bluuebunny/crossref_metadata_2025 huggingface dataset:
Design of miniature directional coupler with wide bandwidth
Authors: Letavin Denis A , Alaev Danil P
Published: February 2021

Miniature directional coupler with wide bandwidth consisting of compact structures and curved lines has been developed. The type of structures was chosen in such a way as to achieve the greatest possible coincidence of their characteristics in the bandwidth with the characteristics of quarter-wave sections. The area of the developed coupler is 69.8% less than the area of the same device in its standard version. Device modeling was performed in the Cadence AWR program. It is shown that miniaturization of the directional coupler caused deterioration of such characteristics as operating frequencies band, preservation of the phase differences between the outputs in a wide frequencies band, and attenuation in the band. A model of the coupler was made, which allowed us to confirm experimentally the correctness of calculations in AWR.
A compact 3-dB coupler with microstrip cells
Authors: Letavin Denis A , Alaev Danil P
Published: February 2021

Research of the design of a coupler with an operating frequency of 1.8 GHz has been conducted. This construction has a small area and can be used in microwave circuits for power division. Suggested construction, taking into consideration the reduced dimensions, has characteristics comparable to the design in the traditional version. Miniaturization of the device was achieved by using synthesized microstrip cells which were installed instead of ordinary sections. The coupler was modeled and fabricated and the measured characteristics are well coincide with the calculations.
Sharing economy as a part of the sustainable development concept
Authors: Absalyamov T , Absalyamova S , Mukhametgalieva Ch , Sakhapov R
Published: February 2021

The article is devoted to the study of sharing economy as a new economic model. Today, sharing economy or economy of joint consumption, is in serious competition with traditional industries. The paper presents basic approaches to determination of the sharing economy essence. It considers the factors contributing to its formation and growth. Among the main factors, the authors highlight technological, economic, environmental and social factors. The paper studies the development dynamics of individual sectors of the joint consumption economy in Russia, their contribution to the implementation of the Sustainable Development Goals. Moreover, the authors explore new trends, such as the expansion of geography, changes in the demographic composition of participants, and the integration of sharing in ecosystems. The risks of further expansion of the sharing economy are studied as well - the risk of personal data leakage, problems with the state of critical infrastructure etc.
A comparison of numerical solvers for the delay eigenvalue problem of coupled oscillators
Authors: Abdelrahman Abdelrahman S. , Al-Qahtani Hussain , Alharbi Fahhad H.
Published: February 2021

In this work, we conduct a comparison for various delay differential equations’ solvers to determine the strength and weakness points of each one. The comparison is clarified through a numerical example in which we consider the coupled harmonic oscillators. We obtain the eigenvalues of the delayed coupled harmonic oscillators system by solving the governing equations by all considered methods. However, the methods of concern in this paper are as follows: the Taylor series expansion, Rekasius’s substitution, self-consistent approach, and the Krylov method with Chebyshev interpolation. The main aspects that we investigate in this paper are the stability, robustness, and numerical efficiency. We found that the Krylov method with Chebyshev interpolation performs better than all the other considered ones.
A mathematical model for calculation of the influence of ferromagnetic components in Vertical Displacement Events and stability simulations of tokamak plasmas
Authors: Atanasiu Calin V. , Zakharov Leonid E. , Hoelzl Matthias , Gerasimov Sergei
Published: February 2021

Iron core transformer tokamaks have a distinct element, namely the iron core which can affect the plasma stability of the plasma. As a consequence of the high non-linear dependence of the magneto-hydrodynamic solutions on the iron permeability μ

Fe
in JET tokamak for example, Vertical Displacement Events (VDEs), equilibrium and stability calculations are more complicated and more time consuming than in air core transformer tokamaks. By considering the ferromagnetic components as a linear, isotropic and homogeneous media on subdomains, it is known that these media can be replaced by a homogeneous one (vacuum) and a surface-current density distribution i

Fe(l) on the separation surfaces between subdomains, with l the curve taken along the curve separating two different magnetic media. For the case of geometry with rotational symmetry, this surface-current density distribution along a curve, in a meridian plane, is given by a Fredholm integral equation of second kind. Practically, the advantage of this method is more obvious for the inverse formulation of the VDEs and stability problems by moving the non-linear term (due to the iron permeability μ

Fe
) from the differential operator to the r.h.s. of the equations. In this paper, we are presenting how the influence of ferromagnetic components in the equations of the surface currents developed in the vessel structures during Wall Touching Kink Modes (WTKMs) can be taken into account and are reviewing the equations to be solved in order to simulate the influence of the ferromagnetic components in VDEs and equilibrium stability calculations. The numerical results of these simulations for a real JET tokamak structure and plasma parameters will be reported in a future paper.
Problems of attracting foreign direct investment into the regional economy
Authors: MGaleeva G , Kadeeva E N
Published: February 2021

