bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterization of single channel liquid light guide coupling and SPAD array imaging for tumour margin estimation using fluorescence lifetime
Authors: Stewart Hazel L , Hungerford Graham , Birch David J S 
Published: July 2020

Abstract
Surgery remains one of the key treatment options for tumour removal, and surgeons primarily rely on eye and touch to assess the boundary between healthy and cancerous tissue with no cellular information as guidance. There is therefore a need for a device or instrument that can be used by the surgeon in real-time during the surgical procedure to ensure as many of the cancerous cells and as few of the healthy cells have been removed as possible. Fluorescence approaches have previously demonstrated significant promise in this application, but clinical take-up has been limited and much more characterization of critical parameters needed before robotic surgery can be contemplated. Here we investigate two time-correlated single-photon counting (TCSPC) fluorescence lifetime systems for the detection of phantom tumour margins derived from silica sol-gels. A simple and low-cost liquid light guide system (LLG) incorporating a single photomultiplier detection channel and translational stage was developed. This provided a useful reference for a compact single-photon avalanche diode (SPAD) array camera system for fluorescence lifetime imaging microscopy (FLIM) which permits up to ∼25 000 in-pixel timing measurements at video rates in ambient light using only low energy (∼30 pJ) diode laser pulses to minimize cell and dye degradation. Measurements of phantom margins with sol-gel doped Rhodamine 6G (R6G) of fluorescence lifetime ∼4 ns using the LLG system demonstrates that for 7 mm excitation diameter and over 5–15 mm sol-gel LLG separation the sol-gel only region could be clearly identified 1 mm after the margin position, a widely accepted minimum surgical resolution. A comparison between measurements with the LLG and SPAD FLIM system using the sub-ns fluorescence lifetime of the FDA-approved dye indocyanine green (ICG) demonstrates that the minimum workable spatial resolution and sufficient speed are only achievable with such faster lifetimes using the SPAD FLIM system.
Silent 3D MR sequence for quantitative and multicontrast T1 and proton density imaging
Authors: Liu Xin , Gómez Pedro A , Solana Ana Beatriz , Wiesinger Florian , Menzel Marion I , Menze Bjoern H 
Published: July 2020

Abstract
This study aims to develop a silent, fast and 3D method for T1 and proton density (PD) mapping, while generating time series of T1-weighted (T1w) images with bias-field correction. Undersampled T1w images at different effective inversion times (TIs) were acquired using the inversion recovery prepared RUFIS sequence with an interleaved k-space trajectory. Unaliased images were reconstructed by constraining the signal evolution to a temporal subspace which was learned from the signal model. Parameter maps were obtained by fitting the data to the signal model, and bias-field correction was conducted on T1w images. Accuracy and repeatability of the method was accessed in repeated experiments with phantom and volunteers. For the phantom study, T1 values obtained by the proposed method were highly consistent with values from the gold standard method, R2 = 0.9976. Coefficients of variation (CVs) ranged from 0.09% to 0.83%. For the volunteer study, T1 values from gray and white matter regions were consistent with literature values, and peaks of gray and white matter can be clearly delineated on whole-brain T1 histograms. CVs ranged from 0.01% to 2.30%. The acoustic noise measured at the scanner isocenter was 2.6 dBA higher compared to the in-bore background. Rapid and with low acoustic noise, the proposed method is shown to produce accurate T1 and PD maps with high repeatability by reconstructing sparsely sampled T1w images at different TIs using temporal subspace. Our approach can greatly enhance patient comfort during examination and therefore increase the acceptance of the procedure.
Noise removal in resting-state and task fMRI: functional connectivity and activation maps
Authors: De Blasi Bianca , Caciagli Lorenzo , Storti Silvia Francesca , Galovic Marian , Koepp Matthias , Menegaz Gloria , Barnes Anna , Galazzo Ilaria Boscolo 
Published: July 2020

