bluuebunny/crossref_metadata_2025 huggingface dataset:
Limit load estimation for finite plates with semi-elliptical defects under tensile loading
Authors: Shi K K , Fu X L , Xie H , Shao X J , Tian J
Published: February 2021

The ASME code allows the designer to circumvent many of the problems arising in design by elastic analysis by performing plastic or limit analysis of the component. Unlike elastic analysis, these analyses take account of the redistribution of stress upon yield. In limit analysis, the calculation of the limit load for finite plate with different semi-elliptical defects is an important stage for mechanical safety evaluation. The elastic compensation technique proposed by Mackenzie can be used to provide the limit load of a structure with a finite element method and aims at producing a suitable stress filed for the lower bound theory. In the present study, it is assumed that the finite plate exists three kinds of semi-elliptical cracks with low aspect ratio a/c (a/c=0.1, 0.5 and 1.0), respectively. The improved elastic compensation technique realized by finite element method is applied in the limit load estimation. At last, the results show that the improved elastic compensation technique can be used to obtain the limit value for the finite plate with different semi-elliptical defects under tensile loading. Moreover, the improved elastic compensation technique can be easily implemented in any finite element method and enables the limit load for any complex structure to be obtained swiftly.
Development and quality control method of variable torque propeller for wind tunnel power simulation
Authors: Jiang Y B , Wei R , Gao L H , Huo G , Cheng L
Published: February 2021

In order to study the comprehensive influence of propeller power and sea surface effect of a seaplane, a composite material variable torque propeller for wind tunnel power simulation was developed. In order to make the quality of wind tunnel test data meet the standard of engineering application and control the quality of propeller products, a quality control method was developed to control the quality of design, checking, manufacturing, verification and operation of the propeller in all stages. In this paper, the research and development process and quality control method of the propeller, tests and the detection results, as well as the application test are described in detail. The results show that the quality control method described in this paper can be used to design and manufacture the propeller products which match the technical indicators, and the power simulation system composed of the propeller can exert slipstream influence on a certain seaplane under various working conditions, so as to meet the requirements of the study on the comprehensive influence of propeller power and sea surface effect of the aircraft.
Optimization design of the reactor coolant pump flywheel comprised of multi-ring packing heavy metal alloy
Authors: Jiang L , Wu C W , Shao X J , Zhang Y , Yu M D
Published: February 2021

To improve energy storage performance of the multi-ring RCP flywheel comprised of inner hub, tungsten alloy ring and outer retainer, optimization design process for the radial thicknesses of components and interference fit assembly is demonstrated. Radial thicknesses of these components and magnitude of interference fit are set as design parameters to construct parametric analysis model. Design of experiments (DOE) technique is adopted to generate design matrix for sensitive analysis. Subsequently, radial basis function (RBF) approximation is employed to search for the optimal design considering structural integrity requirement. Finally, a proper range of the magnitude of interference fit is obtained which can not only prevent neither slippage nor separation between the inner hub and tungsten alloy ring but also ensure the safety of structural strength. In addition, it is found that to ensure a high moment of inertia and energy density, a reasonable large radial thickness of tungsten alloy ring and a reasonable small radial thickness of outer retainer are required.
Numerical analysis of the effect of fuel load on downward flame spread
Authors: Zhu X L , Jiang Y
Published: February 2021

This paper performs parameter studies varying sample thickness and volume density to investigate the effect of surface density on downward flame spread using Direct Numerical Simulation (DNS). Surface density is a significant property that affects fuel loads on the fuel surface greatly. The results reveal that all the thin fuels of 70 – 180 g/m2 attain a steady state, which means that the flame base and pyrolysis front move downstream with the same rate. Moreover, the propagating rates of the flame base and pyrolysis front decrease with the increasing surface density. Subsequently, the flame contour and flame heat feedback in preheated region are studied. Along the flame base downstream, dimensionless flame standoff distance grows gradually till a peak reaches at appropriately (Z-Zb
)/Zf
of 0.23, and then is reduced to a minimum near the flame front. Radiative heat flux occupies the dominant position upstream the flame base, and its distribution with normalized space (Z-Zb
)/Zf
is established. The present paper together with previous works can provide further understanding on the effect of fuel loads on downward flame spread.
Multiscale permutation entropy and supervised classifiers for state detection in an ICE
Authors: Mejía J C , Echeverry J D , Quintero H F
Published: February 2021

