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International Journal of Interactive Mobile Technologies 2025年第3期19卷 170-190页

作者： Al-Nawashi, Malek M. Al-Hazaimeh, Obaida M. Tahat, Nedal M. Gharaibeh, Nasr Abu-Ain, Waleed A. Abu-Ain, Tarik Al-Huson University College Al-Balqa Applied University Irbid Jordan Faculty of Information Technology Department of Information Security and Cybersecurity Philadelphia University Amman Jordan Faculty of Science The Hashemite University Zarqa Jordan College of Science and Computer Engineering Taibah University Yanbu Saudi Arabia College of Computing and Informatics Saudi Electronic University Riyadh Saudi Arabia

The detection of cyberattacks has been increasingly emphasized in recent years, focusing on both infrastructure and people. Conventional security measures such as intrusion detection, firewalls, and encryption are insufficient in protecting cyber systems against growing and changing threats. In order to address this problem, scholars have explored reinforcement learning (i.e., RL) as a potential solution for intricate cybersecurity decision-making difficulties. Nevertheless, the use of RL faces several obstacles, including dynamic attack scenarios, insufficient training data, and the challenge of replicating real-world complexities. This study presents a novel framework that uses deep reinforcement learning (i.e., DRL) to simulate harmful cyberattacks and improve cybersecurity. This study presents an agent-based framework that is capable of ongoing learning and adaptation in a dynamic network security environment. The agent determines the optimal course of action by considering the current state of the network and the rewards it receives for its decisions. The CIC-IDS-2018 database, constructed using Python 3.7 programming, was used. The conducted studies yielded outstanding results, with a detection accuracy of 98.82% achieved for the CIC-IDS-2018 database in cyber-attack classification. © 2025 by the authors of this article. Published under CC-BY.

关键词： Cybersecurity

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Child Head Gesture Classification through Transformers

Child Head Gesture Classification through Transformers

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2022 IEEE Region 10 International Conference, TENCON 2022

作者： Wedasingha, Nushara Samarasinghe, Pradeepa Singarathnam, Dharshika Papandrea, Michela Puiatti, Alessandro Seneviratne, Lasantha Sri Lanka Institute of Information Technology Faculty of Computing Sri Lanka University of Applied Sciences and Arts of Southern Switzerland Switzerland University of Applied Sciences and Arts of Southern Switzerland Switzerland

This paper proposes a transformer network for head pose classification (HPC) which outperforms the existing SoA for HPC. This robust model is then extended to overcome the limited child data challenge by applying tran... 详细信息

ISBN: (数字)9781665450959

ISBN: (纸本)9781665450959

关键词： Transfer learning

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Evaluation of a Digital Tracking Calorimeter for In-Situ Range Verification during Particle Therapy

Evaluation of a Digital Tracking Calorimeter for In-Situ Ran...

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2022 IEEE Nuclear Science Symposium, Medical Imaging Conference, and Room Temperature Semiconductor Detector Conference, IEEE NSS MIC RTSD 2022

作者： Schilling, Alexander Keidel, Ralf Gauger, Nicolas R. University of Applied Sciences Worms Center for Technology and Transfer Worms67549 Germany Tu Kaiserslautern Scientific Computing Kaiserslautern67663 Germany

ISBN: (纸本)9781665488723

When protons or heavier ions are used for radiation treatment, it is paramount to assure quality by performing range verification during or right after treatment. This work presents, for the first time, a feasibility study for proton therapy range verification based on secondary charged particles using the digital tracking calorimeter designed by the Bergen pCT collaboration. Additionally, we compare the precision achievable with protons and carbon ions, by applying regression models to predict the beam range with Monte Carlo-simulated data. The simulated treatment scenario contains a water cuboid phantom of different thicknesses, with protons and carbon ions as treatment modality at different medically relevant energy levels. Results show that the error for carbon ions is lower despite having 100 times fewer primaries simulated, due to the much higher readout yield. The lowest mean absolute error was observed with a kernel regression as 0.27 ± 0.04 mm for protons, and with a Gaussian process as 0.18 ± 0.02 mm for carbon ions, which shows feasibility of range verification for proton and carbon therapy based on charged secondary particles using the digital tracking calorimeter. © 2022 IEEE.

