bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis and design of a new low‐phase noise and Gm‐enhanced class‐C quadrature VCO
Authors: Majd Yasaman , Ebrahimi Emad 
Published: September 2020

This study presents a new low‐power and low‐phase noise Colpitts quadrature voltage‐controlled oscillator (QVCO). The proposed QVCO contains two differential Colpitts voltage‐controlled oscillators (VCOs) that use gain‐boosting technique to enhance the negative transconductance and relax start‐up condition. Both switching and tail transistors are configured in class‐C to improve impulse sensitivity function and phase noise performance of the circuit via better noise modulation function. In addition, flicker noise would be reduced because of the switched‐biasing mechanism of tail transistors. Phase noise analysis shows that changing the bias voltage of switching as well as tail transistors can improve the phase noise performance of the core VCO with overlap reduction of the transistors active time. Consequently, due to no extra noisy elements for coupling and class‐C biasing of all transistors, low‐phase noise quadrature signals are generated. To verify the performance of the proposed technique, post‐layout simulation is performed in Taiwan Semiconductor Manufacturing Company (TSMC) of 0.18 μm Radio Frequency‐Complementary Metal‐Oxide‐ Semiconductor (RF‐CMOS) process at a supply voltage of 1.2 V. Post‐layout simulation results show that the phase noise of the proposed QVCO is −120.6 dBc/Hz at 1 MHz offset from 5.73 GHz operation frequency. The total power consumption of the QVCO is 3.1 mW and the tuning range is from 5 to 5.73 GHz.
Hybrid absorber with carbon black composite and metamaterial structure
Authors: Dehghan‐Banadaki Mohsen , Heidari Abbas Ali , Nakhkash Mansor 
Published: September 2020

This study introduces a new broadband hybrid perfect absorber (HA) that includes metamaterial absorber (MA) and a lossy composite. The unit cell of the MA is in the form of two concentric ring‐based structures fabricated on an FR4 substrate, which provides a broadband absorption band because of two neighbouring resonance frequencies. The composite layer is built by mixing the carbon black powder and epoxy resin in an optimised weight percentage. By modelling the structure with multiple transmission line sections, a closed‐form procedure has been proposed to optimise the HA parameters. The final tuning of the HA parameters is performed using HFSS. A prototype of the HA is fabricated and measured. The results indicate that the proposed HA provides nearly perfect absorption (absorption ratio over 99%) in the frequency range of 2–2.8 GHz. It is, also, polarisation‐insensitive due to its symmetrical design. The total thickness of the proposed structure is 12.5 mm, which is acceptable concerning the absorption rate and the operational frequency bandwidth.
Period–luminosity–metallicity relation of classical Cepheids
Authors: Ripepi V. , Catanzaro G. , Molinaro R. , Marconi M. , Clementini G. , Cusano F. , De Somma G. , Leccia S. , Musella I. , Testa V. 
Published: September 2020

Context. Classical Cepheids (DCEPs) are the most important primary indicators for the extragalactic distance scale. Establishing the dependence on metallicity of their period–luminosity and period–Wesenheit (PL and PW) relations has deep consequences for the estimate of the Hubble constant (H0).
Aims. We investigate the dependence on metal abundance ([Fe/H]) of the PL and PW relations for Galactic DCEPs.
Methods. We combined proprietary and literature photometric and spectroscopic data, gathering a total sample of 413 Galactic DCEPs (372 fundamental mode, DCEP_F, and 41 first-overtone, DCEP_1O) and constructed new metallicity-dependent PL and PW relations in the near-infrared adopting the astrometry-based luminosity.
Results. We find indications that the slopes of the PL(KS) and PW(J, KS) relations for Galactic DCEPs might depend on metallicity on the basis of the comparison with the Large Magellanic Cloud relationships. Therefore we used a generalized form of the PL and PW relations to simultaneously take the metallicity dependence of the slope and intercept of these relations into account.
Conclusions. We calculated PL and PW relations that for the first time explicitly include a metallicity dependence of the slope and intercept terms. The quality of the available data is insufficient, however, and we cannot yet present conclusive results, but they are relevant from a methodological point of view. The new relations are linked to the geometric measurement of the distance to the Large Magellanic Cloud and allowed us to estimate a Gaia DR2 parallax zero-point offset Δϖ = 0.0615 ± 0.004 mas from the dataset of DCEPs used in this work.
An Algorithm Based on Simple CNN and BI_LSTM Network for Chinese Word Segmentation
Authors: Guan Xiaohan , Liu Xin , Liu Zhi 
Published: September 2020

