bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synthesis TiO2 using sonochemical method and responses the CO2 gas of the nanoparticle TiO2 layers on the QCM sensor surfaces
Authors: Mardiana L , Wardoyo A Y P , Masruroh  , Dharmawan H A 
Published: January 2022

Abstract
TiO2 synthesis using sonochemical methods and their coating on the surface of the Quartz Crystal Microbalance (QCM) sensor utilizing the spin coating method has been carried out. The synthesis started by mixing 7 ml of titanium (IV) isopropoxide (TTIP) (97%) in 70 ml of ethanol (96%). The mixture of TTIP solution was stirred for 30 minutes. After ward, the sonication was carried out for 4 hours at a frequency of 40 kHz and heated for 16 hours at 80 °C. To produce TiO2 powder, the precursor was calcined at 500°C for 3 hours. The TiO2 nanoparticle was analyzed using XRD, and the particle size was observed using SEM/Eds. Based on the XRD results, the crystal structure of Anatases was obtained at the 2θ (deg) of 25.503°(101), 29.56° (103), 36.20° (004), 37.977° (112), 48. 25.9° (200), 54.100° (105), 55.272° (211), 62.89°. The particle size from the SEM results showed the average particle size in the range of ±7μm-±54 nm with the majority in ±96 nm. The obtained TiO2 was dissolved with ethanol then the solvent was deposited on the QCM surface using the spin coating method. A homogeneous and porous surface structure is obtained from the SEM observation. The coated QCM was tested for its ability to adsorb CO2 gas. QCM was exposed to CO2 gas for 100 seconds with a constant exposure discharge. A positive response was obtained for the adsorbability of the coated QCM to adsorb CO2 gas with time variations. TiO2’s response against CO2 gas adsorption indicates that TiO2 can be further investigated as a CO2 gas sensor. The measuring response of the TiO2 layer on the QCM sensor was conducted to adsorb CO2 gas.
Thermodynamics of regular Kerr-Sen black hole
Authors: Jayawiguna B N 
Published: January 2022

Abstract
By evaluating the corresponding Killing vector, we study the thermodynamics quantity of regular black hole in the low energy string theory. From our result, we can infer that the regularity of a black hole enables the Hawking temperature to have local optima. The stability of a black hole from the heat capacity is also discussed.
Comparison between the magnetic method data of pseudogravity transformation with gravity anomaly data from satellite imagery in the surrounding of the Sutami Dam to identify subsurface formations
Authors: Sutasoma M , Susilo A , Sunaryo  , Suryo E A , Minardi S , Cahyo R H D 
Published: January 2022

Abstract
Research has been carried out to determine the subsurface formations in the Sutami dam area and its surroundings using the magnetic method of pseudogravity transformation and satellite imagery gravity anomaly data. This study aims to compare the subsurface formations in the area around the Sutami Dam between the data of the pseodu-gravity transformation magnetic method and the gravity anomaly data of satellite imagery. Data acquisition using the pseudogravity magnetic transformation method was carried out using the Proton Precession Magnetometer (PPM) Scientrex Model G-8 with a spacing of 300 meters. Satellite imagery gravity anomaly data was taken from the Gravity Model Plus (GGM plus) with a spacing of 220 meters. The radius of geomagnetic data acquisition was 15 km. The number of data for the magnetic method of pseudogravity transformation was 1,372 measurement points and satellite imagery gravity anomaly data was 3,000 measurement points. The results showed that the rock formations from the magnetic method of pseudogravity transformation and satellite gravity anomaly data were compatible. There are 4 types of subsurface formations in the study area, namely soil (Δρ = 1.6 g/cm3), Butak Volcanic Product (Δρ = 2 g/cm3), Tuff Deposit (Δρ = 2.1 g/cm3) and Campurdarat Formation (Δρ = 2.6 g/cm3).
Digital-based thermoelectric generator
Authors: Azhar  , Lathifah M F , Doyan A , Susilawati  , Hudha L S 
Published: January 2022

