bluuebunny/crossref_metadata_2025 huggingface dataset:
Charge and Discharge of Capasitors: Revisiting the Analogy with Water in Connected Containers
Authors: Hasanah A W , Sunarya A S , Viridi S
Published: June 2022

Analogy can be considered as an approach in teaching an abstract concept, where in electricity related to capacitor, water and containers are sometimes used. In this work we try to summerize available reports related to this. Usually, the water flow (WF) represents electric current, water height (WH) is an analogy to electric potential difference, container floor area (FA) can be viewed as capacitance, hose (HS) is as connecting wire, and water reservoir with large floor area (WR) behaves as a battery. The voltage saturation while charging the capacitor and voltage decaying while discharging capacitor can be obtained with the use of WH, FA, HS, and WR elements. Even it is not so ideal, but the observation tends to show qualitatively similar curves. We also present comparation table between electric circuit and water circuit. Unfortunately, not every aspect in electric side has the counter part in the water side. The difference between the two systems are clear and must be noticed to avoid misconception for the teaching target.
Incorporation of Perovskite Cs2SnI6 into Dye Sensitized Solar Cell Structure and Its Optimization
Authors: Dosi Amaldeus Tani , Rahayu Setiya , Wulandari Priastuti
Published: June 2022

Generation of Dye Sensitized Solar Cell (DSSC) has become one of considerable research in the solar cell technology in the last two decades due to the ease of fabrication process. Several studies have been conducted to improve DSSC performance, for example by modifying the structure of DSSC or by adding perovskite material and metal nanoparticles (Au or Ag). Because lead is toxic and has a negative impact to the environment, other perovskite type of materials that are more environmentally friendly are needed. Tin based perovskite (Cs2SnI6) is known more stable in air than Pb based perovskite and it can be synthesized in an air environment. In this study, we attempt to synthesis Cs2SnI6 perovskite and incorporate the material into N719 dye solution in order to enhance the performance of DSSC. Cs2SnI6 was synthesized by simple chemical mixing at room temperature from CsI and stannic iodide (SnI4). The absorbance spectra of Cs2SnI6 perovskite show two specific peaks at wavelength of 293 nm and 362 nm. The energy band gap obtained by the Tauc-Plot method is about 3.1 eV. The performance of our fabricated DSSC device was done by J-V measurement. In our experiment, the addition of Cs2SnI6 into N719 dye solution in DSSC structure reveals the highest PCE value of 3.97% in comparison to PCE value of reference that is about 1.56%. However, the PCE value was drastically reduced from 4.03% in the 1st week to 1.07% in the 9th week for the case of device with addition ethanol solvent in perovskite
Optimization of metal nanoparticles concentration in dye solution to enhance performance of dye sensitized solar cells
Authors: Rahayu S , Dosi A T , Wulandari P
Published: June 2022

In this study, we incorporate metal nanoparticles of AuNP and AgNP into dye N-719 solution in order to enhance the light absorption of dye-sensitized solar cells (DSSCs) device. AuNP or AgNP was mixed into N-719 dye solution by optimized the concentration of metal NPs. The optical property of the mixtures was investigated by use of UV-Vis spectroscopy while the morphology of the solutions was captured by TEM microscopy. The performance of DSSCs was done by J-V measurement equipped with solar simulator under light illumination of 100mW/cm2. Our fabricated DSSC devices show the enhancement of current density and power conversion efficiency (PCE) with the incorporation of metal NPs into dye layer. Addition of gold nanoparticle capped by dodecanethiols (AuDT) 5.66 wt.% reveals the enhancement of PCE devices from 1.58% without AuDT as reference to 2.77% with AuDT. Similar case for the addition of AgSC8 into dye of DSSC gives the same tendencies.
General Couplings Conditions of Four-Dimensional Maxwell-Klein-Gordon System
Authors: Mulyanto  , Akbar Fiki T , Gunara Bobby E
Published: June 2022

In this paper, we investigate the conditions for the Maxwell Klein Gordon system’s general gauge couplings in (3 + 1)-dimensional Minkowski spacetime. For the multi-interaction of photons and charged spin-0 particle, we begin with the Lagrangian with the general coupling turned on. The equation of motion is then derived in the form of a nonlinear wave equation. We obtained the general solution for the vector potential using the spherical means method. By considering the Coulomb gauge condition, we get the constraint for the couplings, which are critical in proving the global well-posedness of the solution.
The Semiclassical Methods for Hawking Radiations on the Kerr – Newman – Vaidya Black Holes
Authors: Salimi Ahmad H. , Triyanta
Published: June 2022

