bluuebunny/crossref_metadata_2025 huggingface dataset:
Anisotropic monoblock model for computing AC loss in partially coupled Roebel cables
Authors: Otten Simon , Kario Anna , Demenčik Eduard , Nast Rainer , Grilli Francesco
Published: June 2020

When exposed to time-dependent magnetic fields, REBCO Roebel cables generate AC loss resulting from both magnetic hysteresis and induced inter-strand coupling currents. Until now, the AC loss has been computed in a two-dimensional approximation assuming fully coupled or decoupled strands, and a finite inter-strand resistance could be simulated only with three-dimensional models. In this work, we propose a homogenization procedure that reduces the three-dimensional geometry of the Roebel cable to two dimensions, without ignoring connections between the strands. The homogenized cable consists of two parallel ‘monoblocks’ with an anisotropic resistivity. The proposed model enables computation of AC coupling loss without the need for complex three-dimensional simulations. For experimental validation, a Roebel cable with soldered strands was prepared. The inter-strand resistance was determined by applying a transverse current and measuring the voltage profile. Additionally, the AC magnetization loss of the cable was measured in fields of 1 to 50 mT with frequencies of 1 to 2048 Hz using a calibration-free technique. With the measured inter-strand resistance as input parameter, the monoblock model gives a good estimate for the AC loss, even for conditions in which the coupling loss is dominant.
Topological phase transition from T-carbon to bct-C16
Authors: Ding Xian-Yong , Zhang Chao , Gan Li-Yong , Cao Yu , Chen Lei-Lei , Wang Rui
Published: June 2020

The realization of nontrivial fermions in three-dimensional carbon allotropes greatly facilitates topological applications in carbon based-materials. In this work, we find a topological phase transition from T-carbon to bct-C16 based on first principles calculations. After carrying out a heating or a doping process on T-carbon, a new carbon phase termed bct-C16 is obtained. The potential energy and the crystal orbital Hamilton population confirm the phase transition process, respectively. Importantly, we also investigate the quantized Berry phase and drumhead surfaces states, confirming the topological nodal line semimetallic features of bct-C16. Due to the extremely weak spin–orbital coupling effect in carbon, the nodal ring in bct-C16 can be guaranteed to be nearly intact. This work not only provides two methods to obtain the carbon phase bct-C16, but also an avenue for bct-C16 to observe nontrivial fermions.
Exploring classical correlations in noise to recover quantum information using local filtering
Authors: Jones Daniel E , Kirby Brian T , Riccardi Gabriele , Antonelli Cristian , Brodsky Michael
Published: June 2020

A general quantum channel consisting of a decohering and a filtering element carries one qubit of an entangled photon pair. As we apply a local filter to the other qubit, some mutual quantum information between the two qubits is restored depending on the properties of the noise mixed into the signal. We demonstrate a drastic difference between channels with bit-flip and phase-flip noise and further suggest a scheme for maximal recovery of the quantum information.
Modeling and simulation of optimized photonic crystal waveguide for slow-light enhancement
Authors: Hocini A , Maache M , Khedrouche D
Published: June 2020

We present a novel type of slow-light photonic crystal waveguide prepared by changing only the position of the second rows of holes in the direction of light propagation of a line-defect photonic crystal waveguide. A nearly constant group index is achieved of 30, 31 and 32 over wavelength ranges of 10.4 nm, 13.5 nm and 14.5 nm, respectively. In addition, a large normalized-delay-bandwidth product ranging from 0.201 to 0.300 is obtained at the operation wavelength of 1550 nm.
Modeling the CO2 dissociation in pulsed atmospheric-pressure discharge
Authors: Kolev St , Paunska Ts , Trenchev G , Bogaerts A
Published: June 2020

CO2 dissociation and its subsequent conversion into added-value chemicals is a promising strategy for recycling CO2 gas into reusable products. One of the possible methods is direct plasma-induced dissociation. In this work we study the efficiency of CO2 dissociation in pulsed atmospheric-pressure gas discharge between two conducting electrodes by a 0-D numerical plasma model. The purpose of the study is to provide results on the optimal conditions of CO2 conversion with respect to the energy efficiency and dissociation by varying the maximum power density value and the pulse length. The power density is directly related to the discharge current and the reduced electric field in the discharge. We consider pulse lengths in the range from hundreds of nanosecond up to milliseconds. The results obtained show that the dissociation degree and energy efficiency are sensitive to the pulse length (duration) and the power density, so that a considerable improvement of the discharge performance can be achieved by fine-tuning these parameters. The study is intended to provide guidance in designing an experimental set-up and a power supply with the characteristics necessary to achieve optimal conversion.
Computer-aided electron-beam deflection control system
Authors: Koleva E , Koleva L , Mladenov G , Trushnikov D , Andonov A
Published: June 2020