The article discusses topical issues of attracting foreign direct investment in the economy of the Republic of Tatarstan. The assessment of the factors affecting the investment attractiveness of Russian regions made it possible to determine the prospects for the implementation of projects with the participation of foreign investors. In conclusion, the authors highlight the successful practices of attracting foreign investment in the region’s economy.
Differential operators and the symmetric groups
Authors: Nonkané Ibrahim
Published: February 2021

In this paper, we study the action of the rational quantum Calogero-Moser system on polynomials. In this vein, we study polynomials ring over the complex field ℂ as a module over a ring of differential operators by elaborating its irreducible submodules. we endowed the polynomial ring ℂ[x
1
, …, x

n
] with a differential structure by using directly the action of the Weyl algebra associated with the ring of symmetric polynomial ℂ[x
1
, …, x

n
]
Sn after a localization. Then we study the polynomials representation of the ring of invariant differential operators under the symmetric group. We use the representation theory of symmetric groups to exhibit the generators of its simple components.
Analysis and modeling of Fano resonances in coupled cantilevers
Authors: Baquero Hugo Aya
Published: February 2021

The coupled oscillators model has been used for decades to interpret the Fano interference in a variety of systems: optical, plasmonic, and microwave. Hence, Fano resonance can be modeled with a weak or tightly coupled mechanical oscillators system, which provide insight into the interaction dynamics of a radioactive continuum of propagation modes and a discrete state. Therefore, the coupled cantilevers model was implemented in a FEM routine, in order to study and discuss aspects of the Fano resonance. The study of the Fano resonance in coupled cantilevers shows that this model may be applied in the field of micromechanical sensors.
High energy neutrino and gamma-ray emissions from the jets of M33 X-7 microquasar
Authors: Papadopoulos D A , Papavasileiou Th V , Kosmas T S
Published: February 2021

In this work, after testing the reliability of our algorithms through numerical simulations on the well-studied SS 433 Galactic microquasar, we focus on neutrino and γ-ray emissions from the extragalactic M33 X-7 system. This is a recently discovered X-ray binary system located in the neighbouring galaxy Messier 33 which has not yet been modelled in detail. The neutrino and γ-ray energy spectra, produced from the magnetized astrophysical jet of M33 X-7, in the context of our method are assumed to originate from the decay (and scattering) processes taking place among the secondary particles produced assuming that, first, hot (relativistic) protons of the jet scatter on thermal ones (p-p interaction mechanism).
Exploiting Dirac equations solution for exact integral calculations in processes of muonic atoms
Authors: Giannaka P.G. , Kosmas O. , Tsoulos I. , Kosmas T.S.
Published: February 2021

Precise muon wave functions are calculated by solving the Dirac equations within a method based on modern neural networks and stochastic optimization techniques. The reduced radial wave functions (up and bottom) of a bound muon in muonic atoms are then given as linear combinations of the well behaved sigmoid functions. As concrete applications, the known muonnucleus overlap integrals, which determine the structure and evolution of muonic atoms (twobody quantum systems bound together due to the fundamental electromagnetic interactions), may accurately be calculated. In this work, the muon-nucleus integrals for a set of nuclei including the 28Si and 64Zn entering the ordinary muon capture rates are exactly obtained through numerical integrations using Gauss integration algorithms.
Research on Traffic Classification of Auto Machine-learning Base on Meta-QNN
Authors: Xu Xin Yu , Huang Yong Zhong , Luo Yong Cheng , Ouyang Guige , Zhuang Haoyu
Published: February 2021

The traditional traffic classification task relies on feature engineering by experts with specialized knowledge. With the advent of representation-learn-based traffic classification techniques, machines learned to extract features from traffic data and classify them. In this paper, we research traffic classification technology based on representational learning and import auto-machine learning technology to solve the problems of network architecture design and parameter tuning. We also design a befitting reward function for the network architecture model. The experimental results on the USTC-TF2016 dataset and USTC-TF2016-PLUS shows that the network architecture generated by auto-machine learning technology has better training performance and classification accuracy than a traditional neural network.
Characteristic Analysis of Collision Between Drill String and Well Wall
Authors: Huang Zhihong , Wang Hanxiang , Lv Xiaoxiao , Liu Yanxin
Published: February 2021

In order to improve the security of drilling progress and reduce the reliability impact which caused by the collision between drill string and well wall, the finite element analysis software ADINA is used to establish a finite element model to simulate the change of drill string stress after the collision between drill string and wellbore under different factors. The results show that the existence of drilling fluid with higher viscosity, lower revolution speed and autorotation speed of drill string and larger annular space is conducive to reduce the stress value caused by collision between drill string and wellbore and improve the security and stability of the drill string.
Research on Advertising Core Business Reformation Driven by Artificial Intelligence
Authors: Lai Zhenli
Published: February 2021

Driven by big data and artificial intelligence technology, the core business of advertising is gradually becoming intelligent, from consumer insight to advertising information delivery and then to advertising content production. With the continuous progress of cognitive computing technology, it can be predicted that in the future, intelligent advertising will continue to step forward along the trend of “humanization” in line with human needs.
Research on Rapeseed Counting Based on Machine Vision
Authors: Peng Shunzheng , Zhao Zeying , Xiaobo Wu , Yue Yuanbin , Li Lijie , Weng Zhu , Sun Changqing
Published: February 2021