Abstract
A thermoelectric generator or also known as a Seebeck generator is an electrical generator device that converts temperature differences into electrical energy using a phenomenon called the Seebeck effect. To find out the magnitude of the voltage generated by the thermoelectric, a series of tests on the thermoelectric must be carried out where one of the test methods is to provide a significant temperature difference on both sides of the thermoelectric generator using hot water media for the hot side and using ice cubes for the cold side. The test results show that the developed thermoelectric generator can generate an electric voltage of 1189.31 mV.
Characterization of manufacturing indicator electrodes coated PVA-enzyme coated 1X GA and 3X GA 2.9 % coated PVC-KTpClPB coated using potentiometry method
Authors: Hakim S A , Mihardi S , Rais A , Willy  , Panjaitan Y T H 
Published: January 2022

Abstract
Research has been carried out on the manufacture of tungsten indicator electrodes with a diameter of 1 mm coated with PVA-Enzyme coated with PVC-KTpClPB using the biosensor potentiometer method. It has a sensitivity of 19,096 mV/decade, a detection range of 1.10-5 - 5.10-4 M, a detection limit of 1.10-5 M and a correlation coefficient of R2 = 0.9431. This detection range is very small, only a difference of one order to the negative power. On the basis of this small range, the PVA-Enzyme and PVA-Enzyme-GA solutions have been characterized by UV-vis showing a very clear difference in the width of the absorbance peak at wavelength. The indicator electrodes B1-4 and B3-4 have been analyzed using UV-vis, FTIR, SEM-eds and XRD. The method used is the biosensor poteniometric method, urease enzyme immobilization technique, which analytes urea in determining sensitivity, detection range and detection limit, as well as variable signal analysis of 60 signals/second. The results obtained from the indicator electrode B1-4 have a sensitivity of 46.67 mV/decade, a detection range of 10-4 - 10-2 M and a detection limit of 10-4 M, R2 = 99.62 %. The indicator electrode B3-4 has a sensitivity of 38.16 mV/decade, a detection range of 10-6 - 10-4 M and a detection limit of 10-6 M, R2 = 95.42 %. The best results on electrodes B1-4.
The dielectric properties of skin damage and its correlation to free radical intensity caused by UVA/UVB radiation impact
Authors: Faisal M , Juswono U P , Santoso D R 
Published: January 2022

Abstract
The dielectric property in form of dielectric constant of material is a measure of material’s response to a given electric field. Electric fields induce conductive and polarizing currents based on their effect on free charge attached to biological material. This phenomenon occurs at all levels of organization including cellular, molecular and ionic. When the skin is exposed to ultraviolet radiation there will be a series of chain processes that cause emergence of Reactive Oxygen Species (ROS) in the tissue. Reactive Oxygen Species (ROS) in tissue will be very dangerous because it can cause damaging free radicals. Excessive exposure to UVA / UVB radiation causes various kinds of damage which affect the low dipole moment and polarity of cells that make up skin tissue. Dipole moment and low cell polarity will decrease the dielectric constant value of tissue which is triggered by presence of free radicals in form of singlet oxygen (1
O
2) and superoxide anion (O
-*
2).
Research on Modeling and Simulation Technology of Equipment Maintenance Support System Based on Agent
Authors: Xu Qing , Liu Hong-lin , Hou Xing-ming 
Published: January 2022

Abstract
Aiming at the problem that the equipment maintenance support system is difficult to describe with highly stylized mathematical model, a framework model of equipment maintenance support agent is constructed. The paper introduces the Agent modeling method, analyzes the structure and workflow of the equipment maintenance support system, and abstracts the Agent framework structure according to the equipment maintenance guarantee and the modeling characteristics of the Agent. The internal modules of each Agent are designed and the agents are designed. The task environment between them has been studied, and the designed structural model can provide reference for other similar studies.
Research on an Anechoic Wind Tunnel in the Design Phase by Numerical Simulation
Authors: Li Hanqin , Fang Bin , Zhang Yongming 
Published: January 2022

Abstract
As an important facility for acoustic measurement and research in air medium, anechoic wind tunnel requires high acoustic performance. In this paper, the flow field and acoustic characteristics of anechoic wind tunnel were studied by modeling and simulation. The velocity and pressure distribution of the whole flow field in the wind tunnel are obtained by simulation calculation, and the noise source distribution in the anechoic wind tunnel is studied by the broadband noise source method, which provides a reference for the design, construction and optimization of the anechoic wind tunnel.
Resource Allocation for Cloud-Edge-End Simulation System
Authors: Yan Guoqiang , Mao Shaojie , Li Yuping 
Published: January 2022

