bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cross-Media Retrieval Based on Canonical Correlation Analysisand Decision Tree
Authors: Duan Hongye , Wang Meng , Zou Peiqing 
Published: November 2020

Abstract
The retrieval of approximate data from massive multimedia data is the key of computer science research. With the explosive growth of data scale, data retrieval needs to face the overlapping massive multimodal data called “dimension disaster”, and the traditional retrieval methods appeared to be inefficient. The cross-media retrieval with canonical correlation analysis (CCA) is a kind of way to map different media features to the largest correlation isomorphism subspaceand then compare the similarity between cross-media data in this subspace. However CCA is a linear model and it is difficult to map the lower data to the higher semantic. This paper proposed a cross-media retrieval method based on CCA and Decision Tree to solve the problem. CCA was uesd to depict the correlation between image and text feature, Decision Tree was uesd toapproach to feedback and repeatedly adjust the correlation. Experiments on the Wikipedia text-image datasetsverified that the Tree-CM model can mine the complex correlation between cross-media data and has better performance than other state-of-the-art models.
QTPC: A Q-Learning Transmission Power Control Mechanism for Edge-Cloud Wireless Body Area Networks
Authors: Su Haoru , Yuan Xiaoming , Sun Enchang , Si Pengbo , Chen Huamin 
Published: November 2020

Abstract
Wireless body area networks collect biological signals from human body and sensors connect wirelessly for various nonmedical and medical applications. Energy efficiency is one of the most essential problems in wireless body area networks since the limited battery capacity. In this paper, a Q-learning transmission power control (QTPC) mechanism for edge-cloud wireless body area networks is proposed. Simulation results show that the proposed scheme improves the network performance in the metrics of energy efficiency and system throughput.
Individual identification of communication radiation sources based on Inception and LSTM network
Authors: Chen Yiming , Zhu Lei , Yu Lu , Yao Yanyan 
Published: November 2020

Abstract
The difference in fingerprint characteristics of communication radiation sources is small, and it is difficult to extract characteristics for recognition using traditional machine learning algorithms, so deep learning methods are considered. LSTM is an improved recurrent neural network that is good at processing long-term sequence data. The Inception module can obtain features of different scales on the same layer. This article combines the inception structure and the LSTM network to identify 5 USRPs. The data set used in the experiment was collected by USRP and Lab VIEW. Two sets of data were collected based on the obstacles between the sending end and the receiving end, which are closer to the real environment than the data set that only uses software simulation. Compared with other network structures, this method has a higher recognition rate.
Improved whale optimization algorithm based on the tent chaotic mapping and nonlinear convergence factor
Authors: Dong Shuxian , Bu Chunguang , Wang Yongliang 
Published: November 2020

Abstract
To overcome the shortcomings of whale optimization algorithm (WOA) such as the slow convergence rate, and low convergence accuracy, and being easy to fall into the local optimum, an improved whale optimization algorithm based on the tent chaotic mapping and nonlinear convergence factor (TNWOA)is proposed. Firstly, In this algorithm, tent chaotic mapping, which enhances the diversity of the initialization population, is introduced into the initialization of population, therefore, the search space can be searched more thoroughly; Secondly, trigonometric function and the beta distribution are introduced in the convergence factor ‘a’, which balance the global search ability as well as local optimization ability and speed up the convergence speed of the algorithm. Simulation experiments on the four kinds of common test functions on CEC2017 show that under the same experimental conditions, the improved whale optimization algorithm improves the solution accuracy and convergence speed significantly, and its performance is obviously better than other smart optimization algorithms and other improved WOA algorithms.
Discussion on the application of Lagrange mean value theorem
Authors: Jiang Yinshan 
Published: November 2020

