bluuebunny/crossref_metadata_2025_split huggingface dataset:
Attribute-Based Identity Authentication Scheme Based on Linear Codes
Authors: Zhang Zhiqiang , Cao Suzhen , Han Longbo , Liu Xueyan 
Published: September 2020

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

AbstractCloud 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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

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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

Abstract
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.