Thousand-kernel weight is an important agronomic parameter of rapeseed. In order to quickly realize the grain count, shorten the measurement cycle of the thousand-grain weight, in this paper, we propose a grain counting method based on image detection, by testing 300 rapeseed images, and the results showed that the detection rate reached 89.33%.
Research on Small Object Detection Algorithm Based on Feature Enhancement Module
Authors: Han Tongqiang
Published: February 2021

Aiming at the disadvantage of the SSD algorithm’s poor detection effect on small objects in the process of detecting objects, a detection method based on feature fusion and feature enhancement is proposed. Our model combines deep and shallow features to improve the model’s ability to detect small objects. Besides, the idea of a channel attention mechanism is introduced into the model structure to increase the feature extraction ability of the network and effectively improve the detection accuracy of the network. Experimental results show that the detection accuracy (mAP) is 2.3% h igher than that of SSD. The detection accuracy (mAP) is significantly improved compared to the current series of excellent object detection algorithms. The algorithm in this paper can detect small objects that are not detected by most SSD algorithms, which improves the average detection accuracy
Study of Wavelet Transform-based Image Fusion Methods
Authors: Cheng Kairui , Yi Longhao , Li Long , Zhutian Manzi , Sun Guang
Published: February 2021

The main objective of this paper is to get some basic knowledge about image fusion, the methods used for fusion, and the problems that still exist in image fusion technology, and to draw the attention of the research field to image fusion technology through a combination of theory and practice.
Design of Home Care System For Rural Elderly Based on Artificial Intelligence
Authors: Wang Liang Liang , Jia Lian Qin , Chu Feng Qin , Li Ming Xia
Published: February 2021

With the development of Internet of Things technology, cloud computing technology, big data technology, and artificial intelligence technology, the application of these new technologies to rural life can help rural elderly care at home. The home care system for the elderly in rural areas is based on artificial intelligence technology and uses the Internet of things technology to collect real-time environmental parameters at home and to optimize the living environment. It uses intelligent image recognition technology to judge the behavior of the elderly and interlopers and gives effective early warning and alarm. It uses wearable devices to measure the health of the elderly in real-time. It uses the man-machine dialogue program to solve the life needs of the elderly to improve the well-being of the elderly life. It integrates big data and cloud computing technology to process the collected information.
Thai Word Segmentation Based on Sequence-to-Sequence Model
Authors: Wu Hui Wen , Huang Yong Zhong , Li Can Cheng , Zhuang Haoyu , Xu Xinyu
Published: February 2021

Thai as a low-resource language has a large word segmentation performance improvement space. In this paper, we investigate a sequence-to-sequence model for Thai word segmentation with two different recurrent neural networks, which could transform one input sequence into another output sequence. Furthermore, we evaluate datasets in four different fields compared then with other multiple word segmentation models, and the F1 value in the encyclopedia dataset reaches 97.15%. The results show that the proposed model has superior performance and is more effective, it is worth mentioning that the expected results can be achieved even with limited data resources.
Improved Algorithm Based on The Deep Integration of Googlenet and Residual Neural Network
Authors: Huang Xuehua , Chen Weihong , Yang Wangdong
Published: February 2021

In this paper, we propose a new improved algorithm based on the deep integration of GoogleNet and Residual neural network and we call it GRSN. The new improved algorithm has the new advantages of multi-size and small convolution kernel in the same layer in the network and the advantage of interlayer hop connection (bypass) to reduce information loss. The algorithm is applied to the general image data set cifair10, and the experimental results are compared with that of GoogleNet, the accuracy is improved, the convergence is accelerated, and the stability is better.
An Improved Hough Transform Method for Detecting Forward Vehicle and Lane in Road
Authors: Wang Ying Sheng , Qi Yuhan , Man Yi
Published: February 2021

In this paper, we propose an integrated method for lane detection and vehicle detection, which tries to make a real-time analysis of vehicle video for identifying lane, detecting, and tracking forward vehicles. In lane detection, image preprocessing, line detection based on improved Hough transform, and straight-line model reconstruction are used. For vehicle detection, preprocessing, vehicle shadow merging based on the improved search algorithm, regions of interest (ROI) demarcation, lane determination, and vehicle tracking are used. The experiment results show that the time it takes to process an image is about 25ms. Additionally, the lane detection rate of vehicles driving on a structured road is approximately 98%, and the vehicle detection rate of the closest forward vehicle is approximately 81%.
Prediction of User Consumption Behavior Data Based on the Combined Model of TF-IDF and Logistic Regression
Authors: Xiao Shuwei , Tong Weiqin
Published: February 2021

