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检索条件"任意字段=International Conference on Simulation and Modeling Methodologies, Technologies and Applications"

共 3923 条记录，以下是541-550 订阅

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An Empirical Study on Various Workflow Scheduling Techniques in Cloud Computing

An Empirical Study on Various Workflow Scheduling Techniques...

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Advanced Computing and Emerging technologies (ACET), international conference on

作者： Madhumala G R Suma Department of Information Science and Engineering Sri Siddhartha Institute of Technology Tumkur Karnataka

ISBN: (数字)9798350367720

ISBN: (纸本)9798350367737

Cloud computing (CC) is a modern technology which deploys networks of servers, positioned in extensive remote areas, for conducting operations on a larger quantity of data. In CC, a workflow module is employed for representing diverse scientific and web applications. One of the major problems is scheduling larger workflows of tasks on the heterogeneous CC environment. This article summarizes some important research works in the field of CC associated with workflow scheduling (WS). At first, this survey represents the common structure of WS in cloud and then, scheduling approaches are catalogued into four techniques like Machine Learning (ML), Deep Learning (DL), Hybrid and Algorithmic-based approaches are discussed in detail. Thereafter, the research gaps faced by the traditional approaches for WS will help the researchers in future for building an innovative model. This study considers 25 research articles focused on different methodologies employed for WS in cloud. Lastly, the evaluation is performed in the survey regarding year of publication, performance measures, research technique, and attainment of the research models. It is acknowledged that algorithmic based modules are usually employed approaches, while cloudsim is repeatedly applied tool for WS in CC. Moreover, makespan is the utilized analytic measure with superior value.

关键词： Surveys Cloud computing Machine learning algorithms Processor scheduling Estimation Medical services Load management Scheduling Servers Load modeling

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Agility of in Deep Learning Algorithms in Developing Conflicting Attacks Protections and to Secure Vulnerabilities

Agility of in Deep Learning Algorithms in Developing Conflic...

引用

Advance Computing and Innovative technologies in Engineering (ICACITE), international conference on

作者： Renas Rajab Asaad Saman Mohammed Abdulrahman Ahmed Alaa Hani Hawar Bahzad Ahmad Amira Bibo Sallow Subhi R. M Zeebaree Department of Computer Science Nawroz University Duhok Iraq Department of Computer Science College of Science Nawroz University Duhok KRG Iraq Energy Engineering Department Technical College of Engineering Duhok Polytechnic University Duhok Iraq

ISBN: (数字)9798350360165

ISBN: (纸本)9798350360172

Deep learning methods have brought revolution to a variety of applications: from image recognition to natural language processing, and many others. However, their most important vulnerability, when used in adversarial conditions, is a matter of concern that remains up to today. Most importantly, adversarial attacks insinuate the design of input in a way to be capable of bringing errors in the model, hence exposing significant vulnerabilities. This paper investigates the nature of such vulnerabilities and proposes the enhancement of model robustness through comprehensive methodologies. First of all, adversaries would be considered under the threat landscape and classified according to their complexity and impact, should one materialize. The second section would detail all available defense mechanisms, again classified based on strengths and limitations. We propose using the ensemble of adversaries, regularization methods, and dynamic network architecture. We validate this using the empirical testing of the technique over several datasets and models, subjected to a battery of rigorous tests.

关键词： Deep learning Training Heuristic algorithms Computational modeling Network architecture Robustness Protection

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Automated Detection and Classification of Cotton Leaf Diseases: A Computer Vision Approach

Automated Detection and Classification of Cotton Leaf Diseas...

引用

Advances in Modern Age technologies for Health and Engineering Science (AMATHE), international conference on

作者： Swastick Ganguly Jathin S M Mohak M Sanjay BM Somashekhar N Shobharani Department of Computer Science Amrita School of Computing Mysuru Campus Dept of Computer Science and Engineering Gitam School of Technology Gitam University Bengaluru Campus

ISBN: (数字)9798350371567

ISBN: (纸本)9798350371574

Cotton plays a vital role in agricultural sustainability, extending beyond its textile applications. Pathogens pose significant threats to cotton plants and farmers' livelihoods, highlighting the critical need for disease detection to maintain crop health and ensure optimal yields. Our research pioneers a novel approach to disease detection in cotton through advanced image analysis techniques. This involves exploring deep learning methodologies specifically tailored for detecting cotton leaf diseases and enhancing accuracy by integrating CNN models, while balancing labor intensity and cost considerations. Leveraging the Convolutional Neural Networks (CNN), the combination of the interpretability of Densenet 121 with the stability of ResNet 50, assessing the strength of their combined algorithm. This hybrid model accurately classifies various cotton plant diseases, enabling fine-grained analysis. With a precision-driven approach, the proposed model achieves exceptional results, accurately identifying six distinct diseases, including fungal, bacterial, and viral pathogens, with an impressive 96% accuracy rate. The research aims to provide a comprehensive and dependable solution for disease management in the cotton industry, ultimately promoting crop health, productivity, and sustainability

关键词： Deep learning Training Plant diseases Pathogens Accuracy Computational modeling Crops

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Design and Analysis of Microstrip Patch Antenna Using Metamaterial for Biomedical applications

Design and Analysis of Microstrip Patch Antenna Using Metama...