Abstract
In dealing with most Chinese NLP tasks, word segmentation is an indispensable and critical work, and it also affects the accuracy of subsequent tasks. Neither the traditional BI_LSTM network can extract features effectively, nor the CNN network can deal with the timing problem effectively. As a result, this paper proposes a new algorithm to solve these problems. First, the Chinese characters’ feature in a whole sentence is extracted and recombined using the CNN network; then, the recombined feature is combined in BI_LSTM network; finally, each word of the whole sentence which classified by weight sharing and the corresponding classification of each word is the consequent output. Not only the advantages of CNN network are utilized for feature extraction, but also the advantages of BI_LSTM network are retained for timing processing. In conclusion, the learning ability of BI_LSTM network is increased, and the accuracy of output is improved to 98%.
An Affine-Based Algorithm for Registrating Non-rigid 3D Models
Authors: Zhao Hongtian , Zheng Shibao 
Published: September 2020

Abstract
While exploiting isometric method to calculate the correspondence between two non-rigid 3D models, it is difficult to obtain the correct matching relations and tend to fall into local optimum by iterative optimization strategy when using the inappropriate initial spectral value. To address this issue, an affine-based algorithm for labeling non-rigid 3D model is focused on in this paper. First, the approximate rotation and translation parameters between different models are calculated and the model coordinate system is unified through SVD method with over 4 pairs of roughly matched points. Next, the far sampling point algorithm is chosen to obtain a fixed number of uniform discrete 3D points on the two meshes respectively, and then for each sampling point, their neighbor points and corresponding distances are solved by kNN algorithm, after that, the shortest distance between each sampling point pair is calculated via Dijkstra algorithm and is viewed as geodesic distance. Besides, the discrete MRF model is established to optimize the isometric error of different models. Experiment results on both standard datasets and real-life collected models show that the proposed method can avoid local optimum in the whole optimization process. But for the existing method based on isometric optimization, if the initialization is not good, the optimization procedure may negatively get in local optimum and cannot gain the correct model registration and mapping.
Identification of Effective Events Recorded by Optical Fiber Microseismic Monitoring System
Authors: Song Guangdong , Hu Binxin , Zhu Feng , Zhang Hua , Liu Tongyu 
Published: September 2020

Abstract
At present, the development of microseismic monitoring system based on electronic sensors is restricted by the problems of power supply, electromagnetic interference and etc. How to select effective microseismic events from the massive and uninterrupted raw data is also a huge problem. In this paper, the DFB laser is used to demodulate the external vibration signal detected by the FBG sensor. The first arrival time of the P wave and the end point of the signal are picked up by using the improved STA/LTA algorithm. The method of calculating the optimal time window width is established by using the characteristics of periodic vibration wave. The criterion of the effective signal is established by using the maximum energy ratio of the effective signal. The resolution of this demodulation method is 0.01 pm. The criterion of effective signal discrimination can be used to accurately determine whether a channel event belongs to an effective signal or a noise signal. The microseismic monitoring system based on optical fiber sensor meets the needs of monitoring in a harsh mine environment, and the effective event discrimination criterion based on signal deviation is feasible.
DDoS Detection and Protection Based on Cloud Computing Platform
Authors: Jili Tianwen , Xiao Nanfeng 
Published: September 2020