In the era of the rapid development of computers and the Internet, e-commerce has become a part of the economy of many countries. Therefore, how to use historical data of user consumption behavior to predict user shopping intentions accurately and subsequent personalized recommendations has turned into research hotspots in the field of e-commerce. This paper conducts a basic analysis of JD’s e-commerce data based on machine learning. Specifically, this article constructs user-product matrix and product and user clustering by means of text processing and clustering, as well as implements a logistic regression classifier to predict the user’s purchase intention of products in a certain target category in the next 5 days. Based on the JD competition data set, this article has a prediction accuracy rate of 98%. This can help e-commerce companies make better decisions.
Facial Expression Recognition Based on Convolutional Neural Network
Authors: Lu Ruhua , Li Yalan , Yang Pan , Zhang Wenfen
Published: February 2021

At present, facial expression recognition technology is widely used in artificial intelligence, transportation, medical and other aspects, so it has important research value. Traditional facial expression recognition uses manual feature extraction method with low accuracy and weak generalization ability, which is difficult to be applied in real life. With the development of deep learning, convolution neural network appears in people’s vision. Different from traditional manual feature extraction, convolution neural network can learn image features independently, and learn more features. In addition, it has the advantage of sharing the weight with the neural network. Although convolution neural network has multiple advantages, it also has some disadvantages, especially over fitting. In this paper, the model of convolution network is improved based on the classical VGGNet according to the working principle of convolution neural network. In this new model, the number of convolution kernels is reduced in parameters, and the global average pool layer is used to replace the full connection layer in the structure, so as to reduce the degree of over fitting and decrease the operation parameters. Finally, experiments show that the accuracy, generalization and consumption of resource are enhanced in the new model. It is proposed that the new method is better than the traditional convolution network VGGNet.
An Algorithm for Target Detection Based On Aggregation Multi-Scale Feature
Authors: Chen Yishun , Dong Rongsheng
Published: February 2021

In order to alleviate the multi-scale problem caused by the scale change between object instances, pyramids are widely used in target detection. Although these target detectors with characteristic pyramid structure have achieved good results, they have some limitations because they simply construct characteristic pyramids according to the skeleton multi-scale pyramid structure originally used for target classification tasks. In this study, based on M2Det, a multi-scale feature with richer multilevel information is proposed to construct a more effective feature pyramid to detect targets of different scales.First, the basic features with multi-level features will be fused and extracted from the backbone.Then, the basic features are input into the M module, and the features generated by each P module are used as the features of the detection object in the form of dense connection. Finally, the attention mechanism is introduced into the L module to assemble the features with the same scale and construct a feature pyramid for target detection. On the COCO dataset, MLPNet implements the results of AP37.8.
Demodulation and Recognition of Image Transmission Signals for Small Uav Under Non-Cooperative Conditions
Authors: Zhou Zhiyong , Dong Zheng , Jia Tengfei , Dai Huanyao
Published: February 2021

According to the characteristics of CP-OFDM signals, analyzed and studied the subcarrier number estimation, timing synchronization and frequency offset compensation algorithms of CP-OFDM signals under non-cooperative reception conditions, and verified the feasibility of these algorithms based on UAV image transmission signals. As the results show, the algorithm proposed in the article can complete blind demodulation of the CP-OFDM signal and finally complete the sensing and recognition of small UAV signals under the condition of unknown CP-OFDM signal format by means of analysis and estimation algorithms.
Multisource Data-Driven Visual Analysis of Urban Crowd Travel
Authors: Zhang Jianzhong , Wang Fei , Guo Qian , Hong Anding , Chen Jiantao , Zhang Jin
Published: February 2021

Many functional areas have been formed in the development of the city, and the gathering of taxis can basically reflect the travel situation of the crowd. Combining urban functional areas and taxi GPS data to analyze crowd travel conditions can provide decision support for the construction of smart cities. Therefore, this paper analyzed the travel situation of crowd in Changsha urban area based on multi-source data. First, this paper clusters the distribution of public transit stations in Changsha, and then imports the geographic location information of the cluster centers into the Voronoi diagram in ArcGis to divide the urban area of Changsha. Then the divided areas and Point of interest (POI) data are counted and analyzed to obtain the functionality of each area. Finally, the taxi GPS data is clustered according to the time period, and the cluster center is mapped to the urban functional area, to analyzed the crowd clustering situation of each functional area in Changsha in different time periods.
Forecast of Gross Output Value of Agriculture and Forestry in Guangxi Based on Holt-Winters Model
Authors: Li Run , Li Xiangmin , Lu ZhiXiang
Published: February 2021

Agriculture and forestry are the source of food, clothing and subsistence for human beings and also the primary conditions for all production. The forecast of the gross output value of agriculture and forestry directly affects the purchasing, pricing and storage of important plans in the agricultural sector. This paper collects quarterly data from 2012 to 2020 in Guangxi Zhuang Autonomous Region and uses the Holt-Winters prediction model based on the multiplication to fit the historical data. The model was validated by calculating the optimal smoothing coefficient through the minimum residual sum of squares, making predictions and comparing actual values for the data from 2018 to 2020. Finally, the model was used to derive future forecasts for agriculture and forestry from 2020 to 2022, and recommendations for agricultural development were made based on the forecasts.
A Page-topic Relevance Algorithm Based on BM25 and Paragraph-Semantic Correlation
Authors: Peng Shi , Xie Xiaodan , Zhai Jia , Jia Yusheng , Gong Yuxuan
Published: February 2021