Abstract
Aiming at the problem of simulating service requests and optimal scheduling during the operation of the cloud computing/edge computing environment, the real-time optimization scheduling technology of computing resources is studied, and elastic resource optimization scheduling is realized through data feature mining analysis, service load prediction, and collaborative resource management. Ensure that the simulation service quality meets the mission requirements and provide support.
Modeling and Analysis of Spike-Train Based on Poisson-GML
Authors: Li Yuanpeng , Yang Wenge , Fan Yile , Zhang Yu 
Published: January 2022

Abstract
Mathematical modeling is of great significance to the study of brain function. In this paper, an analysis method based on Poisson’s general linear model is adopted to model the brain impulse sequence. First, the ideas of Hodegkin-Hulex model, STA and Poisson’s general linear model are introduced. Secondly, the implementation of the general linear model is introduced. Finally, Poisson GLM Fit Spike-train is simulated and compared with Linear Gaussian-GLM. The AIC tradeoff estimation model fits well. The superiority of Poisson GLM Fit Spike-Train is demonstrated
The (Vertex) Gutman Index of One Vertex Union of Two Cycles
Authors: Wang Kelun , Guo Haili 
Published: January 2022

AbstractThe Gutman index is a variant of the Wiener index, which related to the degree and the distance. In this paper, we study the vertex Gutman indices of a special kind of graphs, one vertex union of two cycles. And the maximum and minimum of vertex Gutman indices are studied. The results show that the vertex Gutman indices has the maximum at the center and has minimum at some vertices nearest the center.
Modeling Thermal Environment Responses to Terrain and Urbanization of Metropolis
Authors: Tao Sulin , Li Yuhong 
Published: January 2022

Abstract
Thermal environment responses to terrain and urbanization of Beijing, a metropolis of China, were simulated by the Weather Research and Forecasting model (WRF) with the single-layer Urban Canopy model (UCM). Four numerical experiments were designed: (1) the control experiment (Control exp), (2) no-terrain sensitive experiment (No-Terrain exp), (3) no-urban surface sensitive experiment (No-Urban exp), and (4) real land surface sensitive experiment (LU exp). Results indicate that better near-surface air temperature simulations were obtained after using MODIS land surface type product data MCD12Q1. The foehn effect due to northwestern mountains in Beijing were simulated to intensify the high temperature intensity in the plain area. Urban heat island effect existed in this area day and night, and the heat island intensity in the nighttime was obviously greater than that in the daytime. As a result of urbanization, the nighttime temperature had risen by 1.5∼3.5 °C and the expansion range of nighttime high temperature areas was basically consistent with the urban expansion range.
Deterministic and Stochastic Modeling Approaches for Saturation Nonlinearity
Authors: Peng Pai , Huang ChunQing 
Published: January 2022

Abstract
Being different from the most traditional methods of nonlinearity modelling, non-parametric modelling approaches viz. deterministic and stochastic approaches for saturation nonlinearity are proposed in the sense of system impulse response. Based on deterministic approach, the closed-loop system involved saturation nonlinearity can be modelled as the response of the closed-loop system that is subject to impulse stimulation. Alternatively, the closed-loop system involved saturation nonlinearity can be modelled in stochastic manner, in which the impulse response coefficients are estimated by the FCOR algorithm. Moreover, it shows some linear relationship of the impulse response coefficients between different saturation ratios in both the deterministic and stochastic models. This is illustrated by three different numerical examples.
A Detection Model of the Moving Direction in Vertical for UAV to Search Ground Infrared Targets
Authors: Yang Yang , Li Zhijun , Wu Yunqiang , Li Ke , Lu Jie 
Published: January 2022