Abstract
Currently, the distributed denial service attacks (DDoS) are increased rampantly on the internet, the threshold of such attacks is relatively low for the malicious attackers. Therefore, the DDoS attacks are serious threats to the security availability of the cloud computing. Aiming at the threats, this paper studies the malicious traffic identification and the detection scheme of the denial service attack under the soft-ware-defined Network (SDN), which uses the SDN forwarder to distinguish the DDoS attack traffic and adopt the corresponding filtering means to achieve protection for the distributed denial service attack. This paper firstly implements cloud platform resource calls, then an attack detection technology based on information entropy is proposed and implemented to carry out the DDoS attack detection, because the size of the entropy value can show the discrete or aggregated characteristics of the current data set, which can be used to detect abnormal data traffic. At last, the experiments are also carried out to verify and analyze the effectiveness of the DDoS attack detection and the protection methods.
An Improved EMD Parallel Steganography Algorithm
Authors: Ke Qi , Liao Qinan , Pan Ruidong 
Published: September 2020

Abstract
In Modification Direction Exploiting algorithm (EMD) exists binary information and multi-band data conversion redundancy problem, this paper proposed a new improved parallel algorithm. In this paper, we change the original EMD algorithm imbed function, and introduce the random safety parameter to improve the security of the algorithm. When 2n is equal to an integer power of 2, the algorithm does not have redundancy of data conversion problem, it can achieve the maximum theory embedding rate and the theory embedding efficiency. This algorithm utilizes multi-core parallel computing to improve operational efficiency. Therefore, the application of algorithm is more flexible and more efficient.
Research on TFIDF Algorithm Based on Weighting of Distribution Factors
Authors: Zhang Xinming , Shi Yuanbo , Wei Haiping 
Published: September 2020

Abstract
The current TFIDF (Term Frequency and Inverted Document Frequency) algorithm cannot effectively reflect the relationship between the importance of a word and its distribution. This paper proposes a Class Variance-Term Frequency and Inverted Document Frequency algorithm. This algorithm improves the TFIDF algorithm based on three distribution factors: category, inter-class and variance. In order to measure the optimization effect of this method, three algorithms were compared using the original algorithm, improved algorithm and TFIDF algorithm based on dual parallel calculation model. Experiments show that the improved algorithm has significantly improved recall, accuracy, and F metric values, comparing with the original algorithm, and has improved compared with the TFIDF algorithm based on dual parallel calculation model. Therefore, the improved algorithm can well adapt to the demand for feature word extraction and has better text classification performance.
Research on Image Preprocessing Algorithm and Deep Learning of Iris Recognition
Authors: Zhou Weibin , Ma Xiaotong , Zhang Yong 
Published: September 2020

Abstract
With the development of information society, biometrics technology has been paid more and more attention. Iris recognition is considered as the most promising biometric authentication technology in the 21st century because of its uniqueness, stability and non-creativity. However, due to the high cost of iris recognition equipment and some defects of the algorithm, iris recognition cannot be applied in real life on a large scale. In this paper, a fast localization iris recognition algorithm is proposed, which combines the iris segmentation algorithm with deep learning to quickly extract the iris region for recognition. Firstly, the pupil edge was extracted by dynamic threshold analysis and contour extraction, and then iris was located by edge detection and gray calculation. Finally, features of normalized images were learned by deep learning network. Experiments show that the method can guarantee the accuracy and efficiency of iris segmentation and has a high degree of recognition and matching.
Research on Construction of Key Personnel Judgment Model Through Data Label
Authors: Li Wei , Chen Changmin , Li Yi 
Published: September 2020

