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Construction of accounting big data analysis platform driven by cloud computing technology 7

Construction of accounting big data analysis platform driven...

引用

7th international conference on Mechatronics and Intelligent Robotics, ICMIR 2023

作者： Yan, Xiaoyun Guangdong University of Science and Technology Guangdong523083 China

ISBN: (数字)9781510668089

ISBN: (纸本)9781510668072

In the current market competition, if enterprises want to occupy a favorable position, they must use information technology tools, give full play to their own production and management advantages, improve market competitiveness and resist risks. the emergence of cloud computing brings hope to the current financial management information construction model. In this paper, an accounting big data analysis platform driven by cloud computing technology is established, and an accounting big data cloud computing task scheduling algorithm based on improved FA(firefly algorithm) is proposed. Aiming at the problem that traditional FA is prone to premature and fall into local optimum, chaotic disturbance strategy is introduced to disturb the part with low target value, and fireflies flying out of the search space are bounced back according to the rebound theory based on real physics in firefly position update, so as to maintain the optimization ability of the population. the research results show that this algorithm can shorten the total execution time of cloud computing tasks by about 21.06%. It is proved that the improved FA has better optimization ability and real-Time performance. © 2023 SPIE. All rights reserved.

关键词： Cloud computing

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ZombieCoin3.0: On the Looming of a Novel Botnet Fortified by Distributed Ledger technology and Internet of things 23

ZombieCoin3.0: On the Looming of a Novel Botnet Fortified by...

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23rd IEEE international conference on High Performance computing and Communications, 7th IEEE international conference on Data Science and Systems, 19th IEEE international conference on Smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Gao, Haoyu Li, Leixiao Lin, Hao Chang, Xiangyang Wan, Jianxiong Li, Jie Zhu, Fangyuan College of Data Science and Application Inner Mongolia University of Technology China Inner Mongolia Autonomous Reg. Eng. and Technol. Research Center of Big Data Based Software Service China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665494571

P2P Botnet is famous for the resilience against termination. However, its dependence on Neighbor List (NL) makes it susceptible to infiltration and poison, also leading to a dearth of adequate protection of Botmaster's identity. So as to overcome these weaknesses, the novel botnet infrastructure combined with blockchain emerges. But due to some flaws such like high latency and expensive transactions fees on blockchain, these new schemes can't satisfy the need of constructing hyper large-scale botnet in practice. We propose ZombieCoin3.0, a Botnet underlying overlay leveraging IoT devices to be maintainers and integrated with Distributed Ledger technology (DLT), which is able to deploy bots fully on blockchain. And it is versatile for file transfer, data feedback and other command and control scenarios that many contemporaries are impotent to cope with. Our proposal eliminates the P2P botnets' dependence on NL and the bottlenecks that other blockchain combined botnets have. Experiments' results authenticated that the effectiveness of our proposal as well as low latency of communication and nearly zero overhead of cost other comparatives unable to attain are achieved. © 2021 IEEE.

关键词： Costs Distributed ledger Botnet Blockchains Proposals Internet of things Low latency communication

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Performance Comparison of Polygonal Loop Frequency Selective Surfaces for Band Stop Applications 7

Performance Comparison of Polygonal Loop Frequency Selective...

引用

7th IEEE international conference for Convergence in technology, I2CT 2022

作者： Bansal, Km. Sonal Joshi, Abhishek Ajay Kumar Garg Engineering College Department of Electronics and Communication Engineering UP Ghaziabad India

ISBN: (纸本)9781665421683

this paper investigates the performance of different polygon geometries of loop frequency selective surfaces (FSS). Various polygon shapes such as triangle, pentagon, hexagon, heptagon, octagon, nonagon, decagon, and circle of FSS, are analyzed and compared using results obtained from software-based simulation. It is observed that the bandwidth of band-stop response and band-stop frequency improves as the number of edges increases in the polygon. the paper exhibits that the bandwidth of the band stop response can be tuned by choosing a suitable polygonal design of FSS. © 2022 IEEE.

