bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on Fire Information Based on Computer Network Technology
Authors: Cai Liu Rong , Ning Tao Hua , Chao Liu Rong 
Published: February 2021

Abstract
In the era of rapid development of information technology, the openness and sharing characteristics of network technology have changed people’s life patterns. Computer information technology not only changes people’s life patterns, but also lays a foundation for the construction of urbanized fire information. Taking the information application of computer network technology as the research object, this paper analyzes the important value and significance of the development of information-based fire protection, as well as the contemporary commonly used technologies, hoping to provide reference for the corresponding units.
Research on image super-resolution based on attention mechanism and multi-scale
Authors: Ren Xiaokang , Li Xingzhen 
Published: February 2021

Abstract
In order to solve the problem of the single feature scale of the generated image in the SISR field and the lack of texture information, a parallel generation confrontation network structure based on the attention mechanism and multi-scale is proposed on the basis of SRGAN, which adopts a dual generator and discriminator combined with attention module model. Train the network to learn multi-scale features, and integrate high-frequency information of different scales in the residual network. The experimental results on Set5, Set14, and BSD100 benchmark data sets prove that the algorithm has a good effect in restoring image detail information.
Research on Intelligent Analysis Technology of Network Security Risk Based on Big Data
Authors: Zhao Yibing , Zhang Juling , Xiang Siyu , Tang Yong 
Published: February 2021

Abstract
Aiming at the severity and distribution of abnormal behaviour, attack behaviour, compliance, and vulnerability of equipment in the power information system, this article applies big data technology to analyse and evaluate abnormal behaviour in the network, and uses machine learning to improve the network, the ability to identify security risks and the accuracy of assessments provide strong guarantees and technical support for improving the security and reliability of power information systems.
Evaluation of multimodal transport for emergency rescue based on online GIS and scheduled timetables
Authors: Long Chen 
Published: February 2021

Abstract
Unlike normalized flow of people and cross-regional transportation of goods, emergency transportation tasks have high requirements for timeliness and accuracy, which in turn places extremely high requirements on organization of transportation resources. Current paper uses modern information technologies such as online information and GIS to coordinate emergency transportation tasks. While considering the simultaneous delivery of portable equipment and materials, aiming at the fastest arrival of emergency rescue personnel in batches, current research studies the integration of batches and multimodal transportation. At the same time, the impact of scheduled timetables of trains and flights on the transportation actions is studied as well. Research shows that, aircrafts may play important roles in emergency transportation under catastrophe scene in China.
Improvement of radar detection capabilities for fluctuating targets using convolutional error control coding technique
Authors: Enma L P , Liu Jian , Wang Jie 
Published: February 2021

Abstract
Fluctuating targets are important phenomenons that affect detection probability. Several investigations about this topic have been carried on with good results to radar capabilities improvement. However, the increasing development of stealth technology has weakened traditional surveillance systems. This work has as main objective to improve radar detection of fluctuating targets using error control codes techniques. The purposed novel idea consists on a long pulse divided into a number of shorter sub-pulses, equally spaced in time duration. The binary phases of these sub-pulses are selected in accordance with Barker codes. Convolutional coding and Binary Phase Shift Keying(BPSK) modulation techniques are used. We determinate the probability of detection computing the bit error rate values. Matlab software is used to make several simulations that back up this theory. The results demonstrate that the probability of detection for Swerling I and Swerling III fluctuating target models is increased with the use of convolutional coding technique to detect and correct sub-pulse errors. This work offers a preliminary analysis of the detection improvement method with the use of error-control coding on radar pulsed with quite generalized assumptions thereby left a bigger space for future work with assumptions to fit practical implementation of the method.
Design of Intelligent Integrated Simulation for Marine Electric Propulsion System
Authors: Chen Xiaomi , Hao Chunxue 
Published: February 2021

Abstract
Based on integrated simulation technology of both marine electric propulsion system and artificial intelligence, a design of intelligent integrated simulation system of marine electric propulsion based on artificial neural network, fuzzy comprehensive evaluation and fuzzy neural network is proposed in this paper. The intelligent module mainly consists of a nonlinear simulation model, simulation evaluation and model optimization. Thanks to adopting an intelligent module, the accuracy of the simulation system is improved. The software implementation of intelligent integrated simulation for marine electric propulsion system is also discussed. The intelligent integrated simulation system of the marine electric propulsion system can guide the related design of electric propulsion system. The design of intelligent integrated simulation system of marine electric propulsion system can also guide the intelligent integrated simulation design of other systems.
Research on Indoor Visible Light Positioning Algorithm Based on K-means Clustering
Authors: Rui Zhang , Yerong Zhang 
Published: February 2021