Abstract
Key personnel are important business objects in the management and control of public security elements. Through big data and machine learning technology, it is of great significance to model the years of police’s experience on research and judgment for the actual combat and the construction of Public Security Prevention and Control System. Aiming at the problem of complicated data type and low quantization degree of public security data, which makes it inconvenient to use machine learning for model analysis directly, a method of constructing public security personnel label system is proposed in this paper to transform complex business data into quantized label features, and on this basis, a key personnel judgement model is constructed by using FP-Growth and XGBoost algorithm. Through comparative analysis, the research results show that the judgment model proposed in this paper is better than the traditional business integral model and logistic regression algorithm in Accuracy, Precision and Recall, which can better serve the actual police combat.
Design and Implementation of Oil and Gas Information on Intelligent Search Engine Based on Knowledge Graph
Authors: Huang Shujun , Wang Yuyan , Yu Xiang 
Published: September 2020

Abstract
With the deepening of oil and gas informatization construction, various types of oil and gas information increase geometrically. In response to the challenges brought by massive oil and gas information in the search process, this paper proposes an intelligent search engine for oil and gas information based on knowledge graph. Functional modules such as knowledge fusion, knowledge processing, semantic relevance judgment, topic classification, and search result set sorting display, using map service as an interactive interface, realize intelligent search of oil and gas information. Compared with traditional search engines, it has more advantages in the search of oil and gas information, and it is easier to understand the user’s search intent in the oil and gas field, effectively improving the quality of search.
Machine Vision Based on Pipe Joint Surface Defect Detection and Identification
Authors: Zhu Li , Bao Xukang , Liu Shousheng 
Published: September 2020

Abstract
In the production process, pipe joints often have surface defects such as cracks, pits, bumps, etc., and the manual detection efficiency is low and the cost is high. This paper presents a machine vision based method for detecting surface defects of pipe joints. The preprocessing algorithm, image initial detection algorithm, image segmentation algorithm and feature extraction algorithm of tube joint surface defect image are studied and BP neural network classifier is designed. Finally, the designed classifier was tested by 300 samples of cracks, pits and bump defects on the surface of the pipe joint. The experimental results show that the recognition rate of the classifier reaches 95.5%, which can better meet the surface of the pipe joint. Defect detection requirements.
Application of an Improved Synthetical Semantic Similarity Method in Water Knowledge Graph
Authors: Gao Kaili , Yan Jianzhuo , Yu Yongchuan 
Published: September 2020

Abstract
In order to integrate different kinds of information in the water affairs field, this paper proposes an improved comprehensive semantic similarity algorithm and applies it to the construction of water affairs ontology. In this article, the algorithm is to give the concept instance similarity algorithm and concept definition similarity algorithm appropriate weight. First, we apply the three algorithms to the concept of the local ontology of smart water, and then calculate the similarity between the concepts to judge the similarity between the concepts to merge the smart water data, and finally compare the similarities of the three algorithms Degree value and calculation and comparison of three similarity variance values prove the effectiveness of the method. It can be seen from the experimental results that the variance of the comprehensive similarity calculation method is smaller than that of the other two methods, and it is easier to determine the similarity between two concepts.
A Multi-UAV Formation Maintaining Method Based on Formation Reference Point
Authors: Jiang Yang , Wang Shunzhang , Lei Lei 
Published: September 2020

Abstract
In recent years, Unmanned Aerial Vehicles (UAV), have been increasingly utilized by scholars. Efficient control of UAV swarms opens a set of new challenges. There are several formation control methods, however, artificial potential field (APF) method has imperfections in formation maintaining and virtual structure is insufficient in collision avoidance. In this paper, we proposed a multi-UAV formation maintaining method combined artificial potential field method and virtual structure approach. The method uses the concepts of attraction and repulsion in the artificial potential field method, combined with formation reference points inspired by the virtual structure points in the virtual structure approach to control the formation. On the other hand, we express the leaders, the followers, and the formation reference points uniformly. When the formation of UAVs is determined, after the leader arrives at target point and hovers, the followers can track the formation reference points. The method can avoid collision between UAVs and achieve the purpose of formation maintaining. Finally, a UAV swarm consists of four UAVs is used for demonstration and verification, and the results of experiment prove the validity of the algorithm.
Robot Path Planning Method Based on Level Set
Authors: Wang Ting , Sui Jianghua 
Published: September 2020