The electron beam processes – 3D selective melting (3D printing), welding, etc. are complex processes with many processing variables, which require integration of interfaces for control of the processes on different levels through hierarchical equipment models, functional data and operation control models. We developed a user interface software application for controlling the electron-beam motion along several types of trajectories and a free complex shape trajectory by controlling the deflection system parameters. Several types of motion patterns with different velocities are realized, together with the possibility of choosing a free trajectory by defining the electron-beam path by a graphical image.
Estimation of HTS electrodes properties for use in piezoelectric resonators
Authors: Nurgaliev T , Beshkova M
Published: June 2020

The microwave (MW) impedance of piezoelectric (PE) resonators with high-temperature superconducting (HTS) and with metal electrodes operating at a longitudinal acoustic waves (AW) frequency of ~2 GHz was modeled using Mason’s and the acoustic transmission line models. The MW impedances of the electrodes were also included into the model and the modeling parameters were chosen so as to be close to those of AlN (PE part of the resonator) and of HTS YBCO, Ag, and Pt (electrodes). It was shown that the limiting Q-factor value due to electric losses in the electrodes (computed under the assumption of small losses in the PE) is very high (~6×105) if even very thin (20 nm) HTS electrodes are used in the resonator at 77 K. The limiting Q-factor value is several thousand in the case of using similar metal electrodes. Thus, the HTS YBCO electrodes can be considered as attractive alternatives for application in PE resonators at low temperatures as they are characterized by low MW losses and affect weakly the resonance frequency.
Study of silicon surface layers modified by hydrogen plasma immersion ion implantation and oxidation
Authors: Szekeres A , Alexandrova S , Terziyska P , Anastasescu M , Stoica M , Gartner M
Published: June 2020

We report a study of p-Si(100) surface layers modified by plasma immersion ion implantation (PIII) and dry oxidation. This is expected to allow one to engineer near-surface layers with different thicknesses and levels of amorphization. Hydrogen ions were introduced into a shallow near-surface Si region through PIII with energy of 2 keV and doses ranging from 1013 ion/cm2 to 1015 ion/cm2. The implanted Si surface was subjected to oxidation in dry oxygen atmosphere at temperatures ranging from 700 °C to 800 °C. The optical and structural properties of the modified Si layers were studied in detail by spectroscopic ellipsometry (SE) in the IR spectral range of 300 – 4000 cm−1. The surface morphology was examined by atomic force microscopy (AFM) imaging at different scales and by fractal analysis. Through decomposition of the main Si-O bands into Gaussian peaks, different Si oxidation states were identified, suggesting non-stoichiometric oxide layer composition.
First observation and study of the K
± → π
±
π
0
e
+
e
− decay with the NA48/2 experiment at CERN
Authors: Bloch-Devaux B
Published: June 2020

The first observation of the rare decay K
± → π
±
π
0
e
+
e
− is reported by the NA48/2 experiment at CERN, based on 4919 candidates with 4.9% background contamination. From the analysis of 1.7 × 1011 kaon decays collected in 2003–2004, the branching ratio in the full kinematic region is measured to be BR(K
± → π
±
π
0
e
+
e
−)= (4.24 ± 0.14) × 10−6. A detailed study of the kinematic space shows evidence for a structure dependent contribution. Both measured BR and structure dependent contribution are in perfect agreement with theoretical predictions based on Chiral Perturbation Theory. Several P- and CP-violating asymmetries are also evaluated.
Prospects for kaon physics at LHCb
Authors: Dettori F
Published: June 2020

Despite not being designed for it, the LHCb experiment has given world-leading contributions in kaon and hyperon physics. In this contribution I review the prospects for kaon physics at LHCb exploiting the already acquired data and the current and future Upgrade scenarios.
Searches for lepton flavor and lepton number violation in K
+ decays with NA62
Authors: Duk V
Published: June 2020

The NA62 experiment at the CERN SPS provides unique opportunity to study rare and forbidden decays of K
+ mesons. Using the data collected in 2017 a search for the lepton number violating decays K
+ → π
−
µ
+
µ
+ and K
+ → π
−
e
+
e
+ has been performed. New upper limits on the branching ratio have been obtained: 4.2×10−11 for the muon and 2.2×10−10 for the electron mode (90% confidence level). These results improve the existing limits by factors of 2 and 3 respectively.
Excitation dependent emission of terbium aluminium garnet doped with gadolinium
Authors: Kaur Jasmeen , Rani Suman , Lal Bansi
Published: June 2020

This study reports the emission (400-700nm) properties of Gd (0.1, 0.5, 1.0 mol%) doped TAG nanophosphor synthesized by sol gel technique. Powder XRD spectra of doped TAG were indexed using JCPDS file No. 17-0735 implying that the basic structure of TAG remained unchanged on doping. The emission was excited with 280, 380 and 460nm radiation from a Xe lamp. The spectral features of the emission spectra were almost independent of both the doping as well as the excitation radiation. However, Gd concentration dependent variations in the emission intensity were observed. The observed emission intensity was maximum in TAG doped with 0.5mol% Gd while quenching was observed at 1.0mol% concentration level. This concentration dependent intensity variation which also depended on the wavelength of the excitation radiation could be due to energy exchange between Gd and Tb ions.
A COMPREHENSIVE REVIEW ON GRAPH PEBBLING AND RUBBLING
Authors: Sreedevi S , Anilkumar M.S
Published: June 2020

