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Autoencoder Integrated Feedforward Neural Network based Intrusion Detection System

Autoencoder Integrated Feedforward Neural Network based Intr...

引用

Advances in Signal Processing, Power, Communication, and computing (ASPCC), IEEE international conference on

作者： Piyush Raj Tushar Prakash Sonu Kumar Ankit Raj Aditya Prakash Mamata P. Wagh Computer Science and Engineering C. V. Raman Global University Bhubaneswar India

ISBN: (数字)9798350355093

ISBN: (纸本)9798350355109

In today’s digital world cyber security is a prominent need. Intrusion Detection system (IDS) is a vital component of cyber security. In this regard, IDS is proposed in this work which combines Autoencoders and Feedforward Neural Network(FNN) to improve security. Autoencoders efficiently extract important features from network datasets, while FNNs are skilled at recognizing complex attack patterns. By merging technologies, proposed model enhances traditional IDSs, boosting their ability to detect new and advanced cyber threats. This comprehensive approach enables to identify subtle changes in attack behaviours, effectively reducing cybersecurity risks. The experimental results confirm that our proposed model outperforms conventional models in terms of overall performance, showing higher detection rates and lower false positive rates. The proposed model is evaluated on the dataset CICIDS 2017. The accuracy of this model is 99.60% on a dataset.

关键词： Computational modeling Autoencoders Merging Intrusion detection Signal processing Feature extraction Boosting Feedforward neural networks pattern recognition Computer crime

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Unveiling Fuzzy Topologies: Innovative Approaches to Topological Structures via Fuzzy Binary Relations

Unveiling Fuzzy Topologies: Innovative Approaches to Topolog...

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Women in computing (InCoWoCo), international conference for

作者： Gnanachandra P Arunthathi C Ananda Priya B Seenivasan M Centre for Research and Postgraduate studies in Mathematics Ayya Nadar Janaki Ammal College (Affliated to Madurai Kamaraj University) Sivakasi India DDE-Mathematics Wings Annamalai University Chidambaram India

ISBN: (数字)9798331518943

ISBN: (纸本)9798331518950

In order to extend classical topology to more flexible and uncertain contexts where membership to sets is not strictly binary, the idea of fuzzy topological spaces is essential. This study presents a novel fuzzy topological structure derived from fuzzy binary relations, offering a broader framework for examining elemental interactions in these kinds of spaces. Fuzzy closure and interior operators that are formed from the binary relations are used to define the new structure. Several examples demonstrate the efficiency and adaptability of this method. An analysis is conducted on the fundamental properties of the resulting fuzzy topology., which include the relationships between the smallest open sets, closure, and interior. Additionally, the study offers important corollaries and theorems that characterize the behavior of these operators and help to clarify the underlying topological structure. These findings provide fresh insights into the study of fuzzy relations and their applications in a variety of domains, including fuzzy logic systems, data analysis, and decision theory, in addition to expanding upon established properties from classical topology.

关键词： Fuzzy logic Uncertain systems Image segmentation Fuzzy sets Fuzzy control Uncertainty Network topology Decision making Topology pattern recognition

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CDE-Net: A semi-supervised nucleus instance segmentation method based on center deviation estimation 22

CDE-Net: A semi-supervised nucleus instance segmentation met...

引用

8th international conference on computing and Artificial Intelligence, ICCAI 2022

作者： Yan, Yi Wang, Da-Han Ye, Haili Zhu, Shunzhi Li, Jianmin School of Computer and Information Engineering Xiamen University of Technology Xiamen361024 China Fujian Key Laboratory of Pattern Recognition and Image Understanding Xiamen361024 China

ISBN: (纸本)9781450396110

Cell nucleus segmentation is an important step in the diagnosis of tumor malignancy. In the case of out-of-focus, the cell nucleus boundary tends to be blurred, which increases the difficulty of cell segmentation and marking. Therefore, in the case of marking only some core instances, it is very important to realize the segmentation of core instances. In this paper, we propose a semi-supervised nucleus instance segmentation method based on anchor bias prediction that is achieved by our proposed center deviation estimation network (CDE-Net). By introducing the CDE branch to predict the offset degree of the anchor frame, and weighting the confidence of the anchor frame, more accurate prediction results can be obtained. The model adopts the semi-supervised training method to progressively learn the CDE-Net model, which alleviates the problem of imbalance between positive and negative samples caused by only marking part of the nuclear samples. The experimental results show that CDE-Net is superior to Mask R-CNN in many evaluation indicators, and achieves SOTA on the partially labelled MoNuSeg data set. © 2022 Association for computing Machinery. All rights reserved.

关键词： Diagnosis

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Determination of pattern recognition Problems based on a Pythagorean Fuzzy Correlation Measure from Statistical Viewpoint 13

Determination of Pattern Recognition Problems based on a Pyt...