Abstract
For the problem of robot path planning under the action of external force field, the directionality of outward force can promote and hinder the movement of the robot. The continuous path planning method can break through the traditional robot path planning algorithm based on grid search. Limit, effectively utilize the external force field existing in the space, and improve the numerical implementation method to ensure the feasibility of the planned path in the strong external force field. Based on the Level Set method, the path planning problem is defined. The particle tracking of the robot is transformed into the numerical evolution of the curve. The optimal time path is obtained by solving the Hamilton-Jacques equation. The numerical calculation accuracy of the improved backward path tracking is guaranteed. The feasibility of planning the path. The simulation results show that the algorithm can effectively deal with a variety of complex external force fields and maintain the path in a strong external force field.
Study on RLS-Type Algorithm of GPS-Guided Range Correction
Authors: Chen Jun , Du Zhonghua , Shen Jian 
Published: September 2020

Abstract
Mitigating the error of GPS measurement signals is essential for the range precision of GPS-guided range correction projectile. In order to improve the range precision, an online method based on recursive least square algorithm (RLS) is applied to calculate the deployment time of brake. First, RLS is utilized to mitigate the error of the velocity, position, angle, etc., measured by GPS. Then, the deployment time can be calculated accurately by means of the appropriate pretreated data. To confirm the effectiveness of the method, a comparison to using least square algorithm and non-algorithm is done. The experimental results demonstrate that the method in this paper takes advantages in terms of online, real-time and the range correction accuracy.
Security Analysis and Optimization of BB84 QKD System Post-Processing
Authors: Zhang Pin , Mao Xiangjie 
Published: September 2020

Abstract
Considering the rapid development of quantum technology, it has become inevitable to use this technology to develop an ultimately secured key exchange system. Quantum key distribution (QKD) technology has become more sophisticated, is expected to provide secure key distribution mechanism for the actual information security systems. The unique advantage of quantum cryptography is precisely its ability to guarantee absolute security. Previous works have demonstrated unconditional security of the ideal BB84 QKD system. However, on a typical QKD system, many practical situations often cannot satisfy the requirements of the ideal condition. This problem causes some security issues for practical QKD system. Therefore, it is necessary to analyze the security of QKD system under practical conditions, and identify the security implications on the practical physical systems and equipment, in order to find a method that guarantees the security of QKD system. The security of QKD system based on BB84 involves many aspects; this paper mainly focuses on how to resolve security issues that may exist, especially in the BB84 protocol post-processing. We introduce ways to tackle these issues and make vital key information leakage very small. Their impact on the security of entire QKD system is analyzed, and the interaction and security optimization between the various parts is researched. Finally, the thesis briefly introduces five sub-modules of post-processing of QKD system: the base comparison, error estimation, information correction, data check and privacy amplification; the existent security factors of each module is given, for error estimation and information correction is provided the secure model with those issues. Thus, the security model of post-processing is further optimized.
A Complete Adaptive Method for Fetal ECG Extraction Based on Single Channel
Authors: Zhang Miao , Wei Guo 
Published: September 2020

Abstract
Based on empirical mode decomposition (EMD) and coherent averaging method, a completely adaptive single channel fetal ECG (FECG) extraction method is proposed. EMD is used to decompose single-lead abdominal ECG (AECG) signals, so that the noise, FECG and MECG components main energy in AECG are distributed in different inherent mode functions (IMF), and R wave detection of MECG is performed by means of IMF, where MECG energy is dominant. MECG was extracted from AECG by means of coherent averaging based on R wave detection results. The remaining signal was named as noisy FECG. Usually, when MECG residue in noisy FECG is large, it needs to be further eliminated. To this end, the same method as above was used again to extract FECG from noisy FECG, and threshold method was used to eliminate MECG residue after extraction of FECG, and then superimposed onto FECG again, in order to recover the non-stationary feature lost in the coherent average process. The effectiveness of the proposed method is verified by the experiments of synthetic mixed signals and real database recorded signals.