关键词： Frequency selective surfaces

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GRDNet: A Lightweight Railway Foreign Object Intrusion Detection Algorithm 7

GRDNet: A Lightweight Railway Foreign Object Intrusion Detec...

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7th international conference on Advanced Algorithms and Control engineering, ICAACE 2024

作者： Wang, Zhaonan Wei, Lin Meng, Caixia Shi, Lei Gao, Yufei Wang, Qingxian School Of Cyber Science And Engineering Zhengzhou University Zhengzhou China School Of Computer And Artificial Intelligence Zhengzhou University Zhengzhou China Zhengzhou Police College Department Of Image And Network Investigation Technology Zhengzhou China

ISBN: (纸本)9798350361445

Railway intrusion detection using convolutional neural networks has significant results, but it requires a large amount of data and arithmetic power to train and deploy neural network models, and it is still a challenge to improve detection accuracy under limited computational resources. Based on this problem, this paper proposes a lightweight railway foreign object intrusion detection algorithm: GRDNet, which firstly adopts a lightweight backbone network GhostNetV2, and makes use of the decoupled fully connected attention mechanism to aggregate local and long-distance information, which significantly reduces the number of parameters and computation while maintaining the detection performance. Next, a deep feature extractor, RSPPFCSPC, is proposed to reduce the computational effort by decreasing the number of channels in the feature map while maintaining the diversity and effectiveness of the features. Finally, a knowledge distillation algorithm is used to improve the accuracy of foreign object localization and classification and reduce the leakage rate of the model. Experiments show that the proposed method is superior to the state-of-the-art work of each comparison. © 2024 IEEE.

关键词： Object detection

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Sentimental Analysis on Twitter Data using Supervised Algorithms 7

Sentimental Analysis on Twitter Data using Supervised Algori...

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7th international conference on computing Methodologies and Communication, ICCMC 2023

作者： Susmitha, C. Nikhil, L. Akhil, L. Kavitha, M. Reddy, V. Surya Narayana Shailaja, K. Department of CSE Koneru Lakshmaiah Education Foundation AP Vaddeswaram India Department of CSE VNR Vignana Jyothi Institute of Engineering and Technology Hyderabad India Department of CSE Vasavi College of Engineering Ibrahimbag Hyderabad India

ISBN: (纸本)9781665464086

Sentimental Analytics is the phenomenon used to show the feelings of different people, emotions, opinions. It is also referred as the opinion meaning, which identifies the emotional tone behind a body of text the Mechanism gives whether the result is positive, negative, or neutral. It gives finer results, to keep track of users, and tells whether the tweet is uplifted or down lifted by the user's content. Machine learning can be analyzed by using various analysis algorithms to provide a precise value. Machine learning algorithms play a major role in various domains, and one of them includes data analysis. In this work, machine learning techniques are used to predict the Twitter analysis. Machine Learning (ML) algorithms such as Support Vector Machine (SVM), Logistic Regression (LR), and Naive Bayes (NB) algorithm are used for implementation. the performance of the implemented algorithm is analyzed in the terms of accuracy, precision, recall, F1-score on the tweets taken from the social media. © 2023 IEEE.

关键词： Support vector machines

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Research on the Co-Creation Construction Model of Digital Education Resources in Internet+ Era 23

Research on the Co-Creation Construction Model of Digital Ed...

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7th international conference on Education and Multimedia technology, ICEMT 2023

作者： Chen, Ruxian Li, Xufeng Bian, Buxing Wang, Jie Cai, Ruiqi Zhang, Jing Department of Computer Science Software Engineering Institute of Guangzhou China Wushen Banner High School Nei Monggol China Leshan Normal University Teaching Departmen China Institute of Computing Science and Technology Guangzhou University China

ISBN: (纸本)9798400709142

With the development of Internet+, an open and innovative educational ecosystem is forming. the combination of Internet and education can greatly promote the integration and utilization of high-quality education resources. Firstly, we analyze the main problems in the construction of digital education resources. Secondly, we explore the co-creation construction model of high-quality mathematical resources among government, enterprises and schools, including the main elements of the model, the connection between the elements and the related mechanism support. Finally, it takes NetPad as an example to carry out practical research on the co-creation of digital education resource in the field of basic education, improving the construction and service level of high-quality digital education resources. © 2023 ACM.