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13th international conference on Advanced Computational Intelligence (ICACI)

作者： Ejegwa, Paul Augustine Feng, Yuming Wen, Shiping Zhang, Wei Chongqing Three Gorges Univ Key Lab Intelligent Informat Proc & Control Chongqing 404100 Peoples R China Chongqing Three Gorges Univ Sch Comp Sci & Engn Chongqing 404100 Peoples R China Univ Technol Sydney Australian AI Inst Ultimo NSW 2007 Australia Chongqing Three Gorges Univ Sch Three Gorges Artificial Intelligence Chongqing 404100 Peoples R China Univ Agr Dept Math Stat Comp Sci PMB 2373 Makurdi Nigeria

ISBN: (纸本)9781665412544

By considering all the three parameters describing Pythagorean fuzzy set, we introduce a new technique of computing correlation coefficient between Pythagorean fuzzy sets from statistical perspective. The correlation coefficient value obtain via this technique shows strength of correlation between the Pythagorean fuzzy sets and indicates whether the Pythagorean fuzzy sets under consideration are related negatively or positively in contrast to other existing correlation coefficient approaches in Pythagorean fuzzy context, which only assess the strength of relationship. Certain numerical examples are considered to ascertain the authenticity of this method over similar techniques studied in intuitionistic/Pythagorean fuzzy contexts. Some pattern recognition problems are resolved with the aid of the new technique. For higher productivity sake, this technique could be approached from an object-oriented perspective.

关键词： correlation coefficient intuitionistic fuzzy set Pythagorean fuzzy set pattern recognition

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The New Answer to Drug Discovery: Quantum Machine Learning in Preclinical Drug Development

The New Answer to Drug Discovery: Quantum Machine Learning i...

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pattern recognition and Machine Learning (PRML), IEEE international conference on

作者： Yew Kee Wong Yifan Zhou Yan Shing Liang Haichuan Qiu Yu Xi Wu Bin He Basis International School Guangzhou Guangzhou China

The Research & Development (R&D) phase of drug development Drug discovery and development (D&D) is a complex and costly endeavor, typically requiring six to nine years [1] and four hundred to fourteen hundred million USD [2] for the research and development (R&D) phase alone. To transform this process, we propose a novel concept that combines Quantum-based Machine Learning network (QML) and Quantum computing Simulation (QS) to expedite the R&D phase to three to six months and reduce the cost to merely fifty to eighty thousand USD. Our approach takes as inputs the target protein/gene structure and the primary assay [3]. For Hit Generation [3], the QML network generates potential hits [4] based on the molecular structure of the target protein, while the QS filters molecules from the primary assay according to their reaction and binding efficacy with the target protein. Then, for Lead Optimization [3], the resulting molecules from QML and QS are compared, and the ones that are common to both processes are subjected to dozens of molecular variations, while others are only modified slightly. Finally, all optimized molecules undergo multiple rounds of QS filtering with high standards for reaction efficacy and safety, producing a few dozen pre-clinical-trial-ready drugs. Our concept of QML and QS integration can also be applied to other fields, such as agricultural research, genetic editing, and aerospace engineering. Keywords: Quantum Computer, Hit to Lead, Lead Optimization Simulation, Machine Learning.

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Research on the Detection of Abnormal Cervical Cells Based on Improved YOLOv7

Research on the Detection of Abnormal Cervical Cells Based o...

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6th international conference on Intelligent computing and Signal Processing (ICSP)

作者： Xuewei Wang Shuang Yuan Lidong Yang Dawei Niu Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing Inner Mongolia University of Science and Technology School of Digtial and Intelligence Industry Inner Mongolia China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

Cervical cytologic screening is clinically important for the prevention and diagnosis of cervical cancer. Aiming at the many challenges in the detection of abnormal cervical cells, including the difficult detection of small targets of abnormal cervical cells, complex backgrounds, and uneven cell morphology, a detection algorithm for abnormal cervical cells based on improved YOLOv7 was proposed. The algorithm utilizes Deformable Convolutional Networks v2 (DCNv2) that adaptively de-tunes the scale and receptive field size to more effectively cope with the complexity and diversity of cervical cell images. The experimental results show that the improved YOLOv7 algorithm mAP achieves 57.26%, up to 73.88% accuracy, and 46.90% recall on the cervical abnormal cell dataset. Compared with the benchmark model, they increased by 4.07%, 3.39%, and 5.69%, respectively.

关键词： Accuracy Sensitivity Shape Prevention and mitigation Signal processing algorithms Signal processing Feature extraction Convolutional neural networks Detection algorithms Cervical cancer

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Assessment of Grid Integration with renewable Energy sources and Electric Vehicle

Assessment of Grid Integration with renewable Energy sources...