引用

AI in Cybersecurity (ICAIC), international conference on

作者： Anshul Shrivastava Rajesh Kumar Kurmendra Department of Electronics and Communication Engineering North Eastern Regional institute of Science & Technology Nirjuli Arunachal Pradesh India Department of Electronics & Communication Engineering Rajiv Gandhi University Doimukh Arunachal Pradesh- India

ISBN: (数字)9798331518882

ISBN: (纸本)9798331518899

Over the past ten years, metamaterials research has attracted a lot of attention. Metamaterials are materials that have been created artificially and exhibit characteristics that cannot be seen in materials that naturally occur. Metamaterials occur in a wide range of forms and exhibit electromagnetic phenomena that are not present in natural materials. When creating a novel metamaterial, simulation can be used to examine both the overall property of the substance and each individual component. The researcher needs to be mindful of a few particular factors when modelling metamaterials. Multiple modeling methodologies are thus employed for the effective development of a gadget. Given that early-stage cancer can be successfully treated with well-established conventional treatments, remote malignant tumor diagnostics is essential to modern medicine’s capacity to treat cancer disorders. Such antennas have been designed so far for many types of diseases using a variety of ways.

关键词： Wireless communication Patch antennas Microstrip antennas Medical services Metamaterials Microstrip Tuning Monitoring Cancer Antenna radiation patterns

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Machine Learning Approaches for Transformer modeling

Machine Learning Approaches for Transformer Modeling

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international conference on Synthesis, modeling, Analysis and simulation Methods and applications to Circuit Design (SMACD)

作者： F. Passos N. Lourenç o R. Martins E. Roca R. Castro-Ló pez N. Horta F. V. Ferná ndez Instituto de Telecomunica&#x00E7 &#x00F5 es Lisbon Portugal Instituto de Microelectr&#x00F3 nica de Sevilla CSIC and Universidad de Sevilla Seville Spain

In this paper, several machine learning modeling methodologies are applied to accurately and efficiently model transformers, which are still a bottleneck in millimeter-wave circuit design. In order to compare the models, a statistical validation is performed against electromagnetic simulations using hundreds of passive structures. The presented models using machine learning techniques have proven to be accurate, efficient, and useful for a wide range of frequencies from (around) DC up to the millimeter-wave range (around 100GHz). As an application example, the models are used as a performance evaluator in a synthesis procedure to optimize a transformer and a balun.

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Evolution of Robotic Simulators: Using UE4 to Enable Real-World Quality Testing of Complex Autonomous Robots in Unstructured Environments 10

Evolution of Robotic Simulators: Using UE4 to Enable Real-Wo...

引用

10th international conference on simulation and modeling methodologies, technologies and applications (SIMULTECH)

作者： Wolf, Patrick Groll, Tobias Hemer, Steffen Berns, Karsten TU Kaiserslautern Robot Res Lab Dept Comp Sci Kaiserslautern Germany

ISBN: (纸本)9789897584442

Robotic simulators are essential for control development since they allow early testing. Additionally, trial time is tremendously reduced in comparison to a real system. In the recent past, many powerful simulation systems emerged, offering a high quality and level of realism. Still, those simulators have some shortcomings concerning the development of complex commercial vehicles that regularly operate within extremely cluttered and unstructured environments. This paper aims to reduce the gap occurring during the simulation and realworld testing to increase the expressiveness of robot control software tests.

关键词： Robotic simulation Sensors Framework Commercial Vehicle Development

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modeling the Influence of Charge Carrier Diffusion on Harmonic Comb Formation in Quantum Cascade Lasers

Modeling the Influence of Charge Carrier Diffusion on Harmon...