关键词： E-learning

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the Parallelized Cuckoo Filter for Cold Data Representation 23

The Parallelized Cuckoo Filter for Cold Data Representation

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作者： Sun, Bowen Luo, Lailong Li, Shangsen Chen, Yingwen Guo, Deke College of Computer National University of Defense Technology China National University of Defense Technology Science and Technology on Information Systems Engineering Laboratory China College of Computer National University of Defense Technology National Lab for Parallel and Distributed Processing China

ISBN: (纸本)9781665494571

Cold data contributes a large portion of the big data today and is usually stored in secondary storage. Various sketch data structures are implemented to represent the stored elements and provide constant-time membership queries. Considering the large volume and infrequent access of cold data, we envision three rationales of cold data representation: 1) parallelized insertion, 2) accurate representation, and 3) constant-time query/deletion. the existing sketches, however, fail to achieve these rationales simultaneously. To this end, we propose a novel sketch named Parallelized cuckoo Filter (PCF) in this paper. PCF divides the standard cuckoo filter into multiple homogenous segments. An additional hash function is introduced to assign an element to a segment. the element will be inserted into the selected segment. With such a design, element insertions in PCF can be naturally parallelized. Besides, as a variant of the cuckoo filter, PCF naturally realizes the accurate representation and constant-time query/deletion requirements. Comprehensive experiments further indicate that PCF achieves the three rationales simultaneously. © 2021 IEEE.

关键词： Hash functions Smart cities Big Data Data structures Standards

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Expeditious Diagnosis of Cerebral Aneurysm on MR Brain Angiogram Images Utilizing Soft computing Techniques 7

Expeditious Diagnosis of Cerebral Aneurysm on MR Brain Angio...

引用

7th international conference on Inventive Computation Technologies, ICICT 2024

作者： Anjaneya, L.H. Maheswari, K. Revathi, N. Siva, K.P. Soudagar, Manzoore Elahi M. Dhanraj, Joshuva Arockia Bapuji Institute of Engineering And Technology Department of Electrical And Electronics Engineering Karnataka Davangere577004 India Cmr Technical Campus Department of Computer Science And Engineering Hyderabad Telangana Kandlakoya501401 India Panimalar Engineering College Department of Electronics And Communication Engineering Tamil Nadu Chennai600123 India Sri Eshwar College of Engineering Department of Computer Science And Business Systems Tamil Nadu Coimbatore641202 India Saveetha Institute of Medical And Techinical Sciences Saveetha School of Engineering Department of Vlsi Microelectronics Tamil Nadu Chennai602105 India Department of Mechatronics Engineering Chennai Tamil Nadu Padur603103 India

ISBN: (纸本)9798350359299

It is always a challenging task for radiologists to detect Cerebral Aneurysms (CA). Unenhanced magnetic resonance angiography (MRA) has become a popular screening tool because of its non-invasiveness, lack of contrast, and ionizing radiation. Because of its screening role, MRA requires a high recognition rate. this paper presents Machine Learning (ML) methods for detecting CA in MRA data. MRA scans of normal and aneurysms are collected and evaluated. this research study is divided into two sections: segmentation and classification. First, K-Means Clustering (KMC) is used for aneurysm segmentation from MR images. Second, image classification is done. For that, the appropriate features are retrieved using feature extraction and selection. then Gray Level Run Length Matrix (GLRLM) is used for feature extraction and the Genetic Algorithm (GA) for feature selection. the GLRLM and GA features are provided independently to the ML models for training and testing. the ML models used in the research work are Artificial Neural Networks (ANN) and Modified Fuzzy C-Means (MFCM). the metrics are employed to evaluate the GLRM and GA features with ANN and MFCM. the combination of GA features with ANN produces the best results when compared to other combinations. the GA with ANN obtains an outstanding 98.33% accuracy, 100% specificity and precision, 96.67% sensitivity, and 98.31% F1 score. © 2024 IEEE.