Abstract
In order to improve the indoor positioning accuracy and reduce the impact of a reflected light on the positioning performance, based on the analysis of the existing RSS positioning algorithm, an improved positioning algorithm based on K-means clustering is proposed. According to the indoor visible light communication system model and optical power distribution, 10*10 receiving points are uniformly selected on the receiving surface of 5m*5m. Through the collection of the received optical power of each receiving point, the K-means clustering algorithm is used to classify 100 receiving points: the first cluster of points is less affected by a reflected light, and the second cluster of points is greatly affected by a reflected light. The second cluster of receiving points is weighted after classifying, and the simulation results show that the algorithm significantly reduces the room edge positioning error, and the positioning performance of the entire room is improved by 28%.
Joint Design of Physical-layer Network Coding and LDPC Code Modulated by 2FSK
Authors: Ling-yun Xie , Meng Tang , Hai-hua Li , Qing-hao Chen , Tai-bin Fang 
Published: February 2021

Abstract
In order to improve the transmission efficiency in wireless communication and reduce the bit error rate in the transmission process, a physical-layer network coding(PNC) system with 2FSK modulation and low-density parity check(LDPC) codes as the channel coding is established, and a relay detection scheme for the system is designed. This scheme first obtains the waveform diagram of the signal in the network encoding process. According to the characteristics of 2FSK modulation, and then we can extracts the prior probability soft information by the waveform characteristics, and finally we can combine the log likelihood ratio belief propagation(LLR-BP) algorithm to complete the decoding and relay mapping process. The simulation results show that the system adopts 2FSK modulation and has superior bit error rate performance compared with BPSK modulation. After introducing low-density parity check(LDPC) codes, the system can ensure high-speed transmission of information while effectively improving system Bit error ratio performance.
Research on UAV Application in Mountain Anti-terrorism Combat
Authors: Wang Wenxin , Jiang Bin , Yang Jian , Li Chao 
Published: February 2021

Abstract
Mountain anti-terrorism operations are an important anti-terrorism battlefield in our country. However, the complex terrain environment and harsh weather conditions in the mountainous areas cause difficulty in battlefield reconnaissance, poor communication guarantees, and difficulty in using the advantages of anti-terrorism forces in equipment, which brings great difficulties to mountain anti-terrorism. UAVs have become a sharp weapon in mountain anti-terrorism operations because of their flexibility and ability to adapt to the environment, and can effectively avoid casualties. Through approach reconnaissance, aerial firepower strike support, and relay communication guarantees, UAVs will show their talents in mountain anti-terrorism operations.
Construction of systems for remote monitoring of measurements of medical signal parameters
Authors: Lapina T I , Lapin D V , Petric E A 
Published: February 2021

Abstract
Some non conventional methods of model identification based on data normalization are presented in the article. The method of Data Normalization can be effectively used in those fields of industry optical engineers and technology processing of optical signals, which suffer from factual difficulties while gathering experimental data. The named method helps to receive information about some tendencies and regularities in process and objects dynamics, identify similarities and differences of their structure, their quantitative estimations, to provide the statistical explanation of experimental data and real-time analysis.
Systematization of approaches to assessing the quality of spatio-temporal knowledge sources
Authors: Savosin S V , Mikhailov S A , Teslya N N 
Published: February 2021

Abstract
There are two main ways of creating and filling spatio-temporal knowledge bases: by professional cartographers and by volunteers using the crowdsourcing concept. The knowledge provided by professionals is highly accurate, but narrow in scope and domain-specific, as well as rarely updated. Editing of this kind of sources is impossible without permission, which makes them closed, despite the possibility of free use of the knowledge itself. On the opposite, ordinary users can provide a large amount of information in various fields of knowledge with minimal delay. However, the quality of such information and its accuracy will differ depending on the subject area and external factors, such as the accuracy of user devices sensors, the distribution of users in the area, etc. The integration of knowledge from various sources will increase the overall accuracy and relevance of the data provided, which can be used to increase quality of decision making. Automatic integration requires the development of methods for estimating quality of knowledge sources, to rank them and choose only those that can provide sufficient quality in the criteria of the problem being solved. This paper presents a systematization of existing approaches to assessing sources of knowledge and, in particular, spatio-temporal knowledge.
The ontology driven SLAM based indoor localization technique
Authors: Shchekotov S V , Smirnov N S , Pashkin M P 
Published: February 2021

