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22nd European Conference on Cyber Warfare and Security, ECCWS 2023

作者： Baror, Stacey Omeleze Ikuesan, Richard Adeyemi Venter, Hein S. DigiForS Research Group University of Pretoria South Africa Computing and Applied Technology Department College of Technological Innovation Zayed University United Arab Emirates

ISBN: (纸本)9781914587702

Developing a generic digital forensic solution in a cloud computing platform that can address the functional requirements of digital forensic stakeholders is a complex process. The solution would require a technology-independent architectural design that addresses the challenges of incident threat identification, triggering, incident threat isolation and investigation. Existing approaches are limited to the functionality that treats these four challenges individually without the due diligence to consider their interoperability. This study proposes a context-independent and technology-neutral architecture to address these issues by developing a digital forensic readiness (DFR) based on a human language communication interaction (HLI) system that could create a cybercrime language as a service (DFClaaS). The functional architectural design of the proposed DFR HLI DFClaaS system comprises microservices, layered and event/component-based architectural patterns on top of cloud architectural patterns. The DFR HLI DFClaaS system integrates flexibility and other quality requirements to separate concerns while accommodating rigid requirements like security and reliability. The developed architecture is essential for any human-centred digital forensic solution. Therefore, integrating the developed architecture presents a reliable baseline for the digital forensic community. © 2023 Curran Associates Inc.. All rights reserved.

关键词： Semantics

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Safety Shielding under Delayed Observation 33

Safety Shielding under Delayed Observation

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33rd International Conference on Automated Planning and Scheduling, ICAPS 2023

作者： Córdoba, Filip Cano Palmisano, Alexander Fränzle, Martin Bloem, Roderick Könighofer, Bettina Institute of Applied Information Processing and Communications Graz University of Technology Austria Dpt. of Computing Science Carl von Ossietzky University of Oldenburg Germany

ISBN: (纸本)1577358813

Agents operating in physical environments need to be able to handle delays in the input and output signals since neither data transmission nor sensing or actuating the environment are instantaneous. Shields are correct-by-construction runtime enforcers that guarantee safe execution by correcting any action that may cause a violation of a formal safety specification. Besides providing safety guarantees, shields should interfere minimally with the agent. Therefore, shields should pick the safe corrective actions in such a way that future interferences are most likely minimized. Current shielding approaches do not consider possible delays in the input signals in their safety analyses. In this paper, we address this issue. We propose synthesis algorithms to compute delay-resilient shields that guarantee safety under worst-case assumptions on the delays of the input signals. We also introduce novel heuristics for deciding between multiple corrective actions, designed to minimize future shield interferences caused by delays. As a further contribution, we present the first integration of shields in a realistic driving simulator. We implemented our delayed shields in the driving simulator CARLA. We shield potentially unsafe autonomous driving agents in different safety-critical scenarios and show the effect of delays on the safety analysis. Copyright © 2023, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Safety engineering

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Secure multimedia communication: advanced asymmetric key authentication with grayscale visual cryptography

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Mathematical Biosciences and Engineering 2024年第3期21卷 4762-4778页

作者： Liu, Tao Vairagar, Shubhangi Adagale, Sushadevi Karthick, T. Karunya, Catherine Esther Blesswin, A. John Mary, G. Selva Tianjin Sino-German University of Applied Sciences Tianjin300350 China Department of Artificial Intelligence and Data Science Dr. D. Y. Patil Institute of Technology Pimpri Pune411018 India Department of Computer Engineering KJEI's Trinity Academy of Engineering Pune411048 India Department of Data Science and Business Systems School of Computing SRM Institute of Science and Technology Kattankulathur603203 India Computer Science and Engineering School of Computing SRM Institute of Science and Technology Kattankulathur603203 India Directorate of Learning and Development SRM Institute of Science and Technology Kattankulathur603203 India