关键词： Machine learning Monte Carlo simulation particle therapy range verification

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Fruits and Vegetable Diseases Recognition Using Convolutional Neural Networks

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Computers, Materials & Continua 2022年第1期70卷 619-635页

作者： Javaria Amin Muhammad Almas Anjum Muhammad Sharif Seifedine Kadry Yunyoung Nam University of Wah WahCanttPakistan National University of Technology(NUTECH) IJP RoadIslamabadPakistan COMSATS University Islamabad Wah CampusPakistan Faculty of Applied Computing and Technology Noroff University CollegeKristiansandNorway Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea

As they have nutritional,therapeutic,so values,plants were regarded as important and they’re the main source of humankind’s energy *** pathogens will affect its leaves at a certain time during crop cultivation,leading to substantial harm to crop productivity&economic selling *** the agriculture industry,the identification of fungal diseases plays a vital ***,it requires immense labor,greater planning time,and extensive knowledge of plant *** approaches are developed and tested by different researchers to classify plant disease identification,and that in many cases they have also had important results several ***,the proposed study presents a new framework for the recognition of fruits and vegetable *** work comprises of the two phases wherein the phase-I improved localization model is presented that comprises of the two different types of the deep learning models such asYouOnly Look Once(YOLO)v2 and Open Exchange Neural(ONNX)*** localizationmodel is constructed by the combination of the deep features that are extracted from the ONNX model and features learning has been done through the convolutional-05 layer and transferred as input to the YOLOv2 *** localized images passed as input to classify the different types of plant *** classification model is constructed by ensembling the deep features learning,where features are extracted dimension of 1×1000 from pre-trained Efficientnetb0 model and supplied to next 07 layers of the convolutional neural network such as 01 features input,01 ReLU,01 Batch-normalization,02 *** proposed model classifies the plant input images into associated labels with approximately 95%prediction scores that are far better as compared to current published work in this domain.

关键词： Efficientnetb0 open exchange neural network features learning softmax YOLOv2

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Multivariable Decoupling Control of Civil Turbofan Engines Based on Fully Actuated System Approach

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Journal of Systems Science & Complexity 2023年第3期36卷 947-959页

作者： PENG Kai WANG Hongxia ZHANG Huanshui ZHANG Zhaorong YANG Fan School of Power and Energy Northwestern Polytechnical UniversityXi’an 710072China School of Electrical and Automation Engineering Shandong University of Science and TechnologyQingdao 266590China Department of Applied Mathematics The Hong Kong Polytechnic UniversityHung HomKowloonHong KongChina. Xi’an Aeronautics Computing Technique Research Institute AVICXi’an 710068China

Gas turbine engines must be operated by means of control,and how to achieve multivariable control decoupling with aero-engine control constraints is an open thorny issue attracting increasingly more *** paper considers the multivariable decoupling problems of aero-engines by using a compound controller,which originates from the fact that it is impossible to eliminate all the nonlinear dynamics of system to obtain desired constant linear closed-loop system by using full actuated control because of modeling errors and some physical *** controllers are involved in the compound *** is a fully actuated controller and the other is classical feedback *** order to use fully actuated control and maintain the accuracy of engine model,a full state scheduling linear parameter-varying(LPV)modeling method is proposed based on fuzzy neural network *** a general input matrix of the system,its generalized inverse is applied to design fully actuated controller to result in a pseudolinear *** with a feedback controller and control limiter,the control synthesis is *** simulation shows that the proposed method is possessed of a better decoupling and tracking effect compared with traditional control approach.

关键词： Compound control decoupling control fully actuated control turbofan engine

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Using Contextual Text Mining and Ontology Methods to Establish a Novel technology Trend and Associative Analysis Framework for Sustainable Energy Development in Taiwan

Using Contextual Text Mining and Ontology Methods to Establi...

