bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhancing detection of steady-state visual evoked potentials using channel ensemble method
Authors: Yan Wenqiang , Du Chenghang , Luo Dan , Wu YongCheng , Duan Nan , Zheng Xiaowei , Xu Guanghua 
Published: February 2021

Abstract

Objective. This study proposed and evaluated a channel ensemble approach to enhance detection of steady-state visual evoked potentials (SSVEPs). Approach. Collected multi-channel electroencephalogram signals were classified into multiple groups of new analysis signals based on correlation analysis, and each group of analysis signals contained signals from a different number of electrode channels. These groups of analysis signals were used as the input of a training-free feature extraction model, and the obtained feature coefficients were converted into feature probability values using the softmax function. The ensemble value of multiple sets of feature probability values was determined and used as the final discrimination coefficient. Main results. Compared with canonical correlation analysis, likelihood ratio test, and multivariate synchronization index analysis methods using a standard approach, the recognition accuracies of the methods using a channel ensemble approach were improved by 5.05%, 3.87%, and 3.42%, and the information transfer rates (ITRs) were improved by 6.00%, 4.61%, and 3.71%, respectively. The channel ensemble method also obtained better recognition results than the standard algorithm on the public dataset. This study validated the efficiency of the proposed method to enhance the detection of SSVEPs, demonstrating its potential use in practical brain–computer interface (BCI) systems. Significance. A SSVEP-based BCI system using a channel ensemble method could achieve high ITR, indicating great potential of this design for various applications with improved control and interaction.
A novel liquid lithium jet-cooled finger-type divertor target concept for fusion power plant application
Authors: Wang Zhen , Zhang Shichao , Chen Zhibin , Jia Jiangtao , Chao Chen 
Published: February 2021

Abstract
The divertor target is the most thermally loaded plasma-facing component in a foreseen DEMO reactor and beyond, which has to tolerate the peak high heat fluxes of up to ∼20 MW m−2 produced by intense plasma bombardment, radiation and nuclear heating. However, none of current designs including water-cooled and helium-cooled concepts can satisfy this requirement. Motivated by the excellent power removal capacity of liquid metal coolant and combined with the structure characteristics of the finger-type helium-cooled target, a novel concept of liquid Li jet-cooled finger-type divertor target for DEMO reactors was proposed in this paper. The performance analysis, including thermal-hydraulics analysis, mechanical analysis and MHD effects analysis, have shown that the proposed design can withstand 20 MW m−2 heat load because the temperatures of the structural materials remain within the thermal rules and the maximum thermo-mechanical stress in the VM-W thimble is approximately 484 MPa appearing in the round corner, which is below the 3S
m limit at the corresponding temperature. Moreover, a theoretical and empirical analysis has confirmed that MHD effects on pressure drop and heat transfer is rather limited in the design. The comparison of this new design with other representative designs including water-cooled ITER-like target design and helium-cooled modular jet target design has been made, and the results shows that the proposed liquid Li cooled target design has better performance under 20 MW m−2 high heat flux and ∼10 dpa neutron irradiation. Therefore, this design is promising to provide a new option for solving the DEMO reactor divertor heat removal issues. Certainly, a large number of R&D efforts are still needed to ensure the success of this concept, particularly in the areas of materials, fabrication and irradiation.
Retraction: Singluar Topoi of Countably Non-local, Continuously Cayley, Maximal Elements and the Continuity of Closed Elements(Journal of Physics: Conference Series
1646 012114)
Authors: Wan Fang 
Published: February 2021

This article has been retracted by IOP Publishing on 18 February 2021 in light of clear evidence that it was computer generated. IOP Publishing is investigating why this was not identified during the submission and peer review process by the conference. As a member of the Committee for Publication Ethics (COPE) this has been investigated in accordance with COPE guidelines and it was agreed the article should be retracted.
Retraction published: 18 February 2021
Neutrosophic Commutative N-ideals in KU-algebras
Authors: Vasu M. , Kumar D. Ramesh 
Published: February 2021

Abstract
In this paper, the new concept of neutrosophic commutative N-ideal in KU-algebras is introduced, and investigated some related properties. Also, a relations between a neutrosophic N-ideal and a neutrosophic commutative N-ideal are discussed. Characterizations of a neutrosophic commutative N-ideal are considered.
The analysis of the FM/FM/1 queue with single working vacation and impatience of customers
Authors: kannadasan G. , Devi D. 
Published: February 2021

Abstract
This paper deals with an M/M/1 queueing system with a single working vacation and reneging of impatient customers and fuzzy parameters. For this fuzzy queueing model, researches fetch performance measure of interest such as the mean number of customer in the system during working vacation, the mean number of customers in the system during regular busy period and the mean of reneging rate of the system. Finally numerical results are presented to show the effects of system parameter.
Privacy Protection Method of Electric Power Network Based on Blockchain
Authors: Zhang Maolin , Zhao Weihua , Shi Wei , Zhou Haiming 
Published: February 2021