Hawking radiation can be described as particle tunnelling picture in semiclassical regime. In this research, we derived Hawking temperature and entropy of non-stationary black hole Kerr - Newman - Vaidya using two semiclassical methods, which are radial null geodesic and complex path analysis. These two calculations gave the same results. The Hawking temperature is, approximately, inversely proportional to the mass and non-stationary term. We also derived the entropy of the black hole that corresponds to the temperature formulations that were derived by semiclassical methods. The entropy formulations that were calculated obey generalized second law of black holes.
Composite of graphene and in-situ polymerized polyaniline on carbon cloth substrate for flexible supercapacitor
Authors: Sembiring Albert Willy Jonathan , Sumboja Afriyanti
Published: June 2022

Flexible and lightweight energy storage is required for powering wearable electronic devices. Among the developed energy storage devices, supercapacitors have gained much interest as energy storage for wearable applications through their long cycle life and high power density. This work presents a flexible supercapacitor based on carbon cloth coated with graphene/polyaniline nanocomposite. Graphene/polyaniline nanocomposite is adopted as active material due to its high stability and the synergistic feature of pseudocapacitive and electrical double layer capacitance. The nanocomposite is synthesized from aniline and graphene in the sulfuric acid solution containing carbon cloth by chemical oxidative method, allowing the aniline to polymerize directly on the carbon cloth and graphene. Flexible supercapacitor devices with PVA/H2SO4 gel electrolyte exhibit an areal capacitance of 194.90 mF/cm2 at a scan rate of 5 mV/s. The device retains 77.21% of its initial capacitance after 500 cycles of cyclic voltammetry tests and exhibits a good performance during bending at 90° and 180°. This work demonstrates the potentials of carbon cloth-based supercapacitors for high-performance wearable supercapacitors.
STEM Project Topics Relevant to the Physics Curriculum at High School Level
Authors: Pangesti Kurnia Ika , Triyanta
Published: June 2022

The scientific process is conducted through investigative activities ranging from simple investigations of the surrounding nature to more complicated investigations to predict natural phenomena and solve various problems. Science learning should be carried out with a scientific approach that emphasizes scientific processes in which interactions with technology, the environment, and other sciences fields could not be avoided. Science learning through a STEM (Science, Technology, Engineering, and Mathematics) education approach is among approaches that are world-widely suggested, including in Indonesia, as can be seen in the national curriculum focal points. Unfortunately, as far as our knowledge is concerned, there is no such guide for teachers in implementing STEM education, including suggestions on the real issues and topics of STEM projects related to those issues. In this paper, based on a study of the content of the physics curriculum at the high school level, we propose real problems related to physics contents and possible STEM project topics derived from these fundamental problems. We emphasize topics that are technologically simple and easy to implement nationally, including in remote areas, but pedagogically contain rich aspects of learning.
Entanglement dynamics of non-linearly coupled spin-boson model using hierarchical equation of motion approach
Authors: Wasesatama V A , Kosasih J S
Published: June 2022

One of the most intensively studied problems in the field of open quantum systems is the spin-boson model. In this paper, we consider an extension of the spin-boson model with non-linear coupling. We solve the entanglement dynamics of two independent spins quadratically coupled to a bath of harmonic oscillators, using numerically ”exact” approach of hierarchical equations of motion (HEOM). Without Markovian approximation, generalized influence functional formulation by Hu et.al is used to describe the environmental effect of noisy quadratic bath in high-temperature regime. Wotters concurrence is then applied to numerically solved reduced density matrix to visualize the entanglement dynamics. By adjusting the environmental parameters, we vary the degree of non-markovianity and found the elongated time of entanglement.
MFUC: Mitigating Transient Congestion for Multi-flow Updating in SDN
Authors: Xia Jiqiang , Zhang Surong , Lan Julong
Published: June 2022

Through the logically centralized control plane, software-defined network (SDN) provides giant convenience for the design of the network strategies, like load balancing, fault recovery, etc. However, when deploying those strategies on the data plane, transient link congestions may occur since the updating process among the distributed switches is asynchronous. To address this issue, we propose a congestion-aware mechanism for multi-flow updating in SDN. We first obtain the real-time traffic size of each flow to be updated through the link monitoring model. Then we use the congestion-aware algorithm to find the potential congested link and construct the dynamic dependency graph of the updating process, to generate the final updating sequence. Finally, the meter table is configured to limit the flow of crucial predecessor nodes that may have congestion deadlocks to mitigate the transient congestion.
A Novel 5G-advanced Core Network Intelligent Operation and Maintenance System
Authors: Zhang Xue , Li Huanan , Wang Dong
Published: June 2022

The 5G core network adopts Network Functions Virtualization technology, which forms a variety of virtual resources for general computing, storage, and network hardware to achieve dynamic and flexible deployment of network functions and resources based on needs. With large-scale commercial deployment of cloud-native 5G core network with network function virtualization technology, the operation and maintenance of 5G core network is facing new challenges. This paper describes the architecture and deployment characteristics of 5G core network, and analyses the challenges brought to operation and maintenance by new network characteristics such as SBA, NFV, MEC and separated UPF, as well as the difficulties of operation and maintenance of virtual deployed 5G core network. Combined with the architecture evolution and function enhancement of 5G-Advanced, the architecture and scheme of A Novel Intelligent 5G-Advanced Core Network Operation and Maintenance System are proposed. The architecture and scheme of 5G core network operation and maintenance system construction were proposed, and suggestions on the organizational structure of 5G core network cloud-network integration operation and maintenance were put forward, so as to provide reference for 5G core network cloud-network integration operation and maintenance. The proposed scheme improves the performance of operation and maintenance of 5G core network significantly.
Design IoT-based Collaborative Framework and Routing Method in Complex Emergency Situation
Authors: Zhu Xiaoguang , Chen Fengzhao , Zhang Yu
Published: June 2022