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2022 IEEE International Conference on Big Data, Big Data 2022

作者： Hsiao, Yi-Hao Chuang, Chia-Yi Huang, Megn-Chi Yang, Chia-Lee Wu, Jyh-Horng National Applied Research Laboratories National Center for High-Performance Computing Hsinchu Taiwan National Applied Research Laboratories Science and Technology Policy Research and Information Center Taipei Taiwan

ISBN: (纸本)9781665480451

In 2015, the United Nations proposed 17 Sustainable Development Goals, SDGs, as the guidelines for all countries in the world to promote sustainable development before 2030. Government Research Bulletin (GRB), the research projects and technical reports sponsored by government, which has long-term, numerous, complete research method, technology development and policy analysis information in Taiwan. Therefore, it is an important and effective way to explore SDG-related information from a large amount of GRB text. In this paper, a novel technologies trend and associative analysis framework which uses contextual text mining and ontology methods is proposed and applied to SDG 7, which "Affordable and Clean Energy". First, we integrate dictionary-based method and semantic textual similarity analysis algorithm to obtain a SDG 7 classifier which can exactly and quickly classify a large amount number of GRB text to SDG 7. Then, two major SDG 7 analysis procedures based on the classification results are implemented. One is using contextual text mining algorithm to obtain energy technologies trend information. The other is adopting ontology method to establish energy technologies associative analysis concept map. According to the analysis results mentioned above, we are able to efficiently incorporate the energy technology with long-term trend, energy technology associative information, and the most influential authors on the specify energy technology in order to generate a global strategy for continuous improvement in Taiwan. © 2022 IEEE.

关键词： Ontology

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ACSLs for Large-Scale Bounded Single Depot Multiple Travelling Salesman Problem

ACSLs for Large-Scale Bounded Single Depot Multiple Travelli...

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Congress on Evolutionary Computation

作者： Shanu Verma Millie Pant Department of Applied Mathematics & Scientific Computing Indian Institute of Technology Roorkee Roorkee Uttarakhand India Department of Applied Mathematics & Scientific Computing Mehta Family School of Data Science & Artificial Intelligence Indian Institute of Technology Roorkee Roorkee Uttarakhand India

ISBN: (数字)9798350308365

ISBN: (纸本)9798350308372

Bounded single depot multiple travelling salesman problem (BSD-MTSP) optimizes salesmen tours with constraints on the number of cities visiting per salesman, which ensures balanced routes. BSD-MTSP presents challenges due to its combinatorial nature and additional complexities arising from multiple salesmen and depot-related constraints. Exact solutions for BSD-MTSP via classical methods are computationally expensive, prompting the use of heuristics and metaheuristics for practical solutions. This paper presents ACSLs, a hybrid algorithm combining initialization heuristic, Ant colony system, and Local search operators. ACSLs efficiently tackles large-scale BSD-MTSPs, demonstrating a superiority of up to 9.964% over the most advanced algorithms through comparative analysis.

关键词： Heuristic algorithms Urban areas Metaheuristics Evolutionary computation Benchmark testing Approximation algorithms Space exploration

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A comparative analysis of the e-government development index (EGDI) 15

A comparative analysis of the e-government development index...

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14th International Conference on ICT, Society, and Human Beings, ICT 2021, 18th International Conference on Web Based Communities and Social Media, WBC 2021 and 13th International Conference on e-Health, EH 2021 - Held at the 15th Multi-Conference on Computer Science and Information Systems, MCCSIS 2021

作者： Kabbar, Eltahir F. School of Computing Electrical and Applied Technology Unitec Institute of Technology Auckland New Zealand

