bluuebunny/crossref_metadata_2025_split huggingface dataset:
Correlation analysis between brain network attributes and skin electrical signals in patients with mild cognitive impairment
Authors: Yu Xiaoping , Zhu Bing , Guo Chunjie , Yang Yu , Li Qi 
Published: March 2021

Abstract
The aim of the study was to explore the correlation between brain network attributes and skin electrical signals in patients with mild cognitive impairment (MCI) for early diagnosis. Neuropsychological assessment for subjects and the resting-state fMRI data were collected. The brain network was constructed based on the resting-state fMRI data, and its attributes were analyzed by graph theory. Then wavelet transform was used to extract the features of skin electrical signal data. Finally, Pearson correlation method was used to calculate the correlation between brain network attributes and skin electrical signal. The results showed that brain network attributes of aLp, aλ, assortativity and synchronization in MCI were higher than those in normal control, while the hierarchical of MCI was lower than that in normal control. There were significant differences between the two groups of skin electrical signals in mean value, maximum value and minimum value. Moreover, the correlation results showed that neuropsychological assessment were correlated not only with brain network attributes but also with skin electrical signals, and there was a correlation between skin electrical signals and brain network attributes. Using skin electrical signals can provide a new early standard to assist in the diagnosis of MCI, with low cost and easy acquisition.
Test and research on suppressing fire of lithium-ion battery with water mist containing additive
Authors: Zhang Yuhang , Zhu Shunbing , Zhuang Weiqiang 
Published: March 2021

Abstract
In order to improve the fire extinguishing effect on lithium-ion battery fires, the paper experimented with compound solution of sodium dodecylbenzenesulfonate-dodecanol-sodium carbonate at a ratio of 3:2:2, polyfiouroalkyll betaine-alkylglycoside-potassium carbonate at a ratio of 2: 3: 3 and monoalkyl ether phosphate potassium-fatty acid ester polyoxyethylene etherurea at a ratio of 3:2: 3. The fire of the lithium-ion battery was extinguished with water mist containing additive compound solution by building lithium-ion battery fire extinguishing experimental platform. The experiment selected four different concentrations of 0.5%, 1%, 1.5%, and 2%. The results showed that the polyfluoroalkyl betaine-alkyl glycoside-potassium carbonate compound solution had better fire extinguishing effect in the early stage of thermal runaway, and the battery did not reignite. The sodium dodecylbenzene sul-fonate-dodecanol-sodium carbonate compound solution took the least time to reduce the battery temperature to below 200 °C. In the later period, the sodium dodecylbenzenesul-fonate-dodecanol-sodium carbonate compound solution has the greatest advantage in cooling rate. In the gas absorption test, the sodium dodecylbenzenesulfonate-dodecanoll-sodium carbonate compound solution has the best absorption effect on methane, and the polyfluoroalkyl betaine-alkyl glycoside-potassium carbonate compound solution releases CO. The concentration of the compound has a more obvious drop than the other two compound solutions.
Automatic splicing of Chinese single-sided shreds based on character feature and typesetting characteristics
Authors: Yang Hongrong , Wang Yunqiong 
Published: March 2021

Abstract
In this paper we proposed an automatic splicing algorithm for regular cross-cut single-sided shreds of pure Chinese document, which was based on the characteristics of character and typesetting. The algorithm began with extracting the characteristics including character width, character height, line height and line spacing, after which the shreds meeting the typesetting requirement were spliced according to the edge similarity. Afterwards, the horizontal projection vectors of the shreds were corrected and the shreds were clustered by row according to horizontal projection similarity. A greedy algorithm with rejection strategy was then used to complete the intra-cluster horizontal splicing of shreds based on edge similarity. The experiment results revealed that the algorithm proposed in this paper had the characteristics of both high splicing speed and high accuracy.
Self-Attention on Sentence Snippets Incongruity for Humor Assessment
Authors: Cao Di 
Published: March 2021

Abstract
Researches on humor identification can advocate a better understanding of human language. Many studies focused on the categorical classification problem of humor, which is less sensible to the intermediate level funny content. Previous work captured the incongruity between words but not sentence snippets. In this paper, a novel method is proposed to exploit snippet-level incongruity features from different aspects, combined with the sentence snippets representations to predict funniness scores. The experiment result shows that this model outperforms most of the competitive methods.
Geometric Artifacts Correction for Computed Tomography Exploiting A Generative Adversarial Network
Authors: Zhu Mingwan , Han Yu , Yang Shuangzhan , Zhu Linlin , Xi Xiaoqi , Li Lei , Yan Bin 
Published: March 2021