It is difficult for the traditional topic relevance algorithm based on word frequency and probability statistics model to deal with the ambiguous topic of search keywords, which leads to the retrieval results containing much information that users are not interested in. To solve this problem, a page-topic relevance algorithm based on BM25 and paragraph-semantic correlation is proposed in this paper. The semantic correlation of one page is calculated by the paragraph-semantic classification using a pre-trained deep neural network model, and is weighted with the BM25 retrieval score. Experimental results show that compared with the traditional BM25 algorithm, this algorithm can effectively improve the retrieval accuracy.
Research on Methods of Parsing and Classification of Internet Super Large-scale Texts
Authors: Song Mengting , Zheng Hang , Tao Zhen , Jiang Jia , Pan Bin
Published: February 2021

Web crawlers are an important part of modern search engines. With the development of the times, data has shown explosive growth, and mankind has entered a “big data era”. For example, Wikipedia, which carries knowledge achievements from all over the world, records real-time news that occurs every day and provides users with a good text search database[1]. Wikipedia updates data up to 50+GB every day. This project focuses on solving the problems of data acquisition and data analysis. At the same time, it downloads and parses the latest data of Wikipedia and analyzes XML files, and then uses SVM algorithm and Naive Bayes algorithm to classify articles, Train the model to download Wikipedia files efficiently and parse XML files.
Evaluation of Equipment Competitive Acquisition Management Based on Entropy Theory
Authors: Jiang Yujiao , Yuan Mingxing , Li Xiaosong
Published: February 2021

Aiming at the evaluation of equipment competitive acquisition management, the paper proposes an evaluation method based on entropy theory. First, the concept of equipment competitive acquisition management entropy is defined. Second, the conceptual model, mathematical model, and evaluation index system of equipment competitive acquisition management entropy are constructed. Finally, taking policy and regulatory entropy as an example, the paper has calculated and analyzed its evaluation results to prove the effectiveness of the method.
The Hybrid Intelligent Optimization Algorithm and Multi-objective Optimization Based on Big Data
Authors: Nie Xin , Luo Jian
Published: February 2021

Multi objective optimization problem (MOP) usually has more than two objective functions, and the optimal solution based on Pareto frontier is obtained. The traditional optimization algorithm cannot meet the needs of industrial application when dealing with multi-objective optimization problems. With the good performance of evolutionary algorithm in solving complex problems, its application field is also extended to multi-objective optimization problems. The Pareto optimal solution and evaluation system of multi-objective optimization problem are analysed. Particle swarm optimization (PSO), one of the evolutionary algorithms based on swarm intelligence, is briefly introduced. The combination of particle swarm optimization algorithm and multi-objective optimization is studied.
Research on E-commerce Supplier Selection Based on Big Data Analysis Technology
Authors: Guan Xin , Zhang Liyun , Zhao Haibo
Published: February 2021

In the analysis of e-commerce suppliers, the use of big data analysis technology is very important. The interference factors in the analysis process determine the supplier’s choice. According to the characteristics of e-commerce, the e-commerce competition model, evaluation matrix, and the intelligentized degree of each index are determined through level analysis. Experience has shown that accurate data on the financial status of the organization can be obtained through intelligent screening methods, which has laid a solid foundation for improving the good cooperation between the original electronic companies and suppliers.
Research on Information Security Defense Based on Improved Identity-Based Dynamic Clustering Authentication Algorithm
Authors: Guo Dandan , Zhang Ningchi , Wang Yanru , Cui Yanzhao , Jiang Bin , She Rui , Liu Hui , Ma Wenjie
Published: February 2021

Big data and artificial intelligence technology, as the unified means and carrier for collecting, storing and computing core data of contemporary power IoT, has diverse and complex characteristics of its data sources and types. And the lack of insecure data access, abnormal response and terminal access rights control leads to the failure of the integrity and credibility of the closed-loop information defense. In particular, wireless sensor networks (WSNs) in power scenarios are more susceptible to malicious attacks. To address the above problems, this paper proposes a power IOT information defense strategy based on improved identity-based dynamic clustering authentication algorithm (IIDC). First, the terminal device sets the private key to solve the key escrow problem of terminal security authentication in the IOT model. At the same time, the improved algorithm dynamically generates pseudo-cryptographic matrix to avoid collusion attack. Finally, a hierarchical privilege management mechanism is adopted to decrypt the terminal authentication once. The proposed algorithm is more suitable for terminal security access and power consumption requirements in WSN-based power IOT scenario, as verified by experimental simulation.
Research on the Construction of standardized WebGL 3D scene Service for Power Grid Service
Authors: Ji Kun , Wu Qiong , Zhang Yanfeng , Liu Ming , Zhen Chao , Zhu Jun , Dong XiangYu , Wang Taiping
Published: February 2021