Abstract

Objective. Blood-oxygenated-level dependent (BOLD)-based functional magnetic resonance imaging (fMRI) is a widely used non-invasive tool for mapping brain function and connectivity. However, the BOLD signal is highly affected by non-neuronal contributions arising from head motion, physiological noise and scanner artefacts. Therefore, it is necessary to recover the signal of interest from the other noise-related fluctuations to obtain reliable functional connectivity (FC) results. Several pre-processing pipelines have been developed, mainly based on nuisance regression and independent component analysis (ICA). The aim of this work was to investigate the impact of seven widely used denoising methods on both resting-state and task fMRI. Approach. Task fMRI can provide some ground truth given that the task administered has well established brain activations. The resulting cleaned data were compared using a wide range of measures: motion evaluation and data quality, resting-state networks and task activations, FC. Main results. Improved signal quality and reduced motion artefacts were obtained with all advanced pipelines, compared to the minimally pre-processed data. Larger variability was observed in the case of brain activation and FC estimates, with ICA-based pipelines generally achieving more reliable and accurate results. Significance. This work provides an evidence-based reference for investigators to choose the most appropriate method for their study and data.
Mechanical Analysis of ROPS Lateral Loading Test-bed for Mining Dump Truck
Authors: Yang Zhijun , Yun Chao 
Published: July 2020

Abstract
This paper analyzes the static load of the ROPS side loading test-bed of the mine dump truck by using the finite element method, obtains the distribution law of the stress and deformation, discusses the feasibility of the simulation analysis, and makes a beneficial exploration for the design and improvement of the similar ROPS in the future.
A Security Refreshing Algorithm of Dynamic Node based on Fast Group-Blind Signature
Authors: Fan Hongbin , Rao Jiamin 
Published: July 2020

Abstract
In the contemporary society, electronic payment becomes a part of people’s life. It can make people’s life more convenient and faster. At the same time, security’s problem and efficiency’s problem in the electronic payment arouse the attention of many researchers. In this paper, we study group-blind signature algorithms in digital signature technology. We take LR98 group-blind signature algorithm as the research object and analyze its problems. The algorithm put the fixed value l as security parameter, which results in the low efficiency of algorithm. In this paper, new security parameters are adopted, and take blind signature method of Boldyreva into consideration, a new group-blind method is proposed, CL-LR98. New method is applied to wireless communication network (WSN). A number of communication nodes (AP) and user terminal (UE) are built, which is used as the experimental environment. New group-blind signature method is applied to dynamic refreshing of WSN nodes, which includes anonymous communication, data transmission. In the process of experiments, new group-blind method has excellent characteristics, it has short signature character length, it can be simply realized and it has better encryption performance. In the node joining part and revocation part of communication process, these excellent characteristics make computation small, make node refresh efficiency high, and it will not cause frequent movement of other communication nodes.
A New 3D Surface Reconstruction Method
Authors: Fu Wei , Wu Lushen 
Published: July 2020

Abstract
The existing complete orthogonal function system cannot introduce the spectrum analysis into geometry information processing field. This paper proposes complete orthogonal v system reconstruction method based on the 3D data mode, and this method is to map surface data model to parametric triangular domain. The complete orthogonal V system in triangular domain is used to expand the surface data model and the 3D model reconstruction with piecewise polynomial is realized, and it has simple operation and can handle any topology grid. The experimental results show that the error of three experimental models is controlled in 0.25 mm, Compared with Voronoi-based method and Yoshimoto’s method, the accuracy of the proposed method is improved obviously, and the orthogonal v system under reconstruction time compared with Voronoi-based method reconstruction time is shortened by 13%. Therefore, reconstruction precision and speed can meet the requirements of industrial design.
Construction and Application of Web-Based Resource Repository of College Physical Education
Authors: Deng Chenliang , Tang Zhaohua , Li Xuemei , Zhao Zhangzhi 
Published: July 2020

