bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mathematical Modeling and Functional Order Pursuits with Separated Dynamics
Authors: Mamatov Mashrabjon , Alimov Xakimjon 
Published: November 2021

Abstract
This work is devoted to the study of the pursuit problem in controlled systems described by a fractional-order equation with divided dynamics. For fixed player controls, representations of solutions are established in the form of analogs of the Cauchy formula using generalized matrix functions. Sufficient conditions are obtained for the possibility of completing the pursuit. Specific types of fractional differential equations and models of fractional dynamical systems are considered. The qualitative dynamics, issues of stability and controllability of such systems are discussed. Considered, try which, the motion of the equation is described with irrational orders. Problems of the type under study are encountered in modeling the processes of economic growth and in problems of stabilizing dynamic systems.
Explicit Exact Solutions of Space-time Fractional Drinfel’d-Sokolov-Wilson Equations
Authors: Lin Hongkua 
Published: November 2021

Abstract
The space-time fractional Drinfel’d-Sokolov-Wilson equations (DSWEs) has attracted many researchers’ attention in recent years. In this study, combining the (G’/G,1/G)-expansion method and a fractional wave transformation, we derive abundant explicit exact solutions of the DSWEs with the conformable fractional derivative. All of the resulting solutions include triangle, hyperbolic and rational function type. It shows this technique is effective and reliable to find exact solutions of other similar nonlinear fractional partial differential equations (NFPDEs).
Numerical Simulation of Granular Column Collapse with Fractal Particle Size Distribution Using Discrete Element Method
Authors: Lai Zhiqiang , Pan Li , Wang Zhongmei , Wang Jiayi , Ren Yanfen 
Published: November 2021

Abstract
This study conducts numerical simulations of the granular column collapse with Fractal Particle Size Distributions (FPSDs) via the Discrete Element Method (DEM) and investigated kinetic behaviours of dry granular flows. The aim of this paper is to explore the effects of the fractal dimension of FPSD on the kinetics of dry granular flows. When the fractal dimension of the flows consisting of granular materials increases, the horizontal particle translational velocities become greater and the mobility improves, whereas the particle rotational velocities decrease. Meanwhile, the change in the potential energy increases, and the particle kinetic energy in the rotational form reduces; thus, the particle kinetic energy in the translational form increases. The reducing particle rotational movement may be related to the reducing particle shearing behaviours because only the contact shearing can affect particle rotational motion. In conclusion, a larger fractal dimension of FPSD of a dry granular flow leads to a longer spreading distance and a smaller rotational velocity.
An Echo Sequence Profile Image Based Ship Target Classification Algorithm for Low-Resolution Radar
Authors: Hang Duoduo , Zhang Ji , Chang Chuanwen , Zhu Wei , Wu Beibei , Zhang Hua , Wang Junbo 
Published: November 2021

Abstract
Ship target classification is of great significance in both military and civilian fields. We propose a ship target classification algorithm for low-resolution radars with echo sequence profile images. This algorithm can be realized in the following steps. First, we collect radar profile image data. We use five perspectives of a radar target, including target shape, Radar Cross Section (RCS), echo amplitude, motion attribute, and features of two-dimensional grayscale maps, to extract eight-dimensional feature vectors. The proposed algorithm uses the Support Vector Machine (SVM) as the classifier, and the parameters of the classifier are optimized by either grid search or the Particle Swarm Optimization (PSO) algorithm. The proposed algorithm is verified through real data classification tests.
Numerical Modeling of A New Virtual Trajectory Password Architecture
Authors: Chen Yuanyuan , Chen Jing , Li Mingzhu 
Published: November 2021