With the increasing maturity of WebGL technology as well as the development and construction of the 3D geographic information system, 3D geographic information sharing service has become the trend of future development. There are numerous three-dimensional data sources of the power grid and many applications across departments and systems, but the three-dimensional geographic information service based on unified standards is still rarely seen. The paper studies and discusses the selection of 3D service standards and the implementation technology of 3D geographic information service for the power grid.
Multi-channel VideoStreaming Technology for Processing Based on Distributed Computing Platform
Authors: Cheng Wei , Tang Yanyang , Yang Wangdong
Published: February 2021

With the rapid development of the Internet, sensor network, and mobile Internet technology, a large number of data sets are continuously generated in the form of streaming in various application fields. At the same time, the processing of stream data has drawn more and more attention because of its application in different situations. To meet the urgent need for the processing of streaming data, there are many computing engines on the market, such as Spark and Flink. Traditional data-flow analysis has many problems in the process of streaming data, such as the high time delay, weak extensibility, and bad adaptability. In order to improve them, people use Kafka as the intermediate-cache and the computing engine that uses Spark Structured Streaming as the streaming data to realize the effective process of multichannel flow data. Considering the present demand for low latency and high flux that are analyzed by urban management in traffic video, processing the data of multichannel traffic video on distributed computing platform realized the tracking and search on motor vehicles, non-motor vehicles, and pedestrians of multiple roads and intersections.
The A Satellite-to-Ground Quantum Key Distribution Protocol Based on Orbital Angular Momentum of Light
Authors: Wang Sheng , Lin Yu , Ye Xun , Zhang Tianbing , Feng Bao , Yu Xiang Bian
Published: February 2021

The orbital angular momentum (OAM) of light has been considered as a promising degree of freedom (DoF) that gives access to a higher-dimensional Hilbert space, which may lead to potential higher capacity quantum communications. Due to the fragility of the OAM state, the traditional view is that turbulence will make OAM-QKD infeasible in satellite-to-ground channels. However, based on the detailed phase screen simulations of the expected atmospheric turbulence, we find that quantum key distribution (QKD) using OAM of the light is feasible in certain system configurations, especially if quantum channel in-formation is utilized in the processing of post-selected states. Therefore, we propose a satellite-to-ground quantum key distribution protocol based on the orbital angular momentum of the light, which uses the principle that OAM-QKD can only be used in high-altitude ground stations with larger receiver apertures with-out using classic optical probes. At the same time, the classically entangled light is used as a probe of the quantum channel and reasonably-sized transmitter-receiver apertures are also employed. Numerical simulation results show that this protocol can lead to positive secret key rates even under circumstances where a sea-level ground station with a reasonable-sized aperture is used. We also found that quantum channel conjugation enables a key rate advantage provided by the higher dimensions of the protocol to be realized.
Key Technologies and Applications of Wild Animal Satellite Tracking
Authors: Huang Tian , Zhou Libo , Zhou Minghui
Published: February 2021

Mastering the laws of wildlife activities and family territory is an important task for wildlife protection, habitat restoration, and epidemic surveillance. Aiming at the shortcomings of traditional wildlife monitoring methods, an overall framework of wild animal satellite tracking system is proposed, and key technologies such as MEMS design, energy optimization, miniaturization and lightweight, wearable methods, and big data platform development are discussed and practiced. The results show that the wild animal satellite tracker developed by the above technology has the characteristics of miniaturization and lightweight, which can better solve the problem of energy supply in the field, and the service life can reach more than 5 years. Cloud recording of wild animal tracking data, Cloud Storage, Cloud computing, and Cloud monitoring. It plays a role in ensuring the data security of China’s wildlife ecological resources and other sensitive geographic information, and also provides scientific and effective technology tools and data support for China’s wildlife research, protection, and management, and is of great significance for serving the national ecological civilization construction.
Computation Offloading Based on Improved Glowworm Swarm Optimization Algorithm in Mobile Edge Computing
Authors: Fu Ke , Ye Jun
Published: February 2021

Mobile edge computing(MEC) has already shown its powerful computing ability in mobile device which can broaden the capacity of computing. However, in view of mobile edge computing system, due to the varying network conditions and limitation of the wireless channel, the problem of long delay and high energy consumption maybe increase in the industrial production line. Therefore, computing offloading was proposed to reduce delay and energy consumption in mobile edge computing but the task allocation of offloading decision still can be improved by using different optimization algorithms. In this paper, we improved computation offloading method by an improved glowworm swarm optimization(GSO) algorithm to solve this problem for multi-user-multi-MEC in mobile edge computing. Compared with existing improved algorithms of computation offloading, the experimental results show that our proposal can reduce the system cost a lot(to 25%) which has a better performance of saving energy and reducing delay in the mobile edge computing environment.
Plasma chemical synthesis of W-C-Co system nano-sized powders
Authors: Astashov A G , Samokhin A V , Alekseev N V , Kalashnikov Yu P , Dorofeev A A , Sinayskiy M A , Pakhilo-Darial I O
Published: February 2021