Abstract
Regarding the relative detection of the moving direction in vertical between the unmanned aerial vehicle (UAV) and the ground target, we have been inspired by the functional advantages of flying insects in nature, such as lightweight, low computational complexity, low power, and the natural characteristics of high adaptability and high reliability in the detection and tracking or escape process of targets. Based on this, with the help of LGMD (lobula giant movement detector) neuron modeling, this paper proposes a detection model of the moving direction in vertical for UAV ground infrared targets based on LGMD neurons modeling (referred to as LGMD-UAVGIT model). In this paper, experiments and tests are mainly carried out on infrared imaging videos taken by UAVs, thus verifying the effectiveness of the new model proposed in the paper for detecting the two typical vertical movement directions of UAVs that are relatively far away from and close to the ground targets.
Prestressed Modal Analysis of Wind Turbine Blade Considering Fluid-solid Coupling
Authors: Li Shanyao , Wang Yingbo , Sun Haipeng , Sun Changle , Zhang Xiaolin , Liu Tingrui 
Published: January 2022

AbstractWind turbine blade is a kind of slender elastic body structure, which is prone to vibration and deformation during operation, seriously affecting the smooth operation of wind turbine. Taking the 1.5MW wind turbine blade as the research object, the three-dimensional shell model of the blade is established based on Solidworks, and the composite material layer design of the blade is carried out in ANSYS ACP. The stress and deformation of the blade in the flow field are studied based on the fluid structure coupling method. The first six natural frequencies and modes of the blade are obtained by taking the stress of the structural field as the prestress of the modal analysis. The results show that flapping and shimmy are the main vibration forms of the blade. When resonance occurs, the fluctuation of the blade in the flapping direction is the largest, and the maximum stress appears near the blade root.
Development of Mobile Robot System Based on Nano-scale Micro-surface Measurement
Authors: Ji Zhongwei , Wang Pan , Jia Jiahao , Ding Yan , Zhao Kang , Liu Tingrui 
Published: January 2022

Abstract
Absrtact. The system development of the mobile robot mainly includes two parts: one is to build a laser interference system based on piezoelectric ceramic dynamic carrier; The other part is the image processing of the interference fringe pattern collected by the interference system. The laser interference system can be installed on the front-end manipulator of the robot as an integral structure. The shape information of the measured micro-surface can be obtained by processing the interference fringes collected by the image acquisition card on the interference system, so as to achieve the purpose of high-precision surface roughness measurement.
Design of a Small Sweeping Robot Based on STM32
Authors: Zhang Xiaosheng , Zhan Gaopeng , Xu Xin , Fang Kai 
Published: January 2022

Abstract
With the continuous improvement of people’s living standards and the emergence of various intelligent appliances, a household floor sweeping robot is designed in this subject, which can automatically clean the ground in the room. The robot takes STM32F103ZET6 single chip microcomputer as the controller, uses two DC motors and L298N driving chips to drive the robot to walk, and uses ultrasonic sensors to detect indoor obstacles, The infrared sensor is used to detect the indoor edge position, the straight travel control of the robot is realized through the coding disk combined with PID algorithm, and the turning control is realized through differential control and PWM speed regulation. The robot can realize the garbage cleaning in the regular room, and has a certain application prospect.
Research on Multi-modal Medical Image Fusion Based on Multi-Scale Attention Mechanism
Authors: He Baiqing 
Published: January 2022

Abstract
Image fusion technology has been widely used and researched in the fields of medicine, aviation, military and civil. Compared with the traditional image fusion technology, the fusion image technology based on intelligent algorithm generates more realistic, clear and reliable images, and has a lot of detailed information. Deep neural networks have rapidly developed into a research hotspot in medical image analysis, which can automatically extract hidden pathological information from medical image data. Multi-scale and attention mechanism are two important modules in neural networks, which can significantly enhance the features extracted by the network. The problems that need to be solved for medical image fusion based on multi-scale attention mechanism include: how to build a multi-scale module, how to build an attention module, and how to combine multi-scale and attention mechanisms. Construct a deep learning network through a multi-scale attention mechanism, and then adjust the parameters and train the network to achieve multi-modal medical image fusion. In the process of building neural networks, multi-scale and attention mechanisms are incorporated, and multi-scale features of multi-modal medical images are extracted and enhanced for fusion. Through a large number of experiments: (1) The edge strength of the fused image is expected to increase by 10%-20% based on the average value of the existing algorithm; (2) The fused image can achieve high color fidelity and rich detailed information; (3) ) The time required for the fusion algorithm is expected to be reduced by 1%-10% based on the average value of the existing algorithm.
Research on Virtual Campus Roaming System Based on unity 3d Technology
Authors: Luo Hua , Zhou Yiren , Li Yuxuan 
Published: January 2022