Abstract
With the development of digital technology, Computer technology, communication technology and multimedia technology gradually infiltrate into each other and become the main core of information technology. In information technology, digital, text, graphics, images, sound, video, animation and other information carriers are spread through computers and the Internet. Due to the openness, sharing, dynamic and other characteristics of the Internet, information security is threatened and interfered. Information security has become a strategic issue that people must pay attention to, which is related to social stability, economic development and national security. This paper studies a new kind of virtual track cryptography, which breaks through the traditional character memory method and transforms it into memory graphics by using mathematical modeling, and changes the surface memory method from memorizing numbers and characters to memorizing trajectory graphics, so as to make the traditional process of people memorizing passwords easier.
Weapon-Target Assignment Problem Using Modified Water Wave Optimization Algorithm
Authors: Wei Yuanfei , Luo Qifang , Zhou Yongquan 
Published: November 2021

Abstract
The weapon-target assignment (WTA) is a classic problem. The WTA mathematical model is that warship formations are reasonably equipped with weapons resources for each weapon system to attack the air threaten targets. The purpose of targets optimization is to maximize combat effectiveness, that is to say, the mathematical expectation is maximum. We adopt the greedy strategy and improved propagation operation is to strengthen the water wave optimization (WWO) search performance. This article elaborates a modified water wave optimization (MWWO) to solve the WTA problem, which can detect optimized allocation decision matrix and search for the maximum mathematical expectation. Based on parameter optimization, the overall performance of the MWWO is more stable, the search speed is accelerated and the accuracy is improved. The experiment results indicate that the MWWO are verified and avoids local optimum, and can be more convenient for solving the WTA and obtain better performance.
Spinneret Image Region of Interest Segmentation Algorithm
Authors: Li Dejun , Zhou Guiyang , Cheng Kang , Wang Cheng , Wang Yifan , Li Guanglong 
Published: November 2021

Abstract
In order to improve the accuracy of spinneret defect detection, a spinneret image region of interest segmentation algorithm is proposed for the problem that the complex background of spinneret image interferes seriously with the subsequent detection. The mask image is obtained by separating the fixed plate area and the spinneret wall area using the diffuse water filling method, and the minimum external circle and the maximum internal circle in the mask image are found using contour detection to obtain the mask image of the spinneret area, and then the spinneret area, i.e. the Region of Interest (ROI), is extracted. The experimental results show that this method can effectively separate the spinneret region and reduce the background interference.
Abnormal Detection to Big Data Using Deep Neural Networks
Authors: Zheng Jian , Li Zhaoni , Li Jiang , Liu Hongling 
Published: November 2021

Abstract
It is difficult to detect the anomalies in big data using traditional methods due to big data has the characteristics of mass and disorder. For the common methods, they divide big data into several small samples, then analyze these divided small samples. However, this manner increases the complexity of segmentation algorithms, moreover, it is difficult to control the risk of data segmentation. To address this, here proposes a neural network approch based on Vapnik risk model. Firstly, the sample data is randomly divided into small data blocks. Then, a neural network learns these divided small sample data blocks. To reduce the risks in the process of data segmentation, the Vapnik risk model is used to supervise data segmentation. Finally, the proposed method is verify on the historical electricity price data of Mountain View, California. The results show that our method is effectiveness.
Dynamic Performance Simulation Analysis of Electric Forklift Truck Based on ADVISOR
Authors: Zhang Li 
Published: November 2021

Abstract
According to the power system selection and technical parameters of the lithium titanate electric forklift that have been matched, the ADVISOR simulation software modeled the parameters of the drive motor, lithium titanate battery, reducer and other major components of the system. The acceleration ability, climbing ability and energy consumption of lithium titanate-electric forklift are simulated, and its technical parameters are obtained, which provides a basis for testing the rationality of system parameter matching.
Design and Simulated Analysis of Low Heat Flux Cold Plate for High-power Power Electronics Equipment
Authors: He Xunan , Kang YuanLi , Li Peng 
Published: November 2021

Abstract
The thesis has carried out design and simulated analysis of low flux cold plate for high-power power electronics equipment. First, according to heat distribution and design requirements, two kinds of flow passage for low flux cold plate is designed. Then performance characteristics simulation of different flow passage for cold plate is performed. And the heat dissipation characteristics of two kinds of flow passage can both meet the design requirements. Finally, from the perspective of high temperature, temperature difference, pressure drop and so on, the simulated results are comparative analysis. And it is helpful to the design and optimizing of cold plate for high-power power electronics equipment.
Engine Fault Detection Approach Based on Angle Domain Signal Model
Authors: Zeng Hai , Zeng Ning , Han Jin , Ding Yan 
Published: November 2021

