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2021 International Conference on Artificial Intelligence, Big data and Algorithms, CAIBDA 2021

作者： Huang, Da Tang, Zheng-Yi Hu, Wen-Yu Wu, Qiang-Zhi Fujian University of Technology College of Computer Science and Mathematics Fujian Provincial Key Laboratory of Big Data Mining and Applications Fuzhou China Fujian University of Technology College of Computer Science and Mathematics Fuzhou China

ISBN: (纸本)9781665424905

At present, there are still some problems about the credible evaluation and management of electric vehicle charging station. In response to such problems, in order to enable more effective evaluation and management of electric vehicle charging stations, and to enable users to obtain a good user experience, this paper proposes a credibility mechanism for electric vehicle charging stations based on a double-layer blockchain. The current credibility mechanisms are all built on the basis of centralization. Once the central server is compromised, it is extremely prone to irreparable situations such as system paralysis. In order to improve the efficiency of consensus in the existing blockchain, this article proposes a method of combining roulette with a consensus mechanism to prevent monopoly, cheating, and improve system efficiency. Through extensive analysis and experimental results, it is proved that the trusted mechanism can well reflect the quality of the charging station nodes, and the addition of roulette can stimulate the positive behavior of each block node. © 2021 IEEE.

关键词： Blockchain

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Implementing and Analyzing Behaviour of ML based Tamil Songs Recommendation System 2

Implementing and Analyzing Behaviour of ML based Tamil Songs...

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2nd International Conference on Sustainable Computing and data Communication Systems, ICSCDS 2023

作者： Garg, Shalini Pooja Chaoudhary, Shailee Lohmor Dixit, Rinku Govil, Nikhil Design and Technology University Mit Art MH Pune India Galgotias University School of Cse Delhi - NCR Gr. Noida India New Delhi Institute of Management Department of Aiml - Data Science New Delhi India Gla University Department of Computer Engineering & Applications U.P. Mathura India

ISBN: (纸本)9781665491990

Music gives listeners a chance to relax, relieve fatigue and connect one culture with another. In such a situation, if the favorite song-music is heard one after another and according to the emotion, it gives a unique and wonderful experience to the listener. It is determined based on the emotion and interest, ratings provided by listeners and search patterns. In this research article, the proposed method presents Tamil songs compilation and recommendation system with the help of these factors. The behavior of this recommendation system is also analyzed in this system. The proposed system is developed in Java programming language by adopting the techniques of Machine Learning. Through this system, listeners have the choice to play category wise songs. As per the listening history and patterns, upcoming songs are predicted to the listeners. This system also provides ratings to each song. This developed application can also be used commercially as it has been validated that the ratings provided by the listeners are in line with IMDb ratings. © 2023 IEEE.

关键词： Recommender systems

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User Behavior Audit System of Real-time Web Log by Spark 3

User Behavior Audit System of Real-time Web Log by Spark

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2021 3rd International Conference on Electronic Engineering and Informatics, EEI 2021

作者： Li, Guonong Hu, Wenyu Chen, Jinbo Ying, Kanghui College of Computer Science and Mathematics Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou Fujian350118 China

With the rapid development of information technology, single sign-on authentication systems have been adopted by organizations to protect their information management systems and other service platforms. With the single sign-on method, users just log in the authentication systems once to access all the information in systems, which are more convenience, but accompanied by user permissions vulnerabilities and information security risks. Users' browsing behaviors reflect the users' usage habits, purposes, and work contents. Risks of information leakage can be reduced by auditing the users' browsing behaviors. After analyzing the web logs of several service systems, we designed a user behavior audit system based on the Spark computing engine, which takes the real-time web log file as the data set. A possible preprocessing method for real-time web log data stream is proposed to extract users' web session data. we used the Spark computing engine and the corresponding analysis to mine users' behavior patterns. The online real-time detection and offline detection of user behavior are realized, and users are divided into three levels: normal, abnormal, and risky. The system administrators or auditors can view the calculation results of each stage online, manage the parameter configuration of the algorithm online, and adjust the user's access right in real-time. © Published under licence by IOP Publishing Ltd.