Entropy has been positioned as a measurement capable of detecting irregularities and uncertainties in time series. Specifically, Multiscale Permutation Entropy (MPE) has positioned itself as an alternative to classical characterization methodologies, managing to identify nonlinear dynamics present in non-stationary signals. MPE has been used successfully to identify states of different systems without relying heavily on factors such as length or sampling frequency. This article presents a robust methodology that combines MPE with a feature selection technique and a supervised classifier (Analysis from Variance (VRA) and K-Nearest Neighbours (KNN) respectively). The robust proposed methodology is validated through two experiments (bearing failures and states of an internal combustion engine (ICE)). The proposed methodology overcomes the experiments with high precision and low computational consumption.
Microstructure evolution and sintering kinetics of Ti(C,N)-based cermet
Authors: Xiao S Q , Gong M F
Published: February 2021

In this paper, the grain growth behavior of Ti(C,N)-based cermet, including the microstructure evolution and sintering kinetics in the sintering process at different temperatures for different holding time, was studied experimentally and theoretically. A comprehensive grain growth model for Ti(C,N)-based cermet was established based on the experimental data. Furthermore, different influencing factors of microstructure evolution during sintering for Ti(C,N)-based cermet were investigated systematically by a scanning electron microscope. The results showed that the sintering temperature and holding time have a significant effect on the microstructure evolution of Ti(C,N)-based cermet. The grain growth rate was the fastest at the temperature range of 1300°C to 1400°C. The grain growth rate was reduced slightly at higher temperatures. A comprehensive sintering kinetics model of Ti(C,N)-based cermet during the sintering process was obtained based on the experimental results via nonlinear regression method.
Research on Relation Extraction Method Based on Similar Relations and Bayesian Neural Network
Authors: Fang Yiqiu , Zang Yingjie , Ge Junwei
Published: February 2021

The solidification of network parameter values for most relation extraction models after training makes the model overconfident in the process of prediction and classification tasks. Moreover, the interference of similar relation in the text data will affect the effect of relation extraction. We propose a relation extraction model based on relation similarity and Bayesian neural network. This model uses the logistic regression loss function to make the training parameters closer to the target relation and away from the similar relation, thereby eliminating the interference of the similar relation in the relation extraction task. In addition, it is also possible to learn a probability distribution from the weights of the Bayesian-LSTM (Bayesian-Long Short-Term Memory) neural network, and retain the corresponding uncertainty on the basis of obtaining long-distance dependence information using LSTM, so that the model learns more data features while performing regularization at the weight level. The model also uses an attention mechanism to pay more attention to useful information. The experimental results on the Wikipedia data set TACRED (TAC Relation Extraction Dataset) data set show that the proposed method effectively improves the effect of the entity relation extraction model.
Research on Fire Information Based on Computer Network Technology
Authors: Cai Liu Rong , Ning Tao Hua , Chao Liu Rong
Published: February 2021

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.
On the Biot–Savart law of electromagnetism applied to the atomic circulation current
*
Authors: Hey J D
Published: February 2021

The law of Biot and Savart, derived by observation of the magnetic field produced by electric current flowing in a macroscopic conductor, is shown to yield the correct expression for the nuclear hyperfine interaction, when applied to the electron circulation current derived for hydrogenic atoms from the theories of Pauli and Dirac, as further developed independently by Darwin, Gordon and Hartree. The law thus applies also on the microscopic scale to the magnetic field generated by the electron probability flux of the various atomic eigenstates, and may clearly be generalised formally for application to many-electron atoms, as outlined by Hartree. The present, fully relativistic, treatment is advantageous in avoiding the usual artificial splitting of the hyperfine interaction into a magnetic dipole–dipole contribution and a separate contribution arising from electron orbital motion. The formula obtained forms the basis for the inclusion of higher order (quantum electrodynamic and nuclear recoil) corrections. Interest in this subject is enhanced by observations of ‘strongly forbidden’ (magnetic dipole) atomic transitions arising from the nuclear magnetic interaction, notably the 21 cm line of hydrogen, which has played an important role in astrophysics, in both measurements of galactic rotation and studies of the early Universe.
Work-Life Experiences of Women in the Construction Industry: A Case of Women in Lagos Mainland, Nigeria
Authors: Tunji-Olayeni P F , Kajimo-Shakantu K , Oni AA
Published: February 2021