Abstract
In order to ensure the integrity and confidentiality of power data in the era of big data, it is very important to protect the privacy of smart grid data information. Analyzing electricity big data can obtain electricity consumption habits of electricity users to guide the formulation of power supply plans. This experiment uses an asymmetric encryption algorithm. The encryption and decryption of the asymmetric encryption algorithm use two different keys to fully guarantee the security of the blockchain system. The experiment is based on the blockchain technology in photovoltaic microgrid electricity trading, which belongs to the current type of trading, which is divided into five stages. The service provider is a node of the blockchain system. All smart contracts are encrypted by the private key of both parties in the transaction and the public key of the service provider, which fully guarantees the privacy of users. The experimental data shows that the smart contract is decrypted by the private key and the public key of both parties, so as to obtain the relevant information of the transaction and make the corresponding power dispatch work during the transaction period.The blockchain system solves the security and privacy issues of both parties in the absence of a third-party intermediary. Therefore, the use of blockchain technology can achieve a higher degree of automation for point-to-point power transactions.
PLC Control System of Pneumatic Manipulator Automatic Assembly Line Based on Cloud Computing Platform
Authors: Zhou Yucheng , Li Yifei 
Published: February 2021

Abstract
With the development of science and technology, cloud computing, big data and artificial intelligence and other new technologies have been applied in all aspects of life. The traditional manual tracking and processing production process has many defects. The application of computer technology to the production line to realize automatic production has the characteristics of high efficiency and integration. This paper studies the PLC control system of pneumatic robot automatic assembly line based on cloud computing platform system. In the research, we use PCL system to scan the data of automatic assembly of pneumatic manipulator processed by cloud computing platform, and write the program into the memory of PCL. At the same time, we connect the field input signal and the controlled actuator to the input end of the input module and the output end of the output module. The user can realize the automatic assembly by running the program. Compared with the number of Pneumatic Manipulators produced by manual production line, the system in this paper has high efficiency and superior performance. Thus, the PLC control system of pneumatic manipulator automatic assembly line based on cloud computing platform can improve the production efficiency.
RETRACTED: Development and Innovation of Music Course Teaching Mode Based on Big Data
Authors: Chen XinYu 
Published: February 2021

Abstract
The development direction of online teaching is personalized and customized teaching based on user needs. Applying big data technology to the online network teaching platform can effectively solve the problems of the huge and chaotic number of teaching resources, the difficulty of user selection, the weak management of the network learning process, the inefficient use of teaching resources, and the lack of user role sense. The purpose of this article is to explore the development and innovation of music curriculum teaching models based on big data. This paper studies the modern network music teaching platform based on big data, realizes the user demand discovery of music teaching platform and optimizes the push of music teaching resources, and realizes the full use of music teaching resources. Starting from five dimensions of user attributes, learning roles, learning process, learning objects and learning tasks, this paper analyzes the user portraits of modern online music teaching platforms based on big data and expresses them based on ontology technology. This article is based on current scholars’ theoretical foundation and practical application research on education big data and smart classroom model, through the previous literature review and analysis, research on the popularization of smart classroom model and actual observation of existing smart classroom models. For the verification of the practical effects of music teaching cases using this model, the author used questionnaire and interview methods to investigate teachers and students, and conducted investigations on teachers from basic information, classroom application and effects, and classroom satisfaction.. Research shows that 29% of teachers are very satisfied with the application of this model, and 16% of teachers are generally satisfied. It can be known that most teachers are quite satisfied with the “smart classroom” teaching model under the big data environment.
Research on Furniture Design System Based on Big Data and Information Technology
Authors: Liao Xiayan , Song Yongjun 
Published: February 2021

Abstract
With the rapid development of my country’s real estate and other pillar industries and the acceleration of urbanization. The furniture industry is also showing a trend of rapid development. At present, Chinese traditional furniture has long been unable to meet the needs of consumers in some functional designs. Based on this, this paper proposes a furniture design system based on big data and information technology. Make full use of the existing network environment, hardware equipment, and software technology to build a furniture product big data cloud platform that can meet the needs of business development on the basis of ensuring that the core business structure is advanced, efficient and stable. This paper studies the huge changes that the home design system will face under the influence of big data, and conducts an in-depth analysis of the industrial environment, operation mode, information transmission security and other characteristics of the home system under the background of the big data era. Research shows that under the background of the era of big data, the establishment of a big data platform for furniture products is facing new development opportunities. The development of electronic information technology provides strong support for platform construction. Utilize electronic information technology to continuously aggregate furniture product information from various channels, deeply analyze the status of furniture products, and explore furniture product quality risks, thereby building a furniture product big data cloud platform.
Digital Financial Transaction Security Based on Blockchain Technology
Authors: Song Huitong , Chen Yansheng 
Published: February 2021