Emergency management affords a crucial responsibility to protect the lives and properties of our society through disaster prevention and emergency responses. Current research applied Internet of Things(IoT) and intelligent models to improve the efficiency of emergency responses. However, in a complex emergency, the responses require more dynamic and collaborative strategies to prevent an emergency at the starting point. Therefore, this paper proposes a collaborative framework and routing method to facilitate the combination of IoT systems and social forces. Firstly, we construct a framework through the induction of current collaborative emergency systems. Secondly, based on multi-modal sensors and directors, we propose a routing method to harness complex emergencies with route optimization and local communication. The complete system could be completed on light equipment and crowding data that are green and sustainable.
A Generalized Projetion Gradient Algorithm for Mathematical Programs with Complementary Constraints
Authors: Zhang Cong , Sun Limin , Xiao Ya
Published: June 2022

Against the shortcomings that many existing algorithms for solving the standard smoothing nonlinear programming would fail if they were used directly to solve the mathematical programs with complementary constraints( MPCC). By using a complementarity function and the idea of smoothing approximation method, the MPCC problem was transformed into a smoothing nonlinear programming. Combined with the supermemory gradient idea, a generalized projection gradient algorithm is proposed and its global convergence is obtained.
Mask Wearing Detection Based on Inceptionv4 and Multi-Scale Retinex Image Enhancement Algorithm
Authors: Zhang Hongfei , Liu Chun , Ho James , Zhang Zhiwei
Published: June 2022

The novel coronavirus is a contagious virus with a high mortality rate, and the international health emergency due to COVID-19 has never stopped since the outbreak, due to this situation, wearing masks has become a basic recommended public epidemic prevention approach for many countries. In the current shortage of medical human resources, we urgently need a non-artificial mask-wearing detection method. In this paper, the multi-scale Retinex algorithm is involved as the preprocessing step of the input image. The mask-wearing detection is based on the InceptionV4 convolutional neural network model. During the experiment, we compared and verified the superiority of the Inception part of the InceptionV4 model compared with the Stem structure of the GoogLenet model, and from LFW (Labeled Faces in the Wild), RMFD (Real-World-Masked-Face-Dataset) more than 10,000 samples were selected from the public datasets for model training. Finally, the precise rate reaches 97.3 %.
Adhesive Abrasive Detection for Diamond Images based on Improved Watershed Algorithm
Authors: Lin Yanfen , Fang Congfu , Gao Lizhen
Published: June 2022

Diamond images have characteristics of adhesive abrasives besides much background noise, irregular abrasive shapes and different abrasive size, which brings big challenges to accurate diamond abrasive detection. Therefore, an improved watershed algorithm is put forward to detect adhesive abrasive in this work. Firstly, the diamond abrasive image is filtered by Gaussian to suppress the background noise, and then the pre-processed diamond abrasive image is reconstructed by morphology. Through the distance transform of the reconstructed image, marking features for subsequent abrasive detection can be obtained. Finally, the watershed algorithm and extended-minima transform are used to finely detect diamond abrasives and separate adhesive abrasives, respectively, so as to realize the accurate detection of adhesive diamond abrasive image. According to the results of detection experiments, the proposed method based on improved watershed algorithm and extended-minima transform can accurately detect adhesive diamond abrasive images, the recall rate of abrasive is 94.8%, which indicates good recognition accuracy and robustness of the proposed method. The accurate detection results can be further used for subsequent image analysis and abrasive feature parameter extraction.
Applications and Current Status of AI in the Medical Field
Authors: Feng ZHAO , Hua XU
Published: June 2022

Artificial intelligence has developed very rapidly in recent years, resulting in a huge impact on all sectors of society. People are also paying more and more attention to AI. Artificial intelligence application in the field of medical treatment are more common, this paper introduces the main applications of artificial intelligence in medicine, common applications include virtual assistant, AI auxiliary diagnosis and treatment, medical robots, etc, through in-depth analysis of the various applications, found applications in the field of artificial intelligence in the process of all kinds of problems,There are common problems such as lack of unified norms and shortage of artificial intelligence talents, and the above problems are discussed in detail.Finding and solving problems provides a strong guarantee for the development of artificial intelligence in the medical field.It is believed that AI will provide greater help to both doctors and patients.
Comparative Analysis of Optimization Schemes of Carry Look-ahead Adder
Authors: Chu Shunan
Published: June 2022