The construction industry has not been able to maximize its full potentials in terms of harnessing the talents and abilities of its diverse workforce. Despite calls for a more pluralistic and inclusive workforce, the construction industry remains male-dominated, thereby limiting its growth potentials. The study examined the effects of workload on family expectations intending to support initiatives on gender equality and equity that will improve working conditions in the industry and eventually increase its performance and competitiveness. The study used questionnaires to achieve the research purpose. The survey was based on a purposive sampling of female construction professionals from different companies in Lagos Mainland, Nigeria. Descriptive statistics and linear regression were used for analysing the data. From the linear regression model, it was revealed that workload affects family responsibility at 73.20%. The significant family responsibilities affected by workload included: making alternative arrangements for children’s school transportation, spending time with spouse, spending time with children, taking care of household chores, and going shopping for the family. The study focused only on female construction professionals working in the Mainland area of Lagos, Nigeria. More empirical evidence of the effects of workload on family responsibilities can be obtained by considering female professionals in other regions of Nigeria. These findings have serious implications on job fulfilment, organizational loyalty, employee retention, and organizational performance. The study recommends flexible working hours and other gender-friendly policies to attain the much desired inclusive, profitable and sustainable construction industry.
The Covid-19 Pandemic: Online Teaching and Learning at Higher Education Institutes
Authors: Armoed Z
Published: February 2021

The most recent public health emergency of global concern has presented itself as the Covid-19 pandemic, which began in late 2019 Wuhan, China and has rapidly spread around the world. This disease has received extensive global attention due to the rapid rate of transmission between individuals, with the elderly easily affected. Countries, economies and sectors around the world faced immediate closure to mitigate the infection rate with scientists constantly searching for a means to eradicate the novel coronavirus disease (Covid-19). The education sector was one of the sectors significantly affected by the onset of the pandemic due the vulnerability of its setting. UNESCO (2020) reported that as of the 6th of April 2020, 1,576,021,818 billion students were affected across 188 countries at all levels of teaching and learning. As a result, the immediate implementation of online teaching and learning modalities were required with a primary focus on maintaining a standard of teaching and learning that met the needs of both academic staff and students. However, due to the socio-economic challenges faced by South Africans, the education sector experienced numerous challenges in the implementation process of online teaching and learning modalities (HEIs). This paper seeks to review the challenges experienced by academic staff and students with the implementation of online teaching and learning modalities at higher education institutes across South Arica amidst a global pandemic. Future research suggestions include a comprehensive research study on the extensive effects of the Covid-19 pandemic on higher education institutes.
Implication of BIM on selected aspects of sustainability
Authors: Mésároš Peter , Smetanková Jana , Mandičák Tomáš , Krídlová-Burdová Eva
Published: February 2021

Sustainability in civil engineering industry represents space for the subject of discussions and extensive research opportunities. On the other hand, this represents worldwide pressure to explore this area. Sustainability in the context of Building Information Modelling technology is also often a controversial topic. BIM technology brings many benefits. Exploring these technologies from the field of sustainability and environmental aspects is more than desirable in the light of global developments in this field. The aim of the research was to point out and propose a structure of environmental parameters based on the acquired knowledge, which will be incorporated into the emerging database of elements - information models. The paper presents a proposal for the structure of the database of structural elements taking into account cost parameters, time parameters, environmental parameters and life parameters, points out the main advantages of the proposed database and defines the aims of further research. The aim of the paper was to analyse the current state and possibilities of implication of certification systems for sustainable construction and describe the current state and impact of BIM implication on selected aspects by survey.
Advanced Treatment Process for Secondary Effluent of Municipal Wastewater Based on A/O Biological Filtration Technology
Authors: Zhengjiang Wang
Published: February 2021

