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Best Selection of Generative Adversarial Networks Hyper-Parameters Using Genetic Algorithm

SN computer Science 2021年第4期2卷 283页

作者： Alarsan, Fajr Ibrahem Younes, Mamoon Informatics and Decision Supporting Systems Higher Institute for Applied Sciences and Technology Damascus Syrian Arab Republic Faculty of Computer and Automation Engineering Damascus University Damascus Syrian Arab Republic

Generative adversarial networks (GANs) are most popular generative frameworks that have achieved compelling performance. They follow an adversarial approach where two deep models generator and discriminator compete with each other. In this paper, we propose a Generative Adversarial Network with best hyper-parameters selection to generate fake images for digit numbers 1–9 with generator and train discriminator to decide whereas the generated images are fake or true. Genetic algorithm (GA) technique was used to adapt GAN hyper-parameters, the resulted algorithm is named GANGA: generative adversarial network with genetic algorithm. The resulted algorithm has achieved high performance;it was able to get zero value of loss function for the generator and discriminator separately. Anaconda environment with tensorflow library facilitates was used;python as programming language was adapted with needed libraries. The implementation was done using MNIST dataset to validate the work. The proposed method is to let genetic algorithm choose best values of hyper-parameters depending on minimizing a cost function such as a loss function or maximizing accuracy function used to find best values of learning rate, batch normalization, number of neurons and a parameter of dropout layer. © 2021, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Discriminator Generative adversarial networks (GAN) Generator Genetic algorithm Image synthesis MNIST dataset

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AlGaAs soliton microcombs at room temperature

AlGaAs soliton microcombs at room temperature

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Wu, Lue Xie, Weiqiang Xiang, Chao Chang, Lin Yu, Yan Chen, Hao-Jing Yamamoto, Yoshihisa Bowers, John E. Vahala, Kerry J. Suh, Myoung-Gyun T. J. Watson Laboratory of Applied Physics California Institute of Technology PasadenaCA91125 United States Department of Electrical and Computer Engineering University of California Santa Barbara Santa BarbaraCA93106 United States Physics & Informatics Laboratories NTT Research Inc. SunnyvaleCA94085 United States

Soliton generation in AlGaAs microresonators at room temperation is reported for the first time. The destabilizing thermo-optic effect is shown to instead provide stability for high soliton repetition rates. The optic... 详细信息

ISBN: (纸本)9781957171258

关键词： Aluminum gallium arsenide

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AIANTAS) for IoT Cyberspace - An Upcoming Cloud-based Security Architecture for Police Authorities 9

AIANTAS) for IoT Cyberspace - An Upcoming Cloud-based Securi...

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9th IEEE International Conference on Information, Communication and Networks, ICICN 2021

作者： Memos, Vasileios A. Psannis, Konstantinos E. Ishibashi, Yutaka University of Macedonia School of Information Sciences Dept of Applied Informatics Thessaloniki Greece Nagoya Institute of Technology School of Engineering Dept of Computer Science Nagoya Japan

ISBN: (纸本)9780738113456

In this research work, we investigate the effects of cybercrime and focus on concerns about cybercrime expansion. Since black-hat hackers are constantly one step ahead of white-hat hackers and exploit new sophisticated hack-tools to intrude to devices and networks to commit cybercrime for different reasons, the utilization of the available emerging technologies can provide better privacy and protection level, while they can be used to combat cybercriminal attacks. This shift to new technologies and methods is regarded to be an urgent necessity today. Therefore, we demonstrate a potential novel security mechanism for Police Authorities, named 'Artificial Intelligence ANTi-Attack System' or simply 'AIANTAS' that aspires to improve the detection rate of cybercriminals and lead to their faster arrest. This model can be integrated into the other National Security defense mechanisms both in Greece and worldwide. © 2021 IEEE.

关键词： Data Analytics

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Efficient Time-Delay System Optimization with Auto-Configured Metaheuristics

Efficient Time-Delay System Optimization with Auto-Configure...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Roman Senkerik Aleksander Byrski Hubert Guzowski Peter Janku Tomas Kadavy Zuzana Kominkova Oplatkova Radek Matusu Michal Pluhacek Libor Pekar Maciej Smolka Adam Viktorin Department of Informatics and Artificial Intelligence A.I. Lab Faculty of Applied Informatics Tomas Bata University in Zlin Czech Republic Department of Automation and Control Engineering Faculty of Applied Informatics Tomas Bata University in Zlin Czech Republic Institute of Computer Science AGH University of Science and Technology Krakow Poland

This paper presents an experimental study that compares the performance of four selected metaheuristic algorithms for optimizing a time delay system model. Time delay system models are complex and challenging to optimize due to their inherent characteristics, such as non-linearity, multi-modality, and constraints. The study includes an explanation of the choice and core functionality of the selected algorithms, which are both baseline and state-of-the-art variants of self-organizing migrating algorithm (SOMA), state-of-the-art variant from the Success-History-based Adaptive Differential Evolution family of algorithms, with emphasis on diverse search (DISH algorithm), and Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithm. The hyperparameters of the metaheuristic algorithms were set using the iRace automatic algorithm configuration framework. The paper emphasizes the importance of metaheuristic algorithms in control engineering for time-delay systems to develop more effective and efficient control strategies and precise model identifications. The experimental results highlight the effectiveness of the state-of-the-art algorithms with specific adaptive mechanisms like population organization process, diverse search and adaptation mechanisms ensuring a gradual transition from exploration to exploitation. Overall, this study contributes to understanding the challenges and advantages of using metaheuristic algorithms in control engineering for time delay systems. The results provide valuable insights into the performance of modern metaheuristic algorithms and can help guide the selection of appropriate adaptive mechanisms of metaheuristics.