Conventional CLA adder has has a large number of transistors and high input impedance, which affects various performance aspects, resulting in high delay and power consumption. Therefore, to increase the performance and reduce delay, several optimized structures of CLA are proposed. From the perspective of structure and power, this paper selects four different design schemes and uses Cadence Virtuoso 90nm technology to compare and analyze the optimization results in aspects of circuit area, delay and power consumption. The analysis results show that the conventional 4-bit adder structure can be improved by designing the carry term Field Effect Transistor (FET) network and replacing the existing gate circuit with a hybrid Gate diffusion technology (GDI) gate, which can reduce the number of transistors and the design circuit area. They also contribute to improving the power consumption, delay, power delay product (PDP) and other performance parameters. Pipeline technology and multi-layer CLA block technology are suitable for carry look-ahead adder with more bits and longer carry chain, which can shorten carry propagation time, further optimize processor performance and improve CPU computing efficiency.
Research on Influence of Battery Energy Storage System on Voltage Transient Stability
Authors: Liu Xinke , Li Peiqiang , Zhang Zhongkai , Zeng Jingjie
Published: June 2022

In view of the current transient stability of the grid voltage, this paper studies the reactive power support of the access point when the energy storage system is connected to the power grid by studying the four-quadrant working mode of the energy storage system. Using the energy storage system built in the Power System Analysis Software Package PSASP and the CEPRI36 node example, the transient stability changes of the power system voltage before and after the energy storage connection are simulated and compared. The results show that the energy storage has a restraining effect on the voltage fluctuation.
Research on accuracy performance evaluation technology of Beidou GBAS reference receiver
Authors: Liu Ruihua , Yang Huanfa
Published: June 2022

The ground based augmentation system (GBAS) uses ground subsystems including reference receivers to provide differentially correction Global Navigation Satellite System (GNSS) data to improve the overall accuracy and integrity of the system. The accuracy of the GBAS ground subsystem is measured in the pseudo-range domain, so it is necessary to perform pseudo-range domain accuracy testing of the GBAS ground equipment. Based on the B-value method, this paper presents the evaluation process of GBAS pseudo-range domain accuracy based on the BDS-3 new frequency points of B1C and B2a. The B-value methodology is based on broadcast pseudo-range correction data, which covers the differential correction data of all reference stations and considers ground system monitoring, and can reflect the impact of the multipath synthesis effect of different receiver combinations on the accuracy of the pseudo-range domain. The real-collected data shows that the built test system can reach a GAD-B3 accuracy level, and the B-value method can effectively evaluate the pseudo-range domain accuracy of BDS-3 GBAS reference receivers.
Research on customer’s electricity consumption behavior pattern
Authors: Wang Yi , Yang Zhengyu , Wang Yaojian , Gu Jie
Published: June 2022

The fine-grained customer load data provides a large amount of information for the analysis of customer’s electricity consumption behavior pattern. Therefore, this paper proposes an algorithm for identifying the electricity consumption patterns of electric power users based on k-means algorithm. Our method is verified on the electricity consumption data of Irish residents and Shanghai Southern Industrial and Commercial users. The experimental results show that our method can divide the curves with similar electricity consumption patterns efficiently.
Reserch on Optimization of Electronic Optical System of X-band Klystron
Authors: Liu Qiang , Shen Bin , Gu Honghong , Liang Yuan
Published: June 2022

This paper has completed the simulation of the X-band 1 MW klystron electronic optical system, and optimized the electron gun and focusing system respectively. The electron gun adopts a single electron beam scheme. The voltage and current of the beam is 80 kV and 45 A respectively, the perveance is about 2.0 μP , and the average emission current density of the cathode is 6.81 A/ cm
2. The focusing system adopts the design of electromagnetic focusing, and the maximum magnetic field in the uniform area is about 0.33 T. The calculation results show that the distribution of the electric field lines in the electron gun area is uniform, the fluctuation of the electron beam is uniform, and the DC pass rate of the electron beam reaches 100%, which meets the design requirements.
Harmonic source identification method based on sinusoidal approximation
Authors: Gao Peng , Tian Mingxing , Wang Lixun
Published: June 2022

The proportion of nonlinear electronic devices such as electric arc furnace is increasing day by day, and the proportion of harmonic content in power grid is also more and more cannot be ignored. Therefore, the identification of harmonic source has received the attention of experts and scholars in the industry at present. Therefore, how to accurately locate and reduce harmonic content from power system source becomes the first step to improve power quality. This paper firstly analyzes the causes of harmonics and points out that nonlinear load is the fundamental cause of harmonics in power system. Secondly, the load equivalent model, the composition of the model and the method to determine the model parameters are established. Meanwhile, the current distortion coefficient is introduced to determine the harmonic source. Finally, an example is designed to verify the feasibility and rationality of the proposed method. Compared with the existing analytical methods at present, the proposed method has significantly improved the accuracy of harmonic source identification.
Recognition of Active Deception Jamming for LFM Radar Based on Hyperdimensional Computing
Authors: Dong Hao , Wang Yan , Hu Wen
Published: June 2022