Abstract
The Lagrange mean value theorem has been widely used in the following aspects;
( 1 )Prove equation; ( 2 )Proof inequality; ( 3 ) Study the properties of derivatives and functions;
(4) Prove the conclusion of the mean value theorem; (5) Determine the existence and uniqueness of the roots of the equation; (6 ) Use the mean value theorem to find the limit.
Research on Top-k Association Rules Mining Algorithm Based on Clustering
Authors: Wu Lei , Wang Zhe 
Published: November 2020

Abstract
Until now, the association rule mining algorithm is still one of the core issues in the field of big data research. At present, there are many research related to association rule mining algorithms, mainly focusing on how to find frequent item sets and how to tailor rules, and based on this direction, there have been many classic algorithms, such as Apriori and FP-growth algorithms. However, most of the above algorithms process and analyze the entire data set, so that although related algorithms can be used to obtain the results, the results are not meticulous. To solve this problem, this paper proposes an algorithm, which first uses the k-means algorithm to perform cluster analysis on the data set to generate a specific number of clusters. Then, in different clusters, the association rules in each cluster are found by the improved Top-k algorithm combined with the correlation coefficient. By integrating clustering and the improved Top-k algorithm, the data set can be analyzed directionally to improve the accuracy and efficiency of the whole algorithm. And the final experiment shows that compared with the original algorithm, the running time is shortened by 14%.
Research on the oriented teaching method of computer network foundation course
Authors: Gan Weimin , Li Yuli 
Published: November 2020

Abstract
In recent development of modern education reform, it is imperative to accelerate high-level education structure adjustment, and the trend from local undergraduate universities transformed to the ones which accord application and technology -type development being the general consensus in the industry. These universities took the demanding of application technology as orientation,definited the subject objection and optimized the teaching method, focused on the combination of theory & practice teaching methods.This article is mainly about the computer network technology application application oriented design concept in teaching.Convey useful simplification of theory to the students and they can learn in order to practise.
Improved PULSE: (Photo Upsampling via Latent Space Exploration of Generative Models) Using Anti-spoofing System
Authors: Wang Yubo , Wang Aaron , Chen Weilan , Jiang Yuting , Wang Shaoan , Jiang Yuzhe , Wang Yuzheng 
Published: November 2020

Abstract
Image super-resolution is typically explained as converting a low-resolution (LR) image into a high resolution (HR) output. However, previous approaches could be blurry and unrealistic, especially for regions with many details. This paper took advantage of Latent Space Exploration from PULSE and a facial liveliness detection algorithm to receive a more accurate and rational outcome. (Related code can be found on https://github.com/cisgroupb/PULSE with Anti Spoofing-Detection)
Semantic Segmentation of Urban Street Scene Based on Convolutional Neural Network
Authors: Li Tingting , Jiang Chunshan , Bian Zhenqi , Wang Mingchang , Niu Xuefeng 
Published: November 2020

Abstract
Artificial Intelligence (AI) has developed rapidly in recent years, making computer vision a hot spot in recent years. As the core technology of computer vision, semantic segmentation has important theoretical significance and practical application value in the field of computer vision. The research purpose of this technique is to classify each pixel in the image and correctly predict the object category of the pixel, that is, to realize the transformation from pixel to object category. Traditional semantic segmentation algorithms cannot meet the requirements of complex image segmentation, and the requirements of complex image segmentation mechanism are also increasing. Therefore, it is of great significance and application prospect to study semantic segmentation algorithm of image. This paper first introduces the current research status in the field of semantic segmentation at home and abroad, tests and analyzes the CamVid data set with three mainstream algorithms, and finally forecasts the semantic segmentation of images.
Research on the Application of Artificial Intelligence Natural Language Processing Technology in Japanese Teaching
Authors: Jing Yao 
Published: November 2020

