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27th International Conference on Soft Computing and Measurements, SCM 2024

作者： Korytov, Pavel V. Kholod, Ivan I. Gribetskiy, Yan Yu. Andreeva, Ekaterina A. Saint Petersburg Electrotechnical University 'LETI' Faculty of Computer Science and Technology Department of Computer Science and Engineering Saint-Petersburg Russia Saint Petersburg Electrotechnical University 'LETI' Faculty of Computer Science and Technology Department of Information Systems Saint-Petersburg Russia

ISBN: (纸本)9798350363708

The task of identifying key skills from job vacancies descriptions is considered in the article. The source data consists of vacancy texts from the 'Jobs in Russia' portal, in which skill-related entities were manually annotated. Keyword extraction methods (YAKE, PositionRank and WikiNEuRal, KBIR-InSpec), and a named entity recognition model trained on the source data are compared. © 2024 IEEE.

关键词： Extraction

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Enhancing handwritten text feature extraction through key point detection and graph representation

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Soft Computing 2024年第21期28卷 12977-12990页

作者： Rahman, Atta Ur Alahmadi, Tahani Jaser Alsenani, Yousef S. Ali, Sania Faculty of Computer Science and Engineering Ghulam Ishaq Khan Institute of Engineering Sciences and Technologies P.O. Box 23460 Topi Pakistan P.O. Box 84428 Riyadh11671 Saudi Arabia Department of Information Systems Faculty of Computing and Information Technology King Abdulaziz University Jeddah21589 Saudi Arabia Department of Computer Science University of Science and Technology Bannu P.O. Box 28100 Khyber Pakhtunkhwa Bannu Pakistan

Handwriting typically consists of a wide range of writing forms with substantial differences in the placements and size of those writing shapes. The arrangement, organization, and spatial association of individual letters, words, and phrases on a written page are all examples of handwritten text structure. This study proposed a novel approach in which a handwritten text structure is primarily transformed into a Cartesian XY-coordinate system while maintaining its shape characteristics. The points on the contour of handwritten text with local maximum bending values are considered hypothetical breakdown points called Key Points (KPs). From the skeletal representation of handwriting, this approach first identifies KPs and their coordinate positions. After that, KPs are transformed into a graph-based representation with vertices and edges. With the use of geometric graphs, this representation attempts to capture the spatial and temporal organization of handwriting. Previous techniques focused on statistical methods, which offer fixed-size descriptions;however, graph-based representations are flexible in size and reveal the relationship between text structure. Graph representations enable the incorporation of contextual information by integrating extra features which improve text accuracy and understanding. The proposed approach is tested for writer identification and verification tasks on four benchmark datasets (CERUG-EN, CVL, Firemaker, and IAM) and one custom-built dataset. The findings demonstrated that the proposed approach obtained state-of-the-art accuracies across all the mentioned datasets. Particularly, it achieved the highest accuracy of 99.75% for identification and 99.81% for verification on the Firemaker dataset. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Feature extraction

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The Future of Online Shopping: Blockchain- Powered E-Commerce Platforms

The Future of Online Shopping: Blockchain- Powered E-Commerc...

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2024 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication, IConSCEPT 2024

作者： Kiran, Ajmeera Sri, Nemani Divya Ayyasamy, Ramesh Kumar Chinnasamy, P. Vellanki, Sreelakshmi Vujwala, Maddula MLR Institute of Technology Department of Computer Science and Engineering Hyderabad India Faculty of Information and Communication Technology Kampar Malaysia School of Computing Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Tamilnadu India

ISBN: (纸本)9798331540685

A cutting-edge online marketplace that uses blockchain technology to transform how we purchase and sell goods and services is known as a blockchain- powered e-commerce platform. This platform uses a decentralized network of computers, also known as nodes, to maintain a transparent and impenetrable record of all transactions instead of depending on a central authority like a bank or a company. A blockchain-based e-commerce platform is a secure, transparent, and trusted online marketplace. It does away with the need for intermediaries, improves security, and provides a world market where users can confidently conduct peer-to-peer transactions. This novel strategy could change how online commerce and shopping are performed. © 2024 IEEE.

关键词： Marketplaces

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Enhanced Feature Selection for Superior Ensemble DDoS Detection in Software-Defined Networks

Enhanced Feature Selection for Superior Ensemble DDoS Detect...