A graph pebbling is a combinatorial game played over a fixed graph and a pebbling move is the method of removing two pebbles from one endpoint and sets one pebble at the other endpoint, while the remaining pebble is dropped. A graph’s rubbling number is the smallest number necessary to ensure that any vertex can be reached from any pebble distribution of pebbles. A vertex is reachable if a pebble can be placed using pebbling or rubbling moves. In this paper we have attempted to give a summary of how graph pebbling have undergone a lot of challenges to derive many strong results in proof complexity. A comprehensive review of the existing works in pebbling and rubbling is carried out in a sequential order.
Pairwise compactness in bihypertopological space
Authors: Singh Harjot , Mishra Sanjay
Published: June 2020

The objective of this paper is to study pairwise open cover and pairwise compactness in hyperspace of a bitopological space, named as bihypertopological space. Various results, analogous to results of compactness in traditional topology, are obtained for bihypertopological space. We also investigate relation between pairwise compactness in bihypertopological space and pairwise compactness in the original bitopological space.
Impact of Yellow Fever with Multiple Control Measures: Mathematical Model
Authors: Kalra Preety , Ratti Indu
Published: June 2020

Yellow fever is a vector borne disease caused by infected mosquitoes. It is a life threatening disease which is endemic in many parts of the world. Continuous efforts to eradicate and minimize the disease burden are being done using theoretical and statistical models. In this paper, we have considered a mathematical model for transmission of yellow fever for human and mosquito populations. Vaccination and insect repellent are introduced in the model as control measures. Stability analysis for disease free equilibrium is being done. The threshold parameter, that is, reproduction number is calculated which will predict the direction in which disease can be eliminated.
On the sum of reciprocals of Jacobsthal polynomials
Authors: Priyanka  , Verma Vipin
Published: June 2020

In this paper, we have obtained the infinite sum obtained from the reciprocals of Jacobsthal polynomial and Jacobsthal-Lucas polynomial. Also, we have obtained some inequalities involving the infinite sum of reciprocals of squares of Jacobsthal polynomial and Jacobsthal-Lucas polynomial.
Reliability and Sensitivity assessment of a Thermal power plant using Boolean function technique
Authors: Dhiman Pooja , Kumar Amit
Published: June 2020

The aim of aforementioned paper is to investigate the terminal reliability, mean time to failure and sensitivity analysis for a thermal power plant based on minimizing Boolean expression approach. A thermal power plant be expressed by four major subsystems namely conveyer, boiler, turbine and generator arranged in mixed configuration. Conveyer and boiler both individually have two units in parallel redundancy. Throughout the task thermal power plant may work in basically three different states namely good, degraded and failed state. The various results regarding reliability, mean time to failure (MTTF) and sensitivity analysis are authenticated with the help of graphs.
The role of combination beads for effective removal of antibiotic cefixime from water: towards of better solution
Authors: Ahmad Aijaz , Dutta Joydeep
Published: June 2020

Presences of antibiotics in water bodies have received widespread attention due to their potential toxicity. In this study, adsorption efficiency of synthesized beads was investigated, which were prepared by using chitosan, almond and walnut shell powder. The properties of the beads were characterized using Fourier-transform infrared spectroscopy analyses (FTIR), Scanning Electron Microscope (SEM) and energy dispersive X-ray analysis (EDX). The functioning of beads was attributed towards its antibiotic adsorption. To study the effect of dosage, pH, initial concentration and time on antibiotic adsorption, a batch adsorption experiment was conducted. Adsorption isotherms and kinetics were also studied. The adsorption isotherm experimental data is aligned with Langmuir for AWC (50% almond shell: 25% walnut shell: 25% chitosan) and CAW (50% chitosan: 25% almond shell: 25% walnut shell) beads. Whereas, WAC (50% walnut: 25% almond shell: 25% chitosan) beads follow Freundlich isotherm. The experimental data was fitted by pseudo-second order. In this study, Low initial concentration of beads was promising material for antibiotic adsorption from contaminated water.
Effect of Heavy Metal Contaminated Waste Water Irrigation on Enzymatic and Non Enzymatic Antioxidants in Some Selected Vegetables
Authors: Singh Jagdev , Mohan Dr Anand
Published: June 2020