Abstract
In the context of artificial intelligence, natural language processing technology has matured and it is a key technology for foreign language teaching and research direction. The application of artificial intelligence natural language processing technology to Japanese teaching is essentially a language processing technology that combines computer science and artificial intelligence. Based on this, this article will analyze the application of artificial intelligence natural language processing technology in Japanese teaching, hoping to have a certain reference significance for Japanese teachers’ educational technology research.
Prediction Method of Enterprise Return on Net Assets Based on Improved Random Forest Algorithm
Authors: Cai Yongsong , Yin Qi , Su Qian , Huang Xinyu , Zhang Yin , Liu Ting 
Published: November 2020

Abstract
In order to accurately predict the change trend of enterprise assets, this paper proposes a prediction method of enterprise return on net assets based on improved random forest algorithm. Firstly, this paper analyzes the research background and significance of the enterprise net income rate prediction, and on this basis, it considers to use the random forest algorithm to achieve the prediction. In view of the shortcomings of the algorithm, the paper introduces the simulated annealing algorithm to improve the random forest algorithm and optimizes the prediction performance of the algorithm in the direction of feature selection, parameter optimization and weight setting, finally establishes the prediction model of enterprise return on net assets. In this paper, the proposed algorithm is compared with other algorithms and results show that the method proposed in this paper has a good prediction effect on the enterprise return on net assets, which is helpful for the capital market to evaluate the asset value and profitability of enterprises.
Analysis of the Impact of Big Data Technology on News Ecology
Authors: Yang Zhang 
Published: November 2020

Abstract
With the rapid rise of big data technology, big data has become an important resource of news media. Big data constantly changes the production of news and the operation of media companies, leading to profound changes in the news ecology. Based on the theory of media technology, this paper studies the problems of news production, news dissemination, news occupation and the evolution of news sources, and analyzes the impact of big data technology on news media, news content, news environment and other elements of news ecology.
Coping strategies of financial work in the era of artificial intelligence
Authors: Chao Fu 
Published: November 2020

Abstract
The emergence of artificial intelligence has accelerated the transformation of financial personnel’s work function from bookkeeping accounting type to operation and management type. Financial personnel have ushered in important development opportunities, but also will face more severe challenges. Through the research on the financial work reform caused by artificial intelligence and the coping strategies of financial personnel, this paper believes that financial personnel should clearly understand the development trend of artificial intelligence, actively meet the challenges, comprehensively improve the ability of financial digitization and lean through learning, establish macro thinking, become the leader of industry and finance integration, and realize their own career transformation and upgrading.
Research on Blended Learning Implementation
Authors: Chuanzhen Song 
Published: November 2020

Abstract
With the advancement of information technology and the gradual advancement of “internet+”, blended learning has become a hot topic in current higher education discussions and research. This paper analyzes the connotation of blended learning and the shortcomings of traditional teaching, it is believed that traditional classroom teaching mode and pure online teaching mode can no longer meet the needs of talents training in higher education institutions in the era of “internet+”. Blended learning is the direction of teaching reform in colleges and universities, and it is an important practice trend of higher education informatization. The implementation of blended learning is not simply a combination of online teaching and classroom teaching, but a systematic project, which needs to be determined from the teaching objectives, teaching link design, online platform construction, classroom teaching guidance, teaching effect evaluation, etc. Starting from the pre-class knowledge learning, in-depth discussion in the class, after-class consolidation and expansion, curriculum assessment and evaluation, teaching effect reflection and other links, we truly achieve the result of “teaching is methodical and learning is effective” to help students learn independently and efficiently to improve teaching effectiveness and students’ practical innovation ability.
Information Security and Adoptable Solutions in the Implementation of Industry 4.0 Strategy for the Fourth-generation Industrial Revolution
Authors: Cheng Xiaolei , Zhang Pinghua 
Published: November 2020

