bluuebunny/crossref_metadata_2025 huggingface dataset:
Identifier and Locator Separation Based Site Multi-homing Path Failure Recovery
Authors: Liu Feng , Gong Cheng , Tu Rui , Tang Huatao
Published: September 2020

Multi-homing is one of the effective ways to defeat path failure and increase the reliability of site network service. However, limited by the TCP/IP architecture, multi-homing has not been well deployment. In this paper, we proposed a sit multi-homing path failure recovery method based on “Locator/Identifier Split” by adding mapping service and RTT cooperative detection mechanism to the edge router. In order to reduce the probing’s cost of the router’s resource and link bandwidth, we also optimized the probing algorithm by reducing unnecessary active probing. The results of simulation test proved that this method could effectively detect the path failure and performance drop including packets delay and packets loss, and made a fast path switch to ensure the normal running of the upper application services (e.g., FTP). We also gave a theory analysis of the overhead brought by the sit multi-homing path failure recovery method. It shows that the addition bandwidth cost is 0.036% of the simulation link bandwidth and our approach is practicable.
Global Scheduling Real-Time Parallel Tasks on Multicore Platforms
Authors: Lei Zhenyang , Lei Xiangdong , Long Jun
Published: September 2020

Traditional real-time task scheduling strategies only considers cores scheduling, and do not take in account memory access and cache effects on multicore platforms. In this paper, we propose real-time parallel scheduling (PRTTS) strategy on multicore platforms. Each task is represented as a directed acyclic graph (DAG). The priorities of tasks are assigned according to task periods (rate monotonic, RM). In PRTTS scheduling strategy, priorities of tasks that access memory are promoted over priorities of tasks not accessing memory. Tasks accessing the data in the cache is dynamically raised to highest priority. The results of simulation experiment show that proposed new scheduling strategy offers better performance in terms of core utilization and schedulability rate of tasks.
A Parameter Eigenstructure Assignment Design with Any Desired State Vector in Linear Time-Invariant System
Authors: Liang Bing , Wang Guosheng
Published: September 2020

The parametric design problem for eigenstructure assignment with arbitrary expected state vector is studied via state feedback in linear time invariant systems. The main idea of the considered problem is to design a parametric form of the state feedback, so that the designed closed-loop system has the desired eigenvalues, the desired eigenvectors and arbitrary expected state vector. Based on the parametric solution for a class of Sylvester matrix equation, the parametric expression of all the state feedback gain matrices is given in this paper. The free parameters including in the state feedback gain matrix can be further used to meet other performance requirements for the control system design. Finally, a simulation experiment is given to illustrate the effectiveness and simplicity of the proposed parametric method for the state feedback eigenstructure assignment problem with arbitrary expected state vector in the linear time invariant systems.
Simulation Research on High-Speed Railway Dropper Fault Detection and Location Based on Time-Frequency Analysis
Authors: Li Jin , Zhang Xuewu , Zhang Cheng , Tian Tiantian
Published: September 2020

In this paper, a machine learning detection method, namely, SVM-ICA, which aims to solve the fault identification of droppers in high-speed railway, was proposed based on time-frequency analysis. The proposed SVM-ICA method can be utilized to detect and locate the faulty droppers. In detail, the time-frequency statistical features of the senor data are firstly extracted and the significant features are selected to construct the training set. Secondly, based on the training set, the support vector machine (SVM) fault detection model is trained. Finally, the trained model is used for detecting faulty droppers, and further the position of the break string can be located by using the independent component analysis (ICA) method. Simulation results show that the proposed fault detection method of droppers based on time-frequency analysis can accurately identify if the string breaks, and additionally can locate the position where the failure occurred.
A Rapid Method of Monocular Image Measurement Based on Rectangle Information
Authors: Ping Zhuolin , Yue Zhenjun
Published: September 2020

A method of rapid measurement of monocular image based on rectangle information is proposed in this paper. Based on the pinhole imaging model, a fast method of calculating the object size in monocular image is derived by fitting the straight line and then finding the intersection point of the straight line. The algorithm can not only measure the size and absolute depth of the object in monocular image, but also meet the conditions of the specific pinhole imaging model with a distance far greater than the focal length. The complexity of the algorithm is low, and it can meet the requirements of real-time calculation. It provides a new idea for the use of small and micro-computing platform.
Big Data Mining Analysis of Key Indicators of Online New Energy Vehicles
Authors: Gu Caidong , Liu Zhaobin , Fang Ligang
Published: September 2020

In this paper, more than 300 new energy vehicle key indicators of online sales are mined, and big data visualization analysis is carried out. In October 2018, big data mining analysis was conducted on the brand, model, pure electric endurance, slow charging time, fast charging time, battery capacity, maximum power, maximum torque, monthly sales volume, annual cumulative sales volume, monthly transaction price, user score, number of public praise, manufacturer guidance price (low) and manufacturer guidance price (high) of each new energy vehicle market in Sina auto.com. The results show that the average pure electric endurance of new energy vehicles is 210.3 km (with a maximum endurance of 613 km), and the average fast charging time is 1.7 hours (with a minimum duration of half an hour). The best-known brand of new energy vehicles is BYD, with the highest market share of BYD and Toyota.
Research on Formation Keeping of Multi-rotor UAVs Based on Improved Virtual Structure Method
Authors: Li Long , Sheng Wei , Hu Chen
Published: September 2020