Parameters have been developed and experimental studies carried out for the synthesis of W-C-Co system nanopowders in a limited jet plasma reactor by interaction of tungsten oxide and cobalt with methane in hydrogen-nitrogen plasma flow generated in an electric arc plasma torch. Nanoscale powders with a specific surface area of about 25 m2/g, consisting mainly of tungsten-carbon phases and cobalt, have been produced.
Creation of polymer-ceramic materials for FDM printing
Authors: Egorov A S , Bogdanovskaya M V , Aleksandrova D S , Osipchik V S , Anokhin A S , Ivanov V S , Ivanov E V
Published: February 2021

This paper discusses approaches and methods for obtaining highly filled polymer-ceramic materials to be used for additive manufacturing purposes. The key deliverable produced in the course of the project work was the development of polymer-ceramic materials that are suitable for extrusion processing and subsequent manufacture of products via Fused Deposition Modeling (FDM).
Synthesis and research of polymer composites reinforced with carbon nanotubes using computer models
Authors: Kobzev V A , Chechenin N G , Bukunov K A , Vorobyeva E A , Makunin A V
Published: February 2021

Nanocomposites are a new type of material that differs from conventional composite materials in the size of the hardening phase. One of the most promising fillers for nanocomposites is carbon nanotubes. The paper studied structural and functional properties of polymer composite materials based on epoxy resins reinforced with carbon nanotubes. Impact resistance at high speed effects of multilayer composites, which are multilayer structures made of glass fabric and basalt fabric impregnated with polymer on the basis of epoxy resins, has been studied.
Magnesium compounds as future high temperature superconductors
Authors: Palii N A , Belousov O K
Published: February 2021

Previously proposed method for calculating the superconducting transition temperature (Tc) of the different substances was used to predict Tc of magnesium compounds. Theoretical calculations show the good agreement with experimental results for MgB2, the only magnesium compound with experimentally proved Tc = 39 K (theoretical value is 40.5 K). The performed computations for binary compounds Mg2X (X: Ge, Sn, Pb) reveal the high potential of magnesium compounds as high-temperature conductors at normal pressure, with predicted superconducting transition temperature up to 70 K.
Chitosan succinate and food-grade chitosan for the creation of tissue-engineering structures by the laser method
Authors: Savelyev M S , Pyanov I.V. , Vasilevsky P N , Fedorova Y.O. , Yu Gerasimenko A
Published: February 2021

Laser radiation makes it possible to form a composite material with laser radiation, which is intended for use as cellular- and tissue-engineering structures. It is important to obtain a uniform distribution of components throughout the volume of such material. Intermolecular interactions between chitosan and single-walled carbon nanotubes (SWCNTs) affect the structure of the composite. The results of IR spectroscopy and nonlinear optical studies have shown that the effect of laser radiation has different effects on the two types of chitosan, which was clearly demonstrated by SEM studies. Upon detailed examination, agglomerates in the composite material are clearly visible. Chitosan succinate less prevents the formation of agglomerates from SWCNTs, as a result of which a high agglomeration of nanotubes occurs among themselves in the composite material. The corresponding formations are distinguishable in the SEM images.
Determining efficiency of inhibition of johar flower ethanol extract (Cassia siamea Lamk.) in the corrosion reaction of A36
Authors: Khairuddin  , Nurhaeni  , Husen H M
Published: February 2021

The investigation about determining the efficiency of inhibition of johar flower ethanol extract in the corrosion reaction of A36 steel (ASTM)/SS400 (JIS) in 3% NaCl solution has been done. This research aims to determine the immersion time and concentration of johar flower ethanol extract in inhibiting the rate of corrosion on steel plates with the highest value of inhibition efficiency. Making the inhibitor is done by extracting the johar flowers using the maceration method. The extract was mixed into the 3% NaCl corroding media with variations in concentrations of 0, 1000; 2000; 3000 and 4000 ppm, then immersed steel plate samples with a size of 50 × 20 × 3 mm for the variation of immersion time 5; 10; 15 and 20 days. Corrosion testing is carried out using the weight loss method. The test results showed that secondary metabolite compounds in johar flower ethanol extract could function as a corrosion inhibitor by inhibiting the rate of corrosion on the steel plate. The inhibition efficiency for johar flower ethanol extract was found in the concentration of 3000 ppm with immersion time for 15 days, amounting to 33.49%.
Effect of nitrogen gas flowing continuously into the pyrolysis reactor for simultaneous production of charcoal and liquid smoke
Authors: Aladin A , Modding B , Syarif T , Dewi F C
Published: February 2021