The secure authentication of user data is crucial in various sectors, including digital banking, medical applications and e-governance, especially for images. Secure communication protects against data tampering and forgery, thereby bolstering the foundation for informed decision-making, whether managing traffic, enhancing public safety, or monitoring environmental conditions. Conventional visual cryptographic protocols offer solutions, particularly for color images, though they grapple with challenges such as high computational demands and reliance on multiple cover images. Additionally, they often require third-party authorization to verify the image integrity. On the other hand, visual cryptography offers a streamlined approach. It divides images into shares, where each pixel represented uniquely, thus allowing visual decryption without complex computations. The optimized multi-tiered authentication protocol (OMTAP), which is integrated with the visual sharing scheme (VSS), takes secure image sharing to the next level. It reduces share count, prioritizes image fidelity and transmission security, and introduces the self-verification of decrypted image integrity through asymmetric key matrix generators, thus eliminating external validation. Rigorous testing has confirmed OMTAP's robustness and broad applicability, thereby ensuring that decrypted images maintain their quality with a peak signal-to-noise ratio (PSNR) of 40 dB and full integrity at the receiver's end. © 2024 American Institute of Mathematical Sciences. All rights reserved.

关键词： Medical applications

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Reduced Order Modeling for First Order Hyperbolic Systems with Application to Multiparameter Acoustic Waveform Inversion

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SIAM Journal on Imaging Sciences 2025年第2期18卷 851-880页

作者： Borcea, Liliana Garnier, Josselin Mamonov, Alexander V. Zimmerling, Jorn Applied Physics and Applied Mathematics Columbia University New YorkNY10027 United States CMAP CNRS Ecole Polytechnique Institut Polytechnique de Paris Palaiseau91120 France Department of Mathematics University of Houston HoustonTX77204-3008 United States Department of Information Technology Division of Scientific Computing Uppsala Universitet Uppsala75105 Sweden

Waveform inversion seeks to estimate an inaccessible heterogeneous medium from data gathered by sensors that emit probing signals and measure the generated waves. It is an inverse problem for a second order wave equation or a first order hyperbolic system, with the sensor excitation modeled as a forcing term and the heterogeneous medium described by unknown, spatially variable coefficients. The traditional ``full waveform inversion"" (FWI) formulation estimates the unknown coefficients via minimization of the nonlinear, least squares data fitting objective function. For typical band-limited and high frequency data, this objective function has spurious local minima near and far from the true coefficients. Thus, FWI implemented with gradient based optimization algorithms may fail, even for good initial guesses. Recently, it was shown that it is possible to obtain a better behaved objective function for wave speed estimation, using data driven reduced order models (ROMs) that capture the propagation of pressure waves, governed by the classic second order wave equation. Here we introduce ROMs for vectorial waves, satisfying a general first order hyperbolic system. They are defined via Galerkin projection on the space spanned by the wave snapshots, evaluated on a uniform time grid with appropriately chosen time step. Our ROMs are data driven: They are computed in an efficient and noniterative manner, from the sensor measurements, without knowledge of the medium and the snapshots. The ROM computation applies to any linear waves in lossless and nondispersive media. For the inverse problem we focus attention on acoustic waves in a medium with unknown variable wave speed and density. We show that these can be determined via minimization of an objective function that uses a ROM based approximation of the vectorial wave field inside the inaccessible medium. We assess the performance of our inversion approach with numerical simulations and compare the results to those given by

关键词： Inverse problems

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Effectiveness of Machine Learning Algorithms on Battling Counterfeit Items in E-commerce Marketplaces

Effectiveness of Machine Learning Algorithms on Battling Cou...

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2023 International Research Conference on Smart computing and Systems Engineering, SCSE 2023

作者： Gunawardhana, H.M.K.T. Kumara, B.T.G.S. Rathnayake, Kapila Jayaweera, Prasad M. Faculty of Computing Sabaragamuwa University of Sri Lanka Department of Computing and Information Systems Sri Lanka Faculty of Applied Sciences Sabaragamuwa University of Sri Lanka Department of Physical Sciences and Technology Sri Lanka Faculty of Applied Sciences University of Sri Department of Computer Science Jayawardanapura Sri Lanka

ISBN: (纸本)9798350341454

For e-commerce marketplaces, counterfeit goods are a major issue since they endanger public safety in addition to causing customer unhappiness and revenue loss. Traditional techniques to identify fake goods in online marketplaces take too long and have a narrow reach, hence they are ineffective. Machine learning algorithms have become a potential tool for swiftly and precisely identifying counterfeit goods in recent years. The usefulness of two machine learning algorithms in identifying fake goods in online marketplaces is examined in this research. The study assesses the performance using a sizable dataset of descriptions, title, prices, and seller names from many well-known e-commerce platforms. The study's findings show that machine learning algorithms significantly affect the detection of fake goods in online marketplaces. © 2023 IEEE.

