bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis on Infection Wave and Decay of Transmission Risk Based on Spatial SIR Model - Taking COVID Epidemic as an Example
Authors: Wang Yunda 
Published: December 2022

Abstract
Starting with the spatial SIR model, this paper gives the strict boundary conditions, and obtains two theorems in the process of infectious disease transmission through theoretical analysis. After that, the partial differential equations are transformed into ordinary differential equations by the method of traveling wave solution, and the solutions of infectious wave velocity and hypergeometric function are further derived. Beside local diffusion operator model, the paper also developed global transmission risk functions as convolution kernels and discovered their properties. The solution of the spatial infectious disease model is visualized by programming, and the influence of parameter changes on the solution is discussed. Finally, some variants of the model in special cases are given. This paper proves that under generalized assumption the three population densities of the spatial SIR model results at the origin cannot take extreme values at the same time, and when the infected density takes extreme values at the origin, the higher-order derivative of the infected density to the space is zero. The hypergeometric function method verifies the solution at infinity of the equations, and the above solution can be used to approximate when the distance from the infection source radius is large. In this paper, the discussion on the impact of the changes of several infectious disease parameters can inspire the methods of epidemic prevention and control.
Feature Selection Based on Stock Prediction Model
Authors: Li Deyang 
Published: December 2022

Abstract
Stocks as an important part of financial investment are becoming more and more popular, and they have higher rates of both returns and risks. Making a prediction for the stock can reduce its risk and help people gain returns. So far, the traditional machine learning model is still unable to achieve ideal accuracy. The paper is devoted to analyzing the input features to improve the performance of stock forecasting models. Aiming at the problem that the traditional stock prediction algorithms produce different accuracy for the models constructed by different input features, the paper, through a method of establishing a long-term memory (LSTM) model, predicts the stock. The Shixia Technology Stock’s history data includes 5 features as the dataset and chooses the different feature as the input. In the experiment in this paper, different results are produced by subtracting one different input feature at a time. Finally, the model’s predictions were compared with each other by the R_square and RMSE, and the analysis revealed which feature could have a greater impact on the stock prediction. The paper finds that the different input features have different influences on the model fitting effect and the prediction accuracy on stock forecasting based on the same neural network model.
Optimal Values Selection of Q-learning Parameters in Stochastic Mazes
Authors: Zhou Xiaolin 
Published: December 2022

Abstract
The model-free characteristic of the Q-learning algorithm, without obtaining information about the environment and being available for agents to learn by themselves, enables Q-learning to be widely applied to path planning fields. Nonetheless, the selection of parameter values will have a crucial impact on the results. In this paper, how to determine an appropriate value of learning rate and discount factor and these parameters’ effect on the overall results will be presented. The agents with different learning rate or discount factor values will perform in randomly generated mazes, the results of which will be aggregated and compared. When the learning rate equals 0.9, under the condition of setting the learning rate as variable and discount factor as invariant, the aggregated data of 0.9 can reach convergence way more quickly than in other settings (0.6, 0.3, 0.1); when the discount factor equals 0.9 and the experiment follows the unique variable principle, the aggregated data of 0.9 searches for shorter path length and faster than other groups (0.6, 0.3, 0.1); when both the learning rate and discount factor are set to 0.9 – other groups are 1.0, 0.1, and 0 – the group of 0.9 is more stable than the group of 0.1 and shows convergence, which does not appear in the group of 1.0 and 0, within 80 iterations.
Variant Modern Solutions to Central Processing Units’ Overheating Problem and Evaluations on Applications
Authors: Zhang Xuan 
Published: December 2022

Abstract
As the society is technologically advancing, there is an increasing demand for advancements in computers. Therefore, computers will be replacing more human jobs in the future which force computers to work more frequently. This foreshadows that computers may encounter more problems such as overheating problem in the future as they are operating. Overheating problem is indeed a problem to be researched because it may cause serious damages to the computer overall, such as shortening its lifespan or reducing its memory. In this article, we aim to demonstrate different existing modern solutions that may prevent Central Processing Units in computers from overheating. Furthermore, this article will be evaluating on the solutions that are presented.
Active Noise Cancellation and Its Applications
Authors: Song Yu 
Published: December 2022

Abstract
The goal of this review is to introduce the concept of Active Noise Cancellation (ANC) technique and explain the core algorithms supporting this technology. Through showing the implementations and major features of those algorithms, we were able to gain a better understanding of what’re the dominating algorithms used by the ANC technology and both the traditional and non-traditional applications of ANC in today’s market. Finally, the review also reveals the potential problem with the ANC technique and the opportunities for improvements.
Optoelectronic Techniques Boost the Investigation on Hysteresis and Ion Migration in Perovskite Photovoltaics
Authors: Chen Ke Liang 
Published: December 2022