Abstract
Blockchain technology is currently recognized as the most potential new key technology, it can bring earth shaking changes, it is expected to trigger a new round of technological innovation and industrial change, and cause market attention. The purpose of this paper is to study the security of digital financial transactions based on blockchain technology. Firstly, the security of sdte is analyzed, and the DoS attacks that each role may launch, the attacks that a single role may send, and the attacks that can be launched by multiple roles in collusion are analyzed. It shows that sdte can resist these attacks and has strong security. Then, the related environment of the system test is described. Then, the performance test and analysis are carried out from the key security transmission, the execution of smart contract in the trusted environment SGX and the total running time. The experimental results show that the extra time consumed by using the k-nearest neighbor (KNN) algorithm to process data is less than 0.45s, At the same time, the additional cost brought by the system is also acceptable.
Application of Ensemble Learning in EEG Signal Analysis of Fatigue Driving
Authors: Rao Songhui , Li Kairui , Wu Jun , Mu Zhendong 
Published: February 2021

Abstract
Fatigue detection has now become an important direction of fatigue driving research. As a reliable physiological signal, EEG signals can be used to detect fatigue driving. This passage uses the idea of ensemble learning to establish an ensemble learning classification model of Bagged Tree, RSM Discrimination and RUSBoosted Tree, and uses the fatigue driving experiment data as the object to divide the fatigue driving object into normal state and fatigue state, using Pearson Correlation Coefficient method build a functional brain network. Six methods of Betweenness Centrality, Edge Betweenness Centrality, Clustering Coefficient, Degree, Local Efficiency, and Rich Club Coefficient are used to process and analyze six kinds of EEG signal characteristics, and then bring them into different in the ensemble learning model, the EEG signal characteristics and the ensemble learning model are matched and selected to improve the accuracy and stability of the detection model. By simulating 24 subjects, the results show that the accuracy and robustness of RSM Discrimination ensemble learning model and Degree method are the best, with an average accuracy rate of 90.35% and a standard deviation of 0.081.
Development of IoT-Based Volcano Early Warning System
Authors: Amaliya Virginia Fahriza , Lakudo Husein , Ulum Afrida Hafizhatul , Destarina Lisa , Seno Sensius , Rakhmadi Frida agung , Aminah Nina Siti , Evita Maria , Djamal Mitra 
Published: February 2021

Abstract
Monitoring volcanic activity this is indispensable for both research and disaster mitigation strategies. Therefore, the presence of volcano monitoring allows the monitoring, data recording and early warning system of volcanic activity from a distance that is real time. Volcanic monitoring system aims to detect any changes in volcanic status. Temperature and humidity become parameters of increased magma activity. Concentration of gasses includes SO2 and CO2, indicates of the depth of magma in volcanic conduit. Magma movement also triggers the earthquake.
The instrument that used in this research are temperature and humidity sensor DHT11, SO2 sensor TGS2602, CO2 sensor MG811, and vibration sensor ADXL345. Temperature and humidity sensors used DHT11 sensors that serve to detect temperature and humidity in the air. DHT11 sensors can detect temperature between 0-50°C and humidity between 20-90% RH. SO2 emissions were detected using TGS 2602 sensors that detects SO2 gas between 0-100 ppm. While CO2 gas emissions used MG811 sensors that detect the presence of CO2 gas between 350-10000 ppm. Furthermore, the vibrations were detected using a digital accelerometer ADXL345 that detects vibrations between 0.1-3200 Hz.
Data from all sensors processed using arduino promini microcontroller and then sent to ESP8266. ESP8266 is a wifi module that serves as a microcontroller enhancement to connect to wifi and create TCP / IP protocol. This module is also used to create an IoT project so that it can be accessed at any time on the web service page. This system will be assembled solar cells as a source of power supply.
Comparatives Studies in Molten Salt Reactor FUJI-U3 with Various Power
Authors: Wulandari Cici , Waris Abdul , Permana Sidik 
Published: February 2021

Abstract
Indonesia has a resource of nuclear fuel which spread around the country, especially in Bangka Belitung, West Kalimantan, West Sulawesi, and Papua. Therefore, Indonesia has a potential in the nuclear energy development. The Generation IV nuclear power system has been developed by the Generation IV Forum (GIF) with its benefits such as highly economical, enhanced safety, low waste production, and proliferation resistant. MSR is one of Generation IV nuclear power system which uses molten salt as a fuel and a coolant. Based on RUPTL (Electricity Supply Business Plan) PLN 2018-2027, Indonesia needs 100 MWe power harness from nuclear energy. This study focuses on a FUJI-U3 reactor, a type of MSR which developed in Japan. Power operation varied from 120-150 MWth 60-100 MWe and using FLiBe as molten salt. The calculation was performed with PIJ and CITATION modules in SRAC 2006 and JENDL 4.0 as nuclear data library.
Problem solution of the elasticity theory for the half-plane
Authors: Thanh L T , Linh H N T 
Published: February 2021