Abstract
The construction of college physical education network teaching resources is based on teaching needs, guided by curriculum innovation, aimed at integrated teaching, and follows relevant national policies to realize the development and sharing of resources. By using the methods of literature, questionnaire, data analysis and action research, this paper studies the related problems, expounds the concept, value, significance and basic structure of the network teaching resource database of physical education in colleges and universities, and studies its construction and application status. On the basis of learning from the good practices of other schools and other disciplines, and taking our school as an example, we have established a physical education network teaching resources database with strong pertinence and practicability, namely AI sports. It basically covers the main courses of physical education and can meet the teaching needs of teachers and students. It not only enriches the means of physical education teaching, but also realizes the integration of physical education teaching and plays an active role in physical education teaching.
Attention-Based Encoder-Decoder Model for Photovoltaic Power Generation Prediction
Authors: Zhu Xiang , Hu Juntao , Song Liangcai , Suo Guilong , Zhan Yong 
Published: July 2020

Abstract
The weather factors that affect the output of photovoltaic power generation systems have great volatility and discontinuities. Thus how to accurately predict the output of photovoltaic power generation has become a crucial issue. In this paper, we propose an attention-based Encoder-Decoder model for photovoltaic power generation. Filtered data based on maximum information coefficient is used as one of the features to reconstruct the experiment data. Then the attention mechanism is introduced to the Encoder-Decoder model, which constructed by Long Short-Term Memory (LSTM) neurons. We implement this experiment based on actual photovoltaic power plant examples and experimental results confirm the accuracy and applicability of the proposed model in predicting photovoltaic power generation
Mechanical Analysis of Floor Heating Decoration of High-rise Residence
Authors: Yang Zhijun , Yun Chao 
Published: July 2020

Abstract
The mechanical analysis of the vertical load and the wind load of the high-rise building is carried out by using the finite element method. The law of internal force and deformation is obtained. It is found that the reinforcement ratio is increased compared with the original design value, and there is a potential safety hazard. It has reference and guidance significance for the future practical design.
Research on Dynamic Allocation Strategy of KU Satellite Spectrum Based on Cognitive Radio Technology
Authors: Zhou Xinsheng , Zhao Lili , Yu Pengpeng , Dong Qicai , Yang Juan , Liu Jing , Zhao Yan 
Published: July 2020

Abstract
Aiming at the problem of insufficient satellite spectrum resources in the KU band, combined with the most advanced cognitive radio technology in the communication field, this paper proposes a dynamic spectrum allocation strategy for KU satellites based on cognitive radio technology. By dynamically allocating frequency resources, the spectrum resources are greatly improved. Use efficiency, while improving the anti-interference ability of the satellite system.
Kalman Filtering Algorithm for Integrated Navigation System in Unmanned Aerial Vehicle
Authors: Lv Wenfa 
Published: July 2020

Abstract
Through the complementarity of the satellite navigation positioning system (GNSS) and the inertial navigation system (INS), the combination of GNSS/INS can make up for the shortcomings of a single system that is difficult to improve, thereby greatly improving the accuracy of the integrated navigation system. In this paper, the transformation relationship between the carrier coordinate system and the navigation coordinate system is deduced, and the INS position and velocity measurement methods are derived. Based on the theory of GNSS/INS loose combined system and Kalman combined filter, the system equation and measurement equation of combined filter Kalman are studied in depth. The principle of discrete Kalman filter is researched, and five basic equations of Kalman filter are given. Then the speed and position model of Kalman filter of GNSS/INS loose combined navigation is derived in detail, and according to the speed and position model perform semi-physical simulation experiments. The experimental results show that the inertial sensor can provide navigation information during the GNSS receiving signal gap, and the position and speed information of the GNSS can also correct the navigation information of the inertial sensor.
A Fatigue Driving Detection Method based on Deep Learning and Image Processing
Authors: Wang Zhong , Shi Peibei , Wu Chao 
Published: July 2020