Multi-UAV cooperative formation flight (CFF) can greatly improve the damage resistance and mission completion efficiency of single UAV, so it has become a research hotspot in recent years. The entire process of multi-UAV formation flight can be decomposed into target tracking, formation keeping, obstacle avoidance and collision avoidance. The research of formation keeping mainly uses the leader-follower or virtual structure method. The former has the problem of single point of failure, and the formation error will be amplified step by step. The latter is difficult to select virtual leader, and is hard to adjust the formation adaptively with limited communication conditions. Based on the virtual structure and multicast method, this paper proposes a recursive fusion strategy which reduces the requirement of communication frequency between UAVs, increases the adaptability of formation to single point of failure, and improves the accuracy and adaptability of formation keeping to a certain extent. On this basis, the cascade PID model is used to design the formation controller. Finally, the effectiveness of the strategy is verified by using MATLAB.
An Empirical Study on the Phenomenon of Information Narrowing in the Context of Personalized Recommendation
Authors: Huang Yijun , Zhou Lan , Zeng Ziqian , Duan Lingli , Wang Jiayu
Published: September 2020

Personalized recommendation services have been widely applied to improve users’ search efficiency, but when filtering information for users, they also hide the risk of the declining in content diversity, which is information narrowing. In this study, comprehensive news and information platforms in China were taken as the empirical research object. The experimental tracking method was used to collecting the content data of client end recommended news. Simpson and Shannon-Wiener indexes were used to measure the information narrowing phenomenon. Questionnaires were used to collect users’ data of news and information applications usage, the perception of information overload, and the perception of information narrowing. The data of questionnaire was analyzed and processed by MATLAB and SPSS 20.0, and the hypothesizes were tested by statistical methods. The results reveal that there is indeed information narrowing phenomenon in news information personalized recommendation service, but most users are unaware of this.
The Best-Worst Ant System for the Lock Chamber Arrangement Problem
Authors: Liu Ruijie , Qin Fang , Li Lin , Bo Yu
Published: September 2020

There are many rivers in china, and the inland navigation resources are abundant. With the fast development of the inland waterway transport and the increasing of quantity ships, it is obviously exposed the deficiency of inland river ship locks navigation capacity. In order to improve the ship lock navigation capability, to ensure safe, convenient, stable and orderly navigation through the ship locks, this paper used a best-worst ant system to solve the lock chamber arrangement optimization problem, established the best-worst ant system for the lock chamber arrangement, implemented corresponding algorithm through further design, and tested the validity of it through the Yangtze Gorges lock chamber arrangement and the Qingyuan Water Conservancy lock chamber arrangement. The calculation results show that the best-worst ant system is effective in application of the lock chamber arrangement.
Multi-source Information Data Fusion Method under Complex Battlefield Situation
Authors: Wang Deyi , Zhang Jisheng , Zheng Shicheng
Published: September 2020

Under complex battlefield situation, the situation information is instantaneous and changeable. The uncertain information always causes difficulty in acquisition information and miscalculation, and lead to low efficiency and poor accuracy for aircraft situation awareness. In order to solve the problem, in this paper it proposes a deep-learning based multi-sensor situation awareness data fusion method. With data acquitted from multiple sensors in multi-band and multi-angle, it realizes multi-sensor information data fusion by comparing and analysing of two AI data fusion methods that one is based on classical evidence theory and the other is based on deep learning. The simulation results indicate that the deep-learning based data fusion method presents higher efficiency in dealing with the environment information fusion with large evidence conflict.
College Students’ Physical Fitness Test Data Analysis, Visualization and Prediction Using Data Mining Techniques
Authors: Liu Yanqin
Published: September 2020

Physical Fitness test analysis is crucial in the field of kinematics and health science, the success of which can potentially help efficiently explore students’ physical issue and promote better physical education as well. Considering that the physical fitness of many college students is declining, it has become urgent to conduct a scientific, rational, and exploratory analysis of physical fitness testing data. In this paper, we visualized and explored several data mining algorithms to learn the relationship among different test items and uncover some potential patterns. Experiments are conducted on a real dataset from department of sport, Xi’an Fanyi University. The experimental results show that Catboost outperforms existing approaches in terms of prediction accuracy and F measure. The promising results will effectively evaluate students’ fitness condition, provide insights on correlation of different test items and assist educators for decision making.
Synthesizing Patterns for Videos Based on the Adversarial ConvNet
Authors: Tian Wei , Lv Jingyuan
Published: September 2020