Abstract
Industry 4.0 is recognized as the fourth-generation industrial revolution, which can drive the development of the world’s smart manufacturing industry. The information security in the implementation of Industry 4.0 strategy was analyzed in this article. The specific measures to ensure the information security of Industry 4.0 were proposed from the perspectives of industrial control system security strategy, security measures, security awareness, data security protection, data security responsibility, and encryption technology. Furthermore, the distributed control system and IT network security communication platform construction are applied to solve the information security problem of Industry 4.0. The adoptable solutions will provide an important reference to maintain the information security of Industry 4.0.
Study of nanomechanical properties of thin films using in-situ “Push-to-Pull” method in the column of transmission electron microscope
Authors: Kiryukhantsev-Korneev Ph V , Loginov P A , Orekhov A S , Levashov E A 
Published: November 2020

Abstract
The purpose of this study was to develop a method for determining the tensile strength of ion-plasma coatings during their nanodeformation in the column of a transmission electron microscope. The advanced oxidation-resistant coating in the Mo-Zr-Si-B system was selected as the object for mechanical testing. Coatings were deposited on alumina substrates by magnetron sputtering with hetero-phase cathode in system MoSi2-MoB-ZrB2 in argon environment. Coating’s characterization and testing were performed using XRD, SEM, EDS, GDOES, TEM, and nanoindentation. Nanomechanical study in TEM column was conducted in binding scheme using Push-to-Pull device and Picoindenter module on lamella prepared by FIB. Problems related to nanomechanical measurements and interpretation of the obtained dependences are discussed. Recommendations for the method of lamella preparing and parameters for testing were developed.
The strength increase by nano-scale particles precipitated during magnesium solid solution decomposition in magnesium alloys with the rare-earth metals of the yttrium group
Authors: Rokhlin L L , Dobatkina T V , Tabachkova N Yu , Tarytina I E , Lukyanova E A 
Published: November 2020

Abstract
Magnesium-base alloys attract a great attention as light structural materials, where economy of weight is of great importance. According to the last investigations, the highest strength properties of these alloys, can be obtained, when they contain some of the rare-earth metals. All of them belong to the yttrium group. Existence of the rare-earth metals in magnesium alloys enable to form in their structures small hard particles, which increase significantly strength of the alloys. The hard particles appear after the special heat treatments and should have the certain measurements and amounts. In this article the main results of some investigations are described, where the best conditions for the heat treatments of the magnesium alloys with high strength were established. The highest strength in the alloys was observed, when the hard particles were nano-scale in them with certain disposition in the structure.
Flutter suppression of wind turbine blade based on nonlinear block backstepping control
Authors: Yi Chenghong , Wang Yingbo , Sun Haipeng , Sun Changle , Zhang Xiaolin , Li Shanyao , Liu Tingrui 
Published: November 2020

Abstract
Aiming at solving the nonlinear flutter problem of aeroelastic system of wind turbine blades, a controller combing block backstepping control and variable pitch motion was designed. Based on the typical blade-section model of the spring-mass-damper and the second-order model of the pitch actuator, nonlinear aeroelastic equation of the system under steady aerodynamic was given. Considering the multivariable, strong coupling factors and the unitary pitch control of the wind turbine blade aeroelastic system, a state space equation for a single-input/multiple-output nonlinear model was deduced. Based on the principle of block control, a nonlinear system with block control standard was obtained, which was composed of two subsystems. In order to suppress blade flutter and protect the blade, backstepping control was used to control blade pitch motion. The nonlinear block backstepping controller was designed by constructing Lyapunov function, and time response which can track the dynamic error of system was demonstrated. The simulation results showed that the designed controller can converge the divergent chattering trend to zero, and make the system globally stable.
Topological Optimization Design of the Gantry Steel Beam of the Simplified Freight Ropeway
Authors: Yi Wang , Enze Cai , Gang Li , Wenchuan Jing , Chaoming He 
Published: November 2020