Through the removal effects of the anoxic/oxic (A/O) biological filtration technology on organic matters, nitrogen and phosphorus, the advanced treatment for secondary effluent of municipal wastewater was analytically characterized by means of filter material selection and natural biofilm start-up. The results show that the composite slag has the best adsorbing effects on ammonia nitrogen and phosphorus, reaching 57% and 32.2%, respectively; as the natural biofilm start-up is smoothly implemented, the removal rate of ammonia nitrogen reaches over 60% in the first phase and over 96% in the second phase. This study provides a reference for the advanced treatment for secondary effluent of municipal wastewater.
Research on the Impact of Rooftop Photovoltaic on Reducing Carbon Dioxide Emissions
Authors: Tang Linyan
Published: February 2021

At present, the biggest environmental problem facing mankind is the rapid change of climate. In order to be able to mitigate climate change, we must attach importance to carbon reduction actions. China has taken many measures to adjust the energy structure to reduce petrochemical energy consumption and carbon emissions as much as possible. In the development of the power industry, the universal application of renewable resources such as solar energy can adjust and upgrade the traditional thermal power structure. The effective development of renewable resources such as solar energy can greatly reduce carbon dioxide emissions, which is an important measure to reduce carbon emissions. The establishment of solar photovoltaic power generation systems on the roof can improve the development level of China’s photovoltaic power generation systems. At the same time, this can also reduce the energy consumption of coal-fired power, which is of great help in reducing carbon emissions. In the process of researching rooftop photovoltaic power generation systems, we need to analyze the importance of solar photovoltaic power generation. Meanwhile, we also need to explore the practical application of rooftop photovoltaic power generation systems, and conduct research and analysis on the factors affecting rooftop photovoltaic carbon emission reductions. Only in this way can we accurately grasp the impact of rooftop photovoltaics on carbon dioxide emissions, and provide a corresponding reference for promoting the widespread application of rooftop photovoltaic power generation systems.
Application Research on Objective Evaluation of Vehicle Interior Odor Based On Weber-Fechner Law
Authors: Li Chuan Jie , Yao Qian , Liu Ya Lin , Wang Yan Meng , Feng Shi Hao
Published: February 2021

In this paper, four typical compounds of odorants were selected as the research objects. The mathematical model hypothesis is established which based on the Weber-Fechner law, and then the relationship between the concentration of odor substances and the odor grade is verified to judge whether this law is applicable to the objective evaluation of vehicle interior odor. The results show that: the concentration of single odor substance and odor grade, the concentration of two kinds of odor substances and odor grade are in accordance with this law. It is proved that the relationship between odor substance concentration and odor grade conforms to the law to a certain extent, which provides an important theoretical basis for objective evaluation of vehicle interior odor and control vehicle environment to create an environmental and healthy vehicle.
The influence of vegetation cover change on the land surface temperature in the central Guizhou urban agglomeration from 2000 to 2019
Authors: Sun Weizhao , Yang Kun , Luo Yi
Published: February 2021

We used land surface temperature (LST) and normalized difference vegetation index (NDVI) data from 2000 to 2019, using change trend analysis, correlation analysis, and other methods to explore the impact of vegetation cover changes on ground surface temperature. From 2000 to 2019, in the central Guizhou urban agglomeration, the LST showed a fluctuating downward trend, with an average trend rate of -5.1%a−1. NDVI showed a fluctuating upward trend, with an average trend rate of 0.56%a−1. The area with increasing LST (P<0.5) accounted for about 9.8%, and the area with a decreasing trend accounted for about 90.2%. The region of NDVI showing an increasing trend (P<0.5) accounted for approximately 97.34%, and the area of decreasing trend accounts for about 2.67%. About 96.8% of the regional area NDVI is negatively correlated with LST, and about 3.2% of the regional area is positively correlated.
Earthquake mechanism analysis of cross-faults system of Zhangjiakou-bohai fault belt in North China
Authors: Hong Li
Published: February 2021