关键词： Authentication

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Novel machine learning investigation for Buongiorno fluidic model with Sutterby nanomaterial

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Tribology International 2024年 199卷

作者： Khan, Maryam Pervaiz Chang, Chuan-Yu Raja, Muhammad Asif Zahoor Shoaib, Muhammad Department of Computer Science and Information Engineering Graduate School of Engineering Science and Technology National Yunlin University of Science and Technology Yunlin 64002 Taiwan Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin 64002 Taiwan Department of Data Science and AI Applications Graduate School of Engineering Science and Technology National Yunlin University of Science and Technology Yunlin 64002 Taiwan AI center Yuan Ze University Taoyuan320 Taiwan

The nanomaterials are frequently employed in a variety of heat transfer applications arising in energy generation, engine cooling, extrusion procedures, heat exchanger, thermos-chemical systems, manufacturing structures, powered plants etc. Experts and researchers in these fields often encounter such materials, leading to discernible impacts on velocity, temperature and concentration profiles. The objective of this study is to represent the mathematical structures for Sutterby nanomaterial fluidic model involving porous medium BFM-SNM using nonlinear autoregressive exogeneous networks backpropagated with Levenberg-Marquardt technique (NARX-LMT). The mathematical design of the model is originally presented by PDEs, which are converted into ODEs system through suitable modifications with alternative transformation incorporating numbers, i.e., Deborah, Prandtl and Reynold, as well as parameters, i.e., magnetic thermophoresis, radiation and temperature. The synthetic data is produced numerically by simulating Adams numerical method for BFM-SNM and the supervised computing paradigm of NARX-LMT is applied to the obtained datasets, and the results of NARX-LMT consistently align with numerical observations for each variant of the presented model, exhibiting negligible errors. The NARX-LMT performance on exhaustive experimentation is effectively illustrated through iterative convergence curves on mean squared error, control metrics of the optimization, distribution of error on histograms and regression outputs for Sutterby nanomaterial fluidic model. © 2024 Elsevier Ltd

关键词： Ordinary differential equations

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Incidence Coloring of Product Graphs of Paths

Incidence Coloring of Product Graphs of Paths

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2021 International Conference on Big data Analysis and computer science, BDACS 2021

作者： Peng, Lizhen Tian, Shuangliang Lu, Qiqi School of Mathematics and Computer Science Northwest for Minzu University Key Laboratory of Streaming Data Computing Technologies and Applications Northwest Minzu University Lanzhou China

ISBN: (纸本)9781665425612

Incidence coloring of graph refers to coloring of its all incidences in which neighborly incidences are assigned different colors. The smallest number of colors in an incidence coloring is incidence coloring number of graph. In this paper, structural coloring method and disproof method are used. we study the incidence coloring of direct products, semi-strong products and strong products of paths of different orders, and obtain the exact values of the incidence coloring numbers. The incidence coloring number of the direct product and the strong product of a path is the maximunm degree plus one. © 2021 IEEE.

关键词： Coloring

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Enhanced Residual U-Net with Attention for Optic Disc and Cup Segmentation in Fundus Images 1st

Enhanced Residual U-Net with Attention for Optic Disc and...

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1st International Conference on Computation of Artificial Intelligence and Machine Learning, ICCAIML 2024

作者： Kamath, Ritesh V. Kedari, Bhavana Girisha, S. Savitha, G. Shreesha, S. Department of Data Science and Computer Applications Manipal Institute of Technology Manipal Academy of Higher Education Manipal India Department of Information and Communication Technology Manipal Institute of Technology Manipal Academy of Higher Education Manipal India

ISBN: (纸本)9783031714832

Glaucoma, a progressive visual disease, damages the optic nerve, potentially resulting in irreversible vision loss. Effective treatment plans and prompt diagnosis are essential for positive patient outcomes. The principal glaucoma-related indication typically revolves around an odd ratio between the diameters of the optic cup and disc. In this regard, fundus images are analyzed for diagnosis of glaucoma. However, image quality, similar characteristics across classes, class imbalance issues, uneven shapes of optic disc and curves, and other factors make correct segmentation of optic disc and curve difficult from fundus images. To address these issues, the work proposes an enhanced Residual U-Net architecture capable of semantically segmenting the optic disc and cup from retinal fundus images. The proposed model has an Attention Module that can effectively extract the necessary feature map for segmentation from the input images. This improves the model’s capacity to pick out important features and eliminate extraneous noise. Using a publicly available dataset, the study analyses the efficacy of the proposed model using both quantitative and qualitative measures. The effectiveness of the model is examined in relation to various loss functions. To emphasize the significance of the suggested model, a comparative analysis between the proposed and the traditional model is also carried out. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Patient treatment

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The acyclic coloring of the Direct product and Semi-strong product of special graphs

The acyclic coloring of the Direct product and Semi-strong p...