In this paper, we proposed the application of the adversarial ConvNet mode with back-propagation algorithm and weighted method for synthesizing dynamic patterns. A multi-layer spatiotemporal filter is designed in the adversarial ConvNet to capture the spatiotemporal information that may be lost in the convolution phase. The model defines probability distributions. The problem of pattern design is to obtain the best synthesis by training these probability models and maximizing the objective likelihood function. In the training phase, multiple layers parameters of filters are updated through the matching between the synthesized videos generated based on the adversarial trained ConvNets and the observed training videos. The maximum likelihood learning algorithm is used to realize the synthesis of real natural image patterns. The effectiveness of this method is evaluated on public DynTex datasets and compared with other technology through the experimental results.
Retrieval of Ocean Wave Parameters Using Envisat Advanced Synthetic Aperture Radar Data and Its Verification Analysis
Authors: Liu Xiaoyan , Yang Qian , Wang Shuying , Zhou Yan
Published: September 2020

Based on MPI iterative retrieve algorithm, we retrieve the 2-D (two-dimensional) ocean wave spectrum by using Envisat ASAR wave mode Single Look Complex (SLC) imageries. The first guess spectrum is a necessary input item to run this MPI algorithm. In this paper, the first guess spectrum was calculated with reanalyzing wind data of ECMWF (European Centre for Medium-Range Weather Forecasts) and NCEP (National Centers for Environmental Prediction) as input wind stress of WAM Model. The Significant Wave Heights (SWHs) retrieved from the first guess spectrum as well as the best fit spectrum corresponding to ECMWF and NCEP wind field respectively are compared with the measurement data from buoys all over the world ocean. The comparison shows that the SWHs retrieved by ECMWF wind are less than field measurement buoy data in general, while the SWHs retrieved by NCEP wind are greater than those buoy data, but the mean SWHs of them fit with the field buoy data are better than whichever pro. However, the MPI algorithm makes the retrieved SWHs more accurate in comparison with the first guess spectrum derived from either ECMWF or NCEP wind field. Moreover, the relative error of the MPI method is improved by ∼12 percent with respect to the first guess spectrum.
Research of Modulation Feature Extraction from Ship-Radiated Noise
Authors: Wang Hongling , Guo Lihua
Published: September 2020

Information degree of the future naval battle will be very highly, and Striving for information advantage is the foundation of winning modern naval battle. Accurate and prompt recognition is the premise and foundation of tactical command. Modern naval battle is fast and complicated, and submarine sonar is required to be able to detect and classify targets fast and precisely. So the passive target detection and identification is the important research part in the modern acoustic technique field. Firstly, the mechanism of ship-radiated noise is analyzed. The envelope detection model of the ship noise is built. The envelope spectrum is extracted. Through the purity of the envelope spectrum and the smoothness of the continuous spectrum, I separate the line spectrum, from which the target base-frequency related with the rotate speed of ship screws can be detected. Secondly, the method of extracting frequency features of the ship radiated noise envelop is presented by using double frequency method, which is the basis of the classification.
Research on Body Mass Estimation Method of Koi Broodstock Base on Feeding State Image Recognition Technology
Authors: Ma Yinchi , Wei Wei , Zhou Chao
Published: September 2020

Koi is graceful and colorful. In the process of breeding, monitoring the growth state and predicting the body mass of the broodstock are both important. The broodstock will surface on the water while being feed. At this time, the digital camera captures the feeding state image rapidly. The head and mouth of the broodstock show the semi-spindle shape and bright color significantly which have very high contrast with the water background in the image. Based on the method of OpenCV image visual, feature triangle was defined based on the extracted colorful semi-spindle shape automatically. The projection area of the triangle in the image was computed through the vector graphics calculation by computer. A great deal of measurement data was taken analysis on the correlation between the shape parameters and the body mass of the broodstock by MATLAB. A correlation analysis model was established between the projection area of the feature triangle and the body mass. Through this method, the body mass of the broodstock in the aquaculture pond was estimated automatically. The estimating error of the body mass was lower than 9 percent. This method will reduce the workload of collecting the growth state data during the breeding process of the broodstock greatly. And the method can also improve the accuracy of the body mass estimating effectively, which has important production and application value.
Attribute-Based Identity Authentication Scheme Based on Linear Codes
Authors: Zhang Zhiqiang , Cao Suzhen , Han Longbo , Liu Xueyan
Published: September 2020

In the multi-user application environment, the simple use of user private key to achieve identity authentication is too single and can not carry out fine-grained access control to users. And there is the problem of user key management, which is easy to produce system bottleneck. In order to solve the above problems, a traceable and revocable attribute-based authentication scheme is constructed based on linear codes, which divides user access rights in a fine-grained manner. The method of direct revocation is adopted in the scheme, and the cost of revocation is lower. When a key abuse occurs or the system suffers a denial of service attack, the true identity of the malicious user can be tracked based on the signature. Finally, the MBDH problem proves that the scheme meets unforgeability, and the performance comparison and numerical analysis show that the scheme has a shorter key length and less computational overhead.
Resource Optimization for Time Slot-Split Noma in Full-Duplex Cooperative Communications
Authors: Sun Fugang , Li Chuanqing , Liu Yi , Wang Xuan , Liu Yi
Published: September 2020