Abstract
Geometrical accuracy of an X-ray Computed Tomography (CT) system is crucial to achieve high quality tomographic reconstructions. Methods to correct the resulting geometric artifacts have been comprehensively described in the past few years. Deep convolution neural network is increasingly used in CT imaging, which has a great potential in image feature learning and processing tasks. In this work, a geometric artifact correction method exploiting generative adversarial networks (GAN) is developed. The U-Net structure is employed as the generator of the network to extract the CT image features with geometric artifacts. The convolutional neural network (CNN) based on image block perception acts as a discriminator for the network, further constraining the optimization of the generator. The proposed method has been shown experimentally feasible for geometric artifacts correction in circular cone beam CT by performing more accurate feature extraction. The peak signal to noise ratio (PSNR) of the corrected phantom images increased by 11.812 on average, and the root mean square error (RMSE) decreased by 9.982 on average.
The generalized convolution formula and its application are discussed
Authors: Yinshan Jiang 
Published: March 2021

Abstract
There are two ways to find the distribution of two-dimensional random variable function: distribution function method and convolution formula method, the distribution function method is too large; calculation is easy to make mistakes, the convolution formula method has limitations must be independent, Now let’s introduce the generalized convolution formula, The generalized convolution formula does not require independent constraints and can simplify the operation.
Low Complexity Beam Selection Scheme Based on Estimated CSI
Authors: Zhao Hang 
Published: March 2021

Abstract
The beam selection technology based on the discrete lens array (DLA) can greatly reduce the number of RF chains required by mmWave massive multiple-input multiple-out (MIMO) system. However, the performance of the existing beam selection schemes is on the premise of perfect channel state information (CSI). While in practical situation, accurate channel state information must be obtained by the base station before beam selection. In this paper, the channel estimation scheme based on support detection (SD) is used to estimate the state information of large-scale channel by utilizing the structural characteristics of beamspace. Then on the basis of group-iteration (GI) algorithm, we propose the group-iteration beam selection scheme based on estimated CSI. The simulation results show that this scheme can achieve the performance close to beam selection scheme based on perfect CSI, and compared with the traditional beam selection schemes, the proposed scheme also shows performance advantages.
RoBERTa-IAN for aspect-level sentiment analysis of product reviews
Authors: Dai Jingrui , Pan Fang , Shou Zhaoyu , Zhang Huibing 
Published: March 2021

Abstract
Accurately mining the emotional information contained in product reviews is of great significance to product sales. Existing research on sentiment analysis of product reviews often ignores the importance of modelling aspect words and context separately. Therefore, this paper proposes a sentiment analysis model for product reviews based on RoBERTa-IAN. Firstly, the context and aspect words of product reviews are transformed into low dimensional vectors through the RoBERTa pre-training model. Then, the low dimensional vector is used as the input of Bi-GRU model to extract semantic features and get the hidden representation. Finally, the attention matrices of context and aspect words are obtained by using the Interactive Attention Networks (IAN), which are used as the input of sentiment classification layer to analyse and classify the sentiment polarity of product reviews. The experimental results on the real commodity Chinese dataset show that the accuracy of RoBERTa-IAN has reached more than 90%.
The Analysis of Manufacturing Service Ecosystem’s Evolution Stability Based on Evolutionary Game
Authors: Zhang Siqi , Luo Li , Li Yue , Shan Renbang 
Published: March 2021

Abstract
In the process of successful establishment and development of service ecosystem organization, manufacturing companies not only pay attention to their own resources, business models and competitive advantages, but also pay attention to the positioning in the manufacturing service ecosystem and the symbiosis with other members of the system to achieve complementarity and symbiotic development of resources among members. Based on this, we take the manufacturing service ecosystem in the transformation and upgrading of the manufacturing enterprises in China as the research object, and comprehensively uses the theory of evolutionary game and ecosystem to study the symbiotic evolutionary stability of the manufacturing service ecosystem. Through simulation, we find that integrator is more sensitive to the change of rights than supplier. Our conclusions have certain reference for manufacturing companies to improve the collaborative operation efficiency of manufacturing service ecosystem.
Research on key problems of Arctic navigation safety
Authors: Yahan Hu , Minglu Ma 
Published: March 2021

Abstract
Arctic shipping can bring significantly potential business profit, which has become a focal point at present. However, compared to the enormous risk, related research on the safety and security issues are not sufficient. In the essay, the natural factors, such as weather, ice are summarized, and the facility insufficiency and human factors aroused by low temperature and severe ice conditions are analyzed. Besides that, the requirement of international conventions has already proposed the basic technical demand for the ship facilities and lifeboat in Arctic area. In the end, the suggestions for safety and security, providing better equipment and facilities, enhancing crew competence, decent preparations before navigation are proposed.
A Distributed Collaborative Supplier Requirements Management Method for Civil Aircraft in Whole Life Cycle
Authors: Zhang Jiejing , Zhang Xinyu , Zhang Xinai , Zeng Jiahui 
Published: March 2021