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2024 IEEE International Conference on Future Machine Learning and Data Science, FMLDS 2024

作者： Alashhab, Abdussalam Ahmed Edrah, Aisha Abbas, Maythem K. Alashhab, Mohamed Alngib, Mohamed Daha, Muhammad Yunis Alasmarya Islamic University Faculty of Information Technology Department of Computer Science Zliten Libya Western University Faculty of Engineering Department of Electrical and Computer Engineering London Canada Asia Pacific University of Technology and Innovation School of Computing Kuala Lumpur Malaysia Universiti Sultan Azlan Shah Faculty of Management and Information Technology Kuala Kangsar Malaysia School of Engineering Ulster University Belfast United Kingdom

ISBN: (纸本)9798350391213

Distributed Denial-of-Service (DDoS) attacks disrupt networks by flooding systems with traffic from multiple sources, making real-time detection essential. Integrating Machine Learning (ML) with Software-Defined Networking (SDN) presents a viable solution;however, existing ML methods often face challenges such as high false positive rates and difficulty detecting sophisticated attacks like low-rate and zero-day DDoS attacks due to inadequate training features. As DDoS attack methods evolve, continuous retraining of ML models becomes necessary. This paper introduces a feature selection approach for ensemble classifiers to improve DDoS detection in SDNs. Through correlation analysis and principal component analysis (PCA), the most relevant features are identified, leading to substantial improvements in model performance. Our evaluation, using diverse DDoS datasets, demonstrates that the proposed method achieves near-perfect accuracy, a 100% true positive rate, and minimal error rates, offering a highly effective solution for DDoS detection in SDNs. © 2024 IEEE.

关键词： Zero-day attack

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Statistical Comparison ARIMA Order Performance In Stock Market 7

Statistical Comparison ARIMA Order Performance In Stock Mark...

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7th International Conference on information technology, InCIT 2023

作者： Deemee, Chanatip Ngampis, Kirati Noraset, Thanapon Thaipisutikul, Tipajin Sun, Min-Te Kitchat, Kotcharat Mahidol University Faculty of Information and Communication Technology Thailand National Central University Department of Computer Science and Information Engineering Taiwan

ISBN: (纸本)9798350358698

Stock market forecasting is important for financial decision-making and risk management. Among the various time series models, the Autoregressive (p) Integrated (d) Moving Average (q) (ARIMA) model has been widely adopted for its simplicity and effectiveness in capturing temporal patterns. However, selecting appropriate ARIMA orders remains a crucial and challenging task, impacting the accuracy of predictions. This paper presents a comprehensive statistical comparison of ARIMA order performance in the context of stock market forecasting. We examine the impact of different ARIMA model orders. Our study utilizes historic New York Stock Exchange (NYSE) stock price data. Our findings shed light on the complex interplay between ARIMA parameters and predictive accuracy, offering valuable insights for robust financial forecasting. © 2023 IEEE.

关键词： Financial markets

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Dynamics analysis and cryptographic implementation of a fractional-order memristive cellular neural network model

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Chinese Physics B 2024年第4期33卷 418-433页

作者：周新卫蒋东华 Jean De Dieu Nkapkop Musheer Ahmad Jules Tagne Fossi Nestor Tsafack 吴建华 Department of Information Engineering Gongqing CollegeNanchang UniversityJiujiang 332020China School of Computer Science and Engineering Sun Yat-Sen UniversityGuangzhou 511400China Department of Electrical Engineering and Industrial Computing University Institute of TechnologyDoualaCameroon Department of Computer Engineering Jamia Millia IslamiaNew Delhi 110025India Department of Physics Faculty of ScienceUniversity of YaoundeCameroon Electrical Engineering Department and Industrial Computing of ISTAMA University of DoualaDoualaCameroon

Due to the fact that a memristor with memory properties is an ideal electronic component for implementation of the artificial neural synaptic function,a brand-new tristable locally active memristor model is first proposed in this ***,a novel four-dimensional fractional-order memristive cellular neural network(FO-MCNN)model with hidden attractors is constructed to enhance the engineering feasibility of the original CNN model and its ***,its hardware circuit implementation and complicated dynamic properties are investigated on multi-simulation ***,it is used toward secure communication application *** it as the pseudo-random number generator(PRNG),a new privacy image security scheme is designed based on the adaptive sampling rate compressive sensing(ASR-CS)***,the simulation analysis and comparative experiments manifest that the proposed data encryption scheme possesses strong immunity against various security attack models and satisfactory compression performance.

关键词： cellular neural network memristor hardware circuit compressive sensing privacy data protection

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Current and Voltage Calculations of the 400 kV Transmission Line Using Laboratory Measurements and computer Simulation 33rd

Current and Voltage Calculations of the 400 kV Transmission...

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33rd International Conference on Organization and technology of Maintenance, OTO 2024

作者： Torma, Matej Fekete, Krešimir Kljajić, Ružica Čvek, Kristijan Faculty of Electrical Engineering Computer Science and Information Technology Osijek University of Osijek Kneza Trpimira 2b Osijek31000 Croatia

ISBN: (纸本)9783031805967

In this paper, the current, voltages, as well as active and reactive power of the 400 kV transmission line are calculated using three different methods. The objective of the paper is to demonstrate and compare three different approaches that are based on laboratory measurement, analytical approach, and computer simulation. Measurements are carried out on the laboratory model of a real-life 400 kV transmission line while analytical approach is conducted using a short line model with lumped parameters. As a last approach, the transmission line is modeled in a computer program for power flow analysis, and power flow simulations with the same parameters as for the previous two methods are performed. All three methods are used to calculate voltages, currents, and powers at the beginning and at the end of the transmission line for a few scenarios. Results are compared and discussed in order to demonstrate the possibilities of the applied approaches for the education of power system engineers. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Power transmission lines