A time-slot-split non-orthognal multiple access (TSS-NOMA) scheme for full-duplex (FD) relaying communication systems is proposed to improve frequency resource utilization. Aiming at the problem of low bandwidth efficiency when users pairing, TSS-NOMA divides the whole time slot into several parts to improve the matching process, where users can occupy all bandwidths in different time slots. TSS-NOMA decodes the information symbols of relay and re-encodes the messages through the new power allocation factors of successfully matched users. The mixed symbols are sent to increase the proportion of central users’ own signals received by themselves, thus improving the performance of the system. To maximize the minimum achievable rate of the system, TSS-NOMA optimizes the power allocation at the base station and the relay. Numerical results show that TSS-NOMA can achieve higher spectral and energy efficiency than some existing schemes.
A System for Source Address Authentication and Anonymous Communication Based on SDN
Authors: Li Ming , Shan Ranran , Tang Yong
Published: September 2020

Based on the idea of SDN (Software Defined Network) management and control separation and the development convenience provided by the programmable interface, we conduct the research on the security during the communication security, and protection for anonymity: (1) For the problem of communication security, we design two source address authentication schemes to detect whether the source host is legal. (2) For the problem of anonymity protection, A series of changes of the IP address in data packets by intermediate SDN switches make it difficult for the attacker to obtain information from both parties in communication. And to ensure that the address generated after the execution of those changes can uniquely identify the current data stream, we proposed the Improved-MAGA algorithm based on MAGA (M-Address Generation Algorithm). (3) For the shortest path routing algorithm, which maybe result in hot-links problems, the measurement link bandwidth utilization is added as a weight vector in the routing process to solve the problem of excessive link load caused by the default routing algorithm.
Dynamic Feature Combination by Agreement for Image Classification
Authors: Li Chenghua , Wang Wanguo , Liu Linzhi , Liang Tian
Published: September 2020

Image classification is a basic and important task in computer vision. Recently, various neural networks have been designed and proved to be very powerful models for image classification. It is natural for thinking of how to gather their strengths together, which refers to feature combination tasks. Traditional combination methods mainly focus on designing specific combination algorithms to achieve higher performance. However, few works consider how to utilize their agreement on a given target (for example, a specific class) to achieve better combinations. This paper presents a novel dynamic feature combination method (DFCA) for image classification problems based on the agreement of the individual features. DFCA promisingly takes the agreement of not only the commonalities, but also the individualities of different features by dynamically updating the weighting coefficients of given features using a routing module. Experiment and extensive analysis on CIFAR-10 prove the effectiveness and promising characteristics of the proposed method.
Numerical Investigation for Separation Characteristics of Transonic Shock Oscillations Based on Parallel Computing
Authors: Zhang Lu , Ma Shuai , Liu Fan , Cui Xingda
Published: September 2020

Shock-induced oscillation is transonic flow instability phenomenon, which brings additional vibration to the aircraft. In this study, the RANS-LES methods with parallel computing were applied to investigate the transonic shock oscillations over a supercritical airfoil. The third-order MUSCL and fifth-order WENO based Roe scheme with adjustable dissipation were applied to study the effects of numerical dissipation. The results shown the numerical dissipation of the spatial schemes has a great influence on the calculation, and the small scale flow structure are suppressed by excessive numerical dissipation. The numerical results present the separation evolution on the upper surface. And periodic variation characteristics of the separation region downstream of the shock wave was discussed. The ratio of the time taken by the shock moves downstream and upstream is 1:1.
Research on Data Verification and Exchange of Heterogeneous Blockchains for Electricity Application
Authors: Wang Hongkai , He Dong , Gao Yan , Wang Xiaoyi , Xu Caichao , Qiu Weiwei , Yao Yiyang , Wang Qiang
Published: September 2020

This paper proposes a verification and exchange method for cross-chain transactions of heterogeneous blockchains for electricity application scenarios and designs a chain-level cross-chain event verification mechanism. For a blockchain platform that requires cross-chain transactions, a Merkel-structured cross-chain event tree is systematically constructed with the collected cross-chain transactions in the generation stage of the block. The target blockchain platform verifies the credibility of cross-chain events based on the Merkel-structured cross-chain event tree and related credible proofs. Cross-chain events are captured through smart contract events, and cross-chain event Merkel trees and Merkel paths are constructed to achieve credible and rapid verification of cross-chain events. The cross-chain experiments are carried out in the main-side chain mode of electricity business scenario, and the integrity of cross-chain transaction is ensured by a cross-chain transaction consistency guarantee mechanism, so as to achieve the purpose of trusted circulation and secure transactions of electricity business data between different application chains.
Study of Performance Measures and Energy Consumption for Cloud Computing Centers Based on Queueing Theory
Authors: Huang Xiaofeng , Wu Denglei , Zhao Ning
Published: September 2020