Abstract
In order to solve the problems of correctness and timeliness of requirement information transmission, effectiveness of requirement collaboration, management and control under the Main Manufacturer-Supplier working mode for civil aircraft, a distributed collaborative management method of supplier requirements in the whole life cycle is proposed in this paper. The definition of this method of supplier requirement distributed collaboration can carry out multi-version, multi-authority and cross regional requirement data exchange for different suppliers at different development phases, and monitor the status of data exchange based on the key elements of supplier requirement management, so as to ensure the requirement collaboration and supplier monitoring management between main manufacturer and supplier.
Research on Modeling of Aircraft-Level High-lift System Architecture Based on SysML
Authors: Yang Hao , Zhan Chao , Wu Haomin , Cui Chao , Hu Renyu 
Published: March 2021

Abstract
The aircraft-level high-lift system architecture of civil aircraft includes functional architecture, logical architecture and physical architecture. The system architecture describes the hierarchical relationship, cross-linking relationship and information interaction between the function, logic and physics of the system. This article is based on the SysML modeling language, using the MagicDraw modeling tool to transform the traditional design work based on experience and documents into model-based architecture design work, using the association and traceability of the model to ensure the integrity of the information in the design process. This article establishes the design relationship between its functional, logical and physical layers of the high-lift system to verify the efficiency of this modeling method.
Study on multiple thermal radiation response of adjacent tanks based on numerical simulation
Authors: Zuo Yawen , Zhang Mingguang , Zheng Feng , Pan Wenjie , Mo Sifan 
Published: March 2021

Abstract
In order to obtain the time to failure of adjacent tanks under multi-thermal radiation conditions, the thermal response of gasoline tanks under multi-thermal radiation was studied. The heat radiation values of the adjacent tanks under pool fire were calculated. The temperature distribution and the corresponding stress of the adjacent tank were studied with ANSYS-Workbench software under the influence of single heat radiation and multi-thermal radiation. According to the physics properties of tank steel Q235B, the time to failure (ttf) of the tank was analysed. The results show that the temperature rise rate affected by the coupling effect of multi-thermal radiation is significantly higher than that affected by single heat radiation; when the storage tank is affected by the single heat radiation, the time to failure is about 22min; when the storage tank is affected by the coupling effect of multi-thermal radiation, the time to failure is about 15min.
Design and mechanical failure analysis of Ti6Al4V alloy thin-walled parts by selective laser melting(SLM) manufacture
Authors: Wang Qun , Zhang Lijun , Xu Xinchen , Yu Xiao , Zheng Yi , Wangping Wu 
Published: March 2021

Abstract
There is a growing interest in using additive manufacturing to produce smart structures, which have the capability to respond to thermal and mechanical stimulation. In this report, Selective Laser Melting (SLM) is used to build a thin-walled titanium alloy structure. The part creating a ultra lightweight is 2.15g, while its strenght achieve at 132.4MPa. The stages of compression process was analyzed in detail, meanwhile the deformation and failure mechanism of the thin-walled part was described.
Quantum Entanglement and Its Application in Quantum Communication
Authors: Zou Nanxi 
Published: March 2021

Abstract
Since the concept of quantum entanglement was proposed, quantum entanglement has been paid more and more attention. Especially in recent years, with the interdisciplinary and interdisciplinary development of quantum informatics, the general definition, physical properties and entanglement measurement of quantum entanglement have been comprehensively and deeply studied. Due to its nonlocality, quantum entanglement has been widely used in quantum information, especially in quantum communication. In view of the application status of quantum entanglement in quantum communication, this paper presents a survey of quantum entanglement and its application in quantum communication. In this paper, 230 staff members from 15 Chinese companies involved in quantum communication are selected as the investigation samples, and the proportion of quantum entanglement in the application is obtained, which can promote the quantum communication. The capacity, speed and security of quantum entanglement and ordinary quantum in the application of quantum communication are compared. Through the analysis, it is concluded that each index of quantum entanglement is conducive to the development of quantum communication. Quantum entanglement provides a technical guarantee for the research of quantum communication.
Fatigue Detection For Online Classes Based on Adaboost
Authors: Mo Qingyu 
Published: March 2021

Abstract
Online Classes has been widely popularized since corona virus doesn’t allow students to have face-to-face classes. However, due to comfortable environment that students have, students may get sleepy in class and cannot help with their fatigue. So students need a supervised environment to alarm them not to fall asleep. So in this article, a real-time method to detect whether the student in front of the camera is sleeping, based on the demo of students in online classes, is introduced. This article focus on detection of states of eyes of students. It uses Adaboost as the training method to detect the face of the student, uses Canny to process the picture with human face, and calculates the area of the exposed eyeball and the radius of the eye. Finally, PERCLOS is used as the criterion to determine whether the student is sleeping in class. The method in this article has high detection rate on faces and eyes, which is respectively 99.7% and 98.5% for image set that made by the author. It can be applied on online classes and shows good results in detecting the fatigue of people in practical.
Overview of the development of speaker recognition
Authors: Yuan Xinyu , Li Guanyu , Han Jiao , Wang Di , Tiankai Zhi 
Published: March 2021

