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Fine-grained vehicle recognition method based on improved ResNet

Fine-grained vehicle recognition method based on improved Re...

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Information Technology and computer Application (ITCA), international conference on

作者： Qi Ailing Tian Ning School of Computer Science and Technology Xi'an University of Science and Technology xi'an China

Traditional image recognition algorithms generally extract features manually and use classifiers for classification. Aiming at the problems of general recognition effect and limited generalization ability, an improved ResNet-based fine-grained vehicle recognition method is proposed. The basic network adopts the residual structure, which improves the flow of information by introducing jump connections and can effectively alleviate over-fitting. And add the Inception module to the ResNet model, It uses different sizes of convolution kernels and has different sizes of receptive fields, which can further improve the recognition accuracy. The optimization algorithm uses Adam optimizer, the experiment uses Stanford University model database stanford cars as the data source, and compares experiments with other methods. The results show that the accuracy of this method on the test set reaches 91%, which effectively improves the recognition accuracy.

关键词： Image recognition Databases Computational modeling Feature extraction Data models Automobiles Kernel

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Heart disease prediction based on random forest and LSTM

Heart disease prediction based on random forest and LSTM

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Information Technology and computer Application (ITCA), international conference on

作者： Yuepeng Liu Mengfei Zhang Zezhong Fan Yinghan Chen International Institute of Education Hebei University of Technology School of information science and engineering University of Jinan The University of Wisconsin Madison America Beijing No.4 High School

According to the World Health Organization, 12 million people die of heart disease every year. About half of the annual deaths are due to cardiovascular disease worldwide each year. [1] Because early prediction of cardiovascular disease greatly reduce the probability of complications in high-risk patients, there is great value in trying to predict the probability of cardiovascular disease more accurately through a heart disease prediction model. In this paper, we constructed a heart disease prediction model based on random forest and LSTM to screen out the main features that may lead to heart disease. Then LSTM, KNN and DNN algorithms are used to test whether the prediction accuracy is improved after screening, and finally, we chose the most accurate algorithm to establish the heart disease prediction model.

关键词： Heart Training Computational modeling Predictive models Tools Prediction algorithms Data models

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A Multi-Tier Trust-Based Security Model (MTTS) for Resource-Constrained IoT Devices to Detect Blackhole Devices and ensure Authentication 2

A Multi-Tier Trust-Based Security Model (MTTS) for Resource-...

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2nd international conference on Mathematical modeling and Computational Methods in Science and Engineering, ICMMCMSE 2020

作者： Prathapchandran, K. Department of Computer Applications Karpagam Academy of Higher Education Deemed to Be University Tamilnadu Coimbatore021 India

In the Internet of Things based military environment, to achieve an assigned task without compromising security concern is a challenging task. Resource-constrained devices, Self-organized, disseminated nature of sensor nodes, unstable topology environment, open wireless medium, and shared network environment make IoT differ from other networks. All together leads to security threats to the IoT environment. The success of any IoT based application depends on effective communication among the devices that can be achieved by routing protocols. Typically, they designed to cope with fruitful communication but in effect, they might be targeted and affected by mischievous devices. Blackhole devices are such devices that aim to disturb the normal routing operations. But the identification of trusted devices that means authentication needs to be provided for successful task completion. At present, trust management plays an important part in prediction construction and appropriate for resource-strained devices. In this article, a multi-dimensional trust-based security model is proposed to guarantee authentication by avoiding blockhole devices based on direct, indirect, sense-making, social, and stereotypes. In addition, the q-learning mechanism is used to enhance the proposed method. The simulation study represents the applicability of the projected model. © Published under licence by IOP Publishing Ltd.

关键词： Authentication

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Cognitive Fatigue Detection in Vehicular Drivers Using K-Means algorithm 2nd

Cognitive Fatigue Detection in Vehicular Drivers Using K-Mea...

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2nd international conference on Innovative Computing and Communication, ICICC 2019

作者： Sharma, Manish Kumar Bundele, Mahesh Computer Engineering Poornima College of Engineering JaipurRajasthan India