Abstract
Engine vibration signals include strong noise and non-stationary signals. By the time domain signal processing approach, it is hard to extract the failure features of engine vibration signals, so it is hard to identify engine failures. For improving the success rate of engine failure detection, an engine angle domain vibration signal model is established and an engine fault detection approach based on the signal model is proposed. The angle domain signal model reveals the modulation feature of the engine angular signal. The engine fault diagnosis approach based on the angle domain signal model involves equal angle sampling and envelope analysis of engine vibration signals. The engine bench test verifies the effectiveness of the engine fault diagnosis approach based on the angle domain signal model. In addition, this approach indicates a new path of engine fault diagnosis and detection.
Modeling and Algorithm Research on Identification of Wrong Wiring Power Supply Region based on Classification Analysis
Authors: Li Zongpeng , Yu Liang , Liu Jian , Su Liangli , Tan Huang , Zhao Jiakui , Lin Xiaojing , Cheng Hui , Zhang Hao 
Published: November 2021

Abstract
The wrong wiring of the power supply region directly affects the accuracy of the metering data. This paper based on the existing data of the power supply regions, defined four indicators which include minimum negative line loss rate, maximum positive line loss rate, minimum power factor and maximum number of negative power values. Then by using the four indicators before and after the wrong wiring rectification of the historical wrong wiring regions and the decision tree algorithm, the wrong wiring regions identification model was built. The identification model was used to identify the wrong wiring regions in all regions of the power company, and the regions identified as wrong wiring by the model were inspected on-site. The inspection result shows that the precision of the model is satisfactory, which can effectively improve the inspection and rectification efficiency of the wrong wiring regions.
Verification Simulation and Development of New Marine Transport Model
Authors: Zhang Jing 
Published: November 2021

Abstract
The structure of the global supply chain creates an imbalance in trade between regions of the world. It creates many empty containers on the ocean shipping route. Focusing on this problem, we will develop an empty container relocation plan for empty containers in a marine container logistics network connecting multiple bases and propose a model that minimizes the total cost of container transportation. The proposed model was verified by the simulation designed and developed in this study, and the effectiveness of the proposed model was shown by the data of the marine transportation company.
Simulation and Research of Urban Intelligent Traffic Light Control System
Authors: Sun Chunling , Liu Fuhai 
Published: November 2021

Abstract
Intelligent traffic light control system belongs to the field of transportation public safety control. So far, the traffic light control system on the market cannot change the working time of the traffic lights according to the actual traffic flow, which is not conducive to the easing of the traffic flow and easy to cause traffic jams. Therefore, it is necessary to solve the problem of the existing traffic light control system which cannot adjust the working hours of the traffic light according to the actual road conditions, so as to alleviate the traffic jam at the intersection to a certain extent. In this paper, the design of intelligent traffic light control system uses AT89C51 MCU as the core device. The system controls the traffic of different times and different conditions, and it can alleviate traffic jam to a certain extent. This paper analyzes the hardware and software designes of intelligent traffic light control system, and simulates traffic light control by simulation software. The system of this paper is simple in structure, economical and practical, reliable in operation and it can effectively dredge the traffic.
Short-Term Wind Speed Forecasting Using Meta Learning-based Elman Neural Network
Authors: Madhiarasan M. 
Published: November 2021

Abstract
Adequate power provision to the customer and wind energy penetration into the electrical grid is necessitated for accurate wind speed forecasting in the short-term horizon to realize the scheduling, unit commitment, and control. According to the various meteorological parameters, the wind speed and energy production from wind energy are affected. Therefore, the author performs the multi-inputs associated Meta learning-based Elman Neural Network (MENN) forecasting model to overcome the uncertainty and generalization problem. The proposed forecasting approach applicability evaluated with real-time data concerning wind speed forecasting on a short-term time scale. Performance analysis reveals that the meta learning-based Elman neural network is robust and conscious than the existing methods, with a least mean square error of 0.0011.
Simulation of the Performance Metrics for Securing DSDV Routing Protocol Based on Trusted Environments
Authors: Feng Chiang Ling 
Published: November 2021