AbstractSpeaker recognition is a technology that recognizes a person’s identity through a person’s voice. Speaker recognition is one of the important research topics in the field of biometrics. This article first introduces the background and research significance of speaker recognition; secondly, it briefly introduces speaker recognition technology; again introduces the method research used in speaker recognition; and finally analyzes the research difficulties and challenges of speaker recognition.
Image Description Generation based on Deep Learning
Authors: Zeng Miaomiao , MuRong Xun 
Published: March 2021

Abstract
The paper firstly explains the importance and research significance of image description generation and makes a brief research summary on the generation of various algorithms for image description; it further introduces the principle and the algorithm process of the LSTM deep learning algorithm in details, specifically describes establishing steps and the model parameter selection process of the LSTM deep learning algorithm of the Microsoft COCO dataset, implements the deep learning models by employing Python, and finally applies the trained LSTM deep learning model to image description generation by using the Microsoft COCO dataset as an instance.
Filling Algorithm of Polygons and Embedded Polygons
Authors: Yang Xiaozhuo 
Published: March 2021

Abstract
In this paper, by studying the laser marking trajectory model, for the two different marking modes of zigzag parallel and contour parallel, with or without contour nesting, different laser marking path generation algorithms are designed. And compare the time-consuming of the two algorithms, discuss and propose methods to optimize the algorithm to improve the efficiency of the algorithm to meet the needs of industrial applications. According to the requirements of the distance between the retracted boundary and the hatch line, the zigzag parallel trajectory generation algorithm and the contour parallel trajectory generation algorithm are designed, and the hatching curve is generated according to the given contour point set. Based on the algorithm above, in the face of contour nesting, the algorithm is improved, and the hatching curve is generated according to the given contour point set. For the zigzag parallel trajectory generation algorithm, considering the intersection of the scan line and the inner contour. For contour parallel trajectories, this paper uses a vertex-based offset algorithm, which takes a long time. This is because the vertex-based offset algorithm is more complicated to solve the problem of self-intersection. This paper proposes that for the zigzag parallel method, the angle of the workpiece can be adjusted to find the optimal angle, so that the marking path is the smallest. And for the contour parallel trajectory generation algorithm, this paper proposes an optimization too.
Rademacher Complexity in Simplex/l∞
Set
Authors: Lu Yuwei 
Published: March 2021

Abstract
When the size of the neural network is too large, calculating the bound of neural network is a difficult problem. Therefore, “size-independent” is what needs to look for here. This paper follows the path of “Size-Independent Sample Complexity of Neural Network ”, and tries to get a better expression of Rademacher Complexity of neural networks.
Communication Modulation Recognition Method Based on Clustering Algorithm
Authors: Cheng Yuyang , Shao Shuying 
Published: March 2021

Abstract
The modular identification of wireless communication signals is widely used in civil and military fields. With the rapid development of modern communication technology in China, signal modulation becomes complex and diverse. How to accurately identify communication signal modulation methods has become a research hotspot. Among them, multi band quadrature amplitude modulation (MQAM) is widely used in microwave communication, satellite communication and network communication. It has the advantages of high frequency band utilization and flexible modulation. Therefore, the recognition of MQAM modulation mode is of great significance. Traditional clustering algorithm has some limitations when it is used to identify MQAM signal modulation, such as too many iterations and long recognition time. For high-order modulated signals, a modulation recognition method based on Constellation Clustering is proposed. The constellation is used as the feature of modulation recognition, and the constellation of received signal is reconstructed in groups. The simulation results show that the collected characteristic parameters have strong interference ability to multi-channel, and the recognition rate reaches 97.6%. It has important engineering application value for signal modulation recognition in low SNR environment.
Higher-Order Quantum Genetic Algorithm and Its Application on Non-Linear Equations
Authors: Jin Lei , Shan Zheng , Hu Chunchao , Xu Le 
Published: March 2021

Abstract
The high efficiency of quantum algorithms is caused by the quantum parallelism of the superposition principle and the quantum entangled, but traditional quantum genetic algorithms only use the quantum superposition principle. In order to further improve the performance of the algorithm, this paper proposes a new higher-order quantum genetic algorithm, which adds quantum entanglement properties on the basis of the principle of quantum superposition. Finally, the traditional quantum genetic algorithm and the higher-order quantum genetic algorithm are used to test a set of nonlinear equations many times. The results show that compared with the traditional quantum genetic algorithm, the evolutionary update operation of the higher-order quantum genetic algorithm does not involve multiple judgment conditions of the traditional quantum gate, requires less evolutionary algebra, and can converge quickly.