ISBN: (纸本)9789898704306

During the past two decades, the United Nations Department of Economic and Social Affairs (UN DESA) published series of reports. Each report presents global survey results that measure e-government development in the 193 UN Member States. The surveys are intended to periodically assess e-government development progress in each of the UN Member States. One of the critical e-government development indicators used in these reports is the E-Government Development Index (EGDI). This quantitative study compares and contrasts the EGDI results (and its principal components indicators) during the past ten years. The study compares the recent two e-government survey results (2018 and 2020) with the (2008 and 2010) results using correlations analysis and cluster analysis. The comparison is performed to achieve two main objectives: first, to measure the degree of EGDI indicators association during the past ten years and detect any significant changes in the overall Member States ranking during the same period. Second, to measure the degree of variation in cluster memberships. The study results show that there is a strong correlation between EGDI scores during the study period. Also, the results show minor changes in cluster membership, indicating that despite the apparent EGDI overall improvements for almost every UN Member State, the situation remains as before. The finds of this study will be of interest to both e-government academics and practitioners. © 14th International Conference on ICT, Society, and Human Beings, ICT 2021, 18th International Conference on Web Based Communities and Social Media, WBC 2021 and 13th International Conference on e-Health, EH 2021 - Held at the 15th Multi-Conference on Computer Science and Information Systems, MCCSIS 2021. All rights reserved.

关键词： Surveys

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Approximate Analytical Solution Using Power Series Method for the Propagation of Blast Waves in a Rotational Axisymmetric Non-Ideal Gas

SSRN

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SSRN 2023年

作者： Gupta, Nandita Arora, Rajan Department of Applied Mathematics and Scientific Computing Indian Institute of Technology Roorkee India

In this paper, the propagation of the blast (shock) waves in non-ideal gas atmosphere in rotational medium is studied using a power series method in cylindrical geometry. The flow variables are assumed to be varying according to the power law in the undisturbed medium with distance from the symmetry axis. To obtain the similarity solution, the initial density is considered as constant in the undisturbed medium. Approximate analytical solutions are obtained using Sakurai's method by extending the power series of the flow variables in power of (a_0)^2, where U and a_0 are the speeds of the shock and sound, respectively, in undisturbed fluid. The strong shock wave is considered for the ratio (a_0)^2 which is considered to be a small quantity. With the aid of that method, the closed-form solutions for the zeroth-order approximation is given as well as first-order approximate solutions are discussed. Also, with the help of graphs behind the blast wave for the zeroth-order approximation, the distributions of variables such as density, radial velocity, pressure and azimuthal fluid velocity are analyzed. The results for the rotationally axisymmetric non-ideal gas environment are compared to those for the ideal gas atmosphere. © 2023, The Authors. All rights reserved.

关键词： Shock waves

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APPROXIMATE ANALYTICAL SOLUTION USING POWER SERIES METHOD FOR THE PROPAGATION OF BLAST WAVES IN A ROTATIONAL AXISYMMETRIC NON-IDEAL GAS

arXiv

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arXiv 2023年

作者： Nandita Arora, Rajan Department of Applied Mathematics Scientific Computing Indian Institute of Technology Roorkee India

In this paper, the propagation of the blast (shock) waves in non-ideal gas atmosphere in rotational medium is studied using a power series method in cylindrical geometry. The flow variables are assumed to be varying according to the power law in the undisturbed medium with distance from the symmetry axis. To obtain the similarity solution, the initial density is considered as constant in the undisturbed medium. Approximate analytical solutions are obtained using Sakurai's method by extending the power series of the flow variables in power of (Equation presented). where U and a0 are the speeds of the shock and sound, respectively, in undisturbed fluid. The strong shock wave is considered for the ratio (Equation presented). which is considered to be a small quantity. With the aid of that method, the closed-form solutions for the zeroth-order approximation is given as well as first-order approximate solutions are discussed. Also, with the help of graphs behind the blast wave for the zeroth-order approximation, the distributions of variables such as density, radial velocity, pressure and azimuthal fluid velocity are analyzed. The results for the rotationally axisymmetric non-ideal gas environment are compared to those for the ideal gas atmosphere. © 2023, CC BY-NC-ND.

关键词： Gases

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