bluuebunny/crossref_metadata_2025_split huggingface dataset:
On the approximation of a Cauchy problem in a non-homogeneous medium
Authors: Aboud F. , Nachaoui A. , Nachaoui M. 
Published: January 2021

AbstractThis paper deals with an inverse Cauchy problem governed by an elliptical equation defined in non-homogeneous domain. We propose two approaches based on alternating algorithm [11] combined with a domain decomposition method [14]. We use the finite elements method to approximate the associate direct problems. Finally, we show the numerical convergence of both proposed algorithms and we discuss there efficiency trough some numerical experiments.
Identification of Complex Network Influencer using the Technology for Order Preference by Similarity to an Ideal Solution
Authors: Ait Rai K. , Agouti T. , Machkour M. , Antari J 
Published: January 2021

Abstract
Marketing through social networks is a recent approach which consists in using these networks to convince potential consumers with the quality of products or services offered by a company. Marketing is developing very quickly, particularly on Facebook, Twitter, LinkedIn, Instagram, YouTube, etc. The major advantage of social networks is the possibility of influencing a panel of people according to their interests but without having the feeling of being guided. Identifying influencers is an interesting topic in social networks, and centrality measures are among the methods used to address this topic. Each measure has some shortcomings. In this paper, we gather centrality measures by using Technology for Order Preference by Similarity to an Ideal Solution (TOPSIS) method, which is a Multi-Criteria Decision Making (MCDM) to identify potential influences in a social network. A case study is presented to explain carefully TOPSIS and to illustrate the effectiveness of the proposed method, three real datasets are used for the experiments. The results show that TOPSIS can rank spreaders more accurately than centrality criteria.
Accuracy assessment of applied supervised machine learning models on usual data probability distributions
Authors: Chefira R. , Rakrak S. 
Published: January 2021

Abstract
In this paper, an application analysis of supervised classification techniques on several probability distributions is carried out. Accuracy as well as usual standard metrics have been highlighted to rate the performance of generated learning models. Using data that fit different distributions, we investigated whether the application of a classification method had an optimizing impact on the accurateness of its correlated learning model.
Anomaly Detection using Machine Learning Techniques in Wireless Sensor Networks
Authors: Ifzarne Samir , Tabbaa Hiba , Hafidi Imad , Lamghari Nidal 
Published: January 2021

Abstract
The number of Wireless sensor network (WSN) deployments have been growing so exponentially over the recent years. Due to their small size and cost-effective, WSN are attracting many industries to use them in various applications. Environmental monitoring, security of buildings and precision agriculture are few example among several other fields. However, WSN faces high security threats considering most of them are deployed in unattended nature and hostile environment. In the aim of providing secure data processing in the WSN, many techniques are proposed to protect the data privacy while being transferred from the sensors to the base station. This work is focusing on attack detection which is an essential task to secure the network and the data. Anomaly detection is a key challenge in order to ensure the security and prevent malicious attacks in wireless sensor networks. Various machine learning techniques have been used by researchers these days to detect anomalies using offline learning algorithms. On the other hand online learning classifiers have not been thoroughly addressed in the literature. Our aim is to provide an intrusion detection model compatible with the characteristics of WSN. This model is built based on information gain ratio and the online Passive aggressive classifier. Firstly, the information gain ratio is used to select the relevant features of the sensor data. Secondly, the online Passive aggressive algorithm is trained to detect and classify different type of Deny of Service attacks. The experiment was conducted on a wireless sensor network-detection system (WSN-DS) dataset. The proposed model ID-GOPA results detection rate of 96% determining whether the network is in its normal mode or exposed to any type of attack. The detection accuracy is 86%, 68%, 63%, and 46% for scheduling, grayhole, flooding and blackhole attacks, respectively, in addition to 99% for normal traffic. These results shows that our model based on offline learning can be providing good anomaly detection to the WSN and replace online learning in some cases.
A new Advanced Greedy perimeter stateless routing for Vehicular Ad Hoc Networks
Authors: Laanaoui D. , Raghay S. 
Published: January 2021

Abstract
In VANET, Vehicles can be seen as probes that locally detect traffic status. Various applications that target transport efficiency could make use of the vast information collected by the vehicles; however, this collection of information needs to be transported over larger distances. For this purpose, various protocols were proposed in the literature and are surveyed in this paper. The information dissemination ‘lifecycle’ is structured in four phases: obtaining information, transport of information, summarization of measurements, and aggregation of information. In this paper, we will focus on the first and second phases to insure the transport of information. And we improve the behavior of GPSR protocol in term of delay and throughput to deal with the limited capacity of the vehicular wireless network.
Recognition of Arabic Handwritten Diacritics using the new database DBAHD
Authors: Lamghari N , Raghay S 
Published: January 2021