Abstract
The classical problem of equilibrium of elastic half-plane loaded along boundary contour can be resolved with different methods. In this paper, the solution is received with a new method that is founded on Cauchy-type integral and Plemelj identity. First, we solve with the general half-plane. Then we consider four special half-planes x2 ≤ 0, x2 ≥ 0, x1 ≤ 0, x1 ≥ 0.
Image Segmentation of Acute Myeloid Leukemia Using Multi Otsu Thresholding
Authors: Suryani E , Asmari E I , Harjito B 
Published: February 2021

Abstract
Acute Myeloid Leukemia (AML) can be identified by utilizing image processing. The stages used in the image processing process include preprocessing, segmentation, and feature extraction. The purpose of this segmentation is to separate objects in the image. One of the image segmentation methods is Multi Otsu Thresholding. This method has a way of working by looking for the threshold value dynamically. Previously there has been researched using the Static Otsu Thresholding method, but the results are still unsatisfactory because the threshold value obtained in the Static Thresholding method is that the threshold value obtained is static, meaning that the threshold value cannot adjust to the brightness level of each image that will be identified. With the background of the segmentation result dissatisfaction factor from the static threshold value, this study aims to carry out the segmentation process to obtain a dynamic threshold value, namely the Multi Otsu Thresholding Method. The Multi Otsu Thresholding method will be applied to segment AML images of M0 and M1 types, with the hope that the segmentation results obtained can be used for the feature extraction process better and are useful for the identification and classification process. Image processing methods used in this research are YCbCr color space, median filter, multi otsu thresholding, and morphological operations. The cell identification process utilizes the cell type classification process using the Naïve Bayes Classifier. The extracted characteristics were WBC (White Blood Cell) diameter, nucleus ratio, and nucleus roundness. Image data to test the process are 29 images of AML M0 and 30 images of AML M1. It was found that the segmentation results using the Multi Otsu Thresholding method can be used for the feature extraction process in AML M0 and AML M1 images and used for the identification process using the Naïve Bayes Classifier resulting in an accuracy of 83.81%, in this case, it has been compared with Static Otsu Thresholding which results with an accuracy of 75.35 %.
Particle approximation of the two-fluid model for superfluid 4He using smoothed particle hydrodynamics
Authors: Tsuzuki Satori 
Published: February 2021

Abstract
This paper presents a finite particle approximation of the two-fluid model for liquid 4He using smoothed particle hydrodynamics (SPH). In recent years, several studies have combined the vortex filament model (VFM), which describes quantized vortices in superfluid components, with the Navier–Stokes equations, which describe the motion of normal fluids. These studies led us to assume that coupling both components of the two-fluid model instead of using the VFM to describe the superfluid component enables us to approximate the system. In this study, we formulated a new SPH model that simultaneously solves both equations of motion of the two-fluid model. We then performed a numerical simulation of the rotating liquid 4He using our SPH. The results showed that the two major phenomena, the emergence of multiple independent vortices parallel to the circular axis and that of the so-called rigid-body rotation, can be reproduced by solving the two-fluid model using SPH. This finding is interesting because it was previously assumed that only a single vortex emerges when addressing similar problems without considering quantum mechanics. Our further analysis found that the emergence of multiple independent vortices can be realized by reformulating the viscosity term of the two-fluid model to conserve the angular momentum of the particles around their axes. Consequently, our model succeeded in reproducing the phenomena observed in quantum cases, even though we solve the phenomenological governing equations of liquid 4He.
RETRACTED: The impact of magnetohydrodynamic on bioconvection nanofluid flow with viscous dissipation and joule heating effects
Authors: Jawad Muhammad , Saeed Anwar , Bilal Muhammad , Gul Taza , Khan Arshad , Nasir Saleem 
Published: February 2021

Abstract
The current research work scrutinizes the bioconvection of nanofluid flow through an expanding sheet containing motile microorganisms with the mutual upshot of heat and mass transmission. Additionally, the convective and slip boundary conditions are also considered. The study is explored under the response of Joule heating, viscous dissipation, and magnetic strength. We used appropriate transformation methods for reducing a set of PDEs to nonlinear ODEs which were further corroborated by the ‘Homotopy Analysis Method’. The assessment is carried out for the numerous values of dissimilar parameters on the velocity and heat transmission profile with the inclusion of the density of motile microorganisms. It has been perceived that the rising trend in the magnetic field reduces the Nusselt number and the velocity near the stretch sheet of the fluid. The motile microorganisms profile displays a lessening behavior for rising values of Peclet number.