The study was conducted to investigate the bioaccumulation of heavy metals (As, Cd,Cr and Pb) and their effect on the antioxidant level and activity in vegetables Raphanus sativus, Spinacea oleracea, Brassica oleracea and Lycopersicum esculentum irrigated with heavy metal loaded waste water of Buddha Nullah. The results of the study revealed bioaccumulation of heavy metals in vegetables and the level of non-enzymatic antioxidants, ascorbic acid and proline and enzymatic antioxidants, catalase and peroxidase was found to be much higher in waste water irrigated vegetables in comarison to the level of bioaccumulation of heavy metals as well as antioxidants in same vegetables irrigated with normal borewell water as control. This indicates that heavy metals induce oxidative stress (ROS) in the plants at cellular level and to nullify the toxic effect these heavy metals the cell mechanism increase the production and activity of both non-enzymatic and enzymatic antioxidants.
Modulating Effect of Drug Chloramphenicol on the Aggregation Behavior of the Ionic Liquid 1-tetradecyl-3-methylimidazolium Bromide: A Conductometric Study
Authors: Kumar Harsh , Kaur Ramanjeet
Published: June 2020

In this report, the influence of addition of different wt. % of drug chloramphenicol on the aggregation phenomenon of 1-tetradecyl-3-methylimidazolium bromide (SAIL) has been extensively examined using conductometric technique at temperatures 298.15K, 308.15K, 318.15K. Utilising the values obtained from conductance measurements, the critical micelle concentration (cmc) and degree of dissociation (α) for the micelles formed in the temperature range of 298.15-318.15K at different wt. % of drug chloramphenicol in the medium have been achieved. The various thermodynamic parameters (ΔGm
0, ΔHm
0, ΔSm
0) of micellization were evaluated by conductivity measurements. Effect of additive (drug) on the aggregation behavior of the ionic liquid have been discussed.
Thermogravimetric Analysis of Pinus Wood For Kinetic Analysis by Using Coats and Redfern Method
Authors: Chouhan Ashish Pratap Singh , Husain Abid , Mukherjee Suman
Published: June 2020

Pinus wood is selected for this study because it is freely available near to Punjab in Jammu & Kashmir region. Kinetic studies are extremely useful for the interpretation of reaction mechanism and catalytic phenomenon, optimization, behavior on molecular basis and build-out of new chemical processes. This study is highly focused to characterize the pinus wood by using proximate analysis, FTIR analysis, calorific value and TGA. In this study kinetics evaluation performed by using Coats and Redfern method, this method is non-isothermal type and throughout this study it was observed that pinus wood has the high thermal stability and it can be used for the applications for the production of clean and eco-friendly energy.
Study on Oxygenation Performance of Solid Jet Aerator having Circular Opening corresponding to Variable Jet Length and Flow Area
Authors: Shukla Bishnu Kant , Sharma Pushpendra Kumar , Goel Arun
Published: June 2020

Mechanical aerators are most commonly used for aeration process in treatment of waste water. Oxygen exchange mechanism by plunging jet of water is a superior method to transfer oxygen into pool of water than regular systems. Surface jet aerators, which are closed and simple systems, are uncomplicated in design, working and maintenance. In this study, experiments were conducted on models of solid jet aerators having circular shaped opening with variable jet lengths and area for different discharges. Penetration depth, oxygen transfer factor and Oxygenation efficiency were measured for different jet lengths, corresponding to each area and discharge. It was observed that penetration depth and oxygen transfer efficiency increments with increase in discharge and jet length in air whereas oxygen transfer factor increases with jet length in air only. With the results achieved, an efficient aerator model was suggested for a given set of inflow and environmental conditions.
A Simulation of Nominal Group Technique using Particle Swarm Optimization
Authors: An Zhenzhou , Yang Yang , Ma Yu , Zhang Jun , Zhou Hui
Published: June 2020

The nominal group technique (NGT) is a pattern of group decision-making technique in organizational behavior. Its research work is mainly focused on applications in different fields, and there is less research on algorithm simulation. In this paper, a method of NGTPSO is proposed in which NGT will be introduced into PSO and an attempt will be made to simulate NGT using PSO. From the perspective of PSO, PSO using NGT adds group decision-making technique. It characterizes the activity of individual and group through the grouping, individual optimizing, small-group discussion operation, large-group discussion operation and large-group decision operation. From the perspective of NGT, the decision process of NGT is simulated by PSO. The results show that the simulations of the algorithm are effective. The simulations show that small-group decision is better than or equal to individual decision and large-group decision is better than or equal to small-group decision. This is consistent with the basic principles of organizational behavior and it provides a good explanation for the relationship between NGT and PSO.
Anomaly Detection for Internet of Things Based on Compressed Sensing and Online Extreme Learning Machine Autoencoder
Authors: Yu Yun , Wu Xiaojun , Yuan Sheng
Published: June 2020

Abnormal events refer to specific events, such as forest fire, occurring in the wireless sensor networks of the Internet of Things (IoT), whose behaviors are quite different from normal events. By learning the underlying structure of sensor data, users can be helped to learn about the occurrence of these events as soon as possible. Due to the large number of sensors in the IoT and the periodic collections of data, sensor data has the problems of high dimensions and large amount, and the transmission of a large amount of data in the network is not a small challenge for bandwidth. In addition, the sensor data is unlabeled, so it is time-consuming and unrealistic to manually label all the data. Abnormal events in the IoT require low delay, such as gas concentration monitoring, In the IoT, data is generated continuously, so a well-trained model cannot remain unchanged, and features of new data need to be continuously learned. On account of the limitation of hardware, edge nodes cannot undertake the complicated and time-consuming task of model training and detection. None of the existing algorithms can meet the above requirements well, so this paper proposed an algorithm based on Compressed Sensing and Online Extreme Learning Machine Autoencoder named COELMAE. The proposed algorithm can carry out anomaly detection in low delay, unsupervised and online learning, and also has low computational complexity. What’s more, the algorithm can reduce the amount of data transferred about 60%.
Overview of two-stage object detection algorithms
Authors: Du Lixuan , Zhang Rongyu , Wang Xiaotian
Published: June 2020