引用

Applied Artificial Intelligence and computing (ICAAIC), international conference on

作者： P. Sivakumar M. Kaleeswari A. Aswini S. Sabapathi P. Manikandan N. Vijayakumar Department of Electrical and Electronics Engineering Rajalakshmi Engineering College Chennai India Department of Electrical and Electronics Engineering M.P. Nachimuthu M. Jaganathan Engineering College Erode

ISBN: (数字)9798350375190

ISBN: (纸本)9798350375206

To maintain a healthy world, the emission of Greenhouse Gases (GHG) should be minimized. Due to the overall economic crisis in the last few years, the fuel cost for running an automobile, power generation, and operating industries become more complicated. To overcome these issues, new technologies should be adopted. Utilizing Electric Vehicle is one of the most important ways to minimize such effects for increasing overall global warming. When such EV Charging S tations (EVCS) are integrated with the grid, it affects most of the parameters and leads to difficult problems like overvoltage, overloading, harmonics, and instability. This research study deals with analyzing the behavior of such EVCS with the grid and renewable energy integrated system, the IEEE14 bus system with the effective utilization of Electrical Transient and Analysis Program (ETAP).

关键词： Renewable energy sources Power system stability Power system harmonics Prediction algorithms Stability analysis pattern recognition Transient analysis Climate change Greenhouse gases Carbon emissions Electric vehicles Electric vehicle charging PI control Power grids

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Credit Card Fraud Detection Using Symbolic Aggregate Approximation

Credit Card Fraud Detection Using Symbolic Aggregate Approxi...

引用

Blockchain computing and Applications (BCCA), international conference on

作者： Snit D. Zerea Belsabel T. Woldemichael Feven B. Araya Richard A. Ikuesan College of Technological Innovation Zayed University Abu Dhabi UAE

ISBN: (数字)9798350351538

ISBN: (纸本)9798350351545

In the current digital age, credit card fraud is a cybercrime that costs billions of dollars every year through fraudulent transactions. This study aims to identify fraudulent credit card transactions using Symbolic Aggregate Approximation (SAX) and anomaly discovery through motifs and discords. To do this, credit card data is used as time series data and then divided into equal-length segments. Each segment is then converted into a symbolic representation using a pre-defined threshold. A web-based interface is further developed to load a collection of credit card transaction data, based on the proposed SAX method. The preliminary results show that the proposed approach is capable of identifying fraudulent transactions within a set of transactions. By integrating this approach with other fraud detection mechanisms, a near real-time fraud detection process can be developed. This approach therefore provides a potential for context-independent fraud detection which is a major challenge in the fraud detection domain.

关键词： Machine learning algorithms Costs Aggregates Time series analysis Credit cards Information age Real-time systems Fraud pattern recognition Security

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Indian Alphabets and Digits Sign recognition Using Pretrained Model 1

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5th international conference on Smart computing and Informatics, SCI 2021

作者： Mistree, Kinjal Thakor, Devendra Bhatt, Brijesh C. G. Patel Institute of Technology Uka Tarsadia University Bardoli India Dharmsinh Desai Institute of Technology Dharmsinh Desai University Naidad India

ISBN: (数字)9789811697050

ISBN: (纸本)9789811697043

Deaf community uses sign language as their natural language and also as their first language. Indian sign language (ISL) is primary language for deaf people of India, which they use for interacting with other people. Also, not all deaf are aware with reading and writing which makes communication even harder for them. The automated sign language recognition system comes as necessity when human interpreters are not available in urgent situations. In India, local sign languages are used to ease communication among deaf, which lacks the use of standardized sign language. It is important to note that each country has its own unique sign language. Indian Sign Language Research and Training Center (ISLRTC) has launched the first ISL dictionary that can be used as national sign language of India. This paper proposes an approach that uses a novel dataset created using signs of alphabets and digits by ISLRTC to recognize images of ISL. Moreover, the approach uses transfer learning that gives good accuracy with limited number of ISL signs. We have achieved 97.26% accuracy using MobileNet as pretrained model using our approach on our own dataset. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： pattern recognition

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Image Texture Analysis with Local Binary patterns: A Review 3

Image Texture Analysis with Local Binary Patterns: A Review

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3rd IEEE international Virtual conference on Innovations in Power and Advanced computing Technologies, i-PACT 2021

作者： Srilatha, N. Reddy, V. Lokeswara JNT University Anantapauramu CSE Department Anantapuramu India KSRM College of Engineering CSE Department Kadapa India

ISBN: (纸本)9781665426916

Local binary pattern (LBP) and its changed forms have been widely used in the many applications of different fields such as image processing, computer vision, model recognition and texture analysis etc. In this paper, we did extensive research-based study on LBP and its forms. The pros and cons of standalone LBP methods which used in many applications were evaluated in this study. Finally, we interpret based on their defects and focused the gapes of recent forms of LBP model signifier. © 2021 IEEE.

关键词： Local binary pattern

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