Abstract
The proposed technique facilitates time-consuming procedure for setting up Wi-Fi or Bluetooth access points, indoor map building and signal propagation model calibration. The technique based on OWL ontology and the SLAM method includes the phase of forming a training sample, as well as the phase of simultaneous navigation and mapping. The SLAM method implements The Gaussian Process Latent Variable Model (GP-LVM). The proposed method is based on solving the regression problem using machine learning methods to form a training sample, as well as solving the problem of reducing the dimension for simultaneous navigation and map building. As a training sample, the smartphone‘s internal sensor readings (steps and rotation angles) and Wi-Fi received signal strength values obtained using crowd calculations are used. The resulting training sample is used to determine the parameters of the correlation function that sets the correlation between the user‘s localization points. The proposed ontology is intended to determine different events occurring during user’s movement and involve the appropriate phase of the proposed technique.
Development of a method for determining the state of a person using a chat bot
Authors: Kulikova J V , Orlova Yu A , Rozaliev V L , Zaboleeva-Zotova A V , Lelikov R L 
Published: February 2021

Abstract
The aim of this work is to develop a method for determining the state of a person using a chat bot. The existing solutions were analyzed, their shortcomings were identified in order to create a more optimal solution. The proposed method is based on the creation of a chat bot based on a neural network. The article presents the types of neural networks with a description of the principles of operation, discusses the possibilities of programming languages for solving the task, and also provides a rationale for the chosen programming language - Python, presents the architecture of a neural network in this language. Since the most important and difficult task when working with a neural network is its training, the article describes this process with a description of each stage of training. Also, the interface of the developed application is presented with an example of the pictures used by the chatbot.
The impact of formative quizzes using CorrectWriting question type on learning word order in an ESL course
Authors: Sychev O A , Prokudin A A , Evtushenko O E , Toporkova O V 
Published: February 2021

Abstract
Studying word order in English sentences is a problem for ESL students whose native languages allow flexible word orders. Developing skills in formulating English sentences often requires trial-and-error process that takes time and requires supervision. Quiz software that is able to analyse students’ answers, and give meaningful feedback on mistakes in word order and hints on fixing them allows training without teacher’s supervision that greatly enhances the amount of attempts a student can do. In this study, we used CorrectWriting question type for Moodle LMS to create formative and summative quizzes for Russian students learning English as a second language. The experiments show that the students who made more than one attempt of formative quizzes had significantly better learning gains than the students who didn’t use formative quizzes or attempted them only once. It also showed vulnerabilities in question design that need to be fixed to utilise software features better in learning process.
Fuzzy cognitive modeling of socio-economic systems taking into account the time factor
Authors: Rogachev A F 
Published: February 2021

Abstract
Analysis and identification of trends in the development of socio-economic and socio-technical systems is a complex problem, the solution of which is an important direction in the development of scientific approaches to management. The use of a cognitive approach based on the construction, structural-parametric identification, and research of fuzzy cognitive maps (FCM) for these purposes is constrained by the complexity of time factor accounting. A review of domestic and foreign sources based on a systematic approach revealed the key areas of time series data Mining, which currently combines statistical, neural network and fuzzy models and technologies for time series analysis (TS), including cognitive approaches. Indirect expert methods used for parametric identification are based on dividing the problem of determining the weights of interaction of factors into simpler subtasks (Saati Method, Jager level method, Churchman-Ackoff method, etc. The elements of the FCM adjacency matrix, which characterizes the mutual influence of concepts, are proposed to be represented as two components – (1) a constant that is indistinctly set by experts; (2) a time-dependent one, the parameters of which are estimated from the analysis of the dynamics of statistical data over a certain period. The use of time-dependent parabolic dependence for setting the elements of the adjacency matrix FCM is proposed. In the further research strict methods for parameterizing dynamic functions that define the level of interaction between NCC concepts can be developed to construct fuzzy cognitive models that explicitly take into account the time factor.
Development of a comprehensive approach to personalized patronage of patients with stable angina using a mobile application
Authors: Orlova Y A , Frolov M Y , Zubkov A V , Sibirny N D , Donsckaia A R 
Published: February 2021

Abstract
This article discusses the problems of modern treatment and patronage of patients in the rehabilitation period. The authors of the work developed a new approach to accompanying a patient suffering from cardiovascular diseases, in particular, such a disease as stable angina was considered. A service was developed that includes an app for the Android mobile operating system and a website. The work describes the main functionality of that service, as well as shows the changes that occurred during the integration of the service into the existing process of patient patronage.
Using the results of remote sensing of land for programmed agricultural production in arid conditions
Authors: Melikhova E V 
Published: February 2021