Abstract
Simplified freight ropeway are mostly built on high mountains and ridges inaccessible by roads, where the gantry of the ropeway needs to be handled manually. The traditional gantry with a single-piece weight of 63.9kg is hard to be handled manually. Based on the existing gantry structure, the single-piece lightest combined gantry construction is analyzed, and finite element analysis is conducted in this paper. After analyzing and calculating the steel beam of the combined gantry, it is determined that the weight of a single steel pipe and that of the steel bushing are 17.7kg and 30.5kg, respectively, which can meet the requirement in manual handling operation in steep terrain. On the premise of considering the cost and weight of the gantry, the H-shaped steel of different materials is determined to be selected for strength and stiffness analysis, and the H-shaped steel beam of Q345 material of 200mm×100mm×5.5mm×8mm is selected as the gantry for topology optimization design and finite element topology iterative calculation in this paper. The stress is distributed uniformly after optimization, and the mass of the steel beam of the H-shaped gantry is reduced from 63.9kg to 49.1kg, which meets the maximum single-lift load of 50kg for an adult man specified in GB12330-90 “the Limit on Carrying-load for Physical Work”.
Research on the problems and improvement measures of Beijing public rental housing households
Authors: Liu Hongjie , Ma Jing , Su Yu 
Published: November 2020

Abstract
Through the investigation of some public rental housing projects in Beijing, the family structure, rent, income and satisfaction of the public rental housing households can be revealed. Through the statistical analysis, we found the following problems: some public rental housing family structure does not match with the type of occupancy; the rental income ratio of part of the public rental housing is unreasonable; some of the households has low satisfaction; the income of part of the public rental housing exceeds the prescribed upper limit. In view of the above problems, this paper proposes solutions: strengthen the planning and design of public rental housing; improve the rent subsidy mode of public rental housing; strengthen the construction of supporting facilities for public rental housing; promote the relevant legislative work of public rental housing.
Attenuation Characteristics of Truck-induced Ground Vibrations Due to Different Truck Weights and Speeds
Authors: Xu Zhaogang , Lou Yu , Chen Liu 
Published: November 2020

Abstract
Knowledge of the attenuation characteristics of truck-induced ground vibrations has gained importance for micro-vibration mitigation of high-tech facilities. This study conducted an in-situ experimental study on the attenuation characteristics of truck-induced ground vibrations. The ground vibrations were generated by the passage of a truck on a low-cost road with different weights and speeds. Eight low frequency, one component, 941B vibration sensors were fastened on the ground surface to record the vertical velocity time histories of ground vibrations at eight measurement points with different distances. The vibration level was evaluated in terms of the vertical maximum displacement obtained by integrating the measured velocity time histories. The vibration level represented by the vertical maximum displacement decayed monotonically but nonlinearly with distance from the road. Ground vibrations at the measurement points that were close to the road decayed more rapidly than that at the measurement points far away. In general, the maximum displacement of ground vibrations induced by the 30-ton truck at a measurement point was smaller than that of ground vibrations induced by the 18-ton truck with the same speed.
Activist Mothers in Need of Public Housing and the Welfare Services: Negotiating Othering, Mothering and Resistance
Authors: Shwartz-Ziv Tamar , Blit-Cohen Edith , Ajzenstadt Mimi 
Published: November 2020

AbstractRecent decades have witnessed an increasing trend towards the development of critical approaches to the study of poverty, which call upon social workers to perceive people living in poverty as active agents who resist their condition. Relatively few studies, however, have examined how women living in poverty, who embody collective-political agency, experience the encounter with the welfare services, and how their manner of organisation is shaped by this encounter. This study examines this issue based on fifteen semi-structured interviews with mothers in need of public housing in Israel who are activists in protest groups against the public housing policy. The findings reveal that the encounter with welfare services generated feelings of othering due to the meanings attributed to their homelessness and to the nature of their mothering. Conversely, activism was perceived as a practice for challenging, redesigning and reducing power relations with the welfare agencies. The findings also show that the encounter shaped the participants’ manners of activist mobilisation. The study contributes to the research literature on social work with women who live in poverty, by highlighting the important role of women’s activism within the encounter.