Biomass waste such as sawdust or red fruit seed waste can be processed into charcoal (carbonized charcoal) and liquid smoke simultaneously by the pyrolysis method. The charcoal process using the pyrolysis method will be more perfect if the reactor is designed in such a way that oxygen from the air is not free to enter the reactor. The small amount of oxygen that is present and enters the reactor can be minimized by flowing inert nitrogen gas into the reactor continuously during pyrolysis. In this study, the effect of flowing nitrogen gas into the pyrolysis reactor was observed with a gas flow rate of 1 liter/minute using raw materials from wood sawdust biomass waste with a pyrolysis time of 2 hours and a pyrolysis temperature of 400 oC. The results showed that the quality of charcoal products was relatively better. The yield of liquid smoke was higher than the results of pyrolysis with nitrogen gas flow compared to without nitrogen gas flow. The calorific value of charcoal without and with nitrogen gas flow is 6828 cal/gram and 7109 cal/gram, respectively, the fixed carbon value is 68.37% and 70.40% respectively, and the yield of liquid smoke is 38.87% and 40.35%, respectively.
Lead(II) adsorption by biochar prepared from tanduk banana peels (Musa X Paradisiaca)
Authors: Fatimah  , Napitupulu M
Published: February 2021

Processing organic waste for use in various sectors is one way to maintain zero-waste and preserve the environment. The banana plant is only a tropical fruit that bears fruit only once and leaves behind the stems, leaves, and banana peels. The use of banana peel as a lead adsorbent was conducted by processing banana peels into biochar. Biochar making a pyrolysis process where the temperature starts from 400°C, 450°C, and 500°C, produces 33.00%, 31.73%, and 29.07% biochar. The biochar moisture content was 12.26%, 11.13%, and 9.32%, while the ash content was 9.62%, 6.08%, and 4.64%, respectively. The ability of biochar to adsorb lead was measured by Atomic Adsorption Spectrophotometry (AAS) with various pH and biochar weight. The optimum adsorption of lead (II) obtained at pH 5 with an adsorption amount of 49.96 mg/g, and a biochar weight of 400 mg with an adsorption amount of 12.49 mg/g
Extraction pectin from squash (Sechium edule sw) peels
Authors: Puspitasari D J , Damayanti N S , Nuryanti S
Published: February 2021

Squash (Sechium eduleSW) peels are wastes that have not been utilized. Inside the squash peel contains high economic compounds namely pectin that is used as a stabilizer in juice, jelly, jam and marmalades. The study aims to determine the effect of sample ratio and time extraction on the yield of pectin and the characteristics of squash skin pectin extracted. The study uses a completely randomized design with two factors, the ratio of samples 1:30, 1:40, 1:50, 1:60, 1:70 b/v dan extraction times 80, 90, 100,120 and 150 minutes. The extraction of pectin is done by citrate acids. The result showed that the optimum yield of pectin as much 22,1% can be extracted at a sample ratio 1:60 b/v and at 150 minutes of time extraction, the yield of pectin can be extracted optimum as much 24,60%. The characteristics of pectin were water content 8,86%, ash content 2,9%, methoxyl degree 12,81%, anhydrogalacturonic acid degree 37,77%, and esterification degree 16,73%. Pectin from squash peel is indicated as low methoxyl pectin that can be formed gel with sugar. The pectin produced has met the pectin quality standard of International Pectin Producers Association 2003.
Identification of stability and productivity the local red onion Palu based on the effect of genotype and planting location using a Structural Equation Model (SEM)
Authors: Junaidi  , Fadjryani  , Raihanah G R
Published: February 2021

The effort to find superior varieties is initially by regarding the genotype and location because of these factors contribute to the significance of the interaction between genotype and location (GEI) on productivity. This study is important in plant breeding because the results can be used to predict and to select the genotypes that are stable and adaptable at different planting location. Paying attention to productivity is not sufficient in the GEI analysis to select superior varieties. As a result, a method such as Structural Equation Model (SEM) is needed to explain the effect of genotype and environmental factors on GEI. The obtained results based on the AMMI biplot showed that the genotypes of red onion which have stable productivity at five planting locations, namely Batu (G1) and Sanren F1 (G4). Furthermore, the genotype that is stable planted in five locations is Kawak (G7). The SEM output showed that physical characteristics affect the number of productivity. However, environmental factors such as altitude, soil physical and acid contribute to the productivity of the plant. Finally, we can conclude that the genotypes planted in low locations with soil pH greater than 6 and dusty loam soil conditions will provide more product of red onion with good quality.
Preserving the heritage of Central Sulawesi batik motif using fractal geometry concept
Authors: Jaya A I , Ratianingsih R , Nacong N , Abu M
Published: February 2021

The heritage of Central Sulawesi batik have to be prevented in order to maintain Indonesian culture. Nowadays, available batik motif of Central Sulawesi needs to be explored to promote its cultural wealth. Using the main concept of fractal geometry, repetition and similarity, some motifs are designed in this research. The concepts make the motifs are displayed regularly. The base of the design is the diversity of the Central Sulawesi that located in Wallacea zone. This principal base makes the uniqueness of the motifs design. The generated motifs are varied by some parameters values that represent some mathematical operation and simulated by jbatik software. The operations are translation, rotation, dilatation, and reflection. This research results some motifes that are namely the waving cactus bloom, cesara, moringa chem, eboni herb, sigi fiesta, and harmony nature. The other advantage of the result is some motifs are also could be applicated as woven motif, the other Indonesian heritage clothing.