ISBN: (纸本)9789811503238

In vehicular drivers, the cognitive fatigue has been one of the major factors that leads to loss of lives or disabilities due to vehicular accidents (Bundele and Banerjee in Proceedings of the 11th international conference on information integration and web-based applications and services, ACM, pp 739–744, 2009 [1]). The factors governing driver fatigue such as monotonous driving, traffic conditions on road, road conditions, insufficient sleep, anxiety, health conditions, work environment, type of vehicle, and driving comfort do affect largely the driving behavior. Many researchers across the world are working finding best suitable methods to minimize vehicular accidents. In this paper, our proposed approach is an alternative solution to detect cognitive fatigue in vehicular drivers to decrease the number of incidence of vehicular accidents specially those occurred due to cognitive fatigue (Hu and Zheng in Expert Syst Appl 36:7651–7658, 2009 [2]). The objective of this work has been to provide simple classification technique using K-means algorithms. The basic K-means and two modified versions have been proposed and validated to reliably detect cognitive fatigue while driving. It is of paramount importance that the sensory parameters are chosen such that they could be used without causing discomfort to the driver and without creating obstruction while driving. The data for simple physiological signals such as skin conductance (SC), oximetry pulse (OP), and respiration (RSP) for pre- and post-driving state of drivers has been used for sensing change in fatigue level of the drivers (Bundele and Banerjee in 2009 second international conference on emerging trends in engineering & technology. IEEE, pp 934–939, 2009 [3]). All features of statistical and wavelet were extracted and analyzed (Brown in D1 Methodological issues in driver fatigue research. Fatigue and driving: driver impairment, driver fatigue, and driving simulation, p 155, 1995 [4]). Selected features were us

关键词： Roads and streets

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Smart Development of Big Data App for Determining the Modelling of Covid-19 Medicinal Compounds Using Deep AI Core Engine System 2

Smart Development of Big Data App for Determining the Modell...

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2nd international Seminar on Smart Molecule of Natural Resources, ISSMART 2020

作者： Cholissodin, I. Sutrisno, S. Santoso, N. Soebroto, A.A. Hidayat, N. Rochman, N.T. Faculty of Computer Science Brawijaya University East Java Indonesia Metallurgy and Materials Research Center Indonesian Institute of Sciences

Smart Big Data App Using Deep Artificial Intelligence (AI) Core Engine System focuses on solving problems related to the difficulty in building a prototyping model computer simulation like in silico as a model initiation of the complex Covid-19 medicinal compound involving Big Data ecosystems such as Hadoop and Spark. The difficulty is for example, currently, it is still very arduous to measure the rate of mixture of a compound when combined with many other compounds, which can consider the trade-off in minimizing the negative effects but optimizing the positive effects. In addition, the computation time becomes very long when using a system that is not in the Big Data ecosystem since this is proportional to the large number of compounds that vary widely and also the number of different situations of Covid-19 patients with other congenital diseases (comorbid) or without congenital disease;thus, it can be considered to be included in a condition that requires a very complex computational process which is very difficult to model using a conventional mathematical approach because the calculations are certainly very complex when compared to approaches using meta-heuristics algorithms such as Particle Swarm Optimization (PSO) which is much easier but requires a very large particle population space and iterative process to achieve global convergence. As a consequence, it requires fast computation processes based on distributed computing such as using the Big Data ecosystem. From the review of these problems, the system was created based on the Computational Intelligence;hence, the end-users, especially the developers, can build an application easier in spite of the complex computations, one of the which is in the meta-heuristic technique to minimize the negative effects and optimize the positive effects of the medicinal compounds by including a lot of data to get a better modeling. Therefore, the prototyping modeling project can be quick and robust, and achieve high perfo

关键词： Iterative methods

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Cloud-Edge-End simulation System Architecture Study

Cloud-Edge-End Simulation System Architecture Study

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Advances in computer Technology, Information Science and Communications (CTISC), international conference on

作者： Guo-Qiang YAN Mao Shao-jie Science and Technology on Information System Engineering Laboratory Nanjing China

ISBN: (数字)9781728165011

ISBN: (纸本)9781728165028

Cloud based simulation system architecture concentrates a lot of simulation resources in the Datacenter for unified management, which has the advantages of efficiency and cost, but also faces problems such as collaborative interaction. A novel simulation system architecture called is proposed. In this architecture, edge computing is introduced. It employed resource virtualization and service technical to get through the integration and interaction of various simulation resources of cloud, edge, and end. It is the further development of cloud architecture-based simulation system architecture, which is conducive to the transfer of simulation ability to application edge frontier.

关键词： Computational modeling Cloud computing Data models computer architecture Analytical models Systems architecture Collaboration

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Comparison Between Two Numerical Methods SPH/FEM and CEL by Numerical simulation of an Impacting Water Jet 2nd

Comparison Between Two Numerical Methods SPH/FEM and CEL by ...