Nowadays, object detection has gradually become a quite popular field. From the traditional methods to the methods used at this stage, object detection technology has made great progress, and is still continuously developing and innovating. This paper reviews two-stage object detection algorithms used at this stage, explaining in detail the working principles of Faster R-CNN, R-FCN, FPN, and Casecade R-CNN and analyzing the similarities and differences between these four two-stage object detection algorithms. Then we used HSRC2016 ship dataset to perform experiments with Faster R-CNN, R-FCN, FPN, and Casecade R-CNN and compared the effectiveness of them with experimental results.
Electrically Tunable Non-volatile Reflective Display Pixel Structure Based on Phase Change Material
Authors: Zhou Tong , Gao Ding , Cao Shiyue , Cheng Zhiyuan
Published: June 2020

A multi-layered non-volatile solid-state reflective display pixel structure composed of a Fabry-Perot type resonance cavity and an ultrathin phase change material film has been fabricated and analysed. By electrically switching the phase states of a phase-changing Ge2Sb2Te5 (GST) film using an electric micro-heater under the stack, a pronounced colour change in pixel structures is observed, which is attributed to the change in the resonance condition of the multi-layered stack. Furthermore, the range of attainable colour can be widened by exploiting a spatial colour mixing structure.
A Study of English-Chinese Translation of Commercial Advertisements under the Background of “Internet +”
Authors: Chen Guoping
Published: June 2020

Under the implementation of the national strategy, “Internet +” is closely integrated with various traditional industries and has become one of the main driving forces for the economic development of the industry. For industrial development, “Internet +” provides technical tools, basic platforms, and link elements for building an ecosystem. The translation of commercial advertisements between English and Chinese is an important part of the language service industry. It is a major member of the cultural industry and guarantees the demand for commercial advertisement language services under the “Belt and Road” strategy in China. The combination of “Internet +” and commercial English-Chinese translation can promote the transformation and upgrading of commercial English-Chinese translation services. When translating commercial advertisements between English and Chinese, it is not only just a simple conversion of corresponding code symbols, but also needs to comprehensively consider the language background of national culture, customs and social development. In the context of “Internet +”, the translation needs to reorganize the original information on the premise of ensuring that the semantics are basically equivalent and the functions are similar. With the help of modern computer network technology and cloud computing platform technology, this article builds an Internet-based translation platform to provide support for the translation, thereby achieving good translation results.
Accurate Exercise Recommendation Based on Multidimension -al Feature Analysis
Authors: Zhang Shu , Cai Jiaqi , Zhuge Bin , Dong Ligang , Jiang Xian
Published: June 2020

With the rapid development of the Internet, online learning has developed rapidly, and learners are increasingly demanding the personalization and practicality of exercise. Facing the massive exercises in the online learning platform and the online examination system, how to choose the exercises that can be targeted and can make up for the knowledge loopholes has become a hot topic in the field of personalized recommendation of current teaching resources. In view of the fact that learners have a variety of learning features, and there are a large number of online exercises, various types and varying degrees of difficulty, this paper proposes a precise recommendation method based on Multidimensional features analysis for exercises. It quantifies the potential relationship between the learner and the exercise from three aspects: the heat of the exercise itself, the relevance of the knowledge among the exercises, and the similarity of the learner’s style, using the linear combination and the Learning to Rank method to build the recommendation model to match learner and exercises exactly. Experiments show that the mean average precision of the ReMFA method reaches 36.8% when recommending five candidate exercises, which can provide learners with personalized exercise recommendation services, thereby improving the learner’s learning efficiency.
Research on Network Isolate Method in Cloud Environment
Authors: Lai Xinming , Wang Haitao , Jing Zhao , Fan Zhang , Chao Zhao , Wu Gang
Published: June 2020

This paper proposes a network isolation method for large-scale cloud environments. The method run an Envoy-based endpoint program to proxy all network traffic on a physical node. And by configuring a route discovery registration center to uniformly maintain the network meta information of all virtual machines, the virtual machine uses the native VLAN technology to divide the user’s subnet to ensure the communication performance of the subnet nodes and the virtual machine network maintained by the route discovery center. Meta information improves the speed of virtual machine ARP addressing and improves cross-node network request performance. Envoy’s network proxy technology is used in conjunction with the route discovery center to broadcast the subnet broadcast communication of all virtual machines to the route discovery center, which improves the accuracy of the broadcast and greatly improves the utilization efficiency of the public network bandwidth.
Architecture of embedded intelligent video analysis system for forest fire prevention
Authors: Zhang Baiguo , Zhang Zhihao
Published: June 2020