关键词： Electronic commerce

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Sustainable energy management in the AI era: a comprehensive analysis of ML and DL approaches

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computing 2025年第6期107卷 1-64页

作者： Javed, Haseeb Eid, Fatma El-Sappagh, Shaker Abuhmed, Tamer Department of Computer Science and Engineering College of Computing and Informatics Sungkyunkwan University Suwon Korea Republic of Technology Management Stony Brook University NY11794 United States Applied Artificial Intelligence College of Computing and Informatics Sungkyunkwan University Suwon Korea Republic of Faculty of Computer Science and Engineering Galala University Suez435611 Egypt Information Systems Department Faculty of Computers and Artificial Intelligence Benha University Banha13518 Egypt

This study comprehensively analyzes the application of innovative deep learning (DL) and machine learning (ML) techniques in smart energy management systems (EMSs), with an emphasis on load forecasting, demand response, and the development of smart energy sectors. The application of various ML and DL models were examined in over 200 studies from 2014 to 2024 in an electrical network's EMS to highlight the key benefits and advances made by each technology for the sustainable management systems in energy sector. The findings emphasize DL and ML models’ enhanced precision and predictive capabilities in load forecasting, their efficacy in enabling efficient demand response mechanisms, and their significance in supporting the development of smart energy sectors. Furthermore, recommendations are made based on the survey results to assist in incorporating these techniques into EMS frameworks, such as investment in data infrastructure, model training and validation, and collaboration between researchers, industry experts, and policymakers. The study also discusses the limitations identified in the literature, such as limited real-world implementations, challenges regarding quality and data availability, and the need for enhanced ML and DL model interpretability. Addressing these limitations can assist in increasing the application and efficacy of ML and DL techniques in EMSs, enabling a more efficient and sustainable energy landscape. Finally, this study facilitates researchers' exploration of ML and DL in energy management, highlighting relevant limitations, strengths, and alternative approaches associated with sustainable energy management. It also indicates potential future research directions for further investigation. © The Author(s) 2025.

关键词： Power management (telecommunication)

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Optimal Deep Convolution Neural Network for Cervical Cancer Diagnosis Model

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Computers, Materials & Continua 2022年第2期70卷 3295-3309页

作者： Mohamed Ibrahim Waly Mohamed Yacin Sikkandar Mohamed Abdelkader Aboamer Seifedine Kadry Orawit Thinnukool Department of Medical Equipment Technology College of Applied Medical SciencesMajmaah UniversityAl Majmaah11952Saudi Arabia Faculty of Applied Computing and Technology Noroff University CollegeKristiansand4608Norway Research Group of Embedded Systems and Mobile Application in Health Science College of ArtsMedia and TechnologyChiang Mai UniversityChiang Mai50200Thailand

Biomedical imaging is an effective way of examining the internal organ of the human body and its *** important kind of biomedical image is Pap smear image that iswidely employed for cervical cancer *** cancer is a vital reason for increased women’s mortality *** screening of pap smear images is essential to assist the earlier identification and diagnostic process of cervical ***-aided systems for cancerous cell detection need to be developed using deep learning(DL)*** study introduces an intelligent deep convolutional neural network for cervical cancer detection and classification(IDCNN-CDC)model using biomedical pap smear *** proposed IDCNN-CDC model involves four major processes such as preprocessing,segmentation,feature extraction,and ***,the Gaussian filter(GF)technique is applied to enhance data through noise removal process in the Pap smear *** Tsallis entropy technique with the dragonfly optimization(TE-DFO)algorithm determines the segmentation of an image to identify the diseased portions *** cell images are fed into the DL based SqueezeNet model to extract deeplearned ***,the extracted features fromSqueezeNet are applied to the weighted extreme learning machine(ELM)classification model to detect and classify the cervix *** experimental validation,the Herlev database is *** database was developed at Herlev University Hospital(Denmark).The experimental outcomes make sure that higher performance of the proposed technique interms of sensitivity,specificity,accuracy,and F-Score.