Abstract
To organize the network in an efficient way to minimize the risk of illegal node and to safeguard protected information, a security mechanism is required to secure communication. In addition, a security mechanism is also required to ensure that received information have not been tampered with. In this paper, a more efficient mechanism for Securing the Destination Sequenced Distance Vector Routing Protocol (SDSDV) is proposed. This paper comprehensively investigates the performance impacts by varying the number of maximum connections and mobility on securing the ad hoc network with Destination Sequenced Distance Vector Routing Protocol (DSDV) Routing Protocol. From simulation results, we explore the causes for performance degradation. Based on the investigation, we indicate that we have to impose restrictions on the maximum connections to acquire an expected performance. These results also reveal that the performance decreases with the increment of the mobility and maximum connections that is unequal to 60. If we want to obtain the optimal performance, the number of nodes in a network should be constrained to be 60 if the maximum connections are 60.
The molten wood’s metal initial velocity variations effect on breaching simulation by MPS method
Authors: Hidayati A N , Waris A , Mustari A P A , Irwanto D , Aprianti N A 
Published: November 2021

Abstract
Series of MPS simulations have been conducted using two-dimensional geometry. The simulation was based on Sudha’s experiment (2018) about initial velocity variations on molten Wood’s Metal (WM). The molten WM would be flowed through nozzle with the diameter was 6 mm. It would impinge to the Woods Metal Plate (WMP) which 270 mm below the nozzle. The WMP diameter was 470 mm. The temperature of molten WM and WMP were set at 573 K and 300 K, respectively. The initial velocity of molten WM was varied at 0.327 m/s, 0.397 m/s, 0.498 m/s in the y-negative direction. The simulation was calculated by using 2D MPS with additional procedures such as heat transfer calculation and defining a new type of wall particle. The results showed some different spread patterns, leading edge and phase fraction change for each initial velocity. It can be concluded that with varying the initial velocity will affect on the radial spread pattern but not so much effect occurs on the phase volume fraction change.
Mathematical modelling of soybean var. anjasmoro plant growth
Authors: Aditiawati P , Viridi S , Palupi S , Rostiani R , Samosir M D , Primaresti P D 
Published: November 2021

Abstract
Thorough understanding of interactions between all factors involved in soybean plant cultivation process is needed to increase the yield. This study is aimed to determine which interaction has the highest correlation according to the Pearson correlation coefficient, to define a certain model for said interaction, and to confirm the identicality of all samples that were observed using destructive sampling method. After being tested using Pearson correlation coefficient, the highest r value is 0,81 which is between plant height and number of leaves, proving they are highly related. Both parameters were simulated in several different ways until it was found that number of leaves variable is best described as function of plant height variable, the equation is y1 = 0,85x1 + c1 where y1 represents number of leaves and x1 represents plant height. Identicality between all plants is not confirmed, thus destructive sampling method is not recommended to be applied for similar studies.
Physical protection system effectiveness calculation in nuclear reactor facility using EASI code: case study sabotage scenario
Authors: Andiwijayakusuma D , Mardhi A , Asmoro T , Setiadipura T , Purqon A , Su’ud Z 
Published: November 2021

Abstract
Every nuclear facility must pay attention to the 3S aspect (Safety-Security-Safeguard) to prevent nuclear accidents. One element in the nuclear security aspects includes a reliable Physical Protection System (PPS), which aims to ward off security disturbances and other illegal acts, i.e., sabotage, theft, Etc. This study evaluates the PPS performance by adversary-path analysis approach using the EASI code for hypothetical nuclear reactor facility to anticipate sabotage attacks as the highest consequences scenario. We perform the probability of interruption (PI) calculation as represented by the effectiveness of the PPS. The study results show that in the PPS design, calculating the PI value using the EASI code confirms the need to pay attention in determining the MVP. The results provide feedback for the PPS designer to accept the current design or strengthen it to obtain a reliable PPS.
Preliminary Neutronic Analysis of 150 MWt High-Temperature Gas Reactor to Produced Electricity in Small Area
Authors: Yuningsih Nining , Irwanto Dwi 
Published: November 2021