Cloud computing, as an effective method to provide computing resource and service to users on demand, is attracting more and more attention. This paper establishes aGI/G/mqueue to characterize the cloud computing centers with general arrival process and service times. We analyze the main performance measures such as the mean waiting queue length and average waiting time of service requests in the cloud computing system. Besides, the energy consumption model of the cloud computing center is established. The results show that increasing the service rate can reduce the average waiting time, the quantity of running servers needs to be varied with the arrival rates of service requests to meet the satisfaction of users. The total energy consumption is connected with the arrival rate, service rate and the quantity of servers in the cloud computing center, but it has nothing to do with the coefficient of variation squared of the interarrival times and service times.
Research on the Sensor-Based Automotive Interior Safety Alarm System
Authors: Fan Xuanxuan , Shen Jie , Zhou Tianhong
Published: September 2020

With the continuous development of the automobile industry, almost every family has a car, so the car safety issue is gradually highlighted. Driving for a long time produce drowsiness; many owners simply sleep in their car, especially younger children who are more prone to the sense of fatigue. In our live, car asphyxiation accidents caused by high temperature and high concentration of carbon monoxide are very common. The automobile has been integrated into people’s life, and its related demands are more diversified. The automobile industry is about to enter the “post-automobile era”. The problem of the interior safety of automobiles is what we need to solve urgently. It is an important means for people to know the safety problems inside the car correctly and take precautions against them. In this document, the status quo of the automotive interior safety problems are described and analyzed. Based on the actual situation, a sensor-based automotive interior safety alarm system is proposed to promote the development of automobile safety industry.
A Cascade Ensemble Learning Model for Parkinson’s Disease Diagnosis Using Handwritten Sensor Signals
Authors: Xu Shoujiang , Zhu Zhaohui , Pan Zhigeng
Published: September 2020

Computer-aided diagnosis of Parkinson’s disease (PD) has gained lots of attention recently, which is mainly performed with machine learning methods using PD patients’ clinical manifestations, such as freezing gait, distorted writing, and abnormal speech. This paper presents a new methodology to differentiate PD patients from healthy controls (HC) based on two datasets regarding handwritten sensor signals. And a novel cascade ensemble learning method which is composed of two random forest (RF) classifiers and two extremely random trees (ExtraTrees) classifiers in each layer is proposed. Augmented features are generated by the four classifiers in a layer, which will be concatenated with the initial input data and fed to the next cascade layer. Finally, the classification result will be obtained from the final layer. To improve the classification performance, we employed principal component analysis (PCA) technique to reduce the dimensionality of sampled signals before they are fed to the ensemble model. Experimental results show that the proposed framework achieved reasonable classification performances with 81.17% accuracy for PD diagnosis.
Research on Innovation Design of Art Wood Printing Machine Based on Ease of Use Theory
Authors: Peng Peng , Zhang Ke
Published: September 2020

The professional traditional printing machine is an indispensable tool in the process of making woodblock prints. However, the disadvantages of high cost, low cost performance, cumbersome machine, high operability and low safety are constantly revealed in the creation of prints. The common printing machines on the market do not meet the needs of users. An art printing machine based on the theory of ease of use is proposed based on the comfort, accuracy and simplicity of printmaking. Through the method of market research, combined with in-depth analysis of the user’s real needs, the ease of use theory is used to analyze the human-machine features of the art printing machine and the feature differences of the print features. A comprehensive summary of the current status of the art printing machine, identified relevant issues, analysis of the factors affecting the ease of use of the art printing machine, and found a new design improvement program.
Comparative Analysis of Position and Pose Estimation Methods of RGB-D Camera
Authors: Liang Bing , Wang Guosheng
Published: September 2020

RGB-D camera can not only collect colour pictures, but also collect the distance between each pixel and the camera, so it can be used as a sensor of visual slam to solve the problem of precise positioning without GPS signal, reduce the calculation of camera pose estimation algorithm, and improve the real-time and accuracy of camera pose algorithm. Based on the vision slam theory of RGB-D camera, three methods of pose estimation based on feature points are implemented, which are the pole constraint method, the PnP method and the ICP method. Based on the experimental results, the polar constraint method, the PnP method and the ICP method are compared and analysed from two aspects of accuracy and real-time, and the advantages and disadvantages of each method are summed up, which is helpful for the selection of algorithm in the camera positioning process under different conditions to optimize the positioning effect.
A Certificate Storage Method for Confirming Video Copyright and Tracing the Source Based on Alliance Chain
Authors: Yang Yang , Yu Dingguo
Published: September 2020

In recent years, with the development and update of business models and emerging technologies, there have been more and more forms of piracy and infringement of online video works. It is difficult for the department with copyright to confirm the copyright of the work and trace the source of piracy. Alliance blockchain technology can be partially decentralized, highly controllable, and data is not public by default, providing new ideas and methods for solving the above problems. The thesis proposes a multi-factor confirmation and traceability depositing method (MCTA) for video works of alliance blockchain. First, the alliance member nodes store the signature information of the person in charge in each step in the private chain during video production; second, the smart contract pre-processes the source video, implants watermarks and calculates video fingerprints, and creates a video ID for each video; Finally, double-factor authentication for the suspected infringement of pirated video to confirm the right. Carry on simulation experiment through Truffle+MiniNet+SimBlock. The results show that the method proposed in the thesis is effective and feasible for depositing video works.
Research on Application of 5G eMTC+HPLC in Intelligent Orderly Charging
Authors: Xiao Deyong , Zhang Xiaohui , Tang Xiaoke , Li Zheng , Luo Dan
Published: September 2020