关键词： Genetic algorithms

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Predictive Insight of Global Warming-A Sustainable Control System 7

Predictive Insight of Global Warming-A Sustainable Control S...

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2023 7th international conference On computing, Communication, Control And Automation, ICCUBEA 2023

作者： Roy, Soumit Mahmudi, Hafizullah Das, Rik Dewan, Jaya H. thepade, Sudeep D. Analytics Presales and Solution PracticeLead Jade Global Chicago United States Data Management and Analytics Kamyab Its Kabul Afghanistan Association for Computing Machinery Ranchi India Pimpri Chinchwad College of Engineering Department of Information Technology Pune India Pimpri Chinchwad College of Engineering Computer Engineering Department Pune India

ISBN: (纸本)9798350304268

Global warming is one of the major issues for decades. Implementation of integrated solution to get sustainable control system has significant challenges. Acceptance of the key precautions and maintenance of sustainability became a bottleneck. the consequence of human social activities increases the consumption of fossil fuels as power resources which indirectly increased the concentration of greenhouse gases and water vapor, in the environment. this causes the earth's average surface temperature to increase. Water vapor is responsible for two-thirds of this issue;however, C02 is proven to be the key factor of global warming. the global temperature could have increased to 3.8 o C in case C02 concentration was doubled. the trend and association between rising temperatures and C02 emissions are shown in this work, along with an explanation of the many methods behind ideal mitigation. One of the goals of this research is to identify the issue area and integrate the climatic data. this will assist in obtaining a dependable control system capable of addressing global warming concerns. this paper outlines how data engineering and analytics may be used to regulate global warming and provides an architecture for the Green Warming Model (GWD). therefore, the primary contribution of this study effort is environment preservation using data engineering and machine learning (ML). © 2023 IEEE.

关键词： Data engineering Global warming Green House IPA SARIMAX

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A Case-Based Reasoning Solution for Urban Drinking Water Quality Control 23

A Case-Based Reasoning Solution for Urban Drinking Water Qua...

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作者： Wu, Di Seidu, Razak Wang, Hao Ban, Xiaojuan Norwegian University of Science and Technology Department of Ict and Natural Science Ålesund Norway Norwegian University of Science and Technology Department of Ocean Operations and Civil Engineering Ålesund Norway Norwegian University of Science and Technology Department of Computer Science Gjφvik Norway University of Science and Technology Beijing Department of Computer Science and Technology Beijing China

ISBN: (纸本)9781665494571

the Urban Drinking Water Supply (UDWS) systems play a vital role nowadays to support global city management, especially in the context of the fast growth of urbanization. In Europe, there is a natural conflict between urban population growth and the aging drinking water supply infrastructure. In particular, according to European standards, water should be drinkable from the taps. the requirements from these standards not only bring easement in our modern daily life but also are examining the robustness of the risk warning and control response in the UDWS system. Water quality as the key factor in the urban water supply is by default strictly regulated in the municipality management. Currently, the most common water quality control is relying on periodic tests for various quality indicators. In addition, further processing in the treatment plant, including measures and doses, is relatively fixed and weak to respond to the risk in UDWS. In order to address these problems, we propose a Case-Based Reasoning (CBR) approach for water quality risk control in UDWS systems. First, we build a case-based analysis computational scheme for the risk control in the UDWS system. then we provide our methods in feature selection and similarity evaluation between different cases. Finally, the results of an industrial case study are presented. this case is based on our data collection from the UDWS system in Oslo city in Norway. the discussion and analysis show the feasibility of this approach and practically provide decision support for water treatment actions. © 2021 IEEE.

关键词： Smart cities Sociology Europe Water quality Control systems Cognition Robustness

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