Abstract
Driving fatigue is one of the important causes of traffic accidents. It is of great significance to study fatigue driving detection algorithms to improve human life and property safety. This paper proposes a fatigue driving detection method based on deep learning and image processing. First, the driver’s face image is obtained in real time through the camera and the face image is detected using the MTCNN model. Next the image processing is performed on the face image, including three steps: grayscale processing, binarization processing, and human eye detection. Then we check the legitimacy of the human eye image and calculate the eye closure rate, and finally use the PERCLOS principle to analyze the fatigue state of the driver. The experimental results show that the proposed method has high detection rate and low false alarm rate, and has strong practicality.
Situation Comprehension for UGV Based on Domain Knowledge
Authors: Wang Chao , Zhang Wanpeng , Yang JingZhao , Chen Shaofei 
Published: July 2020

Abstract
Battlefield situation comprehension (SC) plays an important role in the operation observation-orientation-decision-action (OODA) circle of UGV as the results of SC are the input of the UGV mission planning. A situation comprehension method for UGV based on domain knowledge is proposed to overcome the problems of heterogeneous situation data, various relations and plan to be comprehended. Firstly, an ontology based situation comprehension architecture is given. Then, core ontology for situation comprehension is established, based on which a detailed ontology include the opposing sides classes and environment classes is constructed and steps for building situation inferring rules are listed. Finally, in a frontline defence scenario, different situation types are defined with SWRL and three scenario snapshots are depicted to demonstrate the method proposed in this paper.
Research on Clustering Application Based on Stock Association Network
Authors: Ma Chi , Lu Shengliang , Wang Shaofan 
Published: July 2020

Abstract
This article uses stock market data and text information to construct related complex networks of stock information, and compares the cluster analysis effect of three community discovery algorithms base on two networks to discuss how to classify stocks in order to give Investors provide better reference. First, transform the heterogeneous data into structured data by obtaining and preprocessing. Then, build an association network based on the similarity of stock price fluctuations and the correlation of stock text information. Finally, using three different cluster analysis algorithms to analyze the stock association network and the text similarity network to compare the effects of different algorithms on stock classification.
Research on Simulation Technology of Infrared Missile Battle Scene
Authors: Wang Duo , Luo Huafeng , Li Ming , Wang Yiwen 
Published: July 2020

Abstract
To provide a battle scene for the semi-physical simulation of infrared missile. Picked the main factors of infrared radiation processing, calculated target and background’s temperature, atmospheric radiation transmission, infrared smoke interference. Performed simulation calculation for ship-type target under battle scene and analyzed the simulation results. Provides support for test design.
Satellite Communications Millimeter Wave and RF Technical Analysis
Authors: Cai Chengcheng , Ge Pingxin , Zhang Chengxia 
Published: July 2020

Abstract
This paper introduces the development status and trend of millimeter band of satellite communication. Based on the analysis of the frequency division, spectrum advantages and transmission characteristics of EHF satellite communication, the new technologies adopted in EHF satellite communication are studied, and the special technology and application of the EHF radio frequency circuit are analyzed.
The Development and Application of Remote Monitoring System for Oil Well Working Condition with Mobile Phone Module
Authors: Song Limei , Zhang Jingjing , Hao Cunhe , Qi Huien , Tian Bingying , Li Wei 
Published: July 2020

Abstract
Some pumping wells are remote and distributed, and it is difficult to find problems such as temporary power outages, fault shutdowns, and belt burning, which cause untimely processing, which seriously affects the rate of well opening and reduces crude oil recovery. In order to effectively monitor the operating conditions of pumping units, mobile phone remote monitoring systems have been developed. The system consists of a remote control module, a power supply module, a wireless transmission module, and a mobile phone terminal. It can facilitate front-line employees to quickly monitor oil well operating parameters, detect pumping unit failures in a timely manner, reduce hidden safety hazards, avoid pollution, and provide a powerful technical support for green mine construction.
Spam Filter Based on Naive Bayesian Classifier
Authors: Lv Teng , Yan Ping , Yuan Hongwu , He Weimin 
Published: July 2020