Forest fire has always been an important hidden danger in forestry management. It is necessary to monitor and manage forest fire through video monitoring system. However, due to the lack of real-time performance of traditional video monitoring system and the difficulty in data processing, an embedded intelligent video analysis system is designed. The system uses a software and hardware design method based on Zynq SoC, first, each functional module of the hardware architecture is divided, then the system software is designed, and finally the system is evaluated as a whole. Based on the application requirements of forest fire prevention, this paper focuses on the detailed description of the underlying hardware architecture and operating system software design, and provides some value and reference for the application scenarios of forest fire prevention.
Estimation of triceps muscle strength based on Mechanomyography
Authors: Xie Jiazhi , Zhang Yue , Yang Ke , Xia Chunming
Published: June 2020

The aim of this study is to establish a reliable and widely applicable muscle strength (MS) estimation model based on the Mechanomyography (MMG). Seven healthy male volunteers were recruited to collect MMG and MS during the isometric contraction of their triceps. For MMG, 18 features were extracted. For the extreme gradient boosting (XGBoost) model and the quadratic polynomial (QP) model, the feature combination with the best estimation result was selected. The MS estimation performance of the XGBoost model and the QP model were compared. The performance of the QP model on the estimation of MS in different frequencies, different fatigue states and time periods was evaluated by using t-test. The results showed that when the number of features exceeds three, the model estimation accuracy has not improved significantly; and there was no significant difference in the estimation result of MS between the two models (p < 0.05), though the QP model was slightly better. The normalized root mean square error (NRMSE) and goodness of fit R of the MS estimation by the QP model were: 0.1343 ± 0.0296 and 0.8273 ± 0.0376. There was no significant difference in the MS estimation results in different conditions (p < 0.05).
Drive control strategy of two-wheel independent drive electric vehicle
Authors: Li Jiashun , Yang Yang , Xiong Yuhang
Published: June 2020

According to the advantages of two-wheel independent drive electric vehicle that the torque and rotational speed of the drive wheel can be easily measured, a driving control strategy of driving antiskid control and torque coordination control is proposed based on road surface identification slip rate and adhesion coefficient. The principle of road surface identification is given. According to the signals of wheel speed sensor, lateral acceleration, longitudinal acceleration and torque sensor, the wheel slip ratio, road surface adhesion coefficient, vertical force and longitudinal force are calculated. Combined with μ-S function curve proposed by Burckhardt et al., the road surface adhesion coefficient and optimal slip ratio are identified. Driving antiskid control strategy adopts PID control technology based on road surface identification of optimal slip rate, peak adhesion coefficient and optimal slip rate, which mainly includes four parts: establishment of wheel stress model of two-wheel independently driven electric vehicle, approximate calculation of slip rate and road adhesion coefficient, optimal slip rate estimation based on fuzzy control and PID controller design based on optimal slip rate. The torque coordination control adopts PID control method based on ideal yaw rate.
Research on three-phase four-wire active power filter based on LCLCL coupling structure
Authors: Hu Jinbo , Liang Jiajian , Ding Yizhou , Ding Ankang , Yin Zhanqing , Li Zirui
Published: June 2020

In this paper, the main circuit topology of the three-phase four-wire active power filter (APF) and its harmonic current detection and control algorithm are studied. An active power filter system combining LCLCL filter and a three-phase H-bridge structure is proposed. This paper has applied harmonic detection algorithm based on an improved synchronous phase-locked loop (SRF-PLL) and recursive discrete Fourier transform (RDFT) while using triangular carrier modulation control based on PI adjustment to realize the harmonic compensation of the power filter to the grid current. The system has a notch effect on the harmonic at the switching frequency. It can detect the fundamental component and each harmonic component of the load current separately with a small amount of calculation, good real-time performance. Finally, a 5KVA single-phase APF prototype was built to test the superiority of the main circuit topology and the algorithm of current detection and control.
Firewall Technology in Computer Network Security in 5G Environment
Authors: Song Xinghua
Published: June 2020

in the Process of Computer Network Security Maintenance, Firewall Technology is the Main Security Maintenance Approach and Can Play an Effective Protection Role. Due to the Popularity and Widespread Use of Computer Technology, Network Security Has Received Widespread Attention from All Walks of Life. the Purpose of This Article is to Study Firewall Technology in Computer Network Security Based on 5G Environment. 5G Mobile Networks Also Have Some Shortcomings, Such as Weak Network Penetration Capabilities. Once the Base Station is Not Fully Deployed, There Will Be Gaps in the Borders of Communication Cells, Resulting in Network Data Transmission Interruption. in Order to Solve the Above Problems, This Paper Proposes Mobile Network Optimization Measures. Based on Many Years of Practice and Exploration, It Focuses on Describing the Complex Communication Application Scenarios in Cities, and Introduces a Variety of Mobile Network Optimization Technologies to Achieve Seamless Network Coverage and Ensure That People Can Use Mobile Communication Networks Normally. the High-Speed, Large-Capacity, Low-Latency, and High-Reliability Services Brought by 5G Will Have an Impact on the Local Optical Cable Architecture and Core Utilization. According to the Experimental Results, the Effective Application of Firewall Technology Can Greatly Improve the Security of Computer Networks and Ensure the Security of Computer Networks to a Great Extent.
Image Raindrop Removal Method for Generative Adversarial Network Based on Difference Learning
Authors: Chen Renhe , Lai Zhenyi , Qian Yurong
Published: June 2020