关键词： Biomedical images deep learning cervical cancer pap smear images computer aided diagnosis herlev database

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computing the TCCD-Number for the Strong Product of Graphs and Its Application in Urban Water Treatment: Addressing Water Scarcity Through Drainage Purification

Computing the TCCD-Number for the Strong Product of Graphs a...

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Women in computing (InCoWoCo), International Conference for

作者： S. Kaviya G. Mahadevan C. Sivagnanam The Gandhigram Rural Institute Deemed to be University Gandhigram Tamilnadu India Mathematics and Computing Skills Unit University of Technology and Applied Sciences Sur Sultanate Oman

ISBN: (数字)9798331518943

ISBN: (纸本)9798331518950

A dominating set $S$ of a graph $G$ is termed as a triple connected certified dominating set (TCCD-set) if, for every vertex $v\in S$ , the condition $\vert N(v)\cap(V-S)\vert \neq 1$ holds, and the subgraph $\langle S \rangle$ is triple connected. The minimum size of a TCCD-set is known as the triple connected certified domination number (TCCD-number), denoted by $\gamma_{TCC}(G)$ . This study investigates the behavior of the strong product of graphs with respect to the TCCD-number. The TCCD-set concept offers valuable insights into graph connectivity and its applications in enhancing network reliability. In addition to graph theory, this study examines practical applications, such as the establishment of advanced water treatment plants in strategically chosen locations within cities. These plants enable companies to efficiently purify water while utilizing sufficient resources. This model facilitates a reduction in the installation and maintenance costs of drainage water systems, with a primary focus on transforming drainage water into purified water.

关键词： Costs Purification Computational modeling Urban areas Companies Reliability theory Water pollution Graph theory Maintenance Water resources

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Avian Hazard Mitigation: A Classification Approach to Bird Strike Analysis 5

Avian Hazard Mitigation: A Classification Approach to Bird S...

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5th IEEE International Conference on Advances in Electrical, computing, Communication and Sustainable Technologies, ICAECT 2025

作者： Al-Zadjali, Najiba Said Hamed Savarimuthu, Charles Sudaravadivazhagan, B. Rances, Emanuel O. College of Computing and Information Sciences University of Technology and Applied Sciences-Muscat Muscat Oman University of Technology and Applied Sciences-Al Musanah College of Computing and Information Sciences Al-Musannah Oman College of Engineering and Technology University of Technology and Applied Sciences-Al Musanah Al-Musannah Oman

ISBN: (纸本)9798350356236

Bird strikes during landing or takeoff can result in fatalities and catastrophic accidents, raising concerns about loss of life for the aviation sector. This study explored the potential of employing machine-learning algorithms to mitigate bird strikes in aviation. Bird strike data were collected, and the Boruta algorithm feature-selection technique was applied to identify relevant features for an experiment. Irrelevant features were omitted, and relevant features related to bird strikes were identified for analysis. The multinomial Naive Bayes algorithm is then used to segregate objects based on their features. The experimental results illustrate the power of using machine learning techniques to segregate and analyze bird strike data, thereby aiding in determining the causes and effects of damage. © 2025 IEEE.

关键词： Aviation

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Science to Life: User Experience in Children’s Science Book with Augmented Reality (AR) 11th

Science to Life: User Experience in Children’s Science Book...

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11th International Workshop on Learning technology for Education Challenges, LTEC 2023

作者： Kasinathan, Vinothini Mustapha, Aida Husain, Noor Hanifah Zamnah, Aida Rohizan, Rizawati Faculty of Computing Engineering and Technology Asia Pacific University of Technology and Innovation Technology Park Malaysia Kuala Lumpur57000 Malaysia Faculty of Applied Sciences and Technology Universiti Tun Hussein Onn Malaysia Johor Panchor84600 Malaysia

ISBN: (纸本)9783031347535

This paper proposes an interactive Science book called Science to Life that is supported by Augmented Reality (AR), based on Malaysian Science textbooks from Year 1 to Year 6. The AR application is developed using Unity 3D with the support of the Vuforia engine. The evaluation showed favorable feedback from the users on the roles and capacity of Science to Life in educating young students on the Science subject. This AR book is hoped to spark interest among primary school students to learn and master the Science subject. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Augmented reality

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