Abstract
Spam now accounts for over 70% of all emails and the harm to users is increasing, such as waste a lot of network bandwidth to transfer and space to store, has large quantity, repetitive, fraud, and unhealthy content, etc. As spam is usually embedded in normal e-mails, it is difficult to identify them. This paper analyzed the main technologies to identify and block spam, such as information or content filtering technology, blacklist and white list technology, intention and behaviour analysis technology, etc. A model to determine an e-mail is a spam or not based on naive Bayesian classifier is presented in the paper. The test result shows that the model is effective.
Data System Configuration and Organizing and Management Technologies of Information System
Authors: Wang Hua , Meng Haidong , Zhang Lianwei , Chen Zhengmao , Wang Shan 
Published: July 2020

Abstract
Based upon the synopsis of data system and information system, this paper puts forward the data system configuration of information system and execution process of data organizing and management, and sets forth a series of related technologies, such as data warehouse construction technology, data governance technology, data training and learning technology, data syncretization and analysis technology, and data subscription and distribution technology, and moreover, the effectiveness analysis is carried out with a performance comparison between the prototype and the existed system of data organizing and management. This will benefit the further evolution of information system and the continual improvement of data engineering.
Analysis of Gender-Specific Regulatory Mechanisms on the Oncogenesis and Prognosis of Glioblastoma Multiforme
Authors: Deng Jianzhi , Zhou Yuehan , Long Wenqing 
Published: July 2020

Abstract
In this paper, we focus on find out the key mRNAs and the key regulatory mechanism of the different morbidity of glioblastoma multiforme (GBM) in different genders. 160 GBM patients’ RNA expressed data and clinical data were downloaded from the TCGA GBM project. 103 differential expressed mRNAs (DEmRNAs) between male and female were screened from the RNA matrix by clustering analysis. In the gene ontology (GO) analysis, the DEmRNAs were enriched in 26 GOterms, including 17 biological process (BP), 4 cellular component (CC), 5 molecular function (MF). Among them, AGTR2, CALCA, CALCB, CTSG, GCG, GCGR, HCRT, PRL and RXFP4 were found that enriched in signal pathway hsa04080. A multivariate COX model was constructed by these 9 DEmRNAs. And GCGR, HCRT and CTSG were found as the co-expression mRNAs. In the clinical data analysis, the kmplot survival curve (p = 1.63e-03) indicated that the co-expression mRNAs and the hsa04080 signal pathway would be built the potential regulatory mechanism for the treatment of GBM in different genders’ patients. And it was then proved by receiver operating characteristic (ROC) curve and area under the curve (AUC) value (AUC=0.766).
Aviation Terminal Data Security Architecture Based on Blockchain
Authors: Chen Zhiwei , Xu Aidong , Wen Hong , Zhang Yunan , Xu Xinchen 
Published: July 2020

Abstract
With the advent of the 5G era, the number of UAV (Unmanned Aerial Vehicle) has grown dramatically. Accordingly, UAV need more computing and storage capabilities to complete a variety of tasks (including some collaborative tasks). To meet the requirements of UAV terminals, edge computing nodes and storage devices need to be deployed. But the problem of trust between edge computing nodes will lead to a series of data security problems. The blockchain features, which contain detrust, immutable, decentralized, can solve this problem properly. Therefore, this paper establishes an aviation terminal data security architecture based on the blockchain. Edge computing nodes and storage devices provide computing and storage resources for UAVs. As the core operating mechanism of the architecture, blockchain technology guarantees that the system has Byzantine fault tolerance performance through its consensus algorithm. The blockchain data structure under this architecture also guarantees that the data access records of all nodes will be written on the ledger and the ledger is stored by all miner nodes.