Abstract
Recognition of handwritten Arabic characters is gaining momentum and research in this area has increased considerably in recent years. However, research remains modest compared to that performed in other scripts. This is mainly due to the morphology of Arabic writing, in particular its richness in diacritical marks. This signs are generally recognized by adopting structural or morphological measures. However, the difficulty and variability of handwriting can sometimes be misleading, thus influencing the results obtained. This article presents a new database for Arabic handwritten diacritics (DBAHD). It is designed to serve the Arabic handwriting recognition systems based on segmentation and machine learning.
Modeing and Robust Continuous Power Allocation Strategy with Imperfect Channel State Information in Cognitive Radio Networks
Authors: Chen Zhong , Cai Jun , Zhu Feng , Guo Rui , Niu Gengtian , Liu Yanjie 
Published: January 2021

Abstract
A robust continuous power allocation strategy for secondary users (SUs) with imperfect channel state information (CSI) in the cognitive radio networks is proposed. Modeling the error of CSI by normbounded distribution, we address the optimization of the transmit power allocation at SU under the constraints of average transmit power at SU and average interference power at the primary user. Simulation results show that the proposed robust rools can improve the system performance of the SU.
Theory and Application of Logistic-SVM Two-Stage Hybrid Model
Authors: Liu Pingshan , Zeng Ziming 
Published: January 2021

Abstract
Based on the theoretical analysis, this paper combined the Logistic model and the support vector machine (SVM) to construct a Logistic-SVM two-stage hybrid model for credit risk evaluation. Using the two-stage hybrid model to evaluate the credit risk of pharmaceutical supply chain finance, the results showed that the Logistic-SVM two-stage hybrid model had a higher evaluation level than the single Logistic model and the single SVM model, which verified the superiority and effectiveness of the Logistic-SVM two-stage hybrid model applied to the credit risk evaluation.
Influence of Geometrical Dimensions on Negative Differential Resistance in Silicon Based Trench MOS Barrier Schottky Diode
Authors: Chen Huanwen , Wang Yijun , Zhang Hang 
Published: January 2021

Abstract
In this paper, ISE-TCAD, a device simulation software, is used to carry out simulation experiments on silicon-based trench MOS Schottky (TMBS) diodes with different trench dimensions under the condition of forward biases and obtain a series of experiment data associated with the negative resistance. Simulation results show that TMBS diodes under forward biases produce the negative resistance effect. The negative resistance effect intensifies linearly with the increase of mesa width and mitigates wavily with the increase of trench depth. The coupling effect of trench oxidization layer on electric field attenuates the change in device field strength, leading to the fact that TMBS devices present a weaker negative resistance effect than trench barrier Schottky (TBS) diodes which have the same parameters, but are free of oxidization layer. The study result provides a feasible basis for the effective application of TMBS negative resistance features to the design and production of corresponding semiconductor devices and circuits.
Optimal Control for Acrobot with Two-link Manipulators
Authors: Liu Weicai , Zhang Zhifei 
Published: January 2021

Abstract
This paper presents a unified treatment of the optimal control of under-actuated two-link manipulators. Firstly, a nonlinear invertible transfer is introduced to simplify design of controller, then several optimal control laws are established by maximum principle. Controller for swing-up area is based on performance index, while controller for attractive area is based on LQR (linear quadric regulator). It is proved that optimal control is not singular, invariant sets are obtained by theoretical analysis. The strategy for Acrobat is to use optimal control law to pump manipulators into linearizable area, then switch control law to LQR, which drives system to up-straight position. Local and global stability were analyzed in detail under control strategy using LaSalle’s invariance principle and WCLF (non-smooth control Lyapunov function). Simulation and comparison with previous results show that the proposed approach here is valid and of advantages.
Agent-based Simulation of Multi-UAV Search-track for Dynamic Targets in Sweep Coverage
Authors: Liu Zhen , Liu Yukun 
Published: January 2021

Abstract
Agent-based modeling and simulation is an important method to evaluate the efficiency of the multi-UAV search-track problem. In this article, firstly analyse common strategies and then illustrate sweep coverage in parallel searching with changing formation strategy compared with the traditional scanning strategy. Establish an agent-based model by analysing the properties and behaviours of the car agent and UAV agent. Conduct simulation experiments in Anylogic with two strategies, as the results shown, the changing formation strategy can improve the UAVs’ recognition rate more effectively than traditional scanning strategy. Recognition rate has positive correlation with the speed of UAV and the maximum rotation range of the detection area, and is more sensitive to the changes of speed.
A Fuzzy Clustering Based Collaborative Filtering Algorithm for Time-aware POI Recommendation
Authors: Yin Minghao , Liu Yanheng , Zhou Xu , Sun Geng 
Published: January 2021

