin Yihui , Cheng Jinping , Shen Zhemin
Published: April 2021

In this study, a rapid detection method using picric acid test strip for detection of sodium cyanide in ocean water was established, and an automatic-integrated detection device was set up, which can be mounted on an unmanned surface vehicle. The optimal detection conditions were set as follows: for a 100-ml seawater sample, the weight of tartaric acid solid was 1.5 g, 1–2 drops of 150 g/L sodium carbonate were used to soak the picric acid test strip, the heating temperature was 80 °C, and the heating time was 5 min. Under the optimal conditions, the test result was satisfactory and the detection limit of the method achieved was 0.3 mg/L. This method realizes the remote and rapid detection of sodium cyanide in seawater, which greatly improves the detection efficiency and does not require any personnel to enter the contaminated site. It can be widely used for rapid detection scenarios such as leakage accidents from overseas transportation, lake pollution emergencies and on-site screening.
Proton magnetometer sensor design and its performance
Authors: Ma Ning , Chen Shudong , Zhang Shuang
Published: April 2021

The proton sensor is an important part of the proton magnetometer, which is mainly responsible for generating a polarizing magnetic field and receiving induced signals. This paper presents the design scheme of the proton sensor, including the selection of the internal coil structure of the sensor, the selection of the internal solution, and the design of the sensor shielding layer. Then introduces the proton sensor of the Canadian GSM-19T proton magnetometer, which is one of the world’s leading proton magnetometers. And the performance of the two sensors is compared and analyzed by designing sensor performance test experiment. The experimental results show that the initial amplitude of the test signal of the proton sensor is 2.2V, and the signal decay time constant is 0.86s, the performance is similar to that of the Canadian proton sensor.
Hyper-spectral estimation of soil organic matter in apple orchard based on CWT
Authors: Li Ruiyan , Gao Mingxiu , XU Zexin , Wang Jiafan , Xie Xiaoxin
Published: April 2021

In the quantitative estimation by spectra of soil organic matter (SOM), there are great difficulties in the extraction of characteristic spectral information. It is difficult to effectively improve the correlation with SOM by ordinary spectral transformations, and the spectral estimation models are not high in accuracy and applicability. The purpose of this paper is to explore a more accurate and more suitable non-destructive evaluation model for apple orchard soil. In this paper, an apple orchard in Shuangquan Town, Changqing District, Jinan City, was selected as the study area. The continuous wavelet transform (CWT) was used to process the original soil spectra at multiple scales, and the effect of the estimation model on the SOM correlation at different resolutions was investigated. The results showed that the CWT treatment significantly improved the degree of spectral response to SOM in the orchard. Compared with the original spectra, the prediction accuracy of the model constructed by CWT was higher. After wavelet algorithm processing, the prediction ability of the model tends to increase with the decrease of spectral resolution. The best prediction accuracy was found at the spectral resolution of 20 nm, with the coefficient of determination R2= 0.7547 and the root means square error RMSE=0.0042; the validation accuracy R2=0.8015 and the root mean square error RMSE=0.0039. The model achieved a more satisfactory prediction result at the spectral resolution of 5 nm also. The results show that the broad-band spectral data processed by CWT can be used for accurate monitoring of SOM in apple orchards.
Response of the Riverbed Evolution to Flood Process at A Curved Reach Downstream of Three Gorges Reservoir
Authors: Ge Hua , Deng Chunyan
Published: April 2021

The flood process has a very important impact on the evolution of the river. Based on the two-dimensional mathematical model of water and sediment, the response of the evolution of a curved reach downstream of the Three Gorges reservoir to different flood processes was calculated and analysed in this paper. The results show that under the premise of the same total amount of flood, when the flood process transits from the thin type to the short and fat type, the erosion amount of the channel increases gradually, but the increase extent of the channel above the beach reduced, resulting in the weakened erosion amount of the high beaches in the river.
Analysis of spatial changes in simple dwelling based on sustainable architectural approaches
Authors: Rezeki Simbolon Agustina Sri , Aulia Dwira Nirfalini , Fachrudin H T
Published: April 2021

Occupancy in housing built by the developer experienced changes that are not consistent with the original design, no exception to the pure residential housing program housing subsidies. Generally, the changes made to the residential layout occur after occupancy. Grand Permata Residence II Housing, Deli Serdang Regency is the housing that was built by a developer with a limited area of land and a restricted space of land that will be reviewed with a sustainable architectural approach to get alternative changes to an excellent residential spatial layout. Sustainable Architecture Approach is applied to realize housing that guarantees the well-being of its inhabitants. The method used in this study is a qualitative descriptive method with direct observation in the field and analyzed according to the rules of sustainable living. The results of this study are that changes in residential spatial planning and selection of building materials used are following the concept of sustainable architecture towards sustainable development.