Due to the interference of the external environment such as rainy weather on the camera, raindrops can easily adhere to the lens and seriously affect the quality of the photos taken. Therefore, it is of great significance to remove raindrops from the image and improve the quality of the photo. In this paper, a raindrop method for generative adversarial network images based on differential learning is proposed. The general generative network is to input images with raindrops and output clean images. The generative network in this paper does not directly output clean images, but learning the difference between images with raindrops and without raindrops, then subtract the learned difference from the image with raindrops to generate a clean image. In order to learn this difference more effectively, adding reconstruction loss to the generative network, the pre-trained VGG-16 network is used to extract the difference between the generated image and the real image features and calculate the mean square error. The experimental results show, the method in this paper can not only remove the raindrops in the image well, but also reconstruct the image information of the part blocked by the raindrops. The image processed by the algorithm in this paper is tested using the yolov3 target detection algorithm, which can significantly improve the recognition accuracy of the detection algorithm.
Accurate road segmentation in remote sensing images using dense residual learning and improved focal loss
Authors: Ma Junjun , Xu Zhaohong , Zheng Ergong , Fan Qiongjian
Published: June 2020

In this paper, we propose a road segmentation model using deep learning technology. The model is essentially a U-net with pre-trained DenseNet-169 encoder. Multi-scale and high-level semantic information are extracted effectively by dense residual learning and attention mechanism. In addition, an improved focal loss function is proposed to handle extremely imbalanced road samples. Experimental results demonstrate that our proposed road segmentation model can accurately extract complex road areas in remote sensing images and has IoU of 0.6308 which ranks 22st in the DeepGlobe Road Extraction Challenge leaderboard at the time of writing.
Design of monitoring terminal for SAS based on flexible fabric electrode
Authors: Zhang Shuo , Chang Zhiqiang , Zhang Xiaofeng , Ge Wei , Ji Xiaoqiang
Published: June 2020

Sleep apnea syndrome is a serious threat to the life and health of patients. In this paper, we designed a sleep apnea monitoring system based on flexible fabric electrode, and completed the specific hardware design including flexible fabric electrode, ECG signal conditioning module, microcontroller module and Bluetooth module. Among them, ADS1292 is mainly used for ECG signal conditioning, and EFM32 is selected as microcontroller. Finally, the experimental results show that the collected signal can clearly identify the ECG characteristics such as QRS wave, and meet the requirements of the subsequent research of ECG signal. The terminal equipment we designed is low cost, comfortable to wear, and can be monitored for a long time, which is suitable for daily household monitoring.
A Method of Describing Uncertain Emotions of Facial Expressions
Authors: Lin Junhuan , Chen Yuefen
Published: June 2020

In order to describe uncertain and fuzzy emotions in recognizing facial expressions, a PAD regressive model based on deep convolutional neural network model is built to quantize the emotions, by which the facial expressions can be mapped to the emotional space of PAD. Then the emotional membership function is proposed to describe the uncertainty and fuzziness of the emotions in the space of PAD. Finally the testing results demonstrate that the regressive model performs well in recognizing facial expressions and the results from describing the emotions quantitatively agree with the human cognition to facial expressions.
Real-time detection of UAV detection image of power line insulator bursting based on YOLOV3
Authors: Chen Songbo , Su Chao , Kuang Zhenxing , Ye Ouyang , Gong Xiang
Published: June 2020

The insulator fault of high voltage line is the main factor of transmission accidents, so positioning and detection of burst insulator of power line has become an important part of routine detection. Traditional UAV detection is still mainly to evaluate the image transmitted by UAV manually, which is not only time-consuming, but also not accurate. In this paper, UAV aerial images are used to make datasets, the problem of insulator class imbalance (normal insulator and burst insulator) in the model training process is solved by using data augmentation, an improved depth learning algorithm is proposed based on YOLOv3, which provides rich semantic information for prediction layer by adding feature mapping module. At the same time, the residual network is introduced into the feature extraction, which improves the detection accuracy of small objects, more effectively extracts the object features of burst insulator, carries out real-time object detection and positioning, and completes the daily detection of insulator state of power transmission lines. The experimental results show that the detection accuracy (mAP) of the improved YOLOv3 algorithm is 91.22%, and the detection speed is 28 frames/s. The recall rate and Intersection Over Union (IOU) are also improved.
3D Point Cloud Surface Reconstruction Based on Divide-and-Conquer Method in Laser Scanner
Authors: Lyu Yuan-Zhi , Guo Min , Sha Ou , Zhang Hong-Yu
Published: June 2020