Active deception jamming is one of the common means to jam radar signals. How to effectively recognize active deception jamming is a challenge of modern radar technology. To address the accuracy and real-time of radar active jamming recognition in practical applications, we propose a fast recognition method of radar active deception jamming based on hyperdimensional computing. First, to address the high feature dimensions, we use the sparse representation of time–frequency diagrams as the input, which time–frequency diagrams are constructed by the jamming plus echo signals in multiple consecutive pulse periods. Second, to achieve a high accuracy and real time of recognition, we employ the hyperdimensional computing to map the input to hyperdimensional space for training and recognition. Last, in the recognition stage, the Hamming distance is adopted to measure the similarity of samples. We validate our method on nine types of radar active deception jamming. The experimental results show that compared with the existing mainstream machine learning-based methods, the proposed method greatly shortens the training time on the premise of maintaining a high recognition accuracy.
Control strategy of DC/DC converter for photovoltaic-storage-DC microgrid based on improved LADRC
Authors: Liu Fengyi , Guo Kunli , Hao Yifan , Cai Weizheng , Li Bohao , Lv Jiajun , Liu Luhao
Published: June 2022

Aiming at the problem that the DC bus voltage is easily affected by nonlinear noise of the converter, photovoltaic output power and load disturbance, a bidirectional DC/DC converter control strategy based on the improved Linear Active Disturbance Rejection Control is designed. Firstly, establish the mathematical model of the bidirectional DC/DC converter, and analysis of existing problems in traditional LADRC. On this basis, a new state variable is introduced to observe the differential of the total disturbance to improve its rapidity; Then a lead-lag correction link is connected on the total disturbance observation channel to suppress the problem of high-frequency noise amplification. Finally, the Bode diagram is used to analyze the performance indicators of the improved LADRC. The simulation results show that, compared with the traditional LADRC, the control strategy in this paper reduces the bus voltage amplitude fluctuation by 63%, the adjustment time by 59%, and the inductor current ripple by 66%, which is more superior to suppressing the DC bus voltage fluctuation.
Dual-frequency Hexagonal Helical Microstrip Slot Antenna Loaded with Resonant Ring
Authors: Shan Zhiyong , Gao Mingrong
Published: June 2022

A hexagonal helical microstrip slot dual-frequency antenna loaded with resonant ring is presented in this letter. By loading the resonant ring and slot, the dual frequency of the antenna is realized and the antenna gain is improved. The best performance of the antenna is obtained by the optimization experiment. The simulation results show that when the reflection coefficient of the antenna is less than -10dB, the impedance bandwidth is 1.45GHz-1.78GHz and 2.39GHz-2.52GHz, the corresponding relative bandwidths are 20.4% and 5.3% respectively, and the maximum gain is 3.54dB. The antenna has better performance, it can be used in modern communication systems such as global positioning system (GPS), bluetooth, wireless local area network (WLAN) and WIFI.
Infrared target detection method using adaptive feature fusion
Authors: Zheng Lu , Zhou Tongtong , Peng Yueping , Ye Zecong
Published: June 2022

As the key technology of low altitude airspace security and air attack, vision-based air target detection has better concealment and lower cost compared with radar, radio and other detection methods. Based on yolov3, this paper proposes an air infrared target detection algorithm using adaptive feature fusion, which can effectively improve the accuracy of air infrared multi-scale target detection. Firstly, the construction of air infrared target detection data set is completed, and the target characteristics in the data set are statistically analysed. Secondly, the output layer of backbone is adjusted, and the four times down sampling feature map is used to replace the eight times down sampling feature map to enhance the detection ability of small targets. Thirdly, aiming at the problem of weakening feature expression caused by cross-scale feature fusion in FPN, a pixel level feature adaptive fusion module is designed. Finally, two improved SPP modules are added to neck to enrich the expression ability of feature map through the fusion of local features and global features. Experimental results show that compared with yolov3, our algorithm improves the map from 86.53% to 90.26% while keeping the detection speed basically unchanged.
Direction-of-Arrival Estimation Under Coexistence of both Circular and Strictly Non-Circular Signals in Coprime Linear Array
Authors: Xu Haiyun , Li Hao , Cui Weijia , Yu Zhenhua , Quan Mengjiao
Published: June 2022