Abstract
The article considers methodological approaches to substantiating the main tasks solved by the developed software package for managing agricultural production in the programmed cultivation of agricultural crops. There are characteristic differences in the reflection spectrum of agricultural plants due to the influence of water vapor absorption. The total reflected radiation in the optical and near-infrared range, recorded by remote sensing, depends on the biological and varietal characteristics of plants, the development of the leaf surface, their growth phases, the chemical composition of the soil, and other factors. The set of vegetation indices NDVI and its modifications is justified. Problems of mathematical modeling of irrigation technologies in arid conditions based on differential equations are revealed. The model takes into account agrochemical features of soils, biological properties of crops, agroclimatic conditions, as well as technological parameters of irrigation regimes. The necessity and expediency of using digital information technologies in agricultural production, including irrigation reclamation, for operational management and control of agrotechnological parameters of crop cultivation are justified. A conceptual and logical database model for programmed crop cultivation has been developed. The developed software package will allow systemically aggregating and accumulating agrophysical and hydrometeorological information to justify land reclamation measures.
Performance of FSPAOR iteration for solving one-dimensional space-fractional diffusion equation
Authors: Sunarto A , Sulaiman J , Chew J V L 
Published: February 2021

Abstract
This paper considers the numerical solution of a one-dimensional space-fractional diffusion equation. To obtain the solution, we use an unconditionally stable implicit finite difference approximation with the Caputo’s space-fractional operator. We study on improving the convergence rate of the solution while solving the generated linear system through the approximation equation iteratively. In our study, we apply the preconditioning technique to construct a preconditioned linear system which eventually derives into a Full-Sweep Preconditioned AOR. From the presented results, we show that the proposed Full-Sweep Preconditioned AOR iterative method has superiority in efficiency compared to the basic Full-Sweep Preconditioned SOR and Full-Sweep Preconditioned Gauss-Seidel iterative methods.
Multifunction Trolley Based On Anthropometry for UD. Santosa to Minimize the Physical Workload That Caused by Material Manual Handling
Authors: Milania A F , Prabaswari A D 
Published: February 2021

Abstract
This paper discusses about the manual material handling activities in the UD. Santosa. The activities give a particular injury because of the excessive load. Minimizing manual material handling can decrease and prevent a big number of injuries and fatigue. The increased rate of the injury that happened on the workers is also one of the indicator that there is excessive physical workload. This study aims to minimize the manual material handling and the physical workload by making multifunction trolley using anthropometrics. The method that used in this research is Cardiovascular Load, Anthropometrics. The result shows that the recommended weight load for each operator is 7.30411 kg, 5.93229 kg, 4.949725 kg, 2.88399 kg, and 2.594356 kg to avoid the risk of injury. For the physical workload for operators classified into 60% need to be improved and 40% no fatigue. The size for the multifunction trolley based on anthropometrics is 72.54 cm for the height of incline mode, 134.56 cm for the height of the trolley, 105.813 cm for the height of the of the hand holder, and 9.19177 cm for the width of the hand holder.
Re-Designed Work Station for Breeding Hens Based On Work Posture and Anthropometrics in Widodomartani
Authors: Milania A F , Siregar F M , Arista N , Al-karimah N I , Prabaswari A D 
Published: February 2021

Abstract
Animal husbandry is one of the agricultural sub-sectors that has an important role in contributing quite significantly to the country’s economy and breeding hens are one of those. In setting up breeding hens that sufficiently adequate it does not require substantial capital. However, many breeding hens in designing the work station are less ergonomic, giving rise to the level risk of musculoskeletal disorder. The aim of this study is to assess the work posture of the operators and from the result of this study, it can be proposed improvement of the work station to improve work posture and to reduce the level of Musculoskeletal Disorder. The method that used in this research is Quick Entire Check, Nordic Body Map, and Anthropometrics. The result showed that the exposure level operator 1 got value 41.47%, the action that needs to be done is need more research to make it safe. While operator 2 got value 55.68%, the action that needs to be done is doing another research and change the activities. Also, it can be seen if the pain felt by the two operators is in the neck, buttock, shoulder, arm, calf, and knee. From the research results, the recommendation given is to redesign work stations that pay attention to work posture by implementing anthropometry and adding several innovations.