As to the problem of surface reconstruction in 3D laser scanner, we propose a divide-and-conquer based method, and realize the continuing growth of the reconstructed surface through comprehensive analysis of the correlations of scanning line point cloud data. First of all, filter the scanning line point cloud data, then confirm the relationship between the newly-insert point and the generated surface by using the local search algorithm based on adaptive point cloud segmentation, and finally, classify the newly-inserted points as sparse points, density points, growth points and flyback points by using the given maximum and minimum distance thresholds, and then the specific surface reconstruction is performed according to the point’s classification. The experimental results show that the local search algorithm greatly reduces the calculation of the insert location of the point cloud compared with the global traversal search algorithm; the proposed method can process the flyback points, enhancing the repairability and the expandability of the reconstructed 3D surface compared with the traditional method. Furthermore, the quality of the reconstructed 3D surface, the generating speed and the occupation of storage space can all be controlled by adjusting the maximum and minimum distance thresholds according to actual demand.
Research and Application of Multiscale Representation and Regularization Method in Image Recognition
Authors: Heng Wang , Zheng Bi-Geng
Published: June 2020

Image Recognition is the Use of Computers to Process, Analyze and Understand Images to Identify Different Patterns of Objects and Images. in This Paper, We Introduce the Idea of Nonlocal Processing on the Basis of Regularization Tv. the Process of Image Recognition System is Divided into Five Parts: Image Input, Preprocessing, Feature Extraction, Classification and Matching, in Which Preprocessing Can Be Divided into Image Segmentation, Image Enhancement, Two Value Reduction and Refinement and So on. the Paper Presents Research and Application of Multiscale Representation and Regularization Method in Image Recognition. At the Same Time, through Programming in the Matlab Programming Environment to Achieve the Relevant Algorithm, through the Actual Image Recognition Experiments, the Use of These Conclusions, and Finally to Accurately Identify the Results.
Research on Short-term Traffic Flow Forecast and Auxiliary Guidance Based on Artificial Intelligence Theory
Authors: Wang Rongxia
Published: June 2020

With the development of social economy, intelligent transportation system (ITS) has been booming. It is mainly to realize the omni-directional, real-time, accurate and efficient guidance and control of transportation in a large range. Traffic flow prediction, especially short-term traffic flow prediction, is the basis of urban traffic control and guidance, so traffic flow prediction system is one of the important subsystems in its. Short-term traffic flow prediction technology belongs to the important research field of intelligent traffic control and vehicle guidance. It can help cities to conduct intelligent traffic guidance and enable users to choose the optimal path. Prediction of road traffic flow state and auxiliary guidance are very important basic theories. Based on the theory of artificial intelligence, this paper analyzes the short-term traffic flow prediction and auxiliary induction methods, points out the limitations of the existing prediction methods, and proposes a short-term traffic flow intelligent prediction method combined with artificial intelligence technology.
Development and Trend of Space-based Information Network
Authors: Liu Zhenhua , Lin Chuanwen , Chen Gang
Published: June 2020

With the development of space-based technology, the construction of the space-based network has been into a period of major change, countries are putting forward their own space-based network and getting them off the ground. This paper analyzes the space-based network development situation, introducing the SCaN network in the United States, Europe ISICOM plan and the development of China’s SGIN, discussing the trend of the development of the space-based information network. At present, the construction of space-based network is still based on the foundation network as the core, the space-based system as the expansion, based on the communication interruption satellite, gradually evolves into the space-based network, in the future it will integrate the space-based navigation, space-based information acquisition to form a space-based integrated information network.
Comprehensive Evaluation Method for Network Node Importance based on Constructed Tree
Authors: Yang Yuxin , Peng Yali , Huang Minghe
Published: June 2020

The importance measurement of nodes in directed weighted networks is of great significance for theoretical research and practical application of networks. Aiming at the directed weighted network model in actual networks, based on the special transformation of graphs and tree roots, this paper proposes a comprehensive quantitative assessment method for the importance index of nodes based on the directed weighted network’s global properties, local attributes, network location and bidirectionally propagation. This method transforms the nodes to be analyzed in the graph to root, constructs a bidirectional depth-affected XD tree and a breadth-affected XB tree with the node to be evaluated as the root of the tree. Then comprehensively consider the two-way influence of the node level, node neighbors and the closeness between neighbors in the two trees constructed, and the in-out effects, build a deep impact evaluation model at the two-way level, two-way neighbor information and comprehensive evaluation index of clustering coefficient. By calculating the comprehensive importance value of each node in the network, the comprehensive ranking of the importance of the nodes in the network can finally be obtained. The robustness experiment of ARPA network shows that the G value of the important node quantified by this method has absolute advantages, this method can effectively analyze key nodes in the network.