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Fractal Measurement of Images Human Brain from MRI

Fractal Measurement of Images Human Brain from MRI

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2024 Cognitive Models and Artificial Intelligence Conference, AICCONF 2024

作者： Anarova, Shahzoda Jabbarov, Jamoliddin Uralova, Iroda Tashkent University of Information Technologies Department of Convergence of digital technologies Computer Engineering Faculty Tashkent Uzbekistan Department of Computer science and technology Intelligent systems and computer technologies Faculty Samarkand State University Samarkand Uzbekistan

ISBN: (纸本)9798400716928

This article is devoted to the determination of the fractal size of the damaged part of the human brain on the basis of images obtained from MRI (magnetic resonance imaging). There are various mathematical methods for determining the size of fractal structures, this article uses two variants of the cell counting method and describes the analysis of errors in determining the fractal size of the damaged part of the human brain. The article shows that the damaged part of the human brain has a fractal structure and that it has a fractal dimension. Fractal measurement has also been used to determine the size of the damaged part of the human brain, unlike common methods. In determining the fractal scale, cases of changes in human body organs were not taken into account. In the article, the determination of the size of the damaged part of the human brain is studied on the basis of mathematical formulas. Two different variants of the special cell counting method were used to calculate the fractal measurements, as well as the corresponding number of experimental results. In addition, these measurements were used to assess the extent to which patients suffered brain damage and to provide information on the practical application of these fractal measurements. © 2024 ACM.

关键词： Magnetic resonance imaging

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The Role of ERNIE Model in Analyzing Hotel Reviews using Chinese Sentiment Analysis

The Role of ERNIE Model in Analyzing Hotel Reviews using Chi...

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2023 International Conference on computer Communication and Informatics, ICCCI 2023

作者： Jie, Lee Hao Ayyasamy, Ramesh Kumar Sangodiah, Anbuselvan Jalil, Norazira Binti A Krishnan, Kesavan Chinnasamy, P. University Tunku Abdul RahmanKampar Faculty of Information and Communication Technology Malaysia Faculty of Computing and Engineering Quest International University Ipoh Malaysia Universiti Malaya Faculty of Computer Science and Information Technology Kuala Lumpur Malaysia MLR Institute of Technology Department of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798350348217

This research aims to find the best deep learning model to do Chinese sentimental analysis. BERT's model may work well in the English language but not work in the Chinese language. English is easier to encode in embedding space, and words are separated by space characters, unlike Chinese words, which do not exist separate by the area. BERT Chinese model work on character level encoding is not enough to make the BERT model adapt to Chinese NLP tasks. The BERT Model and ERNIE models are the current state of art pre-training language models. Word level embeddings and input is needed to improve the BERT model to perform in Chinese Sentiment Analysis. With the motivation to improve the Chinese Sentiment Analysis, this study will explore the role of different models to propose a better version of the ERNIE model. This study will limit the scope to improve Chinese sentiment analysis among different NLP tasks. © 2023 IEEE.

关键词： Sentiment analysis

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Sustainable-Security Assessment Through a Multi Perspective Benchmarking Framework

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computers, Materials & Continua 2022年第6期71卷 6011-6037页

作者： Ahmed Saeed Alfakeeh Abdulmohsen Almalawi Fawaz Jaber Alsolami Yoosef B.Abushark Asif Irshad Khan Adel Aboud SBahaddad Md Mottahir Alam Alka Agrawal Rajeev Kumar Raees Ahmad Khan Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical and Computer Engineering Faculty of EngineeringKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Technology Babasaheb Bhimrao Ambedkar UniversityLucknow-226025Uttar PradeshIndia Department of Computer Science and Engineering Babu Banarasi Das UniversityLucknow-226028Uttar PradeshIndia

The current cyber-attack environment has put even the most protected systems at risk as the hackers are nowmodifying technologies to exploit even the tiniest of weaknesses and infiltrate *** this situation,it’s critical to design and construct software that is both secure and *** security is the most well-defined aspect of health information software systems,it is equally significant to prioritise sustainability because any health information software system will be more effective if it provides both security and sustainability to the customers at the same *** this league,it is crucial to determine those characteristics in the systems that can help in the accurate assessment of the sustainable-security of the health information software during the development *** research work employed the Fuzzy Analytic Network Process(Fuzzy ANP)to estimate the impact of the overall sustainable-security of health information software systems and their characteristics in order to achieve a high level of ***,the study validates the efficacy of the Fuzzy ANP procedure by testing it on five different versions of a health information software system through Fuzzy Technique for Order of Preference by Similarity to Ideal Solutions(Fuzzy TOPSIS).Despite the sensitivity of the health information software systems,this study employedmultiple versions of health information software *** compared with the existing procedures for testing the sustainable-security of health information software systems,the outcomes were conclusive and significantly more *** saving time and resources,the mechanism suggested in this research work aims to establish an outline that software practitioners can follow to enhance the sustainablesecurity of health information software systems.

关键词： Sustainable-security sustainable health information software systems analytic network process fuzzy logic

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