Abstract
Perovskite solar cells (PSCs) have drawn much attention in the photovoltaic field. At present, the energy conversion efficiency has achieved 25.5%. However, the hysteresis effect in the characterization of PSCs seriously affects the accuracy of PSCs technology. Therefore, hysteresis effect has become the object of attention in order to improve PSCs. In this paper, various photoelectric characterization techniques are mentioned for the study of hysteresis phenomena. Photoelectric characterization methods, space charge limited current, electrochemical impedance spectroscopy, transient photocurrent/photovoltage are introduced. In the end, hysteresis is a shift in the representation of carrier dynamics due to ion migration. Hysteresis shows a characteristic of sweep speed dependence, indicating that ion migration is a slow and low frequency behavior. By increasing the bias voltage, ion migration can be more intense and the hysteresis will be more obvious.
Impacts of Laser Power and Scan Speed on Temperature Field and Molten Pool of ZL104 Aluminum Alloy Selective Laser Melting
Authors: Shi Yuxuan 
Published: December 2022

Abstract
Selective laser melting (SLM), a significant branch of laser additive manufacturing (LAM) technology, has become a popular topic of research in engineering, materials and many other disciplines. SLM can transform metallic powders directly into 3D components, which allows SLM to offer the unique flexibility of manufacturing parts with complex structures. The quality of the product is closely related to the characteristics of the temperature field, as well as that of the molten pool. Because of the high localized temperatures and the rapid cycles of melting and solidification during SLM, it’s difficult to monitor the temperature field in real time. Hence, numerical simulation is often used to study the SLM process. In this work, the SLM process of ZL104 aluminum alloy was simulated using the CFD method, and the influences of processing parameters, including laser power and scan speed, on the temperature field and the characteristics of the molten pool have been investigated. Results showed that when the laser power increased, the peak temperature of the molten pool also mounted, however, the maximum temperature of the molten pool fell as the scan speed rose. The dimensions of heat affected zone (HAZ), including the width and depth, increased with growing laser power, but decreased with the increase of scan speed.
Daylighting Performance of Sunlight Transmission and Concentration via Plastic Optical Fibers
Authors: Chen Zeyao 
Published: December 2022

Abstract
The energy-saving technology of this thing is thriving. One of promising technology is the daylighting system via optical plastic fibers. It has many advantages, and its characteristics need further research. This paper analyses the transmission characteristics, attenuation rate, and incident angle of the optical fiber. The test data shows that the spectrum, color rendering index are good, and the energy efficiency is high. This shows that plastic optical fibres have excellent development prospects for daylighting.
A Sensor Array-based Control System Design for the Interior Environment of Driverless Cars
Authors: Li Xinran 
Published: December 2022

Abstract
Highly intelligent driverless cars require intelligent, user-friendly and high-safety interior environment control systems to match. In this paper, through the use of vision sensors, sound sensors and a variety of environmental sensors to form a sensor array, and through the embedded microprocessor for centralized control, the design completed with face recognition door opening, cry detection window opening, vibration detection alarm, haze detection defrost, automatic thermostat control, automatic light brightness control, internal environment remote monitoring and other functions in one of the driverless car intelligent internal environment control system. The test results show that the system designed in this paper is a good solution to the problem. The test results show that the system designed in this paper is functionally rich and scalable, highly intelligent and suitable for the needs of the general public, and helps to improve the ride comfort and safety of driverless cars.
The Application of Computer Aided Optimization Design
Authors: Bao Longfei 
Published: December 2022

Abstract
The Computer Aided Optimization Design (CAOD) is one of the most significant piece of software in the world especially for companies involved in manufacturing and designing. The software can be used for different objectives when paired with other software in the company. This paper mainly introduces the application and benefits of CAOD in five different fields. First, the CAOD is critical for design engineers involved in designing automotive and airplane body shapes to achieve various objectives such as high capacity, fuel efficiency, and high performance. Second, it can be applied to turbines for wind mills to ensure they are long enough and can operate optimally even at slow wind speeds. Third, it can benefit the manufacturing process to redesign the factory floor and setting up machines in various sections on the factory floor. Moreover, CAOD has also diversified into other areas such as healthcare where it is used in robotic surgery system and repair of intense fractures and damages. Last but not least, the greatest application of CAOD may lie in the computer animation industry.
Design and Optimization of Automotive Air Conditioning Duct Based on CFD Algorithm
Authors: He Jiahao 
Published: December 2022