Abstract
with the development of virtual simulation technology and network technology, the application of virtual technology in education, games and so on is deepening. Use 3ds Max and unity 3D software to organically combine 3D technology with virtual reality. Taking the hero campus of Nanchang Institute of technology as the design case, this paper aims to develop a multi-user virtual campus roaming system, so that users can truly experience the campus environment anytime and anywhere through the network and roaming equipment, and play a positive role in the information construction of colleges and universities in the future.
Research on Software Defect Prediction and Analysis Based on Machine Learning
Authors: Peng Xuemei 
Published: January 2022

Abstract
The defects of machine learning prediction technology can be more comprehensive and automatic learning model to find the defects in software has become the main method of defect prediction, selection and study of algorithm is the key to improve the accuracy and efficiency of machine learning. Comparing different machine learning defect prediction methods reveals that the algorithms have different advantages in different evaluation indicators, the use of these advantages and combining the stacking ensemble learning method in machine learning is put forward different prediction algorithm of prediction results. As software metrics and again the prediction model of software defect prediction combined machine learning algorithm is based on the experiment with the model of Eclipse, the data sets show the effectiveness of the model.
DOA Estimation of Underwater Acoustic Targets Based on Bayesian Compressed Sensing
Authors: Liu Fei 
Published: January 2022

Abstract
Aiming at the performance degradation or even failure of existing underwater acoustic target direction of arrial (DOA) estimation methods under the conditions of low signal-to-noise ratio and low snapshot, a underwater acoustic target DOA estimation method based on sparse Bayesian compressed sensing theory is studied, and simulation experiments are carried out by MATLAB to verify the feasibility and effectiveness of the proposed method. Simulation results show that compared with CBF , MUSIC and OMP algorithms, the proposed method can improve the estimation accuracy in the case of lower snapshot number, lower number of array elements and smaller array element spacing, and can achieve high resolution DOA estimation in the case of low signal-to-noise ratio and close position of multiple target signals.
Strength Analysis on the Frame of Off-way Wide-body Mining Dump Truck Based on Finite Element Analysis
Authors: Liu Weiwei , Liu Jiang 
Published: January 2022

Abstract
The frame is an important component for the off-way wide-body mining dump truck. The carrying capacity of the truck is greatly affected by the strength of the frame. The finite element analysis was used to simulate the strength of the frame under the work condition of full load and lifting. The maximum stress of the frame is 214MPa under the full load condition, and the maximum stress of the frame is 459MPa under lifting condition. The upper surface of the frame near the rear axle is the more dangerous section for the frame under the two working conditions. The stiffness of the front leaf spring has very impact to the maximum stress of the frame for both full load condition and lifting condition, but has some impact to the maximum stress near the support of the front leaf spring.
High-Frequency Vibration Control of Rotating Beam Based on Trailing-edge Flap
Authors: Wang Jian , Li Shanyao , Sun Changle , Liu Tingrui 
Published: January 2022

Abstract
Abstract This study is to investigate an active control method, based on trailing-edge flap, in high-frequency vibration control of rotating blade beam. The structure is modeled as composite blade beam with circumferentially asymmetric stiffness configuration, which is based on analysis of the elastic flap-wise/twist displacements and incorporates the angle control of trailing-edge flap driven by a stepping motor. Aerodynamic expressions are based on a novel quasi-steady model suitable for trailing-edge flap. Based on a strip theory, the multi-body dynamic aeroelastic system is analyzed and solved. The active control is realized by Hœ algorithm using linear matrix inequality (LMI) design. This study is to investigate time-domain stability analysis and robust control method, realize displacement response analysis and robust performance analysis, and input signal display of trailing-edge flap angle. The optimization mechanism of LMI is to optimize uncertain robust performance parameters based on the selection of robust control parameters, so that the controlled displacement and control input are kept within reasonable ranges. The reliability and robustness of H» control algorithm based on LMI are verified by comparisons of the results of high-frequency vibration control using different robust performance parameters.