Direction-of-arrival (DOA) in coprime linear array involves the problem that existing algorithms have less taken signal features into consideration. Considering that there is coexistence of multiple both circular and strictly non-circular signals in communication systems, an approach to DOA estimation of high accuracy and degree of freedom is proposed in this letter. We first use the ellipse covariance matrix and matrix completion method to reconstruct the covariance matrix of a virtual linear array. This virtual matrix only concludes the components of noncircular signals. Then, we similarly use the covariance matrix and matrix completion method to reconstruct a new covariance matrix including all signals of another virtual linear array. We use the virtual non-circular covariance matrix to eliminate the non-circular components in another virtual matrix. Finally, this matrix only concludes the circular signals. And we apply multiple signals classification to obtain the DOAs of two kinds of signals separately. Simulation results show that the proposed algorithm can obtain a highest degree of freedom than existing algorithms and hold on a preferable accuracy.
Global Importance Analysis of Nodes Based on Complex Network Theory
Authors: Lin ShengNan , Li Shuai , Su Yang
Published: June 2022

Aiming at the effectiveness of global importance index of nodes in directed network, according to complex network theory, using degree index, intermediate centrality index, proximity centrality index and PageRank algorithm, the importance ranking of nodes is obtained,The global efficiency of the network and the number of nodes in the maximum connected subgraph are used as the criterion to attack the directed network with priority of node importance, analyzing the effectiveness of four indexes to evaluate the global importance of nodes.The global importance of nodes is studied by using the index with high effectiveness. By protecting the nodes with high global importance, the survivability and the overall efficiency of the directed network can be improved.
Parameter Estimation Processor for K-distribution Clutter Based on Deep Learning
Authors: Zhang Liang , Yang Wei , Zhi Shuaifeng , Yang Chen
Published: June 2022

This paper concerns the problem of parameter estimating of K-distribution. In previous work only the shape parameter of K-distribution is estimated from which the scale parameter is calculated. Therefore, the accuracy of the estimated scale parameter is largely determined by the accuracy of shape parameter estimation. In order to decouple the estimation of scale and shape parameters, in this work, deep learning is considered as the main tool to achieve K-distribution parameters estimation as a regression task. Specifically, a parameter estimation processor combining CNN with LSTM is constructed. The ground truth of the two parameters are taken as labels, and the weighted losses of the two parameters construct the total loss function of the network training. The effectiveness and superiority of the proposed estimation processor are verified on the simulated data and the real sea clutter data.
Performance analysis of empirical models of sea surface reflectivity based on measured data
Authors: Yang Boyu , Jiang Min , Wang Jianming
Published: June 2022

The empirical models of sea surface reflectivity have many categories and different applicable conditions. In order to solve the problem of how to select the best models in different environments, we make a systematic analysis of the performance of different models based on the measured data of sea surface and the meteorological observation data in the Northwest Pacific. The results show that the accuracy of the empirical models of sea surface reflectivity may be biased when only the sea state is used as the description of sea surface roughness. For low radar grazing angle, NRL and HYB models can obtain better performance. It is recommended to add a fixed offset for NRL model at medium grazing angles. Constant gamma model can get better fit at high radar grazing angle.
Dynamic Cache Replacement Strategy of Space Information Network Based on Cache Value
Authors: Cai Rui-yan , Qian Yang , Wei De-bin
Published: June 2022

With the development of space network communication technology, satellite cache becomes possible. However, due to the limited space on the satellites, content replacement has become a major factor affecting network performance. Aiming at the limited cache resources of space network nodes and the low cache hit rate of nodes, a space information network dynamic cache replacement strategy (SINDR) based on cache value is proposed. On the basis of considering the popularity of the content and the cost of caching, the strategy also calculates the caching value of the content by quantifying the entropy increase of the node, and assigns a reasonable weight to each factor according to the Analytic Hierarchy Process. The cache value function is reconstructed; finally, the content of the virtual node and the physical satellite node that will serve the area is replaced by combining the characteristics of the space network, so as to obtain the optimal utilization of satellite cache resources. The simulation results show that, compared with the existing cache replacement strategies, the cache replacement strategy proposed in this paper can effectively improve the average cache hit rate and reduce the average user acquisition delay in the space information network environment.
Multi-channel information acquisition system based on heterogeneous platform
Authors: Liang Xiaolong , Li Hong
Published: June 2022

The acquisition system based on hardware circuit control has more advantages in stability and rapidity than the acquisition system controlled by software. Using heterogeneous platform to complete the acquisition of various parameters of power grid based on hardware circuit is a basic work of smart grid. Therefore, a set of multi-channel data acquisition system based on heterogeneous platform Zynq-7020 is designed to meet the measurement and monitoring requirements of insulation oil temperature and water content in transformer. Firstly, the paper expounds the design idea. Then, taking the heterogeneous platform integrating ARM and FPGA as the core, the system circuit is designed. Furthermore, the design of data acquisition, processing and transmission is completed based on Verilog and C language. Finally, the experimental data of the system are given. The experimental results show that the system has the characteristics of strong expansibility, high precision and strong stability.
Research on IPSO-RBF transformer fault diagnosis based on Adam optimization
Authors: Shao Ningning , Chen Xiaoqiang , Wang Ying
Published: June 2022