In this paper, aiming at conventional charging of electric vehicles, it is impossible to form intelligent and efficient energy management, and it is impossible to participate in peak and valley regulation of power grid, so a new intelligent orderly charging network is studied and constructed. HPLC has been widely used as a mature technology for the collection of household electricity information. It has the characteristics of simple wiring and high communication reliability. 5G eMTC technology, with low power consumption, appropriate rate, deeper coverage, lower cost and high security slicing communication technology, that can provide services for ubiquitous electric Internet of things, such as orderly charging. According to the advantages of 5G eMTC and HPLC technology, this paper proposes the strategy of 5G eMTC + HPLC to build a new intelligent orderly communication network, and proposes a solution when the orderly charging network coexists with the existing HPLC information acquisition and communication system. Next, this paper studies the main functional modules of 5G eMTC + HPLC orderly charging system and the orderly charging business process.
An Electricity Cross-Chain Platform Based on Sidechain Relay
Authors: Wang Hongkai , He Dong , Wang Xiaoyi , Xu Caichao , Qiu Weiwei , Yao Yiyang , Wang Qiang
Published: September 2020

Based on sidechain relay strategy, a cross-chain platform BitXhub-PI is implemented to realize the interoperability between the heterogeneous blockchains for electric power industry. The platform is composed of three roles: relay chain, application chain and cross-chain pier, and it has three core functional characteristics of universal cross-chain transmission protocol, heterogeneous transaction verification engine, and multi-level routing to ensure the security, flexibility and reliability of cross-chain transactions of electricity business. The platform provides a unified cross-chain contract template for homogeneous and heterogeneous electricity application chains, and the relay chain contains a dynamically upgradeable verification engine. The experiments show that the platform guarantees asynchronous distributed electricity business transactions between heterogeneous blockchains, achieving high performance with high throughput, low latency, high scalability, and low overhead.
Research Design of Intelligent Toothbrush for Preschool Children Based on KANO Model
Authors: Xue Ying , Fang Xuelian
Published: September 2020

In order to effectively obtain the user demands of children’s intelligent toothbrush and improve the use experience of children’s products. This paper explores user demands from the perspective of both parents and children. According to the Kano model, the user demands of both parents and children are analyzed, the nature of different demands is clarified, and the importance of various demands is calculated, so that the design can be targeted from the demands. Through this demand analysis method, we summarized the most important demands of children’s intelligent toothbrush, starting from what we can achieve the most satisfactory effect. In this paper, Kano model is used to analyze the demands of parents and children. Taking children’s toothbrush as a design case, the feasibility and validity of Kano model for children’s intelligent toothbrush are verified, and the user demands can be grasped more accurately.
Climate, snowmelt dynamics and atmospheric deposition interact to control dissolved organic carbon export from a northern forest stream over 26 years
Authors: Meingast Karl M , Kane Evan S , Coble Ashley A , Marcarelli Amy M , Toczydlowski Dave
Published: September 2020

Increasing concentrations of dissolved organic carbon (DOC) have been identified in many freshwater systems over the last three decades. Studies have generally nominated atmospheric deposition as the key driver of this trend, with changes in climatic factors also contributing. However, there is still much uncertainty concerning net effects of these drivers on DOC concentrations and export dynamics. Changes in climate and climate mediated snowfall dynamics in northern latitudes have not been widely considered as causal factors of changes in long-term DOC trends, despite their disproportionate role in annual DOC export. We leveraged long-term datasets (1988–2013) from a first-order forested tributary of Lake Superior to understand causal factors of changes in DOC concentrations and exports from the watershed, by simultaneously evaluating atmospheric deposition, temperature, snowmelt timing, and runoff. We observed increases in DOC concentrations of approximately 0.14 mg C l−1 yr−1 (mean = 8.12 mg C l−1) that were related with declines in sulfate deposition (0.03 mg

SO

4

2
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l−1 yr−1). Path analysis revealed that DOC exports were driven by runoff related to snowmelt, with peak snow water equivalences generally being lower and less variable in the 21st century, compared with the 1980s and 1990s. Mean temperatures were negatively related (direct effects) to maximum snow water equivalences (−0.71), and in turn had negative effects on DOC concentrations (−0.58), the timing of maximum discharge (−0.89) and DOC exports (indirect effect, −0.41). Based on these trends, any future changes in climate that lessen the dominance of snowmelt on annual runoff dynamics—including an earlier peak discharge—would decrease annual DOC export in snowmelt dominated systems. Together, these findings further illustrate complex interactions between climate and atmospheric deposition in carbon cycle processes, and highlight the importance of long-term monitoring efforts for understanding the consequences of a changing climate.
The effects of different types of vegetation restoration on wind erosion prevention: a case study in Yanchi
Authors: Luo Qi , Zhen Lin , Xiao Yu , Wang Haiyan
Published: September 2020