North China is one of the earthquake-prone areas and Zhangjiakou-bohai belt is one of the main seismic tectonic belt in North China. There are many cross-faults in the belt and strong earthquakes occur at the intersection of faults. In order to explore the fault behavior and strong seismic mechanism of cross-fault system, we establish 3D finite element models to simulate the sliding activity of faults under the regional tectonic environment.
Analysis of Topographic Features Based on Yunnan Fire
Authors: Shangqi Duan , Haidong Chen , Xingke Ge , Shuangde Huang , Tao Wang , Debin Xu , Baoyu Xu
Published: February 2021

The Yunnan power grid has the characteristics of wide distribution and large geometric size, which makes the power grid vulnerable to natural disasters such as wildfires. The unique topography and climatic conditions of transmission lines crossing mountains, forests and other zones can easily lead to the outbreak of mountain fires, or even the tripping of transmission lines. In serious cases, transmission towers may be destroyed, thus causing major power accidents. The occurrence of mountain fire is closely related to topographic factors, and the change of each topographic factor (elevation, slope, slope direction, etc.) has a certain influence on fire. This paper mainly studies the relationship between three terrain factors and fire. Based on the statistical analysis of remote sensing data from 2005 to 2020, the terrain features and their influence of fire spots in Yunnan province were analyzed. The results show that most of the fires occur within the range of 1000-2000m above sea level, and the fires occur frequently. The frequency of fire occurring below 1000m and above 2000m is low. The occurrence frequency of fire is higher in the gentle slope range, among which, the number of fire point samples is the largest within the range of 5°-15°, followed by 0°-5°and less than 15°.In this paper, eight slopes are divided to make statistics of fire points, and the number of fires in different slopes also fluctuates, among which the south slope has the highest fire risk, accounting for 16.0%.The West Slope accounted for only 10.0%, with the lowest fire risk. Terrain factor is a fixed variable that has a fixed influence on the regional fire risk. Therefore, terrain analysis of fire is of great significance for the prevention of mountain fires in power grid.
Change trend analysis of the time-series shadow-eliminated vegetation index (SEVI) for the Wuyishan Nature Reserve with the Sen+Mann-Kendall method
Authors: Jiang Hong , Wu Yongfeng
Published: February 2021

In order to reveal the characteristics of spatial distribution and dynamic change of the forest in the Wuyishan Nature Reserve from 2000 to 2019, the recently proposed shadow-eliminated vegetation index (SEVI) and the method of Sen+Mann-Kendall were used together in this study. The results show a trend of “decreasing first and then increasing” of vegetation cover change of the Reserve during the sub-periods of 2000-2011 and 2012-2019, but, as a whole, the vegetation cover of the Reserve was improved during 2000-2019, with 43.76% slight improvement and 55.18% significant improvement, approximately.
Electromagnetic Signal from a Circumbinary Gas Disk Around Merging Binary Black Holes
Authors: Huang Zhuoyun , Yu Haoran
Published: February 2021

The detection of gravitational waves (GW) is a major achievement in physics and astrophysics. Up to now, more than 30 GW events resulting from the merger of compact celestial bodies have been observed by LIGO and VIRGO. Because electromagnetic radiation is the main method for studying astrophysical processes, whether physics can be combined with astronomy depends on whether the corresponding body of gravitational wave events can be found on electromagnetic radiation. Unfortunately, only the electromagnetic counterparts of the twin neutron star merger are currently seen. In gravitational wave astronomy, a very important subject is: Is it possible to generate electromagnetic radiation when the two black holes’ merge? In this essay, the dynamic process of the gas disk surrounding the binary black hole is studied through numerical simulation, and the long-term evolution process of these gases on the cosmological time scale is studied at the same time. The evolution process of the gas disk of the ring binary black hole can be obtained, which provides a theoretical limit on whether the electromagnetic counterpart of the merger of the binary black hole can be seen in the future.