Abstract
Location based social network develops and gets widely concern along with the population and widespread use of mobile. Point of interest(POI) recommendation become one of the most widely application among location-based service. To get better POI recommendation performance, a fuzzy clustering based collaborative filtering algorithm (FCCF) for time-aware POI recommendation is proposed in this paper. It first constructs the user feature vector from users’ check-in behaviours. Individual’s check-in behaviour can be under the influence of location region and time slots, so user’s feature consists of two parts. One is the vising frequency of each user in different location regions, and the other is the vising frequency of each user in different time slots. Next fuzzy c-means is adopted due to its simplicity to group users according to user feature vector. Then the user similarity computation can be limited in the similar small user groups. In the end, a collaborative filtering algorithm is applied to recommend a number of top-N POIs at a given time for the target user. Some experiments are conducted and the comparative results on Foursquare and Gowalla show that FCCF has higher precision and recall value than the comparative algorithms.
Numerical Analysis and Investigation on the Drawbending Springbackand Fracture
Authors: Ma Wenyu , Yang Jianwei , Li Xiaoqiang , Dou Luyi , Yao Ye , Zhang Yongqiang 
Published: January 2021

Abstract
In this paper, the effect of process parameters on the drawing springbackand fracture mechanism of high strength steel in drawbending process was investigated. The fracture behaviour and fracture morphology were observed and analyzed using Scanning Electron Microscope (SEM). The process parameters studied in this paper includes drawing speed, roll radius, drawing force and roll radius. The springback angle measurement method for drawing springback was also introduced and applied. The conclusions were drawn from the results. The drawbending springback angle increases withthe increase of drawing velocity. The springbackdecreases with the increase of the round roll. The large bending angle leads to the large springback. The large tension force can decrease the springback angle. The springback increases with the increase of the drawing distance. The fracture with theplane angle of 60 indicates a shear fracture and thedominated brittleness mode, which is induced by a large radius against thickness value. The fracture vertical to straight side indicates the ductility tension fracture, which is induced by a small radius against thickness value.
Application of Algorithm with Novel Successive Approximate Registration Method of Medical Image
Authors: Yang Yunfeng , Wang Fei , Guan Chen 
Published: January 2021

Abstract
Medical image registration is widely used in the clinical field. A simple and effective registration method for medical images is proposed, which is not only used images’ hierarchical information, but also the successive approximate method is used. It mainly includes two steps, which are the coarse registration and the fine registration. In the coarse registration procedure, the couple images’ edge features are extracted. Further more, the contour line features are extracted based on the edge features. The contour lines are selected as registration objects to accomplish the coarse registration based on the Principal Axis method. In the second registration procedure, i.e. the fine registration, the hierarchical information of the images are obtained by the convolution operator and pooling method firstly. Then these information are matched from the last scale to the first scale to obtain the last registration result. The proposed method’s validity is proved by different registration experiments, and the proposed method can also be applied to incomplete images’ registration. The error of registration is less than one pixel unit in the different registration experiments of the proposed method.
Numerical Simulation Study on Air - side of Diesel Locomotive Finned Tube Double Channel Radiator
Authors: Guan Ying , Cui Hongjiang , Li Minghai 
Published: January 2021

Abstract
Based on the heat transfer and flow resistance of diesel locomotive radiator, the influence was studied about the cooling air inlet speed on heat transfer coefficient and pressure loss of finned tube double channel radiator with louver by using CFD method. Temperature field, speed field and pressure field distribution of radiator calculation results were analyzed. The radiator was tested at different cooling air inlet speed, compared test results with simulation results, the greatest relative error of the heat transfer coefficient and pressure loss were 7.21% and 7.72%, respectively.
Research on Traffic Dispatching Scheme of Multi-service Data Center for 5G Smart Grid
Authors: Sun Yanzhi , Liu Yuming , Tian Feng , Wen Quan , Jiang Liqiong 
Published: January 2021

Abstract
Aiming at the flow scheduling problem of 5G power network multi-service data center, this paper designs and proposes a multi-service-oriented multi-factor flow scheduling scheme. Based on the shortest path algorithm, this paper improves and perfects the traffic scheduling strategy, and introduces a set of scoring mechanism. The number of hops, the number of large flows and the remaining bandwidth of each path are used as scoring indicators, and the path with the highest comprehensive score is selected. As the forwarding path of traffic. Based on the Mininet simulation platform, use Ryu to control to generate probability model traffic to simulate data center network traffic. The experimental results show that the scheme improves the network throughput and bandwidth utilization, and improves the performance of the data center network.
Optimization Analysis of AR-HUD Technology Application in Automobile Industry
Authors: Zhang Miaoxuan 
Published: January 2021