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2nd international conference on Advanced Materials, Mechanics and Manufacturing, A3M 2018

作者： Ben Belgacem, I. Khochtali, H. Cheikh, L. Barhoumi, E.M. Ben Salem, W. Laboratoire de Génie Mécanique Ecole Nationale d’Ingénieurs de Monastir Université de Monastir Monastir Tunisia Institut Préparatoire aux Etudes d’Ingénieur de Monastir Université de Monastir Monastir Tunisia Department of Electrical and Computer Engineering College of Engineering Dhofar University Salalah Oman Institut Supérieur des Arts et Métiers de Mahdia Université de Monastir Monastir Tunisia

ISBN: (纸本)9783030242466

In this paper, we present a numerical simulation of a round jet impacting a polymer plate using the coupled Smoothed Particle Hydrodynamics (SPH) and Finite Element (FE) methods. Numerical results are compared with the results from other simulations carried out by other numerical method based on the Eulerian Lagrangian (CEL) formulation presented in the work of [1]. Results from the CEL method were experimentally validated in the work of [2]. A water jet with a spherical head was used at an initial speed of 570 m/s to impact on a flat plate made of Polymethyl-Methacrylate (PMMA). To simulate the entire process, the SPH method was used to model the water jet and the FE method was used for the modeling of the PMMA structure. The distribution of the pressure on the impact surface and the resulting deformation of the structure were discussed. A Numerical model was developed using ABAQUS/Explicit version 6.14. Results of the coupled SPH-FE simulation were further validated. It is demonstrated that the (CEL) method presents smoother curves compared to the SPH method. The numerical model using the SPH/FE method proves its ability to produce the entire physical processes of the impact. © 2020, Springer Nature Switzerland AG.

关键词： Coupled Eulerian-Lagrangian Polymethyl-Methacrylate Smoothed particle hydrodynamics Water jet

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Research on the Application of Deep Learning Technology in Intelligent Dialogue Robots

Research on the Application of Deep Learning Technology in I...

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Information Technology and computer Application (ITCA), international conference on

作者： Xianyi Zeng Donggui Liang Zhehui Liang Guanghui Chen Yong’en Li Guangzhou Power Supply Bureau Guangdong Power Grid Co. Ltd. Guangzhou China

With the breakthrough of the application of deep learning technology in computer vision and natural language processing tasks, the application of deep learning to intelligent dialogue robots has become a new research hotspot. As a novel way of human-computer interaction, intelligent dialogue robots are becoming one of the entrances of mobile search and services, and are increasingly being paid attention to by enterprises and society. However, there are still some problems in the current dialogue robot, such as insufficient use of multi-modal information and weak emotional expression ability. In this paper, a multi-modal intelligent reply generation model based on seq2seq + attention is proposed by using deep learning algorithm, which can effectively use multi-modal information such as text, picture and video to interact. At the same time, on the basis of considering the contextual content information, the model further integrates the emotional transfer change information of the dialogue text. Experimental evaluation results show that the combination of emotional intelligence can make text response generation more emotionally expressive and more vivid response generation results.

关键词： Deep learning Human computer interaction computer vision Computational modeling Semantics Natural language processing Task analysis

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Research on RGB Visible Light Communication Technology Based on OFDM 1

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2nd international conference on Internet of Things, Communication and Intelligent Technology, IoTCIT 2023

作者： Liang, Zhixun Zhao, Jiaqi Yi, Yunfei Shi, Yunying Fan, Yuanyuan School of Big Data and Computer Hechi University Guangxi Yizhou546300 China

ISBN: (数字)9789819727575

ISBN: (纸本)9789819727568

White LED light source is used in RGB visible light communication (VLC) technology, composed of red, green and blue, the three basic colors for data transmission. The transmission rate of RGB VLC technology has been achieved more than 10Gbps, Through improved modulation technology and reception algorithm. However, the spectrum utilization efficiency of RGB visible light communication is low. Weak anti-multipath interference ability and serious nonlinear distortion are also problems. In this paper, Orthogonal frequency division multiplexing (OFDM) technology is used. Through this technology, the data transmission rate and communication quality are improved. And the theory of RGB visible light communication technology based on OFDM is analyzed, a communication model is established, and the frequency utilization efficiency and anti-multipath interference capability of OFDM are verified by MATLAB simulation. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Visible light communication

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Research on commanding ability evaluation of primary emergency rescue commander

Research on commanding ability evaluation of primary emergen...

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international conference on Economic Management and Model Engineering (ICEMME)

作者： Tang Huaqing Chinese People’s Police University Langfang China

ISBN: (纸本)9781728191447;9781728191454

Through the research on principle of emergency rescue tactical, commanding procedure and quality of emergency rescue commanders, the evaluation index system of primary commander's command ability is obtained on the basis of principle of evaluating commanders' command ability, which mainly includes receiving emergency order and rushing to disaster site, safety protection, command coordination, rescue operation, comprehensive support, etc. Using fuzzy comprehensive evaluation method, the weight of each index system is determined scientifically, and the fuzzy comprehensive evaluation model is established. In order to ensure the rationality of the final result, the influence of experts' authority and experience on the index weight is modified, and the model is verified by examples. The result shows that the method can comprehensively reflect the command ability of primary firefighters, and has certain guiding significance for improving the quality of primary commanders of rescue teams and improving the overall firefighting and rescue capability of emergency rescue teams.

关键词： Training Economics computer simulation Computational modeling Stability criteria Decision making Dispatching

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