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2021 International Conference on Big data Analysis and computer science, BDACS 2021

作者： Lu, Qiqi Tian, Shuangliang Peng, Lizhen Northwest for Minzu University Key Laboratory of Streaming Data Computing Technologies and Applications Northwest Minzu University School of Mathematics and Computer Science Lanzhou China

ISBN: (纸本)9781665425612

An acyclic coloring of a graph is a proper vertex coloring without dichromatic cycles. The acyclic chromatic number of G, denoted a(G), is the minimum number of colors required for acyclic coloring of a graph G. We study the acyclic coloring of the direct product, semi-strong product of paths and stars, and the corresponding acyclic chromatic number are determined. © 2021 IEEE.

关键词： Coloring

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Proper lucky number of product graph of path

Proper lucky number of product graph of path

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2021 International Conference on Big data Analysis and computer science, BDACS 2021

作者： An, Zhuomo Tian, Shuangliang Jin, Cai Northwest for Minzu University Key Laboratory of Streaming Data Computing Technologies and Applications Northwest Minzu University School of Mathematics and Computer Science Lanzhou China

The proper lucky label is based on the lucky label to make the color sum of any two adjacent vertices are different. In this paper we determined the proper lucky number of cartesian product, direct product and semi-pr... 详细信息

ISBN: (纸本)9781665425612

关键词： Set theory

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Short-term household load forecasting model based on variational mode decomposition and gated recurrent unit with attention mechanism

Journal of Network Intelligence

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Journal of Network Intelligence 2021年第1期6卷 143-153页

作者： Lin, Fu Liu, Shi-Jian Chao, Han-Chieh Pan, Jeng-Shyang College of Computer Science and Mathematics Fujian University of Technology Fuzhou350118 China Department of Electrical Engineering National Dong Hwa University Hualien Taiwan Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou350118 China College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China

The household load is an important part of the load. Accurate short-term household load forecasting is of great help to issues such as power price formulation, demand response, or power transmission. This paper proposed a forecasting model based on Variational Mode Decomposition (VMD) and Gated Recurrent Unit (GRU) combined with self-attention mechanism (SAM) and attention mechanism (AM) for short-term household load forecasting. First, we use VMD to decompose household electricity load data, extract sub-sequences with strong periodic information, and reorganize the original data sets with sub-sequences and data pre-processed. The new data sets contain more abundant information. Secondly, GRU combined with SAM and AM forecasting model for learning and training to obtain results. Finally, RMSE and MAPE evaluation functions are used for method evaluation to verify the superiority of the proposed scheme. The RMSE and MAPE of the proposed method are 0.193 kW and 15.567%, respectively, which are more favorable than traditional GRU. © 2021, Taiwan Ubiquitous Information. All rights reserved.

关键词： Variational mode decomposition

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AIML for Road Accident Analysis 4

AIML for Road Accident Analysis

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4th International Conference on Advancement in Electronics and Communication Engineering, AECE 2024

作者： Rathore, Saurabh Pratap Singh Sanitha, P.C. Varshney, Manoj Verma, Anupama Vashisht, Manisha Saharan, Aaryan Icapsr Management & Research New Delhi India Dhanalakshmi Srinivasan University Dept. of Ai and Data Science Coimbatore India Mangalayatan University Dept. of Computer Engineering and Applications Aligarh India Usha Martin University Dept. of Business Management Ranchi India Lingayas Vidyapeeth University Dept. of Cse Faridabad India Chandigarh University Dept. of Cse Chandigarh India

ISBN: (纸本)9798350364729

Road traffic accidents pose a significant threat to both developed and developing nations, prompting global efforts to enhance road safety. With cars and drivers on the roads, pedestrians also face risks, often becoming innocent victims of accidents. Various factors contribute to road accidents, including driving under the influence, weather conditions, speed, road type, light conditions, road surface, and design. These accidents can cause severe, sometimes unseen injuries with lasting health implications. This study aims to explore road accidents in India using the random forest classifier algorithm and machine learning techniques. © 2024 IEEE.

关键词： Highway accidents

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