Abstract
There are small areas in Indonesia with insufficient electricity. High-Temperature Gas Reactor (HTGR) is a promising nuclear power plant that can be used in such areas as its capability to produce electricity and co-generation applications. A preliminary study on the neutronic aspect of the 150 MWt HTGR design is performed in this research. High Temperature Engineering Test Reactor (HTTR) is used as a basic model. The calculation was performed by Standard Thermal Reactor Analysis Code (SRAC) code, and Japanese Evaluated Nuclear Data Library (JENDL) 4.0 as nuclear data library. As a result, by increasing HTTR fuel assembly geometry to 1.5 times its original and using higher uranium enrichment, the reactor can be operated for five years.
Neutronics performances of gas-cooled fast reactor for 300-600 MWt Output Power with Modified CANDLE burn-up scheme in radial direction
Authors: Irka F H , Suud Z , Irwanto D , Khotimah S N , Sekimoto H 
Published: November 2021

Abstract
Gas-Cooled Fast Reactor-GFR is a Generation IV reactor that is helium-cooled and has a closed fuel cycle. Due to the target operation on 2022-2030, this reactor type still needs further research and development technologies. We investigated the neutronics performances of a GFR balance type core with some modification of CANDLE (Constant Axial shape of Neutron flux, nuclide densities and power shape During Life of Energy production) burn-up scheme in the radial direction. The output power varied from 300 to 600 MWt. The neutronics calculation was performed using SRAC 2002 with JENDL 4.0 nuclear data library. The analysis indicate the reactor could operate critically for ten years without refueling with burn-up level 20% HM.
Comparative of blanket reactor design in assuring of tritium self-sufficiency
Authors: Maemunah I R , Su’ud Z , Waris A , Irwanto D , Yazid P I 
Published: November 2021

Abstract
The comparison of four blanket modules in DEMO made up the optimization material having a reasonable requirement as blanket material in this study. Either neutron flux distribution in blanket material or material endurance under neutron irradiation, from four modules, the WCLL has a high tolerance neutron distribution and the best neutron irradiation endurance. Furthermore, many suggestions closed to the statement to use the benefits of water coolant and lithium lead (compose Li-6) as a material component in the blanket.
Physical forces driving chlorophyll-a variability in the South Java Sea Shelf: a spatio-temporal analysis
Authors: Budiman A S , Bengen D G , Arifin Z , Nurjaya I W , Ismail M F A 
Published: November 2021

Abstract
The wind and current are two physical forces that strongly influence the biogeochemistry in coastal waters. Both of these forces could enhance the Chlorophyll-a (Chl-a) concentration through the upwelling process. Here we examine the contribution of the wind and current to the Chl-a variability in the South Java upwelling system in terms of wind stress and bottom stress respectively using satellite-derived and reanalysis data from 2002 to 2017. Ten longitudinally cells were used for further analysis. A long-term Chl-a shows a strong longitudinal gradient of Chl-a with the highest value on the shelf. Seasonal and Inter-annual Chl-a analysis shows the evidence of the monsoonal winds and other forcing effects relevant to the previous studies. Wind stress (τwx
) has a strong seasonal variation which is upwelling- favorable during southeast monsoon coincide with higher Chl-a suggesting wind as the main forces during that time, while bottom stress (τbx
) has more complicated variations, but it’s seen that τwx
mostly downwelling-favorable or eastward circulations. There were about 39.92- 52.94% of positive Chl anomalous events generated by the combination of upwelling- favourable τwx
and downwelling-favorable τbx
, higher than other combinations. In terms of Oceanographic drivers, the wind has a higher effect on enhancing Chl-a through a negative correlation. τwx
leads the Chl-a anomalies by about 15 – 24 days with a correlation coefficient of more than 0.6.