Abstract
Nowadays, the air conditioner (AC), as an important guarantee for driving comfort and endurance, has attracted more and more attention. The pipe connecting the air conditioner refrigerator and the air outlet of the cockpit instrument panel is known as the air duct. Its structural characteristics and fluid flow characteristics are related to the refrigeration efficiency of the whole air conditioning system. The air supply performance of the air duct directly affects the uniformity of the temperature field and speed field in the car, thus affecting the comfort performance of the car [2]. Limited by the layout space, the design of air conditioning duct is the most difficult part of the design of automobile air conditioning system [1]. Therefore, how to optimize the air duct of automotive air-conditioning to meet the size design of the car while being more energy-efficient is an important research direction. This paper focuses on the simulation design and further optimization of the model of the air duct of automotive air conditioning through CFD algorithm. The author uses the Soildworks software for preliminary modeling, meshes the established model with Meshing, and applies the Fluent software to simulate the fluid flow characteristics in the pipe. By inputting a given flow to the inlets, the air volume of each outlet can be simulated. Based on the initial air-conditioning duct model of a vehicle model, the pipe turbulence problem and the uneven distribution of air volume at each outlet in the simulation process are improved under the condition of ensuring the existing size, and finally the rationality of the improvement is verified.
Research on transformer condition evaluation based on oil chromatography differentiation threshold
Authors: Yang Pei , Qiao Junfeng , Wang Gang 
Published: December 2022

Abstract
As one of the important power transmission and transformation equipment, the reliability of transformer is directly related to the safe operation of power system. At present, the on-line monitoring technology based on dissolved gas analysis in oil is widely valued by researchers all over the world because it can continuously monitor the operation status of transformers and timely and effectively find the early faults of transformers. In this paper, the on-site oil chromatography data are differentiated and classified according to the voltage level of the transformer. The curve fitting method is used for statistical analysis and to build a distribution model. The cumulative probability is associated with the defect rate and failure rate of the equipment, and the corresponding threshold value is obtained by using the inverse cumulative distribution function as the attention value and warning value. By using this method, the attention values of the volume fraction of dissolved gas in oil and the gas production rate of dissolved gas in the existing national standards are improved, and the corresponding warning values are calculated to make the warning mechanism more flexible and reliable.
Partial discharge location method in GIS coaxial bus structure based on multi-normal photoelectric array
Authors: Li Chen , Ren Ming , Wang Yue , Guan Haobin , Xia Changjie , Yu Jiahe , Zhang Tao , Miao Jin 
Published: December 2022

Abstract
Partial discharge is an important reason for the failure of GIS equipment, and its detection can determine the type and position of the defect in GIS. In the discharge inspection, accurate positioning of defects can provide an important reference for maintenance. In response to this, this paper proposes a discharge optical location method based on multi-normal photoelectric array. Based on the SiPM sensor, a multi-normal array is designed and built into the coaxial structure of GIS equipment. Measuring the responses of each unit in the array to get the response ratio of each element and calculate the direction of the discharge light in space. This paper firstly introduces the array structure, and proposes a solution algorithm in space, which uses the proportional relationship of multi-normal elements to solve the discharge direction. Secondly, the feasibility and error source of this method are verified in the simulation software. Finally, the application effect of this method in actual power equipment is verified by actual measurement, and the results show that this method can accurately locate the partial discharge in GIS.
Prediction of Ultra-Short-Term power system based on LSTM-Random forest combination model
Authors: Fang Ziqiang , Yang Ziteng , Peng Haiyang , Chen Guoqing 
Published: December 2022

Abstract
The ultra-short-term forecast of the power load system plays an important role in the operation of the power market and economic dispatch. An excellent ultra-short-term power load prediction model can not only greatly reduce the loss of power operation, but also make a reasonable power generation plan accordingly to reduce the waste of power. In this paper, a model applicable to forecasting the ultra-short-term power system is proposed by combining LSTM and Random Forest using the reciprocal error method, based on the power load data of the 10th Teddy Cup Data Mining Competition. The illustrating example shows that the mean absolute percentage error (MAPE) of the combined prediction model of LSTM-Random Forest is 1.40%, the error of the combined model is significantly lower than the uncombined model, implying that the prediction accuracy of the combined prediction model is significantly higher than that of the LSTM model and Random Forest model.
Preparation and electrochemical properties of vanadium-based anode materials for zinc ion battery
Authors: Ren Jiaxin , Yang Chun , Zhou Beibei 
Published: December 2022