Improving wind erosion prevention in the key ecological zones of sand fixation are closely linked to human welfare in China and Northern Eurasia. In this research, we studied the sand transport rate (STT), soil water content (SWC), and retention rate of the wind erosion prevention services (RR) in five experimental zones in Yanchi Country, including bare sandy land (BL), and four restoration zones with different types of vegetation restoration approaches, including artificial restored grassland with low-coverage (AGL), artificial restored grassland with high-coverage (AGH), artificial shrub land (AS), and naturally restored grassland (NG). The results showed that: (1) From 2006 to 2018, the STTs of the four restoration zones were lower than those of BL, and those of the AS were much lower than those of AGL, AGH, and NG; (2) in the rainy season, the SWCs of AS, NG, AGH, AGL, and BL were 3.01%, 2.80%, 2.79%, 2.68%, and 2.41% respectively. In the dry season, the SWCs of NG, BL, AGH, AHL, and AS were 2.86%, 2.93%, 3.00%, 3.08%, and 3.20%, respectively. The differences in the SWCs between the two seasons of BL were the largest (0.52%), while those of NG were the lowest (0.06%); (3) the annual average RRs in AS, AGH, NG, and AGL were 74.41%, 69.41%, 69.28%, and 61.64%, respectively, while the annual change of the RR in the NG was the smallest. This study reveals the effects of different types of vegetation restoration on wind erosion prevention in Yanchi country, thereby providing a scientific basis for policymakers to engage in effective vegetation restoration and formulate ecological protection policies.
Urbanization drives convergence in soil profile texture and carbon content
Authors: Herrmann Dustin L , Schifman Laura A , Shuster William D
Published: September 2020

Urban development has driven extensive modification of the global landscape. This shift in land use and land cover alters ecological functioning, and thereby affects sustainable management agendas. Urbanization fundamentally reshapes the soils that underlay landscapes, and throughout the soil profile, extends impacts of urbanization far below the landscape surface. The impacts of urbanization on deeper soils that are beyond the reach of regular land management are largely unknown, and validation of general theories of convergent ecosystem properties are thwarted by a dearth of both level of measurement effort and the substantial heterogeneity in soils and urban landscapes. Here, we examined two soil properties with strong links to ecological functioning—carbon and mineral-fraction particle size—measured in urban soils, and compared them to their pre-urbanization conditions across a continental gradient encompassing global soil diversity. We hypothesized that urbanization drove convergence of soils properties from heterogeneous pre-urban conditions towards homogeneous urban conditions. Based on our observations, we confirm the hypothesis. Both soil carbon and particle size converged toward an intermediate value in the full data distribution, from pre-urban to urban conditions. These outcomes in urban soils were observed to uniformly be fine textured soils with overall lower carbon content. Although these properties are desirable for supporting urban infrastructure (e.g. buildings, pipes), they constrain the potential to render ecosystem services. Since soil profile texture and carbon content were convergent and observed across 11 cities, we suggest that these property profiles can be used as a universal urban soil profile to: 1) provide a clear prediction for how urbanization will shift soil properties from pre-urban conditions, 2) facilitate the adoption of commonly-accepted soil profiles for process models, and 3) offer a reference point to test against urban management strategies and how they impact soil resources.
The Ising correlation C(M, N) for ν = −k
Authors: Boukraa S , Maillard J-M , McCoy B M
Published: September 2020

We present Painlevé VI sigma form equations for the general Ising low and high temperature two-point correlation functions C(M, N) with M ⩽ N in the special case ν = −k where ν = sinh 2E

h
/k

B

T/sinh 2E

v
/k

B

T. More specifically four different non-linear ODEs depending explicitly on the two integers M and N emerge: these four non-linear ODEs correspond to distinguish respectively low and high temperature, together with M + N even or odd. These four different non-linear ODEs are also valid for M ⩾ N when ν = −1/k. For the low-temperature row correlation functions C(0, N) with N odd, we exhibit again for this selected ν = −k condition, a remarkable phenomenon of a Painlevé VI sigma function being the sum of four Painlevé VI sigma functions having the same Okamoto parameters. We show in this ν = −k case for T < T
c and also T > T
c, that C(M, N) with M ⩽ N is given as an N × N Toeplitz determinant.
InGaAs x-ray photodiode for spectroscopy
Authors: Whitaker M D C , Lioliou G , Krysa A B , Barnett A M
Published: September 2020