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international conference on Electromagnetics in Advanced applications (ICEAA)

作者： Lukas Seitner Johannes Popp Felix Naunheimer Georg Janowski Michael Haider Christian Jirauschek TUM School of Computation Information and Technology Technical University of Munich Garching Germany

The quantum cascade laser (QCL), operating as an optical frequency comb, is highly attractive for applications in metrology and sensing. Recently, the generation of coherent optical frequency combs in QCLs with large intermodal spacing has been demonstrated. These harmonic combs promise superior quantum features and may expand the scope of photonic quantum technologies. This paper presents a numerical study of self-starting harmonic mode-locking in terahertz QCL devices in the presence of charge carrier diffusion. With our detailed multidomain simulation approach and the possibility of artificially turning off spatial hole burning, we observe a strong dependence of the laser state on the strength of the population grating.

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A 3-D Printed Trapezoidal Antenna for X-Band Wireless Communications applications

A 3-D Printed Trapezoidal Antenna for X-Band Wireless Commun...

引用

international conference on Futuristic Communication and Network technologies, CFCNT 2020

作者： Ahmed, Ashraf E. Ali, Wael A. E. Chowdhury, Apurba Das, Sudipta Electronics and Communication Engineering Department College of Engineering Higher Institute of Engineering and Technology King Marriott Alexandria Egypt Alexandria Egypt Mallabhum Institute of Polytechnic Bishnupur Bankura India Department of ECE IMPS College of Engineering and Technology Malda West Bengal India

ISBN: (纸本)9789811646249

By reason of a fast growth in the 3-D printing technology, 3-DP trapezoidal antenna is proposed, designed and then simulated. This paper that introduces a new 3-D printed trapezoidal antenna operates accurately in X-band for wireless communication applications. It is designed by a low-cost polylactic acid (PLA) substrate with relative permittivity of 3.1 and having compact size of 13.11 × 21.36 × 1 mm3. The proposed antenna has S11 of –21.67 dB at 10.1 GHz. The suggested antenna has gain of 5dBi as individual element. modeling and simulation of the suggested antenna are performed by Ansoft High Frequency Structure Simulator (HFSS 13). © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Microstrip antennas

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Automated Detection and Response to Cyberbullying Using Machine Learning

Automated Detection and Response to Cyberbullying Using Mach...

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Digital applications, Transformation & Economy (ICDATE), international conference on

作者： Salmi Younes Debabha Ramzi Salem Osman Mehaoua Ahmed Université Paris Cité Paris France

ISBN: (数字)9798350310689

ISBN: (纸本)9798350310696

Cyberbullying poses a significant threat to the mental and emotional well-being of individuals, particularly in today’s digital age, where online communication and social media are pervasive. Current automated content moderation solutions often struggle to effectively detect and filter offensive messages. In this paper, we present an innovative bot designed to combat cyberbullying by detecting and reporting insults in both voice and text messages. Our bot utilizes OpenAI’s API, speech recognition technology and machine learning models to detect cyberbullying. We discuss the challenges related to detecting and preventing cyberbullying, the technologies and methodologies employed in our bot, and the results of its performance in detecting and filtering offensive messages. The proposed solution demonstrates its effectiveness and potential for real-world applications, offering an accessible and powerful tool for promoting a safe and respectful online environment.

关键词： Support vector machines Adaptive learning Adaptation models Biological system modeling Refining Cyberbullying Machine learning

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Analytical and Experimental Approach for modeling, simulation and Validation of Two-Wheeled Self-Balancing Robot

Analytical and Experimental Approach for Modeling, Simulatio...

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international conference on Inventive Computation technologies (ICICT)

作者： Gokarna Baskota Ranish Devkota Sadanand Paneru Shuruchi Yadav Deependra Neupane Om Prakash Dhakal Department of Electronics and Computer Engineering IoE Eastern Regional Campus Tribhuwan University Dharan Nepal Department Electrical Engineering IoE Eastern Regional Campus Tribhuwan University Dharan Nepal

Two-Wheeled Self-Balancing Robot (TWSBR) has many applications and is an important research topic in robotics and control engineering. The principle behind the operation of a TWSBR is an inverted pendulum. The mathematical modelling of the TWSBR is still challenging as it includes non linear components to operate. This study aims the analysis of a two-wheeled, micro-controller based fabricated TWSBR. The linear mathematical model of each of the components of TWSBR has been obtained. Some of the components has been modelled using experimental model identification method while some are represented analytical approximations. A PID controller has been used to balance the TWSBR in upright position. The overall system has been simulated in MATLAB/SIMULINK. The result from the simulation is compared with real time hardware setup of the system to validate the mathematical model and stability of the TWSBR. The investigation has shown adequate accuracy in the models of components used in TWSBR. Moreover, the simulated results shows similar behaviour to that of hardware realization of the robot. This study may help on several research related to system identification, mathematical modeling and controller design of TWSBR.

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