As the lifeblood element of the power system, the transformer plays a pivotal role in power transmission and voltage conversion. The fault prediction of the transformer can not only realize the early warning before the fault but also provide theoretical support for the formulation of a transformer maintenance scheme, which can improve the safety and reliability of the power system. In this paper, a new method of transformer fault diagnosis based on dissolved gas in oil is proposed by combining the Adam optimization algorithm based on the classical momentum concept with the PSO algorithm. Firstly, a PSO-RBF transformer fault diagnosis model is constructed. Through the simulation experiment of nonlinear collocation of acceleration factors, the nonlinear exponential decreasing collocation is used to improve the optimization ability of particle swarm optimization. The simulation analysis is carried out based on the transformer fault data within the jurisdiction of Lanzhou electric power company. The diagnosis results verify that the diagnosis rate and stability of the IPSO-RBF-Adam transformer fault diagnosis model are better than the PSO-RBF model.
Power grid expansion planning model based on improved quantum evolutionary algorithm under supply-demand balance constraints
Authors: Zhang Linyao , Zheng Jieyun , Chen Hao , Wu Guilian
Published: June 2022

In order to improved the accuracy of power grid expansion planning, shortened the planning time and reduce the investment cost, a power grid expansion planning model based on improved quantum evolutionary algorithm under the constraint of supply and demand balance is proposed. Using SWOT analysis method and analytic hierarchy process, this paper qualitatively analyzes the comprehensive situation of Shaanxi Power Grid Company, establishes the evaluation index of supply-demand relationship, and constructs the power grid expansion planning model. Through the rotation angle strategy, the quantum evolutionary algorithm is improved to solve the power grid expansion planning model and obtain the optimal solution of power grid expansion planning. The experimental results show that the proposed method has shorter planning time and higher accuracy, and can effectively reduce the investment cost.
Boruta-XGBoost Electricity Theft Detection Based on Features of Electric Energy Parameters
Authors: Chen Xiao , Qiu Xinyu , Ma Yunlong , Wang Liming , Fang Lei
Published: June 2022

Electricity theft detection is critical for the safe and effective development of the electric power system. The existing methods that are used to detect electricity theft rely on historical load data and are considered to have poor timeliness. Their detection results have limited reference to power supply enterprises’ investigation on electricity theft. Therefore, this paper proposes the Boruta-XGBoost power theft detection model based on multiple features of electric energy parameters. The model converts electricity theft detection problem into a multiclass classification problem. First, the features of various electric energy parameters that are collected by the electric energy metering device are used to construct the original dataset. Then, the Boruta algorithm is used to select features and reconstruct the dataset based on the selection results. Finally, the reconstructed dataset is used to train an XGBoost model that can detect the type of electricity theft based on the features of real-time electric energy parameters. In order to verify the effectiveness of the model, a comparative experiment is conducted in this paper. The reconstructed dataset is used to train the following algorithms: LightGBM, CART, SVM, and logistic regression models. The test results show that the Boruta-XGBoost model in this paper has the best effect on electricity theft detection.
Design of Mobile ad-hoc network scheme based on SDN
Authors: Huang Xiaoyu , Su Mingxia
Published: June 2022

With the expansion of application scale, the network structure and organization mode of traditional MANET are limited by factors such as bandwidth optimization, power control and node mobility. The stability of network performance and the use efficiency of upper layer applications are also seriously affected. In order to solve this problem, Mobile ad hoc network (MANET)scheme based on SDN is proposed to establish a flexible and programmable data forwarding mechanism in MANET. The dynamic deployment mechanism of network functions and the globally consistent cooperative control mechanism realize the global network performance optimization and efficient management control. Finally, the test shows that SDMENT improves the flexibility of MANET network and makes the software of MANET have the significance of engineering application.
Design of a wireless communication system for distribution monitoring
Authors: Huo Chao
Published: June 2022

According to the requirements of wireless communication in medium and low voltage distribution monitoring system, this paper designs a wireless signal networking method at medium and low voltage distribution side, and analyzes the networking mechanism between each protocol layer, including important wireless avoidance mechanism, networking mechanism of network layer and application layer. Aiming at the problem of network connectivity, a wireless networking algorithm based on optimal distance is proposed, and other common wireless networking algorithms are studied at the same time. The networking algorithms are simply evaluated and compared, and the advantages of this strategy in wireless networking are verified by experimental simulation and analysis.
Research on univariate anomaly diagnosis of gas pipeline measurement data based on Random Forest algorithm
Authors: Quan Qing , Li Dan , Wang Shouxi
Published: June 2022

The basis of univariate anomaly diagnosis of pipeline system is that univariate time series can reflect fault information of the system. Random Forest belongs to random sampling with put back, which can efficiently process high-dimensional data. This paper firstly combines measurement data with control graph theory, obtains sample data of different modes by Monte Carlo method. Then, Gini Impurity values of random forest algorithm are introduced to sort and optimize the feature of sample data. Finally, the Random Forest is used to realize the high precision intelligent recognition of different modes of the measurement data control chart, and the univariate anomaly diagnosis of the gas pipeline measurement data is realized combining with the fault knowledge base.
Lightweight hybrid signature scheme for Internet of Thing based on bilinear mapping
Authors: Duan Gangpeng
Published: June 2022