Abstract
Although water zinc ion battery (ZIBs) has certain advantages in production and application period, but the speed performance and service time is not strong, always hinders the reusability and rapid charging technology. In order to solve this problem, researchers proposed to improve the reaction kinetics on the basis of stable electrode structure. So this article research using solvent and adding thiourea to design a hybrid structure, the structure is made from manganese doped V6O13 nanobelts and navier-stokes modified porous carbon structure, consisting of one dimensional porous nanometer structure can form diffusion channels, and can provide relatively abundant energy storage sites, and zinc ions doped into V6O13 electronic structure can be further adjustment. In order to effectively control the huge volume expansion and optimize the electrical conductivity, n-S modified carbon structure with electrical conductivity can be used to protect the nanoribbons and effectively improve the electron transport rate in the electrochemical reaction. This electrode structure can not only accelerate the diffusion rate and reaction kinetics of zinc ions, but also show cyclic stability and high rate performance. This study mainly analyzed the application effect of reduced graphene oxide coated with sea urchin-like VO2 as anode material of water zinc ion battery, so as to provide effective basis for material preparation and electrochemical performance research.
Overview of the IV International Conference on Applied Physics, Information Technologies and Engineering – APITECH-IV 2022
Authors: Barakaev N R , Sharipov M Z , Abrorov A S , Rakhmonov Kh K 
Published: December 2022

Abstract
The overview describes the main directions and results of the IV International Conference APITECH-IV 2022 held in Bukhara, Uzbekistan on 6-9 October 2022. It gives the details about the participants and the proceedings. The purpose of the Conference is to share the experience of leading experts in the application of modern methods of applied physics and information technology in high-tech production, in the fields of aerospace, energy, chemical and oil and gas engineering.
Varizonicity and surface levels in ionic crystals
Authors: Karimov Z I , Mukimov K , Oksengendler B L , Suleymanov S X , Iskandarova F A 
Published: December 2022

Abstract
The problem of the formation of varizonicity in ionic crystals is investigated. It is shown that in this case the electronic structure of the surface states becomes special – a near-surface potential well appears, as a result of which the local states radically differ from the Tammov states. A similar effect, in principle, should take place in cases of varizonicity of covalent crystals, which is due to special alloying in them. A consideration is made about the special situation in HTS materials: a combination of external and internal varizonality.
Computer simulation of ice film sputtering from Au(111) surface
Authors: Kutliev Uchkun , Otabaeva Kamola , Karimov Mukhtorjon , Woiciechowski Igor 
Published: December 2022

Abstract
Mass spectrometry of secondary ions represents a combination of analytical methods, which allows you to study the molecular characteristics of the solid state. On the basis of this method, the use of charged charging frequencies is directed at the power, usually in the range of tens of thousands of electron volts. Based on the molecular dynamics method, we simulated sputtering process in the form of water molecules and clusters of water films covering Au(111) on the surface at normal incidence. It is shown that the obtained mass spectra of sputtered particles contain peaks related to several water molecules. The analysis of the obtained results showed that peaks were formed on the mass spectrum of sputtered particles, which belong to water molecules, water clusters, and Au atoms. The results played a huge role in studying the surface of thin films and molecular spectroscopy. The obtained calculation results showed that the number of incident particles directly affects the sputtering process, that is, the greater the number of incident particles, the more intense the process of sputtering of the atoms of the upper layers of the substrate. This is due to the fact that the incident ions, destroying the structure of the crystal, namely, violating the periodicity of the upper atomic layers, remain in the substrate of the crystal.
Modeling of nonequilibrium cross-diffusion systems
Authors: Mamatov A U , Nurumova A Yu 
Published: December 2022

Abstract
In this research, we investigate the modeling of cross-diffusion systems that are not in equilibrium. For a particular equation, it is shown that the parameter values exist and have a numerical solution. A source describes the system of equations considered in this study as being based on the majority of physical processes, such as the cross-diffusion process in this system, thermal conductivity, and polytrophic filtration of gas and liquid in nonlinear media. Numerous partial solutions exist for these equations. The development of an integral self-similar solution is one of the most important approaches to analyzing the problem at hand. Initial construction of a system of self-similar equations using a nonlinear subtraction technique. The front for the equation of nonlinear heat generation with doubled energy was estimated, the localization process was observed, new effects were observed, an algorithm was constructed based on the obtained self-similar solution, a program code was developed in the programming language, and the process modeling was visualized.
Mathematical modelling of motion control system in the MLC mode
Authors: Smirnov Mikhail N , Smirnova Maria A , Smirnov Nikolay V , Smirnova Tatiana E 
Published: December 2022

Abstract
Performing different manoeuvres in vertical and horizontal planes is one of the most important tasks that rise during the control of any object. In the paper the problem of implementing movement in the mode of moving along a linear coordinate (depth) for an unmanned underwater vehicle is considered. The algorithm for construction the control law that satisfy the specified conditions, e.g. the specified equilibrium position in vertical plane, astaticism, is presented. The control law with filter is constructed. This algorithm was implemented in MATLAB with the subsystem Simulink. MATLAB one of the most powerful systems for computer modelling and analysis of dynamic systems, so this algorithm and its realization with small changes can be easily used for any object.