Abstract
Currently, how to make the driving system safer and more intelligent has been a heated topic. To achieve the goal, quite a few companies argued about introducing HUD technology, which was originally used in aircraft, to the automobile industry. In order to make HUD have better performance in the new area, the public’s attention was paid on the combination of AR and HUD technology. AR-HUD is seen as a good way to improve the convenience and safety factor of driving. This article introduces the usage of AR-HUD in the traffic analysis, man-machine interactive, intelligent navigation and aided driving. Moreover, SWOT method was introduced to this new area, to find out the prospect of AR-HUD application. It is found that although AR-HUD is technology is still relatively immature up to now, it has the power to have broad application space in the future. AR-HUD’s time is around the corner.
Optimization Technology of Passenger Service System based on Railway Intelligent Robot
Authors: Zhao Jiayu , Feng Fan 
Published: January 2021

Abstract
In the post-epidemic era, with the continuous increase of passenger flow in railway stations and people’s increasing attention to public health, traditional service methods such as meal delivery and ticket checking in railway stations cannot keep up with the rhythm of the times, and the transportation sector is facing how to solve the problem of contactless services. This product uses STM32F103 as the core controller to develop a multifunctional intelligent robot system for trains. The system uses A* and artificial potential field algorithms for path planning and obstacle avoidance, combined with integrated software services, cooperates with the cloud to record various data, and finally add intelligence. The power management system ensures that the system can safely, efficiently, accurately and lastingly complete functions such as online ordering, smart ticket checking, temperature measurement and crew call. On the basis of the existing technologies, this paper makes a little technical integration and innovation to complete an intelligent robot system.
Convergence - Divergence of the Finite Volume Method for the Fluid and Heat Flow in Heterogeneous Porous Rocks
Authors: Suárez-Arriaga Mario-César , Verma Mahendra Pal 
Published: January 2021

Abstract
Fluid velocity has an important impact in the Finite Volume numerical method (FVM) used to model fluid and energy flows in heterogeneous porous media. This formulation is based on the energy flow conservation equations under local thermal non-equilibrium conditions (LTNE). The heat transfer from the solid matrix to the moving non-isothermal fluid inside the pores is simulated for several velocities and global different heat transfer coefficients. During the numerical simulation of coupled heat/mass flow in a heterogeneous porous system it is necessary to average highly variable physical parameters at the boundaries between different domains represented geometrically in the computational mesh of the FVM. This can be effectively achieved using appropriate average techniques at the contact interfaces of each domain. The averaging process should correctly represent the behaviour of the fluid velocity crossing different areas of the reservoir. Many numerical divergence problems arise from the fluid velocity value and the interfacial interactions at the boundaries of different continua. The averages have a decisive influence on the numeric results of the simulation. A very stable, convergent averaging scheme for the FVM is presented herein and compared to new analytical diffusion-convection models. Especial attention is paid to the dynamic process of cold water (50°C) injected into a geothermal reservoir at higher temperature (350°C). The fluid temperature profile is calculated when the fluid migrates at constant speed through a permeable corridor from a fluid injection point to an extraction zone. The physical reason for the divergence of a numerical model, and the exploration of the range of validity of the LTNE hypothesis during the injection of cold water into a hot reservoir are both explained.
Research on the Optimization of Urban Cold Chain Logistics System Based on the Example of Guangzhou
Authors: Kuang Mo , Du Yong , Kuang Da , Zhu Xiangyi 
Published: January 2021

Abstract
In view of the realistic environment of the cold chain logistics development in Guangzhou, this paper aims at analyzing the present pre-cooling equipment of the cold chain logistics in Guangzhou, the lack of cold storage facilities, the incomplete cold chain structure, the lagging of the development of the third-party cold chain logistics industry, the lack of trace ability of the products, the information tracking mechanism and the deficiency of the standard specifications of the cold chain, the shortage of cold chain professionals etc., and the countermeasures are put forward from three aspects: strengthening the policy support for the overall planning of the cold chain logistics; strengthening the construction and improvement of the cold chain logistics system and the platform and the main body; and developing the Guangzhou cold chain logistics industry in various modes.
Optimization of Power Supply Section Planning in Medium-Speed Maglev System
Authors: Zhou Haoran , Meng Lingyun , Lai Qingying , Xu Yazhi 
Published: January 2021

Abstract
The power supply planning of medium-speed maglev system (MSM) is related to line capacity greatly. To improving sectional through capacity, this paper takes the problem of dividing power supply zones of MSM as research object, i.e, the optimization of power supply planning. With the known number of zones, optimization object is maximum line capacity without consideration of generalized cost. Considering factors such as stator position in section, train speed profile characteristics, blocking time and blocking time overlap method, an optimization model of MSM stator combination is established. According to the given relative position of stators and target speed profile, a genetic algorithm is designed to obtain power supply plan that meets the target expectation. This method provides guidance for the future MSM power supply planning.