A prototype In0.53Ga0.47As p+-i-n+ x-ray photodiode, fabricated from material grown by metalorganic vapour phase epitaxy, was investigated as a novel detector of x-rays. The detector was connected to a custom low-noise charge sensitive preamplifier and standard readout electronics to produce an x-ray spectrometer. The detector and preamplifier were operated at a temperature of 233 K (−40 °C). An energy resolution of 1.18 keV ± 0.06 keV Full Width at Half Maximum at 5.9 keV was achieved. This is the first time InGaAs (GaInAs) has been shown to be capable of spectroscopic photon counting x-ray detection.
Study on the mechanism of forming silver nanoparticles on micron-scale flake silver powder
Authors: Tang Lin , Gan Guoyou , Yu Xianglei , Liu Chengbin , Cheng Junhua
Published: September 2020

Due to the high conductivity and stability of silver, silver ink has been widely used in the field of printed electronics. However, since mechanical strain would cause the contact between key particles to be broken. Recently, higher requirements have been put on the bending resistance of silver paste. In this experiment, by preparing Ag NPs: Ag Flakes composite materials of 20:80 and 30:70 respectively, a new method for preparing stable modified flake silver powder is proposed, and the attachment and growth methods of Ag NPs reduced on micron flake silver powder is discussed. Flake silver powder, dispersant and reducing agent are added to the silver-ammonia complex, and the nano-silver particles are reduced on the flake silver powder by controlling the reaction conditions. When Ag+: Ag Flakes in the solution is 30:70, there is a clear interface between the silver particles and the silver flakes, and the size distribution range is between 10 and 100 nm; when Ag+: Ag Flakes is 20:80, the distance between the nano-silver particles and the silver plate crystal plane is about 0.222 nm and 0.260 nm, these spacings represent the (1–12) and (004) planes of Ag, respectively. The reduced silver particles grow on the surface of the silver sheet, the size is about 5 ∼ 60 nm, and form a sheet-point combination of shaped silver powder, which can be used to make conductive silver paste with cost and performance competitiveness. The reaction can be completed at room temperature (5 ∼ 25 °C) and atmospheric pressure (80 ∼ 100 kPa), the operation is simple, the reaction time is short, and it has a positive effect on the commercial production of printable highly conductive silver paste.
Effect of background fluctuation on velocity diagnostics by Mach probe
Authors: WEI Yunxiao , GAO Zhe
Published: September 2020

The effect of background fluctuation on velocity diagnostics is discussed and studied. The kinetic theory of Mach probe (MP) and the theory of BGK mode are combined to evaluate how the measurement of MP is affected by electrostatics fluctuation. It is found that the quantity of speed by the MP model is closer to the effective velocity in the picture of momentum flux rather than the real mean velocity, while, with high fluctuation, the fitting parameter of MP’s exponential formula should be corrected.
Cigarette Smoking and Minority Stress Across Age Cohorts in a National Sample of Sexual Minorities: Results From the Generations Study
Authors: Gordon Allegra R , Fish Jessica N , Kiekens Wouter J , Lightfoot Marguerita , Frost David M , Russell Stephen T
Published: September 2020

Background

Sexual minority populations in the United States have persistently higher rates of cigarette use than heterosexuals, partially driven by exposure to minority stressors (e.g., discrimination and victimization). Little is known about cigarette use across cohorts of sexual minority adults who came of age in distinctly different sociopolitical environments.

Purpose

To examine cigarette use and minority stressors across three age cohorts of U.S. sexual minority adults.

Methods

We used data from the Generations Study, a nationally representative sample (N = 1,500) of White, Black, and Latino/a sexual minority adults in three age cohorts (younger: 18–25 years; middle: 34–41 years; and older: 52–59 years). Survey data were collected from March 2016 to March 2017. We used sex-stratified logistic regression models to estimate adjusted odds ratios (aORs) and 95% confidence intervals (CIs) for associations between age cohort, minority stressors (discrimination and victimization), and two indicators of cigarette smoking (lifetime use and current use).

Results

Prevalence of current cigarette use in each age cohort was high (younger: 20%; middle: 33%; and older: 29%). Relative to the younger cohort, men and women in the middle- and older-age cohorts had significantly higher odds of lifetime and current smoking (e.g., men, current, aOR [95% CI]: middle = 2.47 [1.34, 4.52], older = 2.85 [1.66, 4.93]). Minority stressors were independently associated with higher odds of current smoking; when victimization was included, the magnitude of the association between age cohort and current smoking was diminished but remained significant.

Conclusions

Smoking cessation interventions must consider the role of minority stress and the unique needs of sexual minority people across the life course.
Brazil and the multipolar world
Authors: Pereira Anthony W.
Published: September 2020

‘Brazil and the multipolar world’ examines Brazil’s foreign policy tradition. Brazil has a strong diplomatic tradition that emphasizes moderation, the peaceful resolution of conflicts, and Brazil’s ability to seek consensus by maintaining dialogue with almost all other states. Indeed, Brazil usually positions itself in favour of moderate reform of the institutions of global governance and as a gentle critic of the inequalities and injustices of the international system. The chapter then describes Brazilian contributions to global politics in areas such as international development, the environment, security, and global health. It also looks at the rupture promoted by the Bolsonaro administration in 2019.