Most of the existing IoT communication encryption schemes have the following two problems: the sensor side needs to perform complex bilinear mapping calculations; most schemes separate key agreement and data encryption, which increases the user’s computational burden and management difficulty. This paper proposes a lightweight IoT hybrid signature scheme based on bilinear mapping. In terms of transmission efficiency, the calculation process of the bilinear map is transferred to the initialization phase of the system. The sensor side only needs low-cost operations such as hash mapping and exponential operation, which reduces the overall computing cost of the solution. In terms of security, the mathematical difficulty caused by the bilinear mapping calculation in the initialization phase is used to ensure the security of data transmission. In solving the problem of key management, the scheme uses the semi-trusted key generation center (KGC) and sensor ID to generate user session keys and data keys, which solves the public key authentication and key escrow problems of massive sensors in the Internet of Things.
Research on 3D face measurement for facial virtual plastic surgery
Authors: Su Liwei , Li Guiwen , Liu Zhenyao , Ji Xiaoqiang
Published: June 2022

Calculating the key data of human face through three-dimensional face model can help doctors predict the surgical results before plastic surgery, guide the formulation of surgical plan and reduce the surgical risk. In this paper, 3D face measurement technology is studied, and the area of plastic area is calculated by slice method. A large number of experimental tests show that the average errors of facial geometric feature measurement, area measurement are 0.458mm and 0.65mm2 respectively. The rating of simulation results provided by plastic surgeons shows that facial measurement technology can effectively improve the success rate of plastic surgery. Compared with the original face, the edited 3D face is more attractive in respecting the following beauty standards: “three courts and five eyes”, golden section, etc.
DADDE:deep anomaly detection with density estimation
Authors: Duan Shunran , Jiao Longlong , Yin Meijuan , Yü Lanlan
Published: June 2022

The problem of abnormal nodes detection in attributed network is widely used in daily life, such as social networks, cyberspace security, financial fields and so on. Most existing detection methods ignore the relationship between structure information and attribute information in attributed network. Although some methods consider the relationship between them, but it can’t distinguish the types of abnormal nodes well, that is, attribute exceptions or structural exceptions. Aiming at the shortcomings of existing methods, this paper proposes a deep anomaly detection model combining density estimation. The idea of detecting abnormal nodes by reconstruction error is used, the structure information and attribute information of attributed network are reconstructed respectively, and abnormal nodes are detected by density estimation based on reconstruction error and embedding vector of nodes. In this paper, the validity of DADDE model is proved by experiments on three commonly used data sets in this field.
Solve the Optimal Strategy of “Desert Crossing” with multi-goal programming
Authors: Dai Yifan , Zhou Xinyi , Mao Jingyi
Published: June 2022

In this paper, we take a game called “Desert Crossing” into research. With the game strategy of avoiding failure and maximizing the revenue, we proposed a topological model for removing redundant paths in maps with Dijkstra. For the simple case of known daily weather in the game, we established a goal programming model with the constraint of game rules. A method based on Tree DP is proposed to solve the complex mathematical model. For the complex case of random weather, a probability model of weather is established by Markov Chain, and a multi-goal programming model is proposed.
Two inequalities for the minimal eigenvalue of M-matrices
Authors: Zhong Qin
Published: June 2022

M-matrices are closely related to nonnegative matrices and they have extensive application background in computational mathematics and related fields. Some properties on the minimal eigenvalue of M-matrices are presented in terms of the relationship between the nonnegative matrices and the M-matrices.
Design of coupling alignment system based on single chip microcomputer
Authors: Zhang FuQiang , Zhang FuQuan , Liu JingXia
Published: June 2022

Aiming at the problem of coupling alignment, a dynamic alignment method based on laser method is proposed and verified by simulation. The design content mainly includes: the collection and processing of sensor current, the data processing of single chip microcomputer, the communication of upper computer and the writing of program. The results show that the designed alignment method can display the changes of various data in real time and monitor the alignment state of the coupling in time.
Design of prefabricated foundation for 66kV tower assembly and simulation of mechanical properties and grounding current density distribution
Authors: Li Guanhua , Liu Rui , Dai Xu , Wang Shengfu , Du Desheng , Wang Liang
Published: June 2022

Most of the existing transmission line tower foundations are cast-in-place foundations, and there are many obvious disadvantages of this operation method, such as its long construction period, poor generality, and inability to construct in winter. In this paper, we propose an assembly type prefabricated foundation for 66kV transmission line towers. And use SOLIDWORKS to simulate and analyze the mechanical properties of the foundation, analyze the current density distribution of the designed foundation with CDEGS simulation, and add reinforcement cage to optimize its current density distribution. The results show that the designed foundation meets the requirements of its working conditions.