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Mechanisms of Formation and Modeling of the Refractory Compound Film Structures

Mechanisms of Formation and Modeling of the Refractory Compo...

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International Conference on Nanomaterials: Application & Properties (NAP)

作者： Alexander Goncharov Ivan Kolinko Dmytro Shyrokorad Grygoriy Kornich Andrii Yunda Svetlana Goncharova Department of Applied Mathematics and Complex Systems Modelling Sumy State University Sumy Ukraine Institute of Materials Science Slovak University of Technology in Bratislava Slovak Republic Computer Sciences and Technologies Faculty National University “Zaporizhzhia Polytechnic” Zaporizhzhia Ukraine Institute of Applied Physics National Academy of Sciences of Ukraine Sumy Ukraine Department of Biophysics Biochemistry Pharmacology and Biomolecular Engineering Sumy State University Sumy Ukraine

ISBN: (数字)9798350380125

ISBN: (纸本)9798350380132

In this work, the molecular dynamics method was used for modeling the formation of critical nuclei at the initial stage. The deposition of a titanium nitride film on an iron substrate was chosen as a model object. The 2NN MEAM multiatomic potential was used to calculate the interaction between atoms. Simulations of N and Ti atom deposition on an Fe(100) substrate were carried out using the MPI version of the open-source program LAMMPS (Molecular Dynamics Simulator). The substrate was modeled as a semi-infinite crystal with a frozen lower atomic layer, periodic boundary conditions at the lateral crystal sides, and a free deposition surface.

关键词： Atomic layer deposition Crystals Atoms Titanium nitride Boundary conditions Iron Compounds Substrates Surface treatment

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Simulation-Based Metrological Temperature Ensuring and Control of the Temperature Field in an Induction Furnace Based on Various Parameters

Simulation-Based Metrological Temperature Ensuring and Contr...

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International Conference on computer and Automation engineering, ICCAE

作者： Jan Rybář Samuel Emebu Sayed Yousuf Sayed Sohaibullah Zarghoon Lukáš Bartalský Peter Onderčo Andrej Smetánka Radek Matušů Faculty of Mechanical Engineering Institute of Automation Informatization and Measurement Slovak University of Technology Bratislava Slovakia Department of Separation Science LUT School of Engineering Science Lappeenranta-Lahti University of Technology Lappeenranta Finland Department of Auto mechanical Engineering Faculty of Electro-Mechanic Kabul Polytechnic University Kabul Afghanistan Department of Automation and Control Engineering Faculty of Applied Informatics Tomas Bata University in Zlín Zlín Czech Republic

ISBN: (数字)9798331533816

ISBN: (纸本)9798331533823

Induction heating is widely used in industrial furnaces because of its rapid response time and high energy efficiency. To design and optimize these furnaces, computer-aided simulations are essential. This study aims to develop an accurate temperature field model for a square cross-section steel billet in an induction furnace by leveraging various parameters in COMSOL Multiphysics software. The simulation analysis incorporated temperature dynamics, considering skin depth, temperaturedependent, and constant parameters of the steel billet. The datadriven model was converted into a state-space representation utilizing MATLAB's System Identification Toolbox. This conversion facilitated the design of a Linear Quadratic Regulator (LQR) with integral gain and pole placement. Further, these controllers' performance was analyzed, and controllers were successfully implemented to regulate the temperature field of the billet from initial temperature to reference temperature, utilizing the distributed parameter system control circuit.

关键词： Billets Analytical models Temperature Accuracy Computational modeling Furnaces Mathematical models Temperature control Steel Induction heating

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The Integration of 6G and Blockchain into an Efficient AIoT-Based Smart Education Model

The Integration of 6G and Blockchain into an Efficient AIoT-...

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IEEE World Symposium on Communication engineering (WSCE)

作者： Anna Lioupa Vasileios A. Memos Christos L. Stergiou Yutaka Ishibashi Konstantinos E. Psannis Dept. of Applied Informatics School of Information Sciences University of Macedonia Thessaloniki Greece Dept. of Computer Science Graduate School of Engineering Nagoya Institute of Technology Nagoya Japan

The technological advances impact the future classrooms and the whole education system. The evolution of 6G promises faster speeds based on terahertz, wireless communication, the leverage of artificial intelligence (AL), virtually reality (VR) and generally a fully connected world. The use of applications of IoT and AIoT improves the education environment, but the intelligent network services undoubtedly gather, store and analyze big data which are vulnerable to attackers. As a solution we may consider the technology of blockchain. The trust and security of next generation intelligent networks are essential part of their design. In this article we suggest a data security system based on blockchain for AL applications in 6G networks. First, we present two Al-enabled applications, indoor positioning and mobile payment within the framework of 6G in the university area. We present the efficiency of blockchain in data security for Al-enabled systems using two case studies of indoor positioning system and mobile payment. The 6G system which is fully supported by Al and the integration of this in technology of blockchain, is ensured the security in future wireless communication.

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Construction of Countably Infinite Programs that Evade Malware/Non-Malware Classification for Any Given Formal System

SSRN

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SSRN 2024年

作者： Stamatiou, Yannis C. Liagkou, Vasia Spirakis, Paul G. Nastou, Panayiotis E. Computer Technology Institute and Press - "Diophantus" University of Patras Campus 26504 Greece Department of Computer Science University of Liverpool UK and Computer Engineering and Informatics Department University of Patras 26504 Greece Department of Business Administration University of Patras 26504 Greece University of Ioannina Department of Informatics and Telecommunications Koatakioi Arta 47100 Greece Department of Mathematics University of the Aegean Applied Mathematics and Mathematical Modeling Laboratory Samos Greece

The formal study of computer malware was initiated in the seminal work of Fred Cohen in the mid-80s who applied elements of Computation Theory in the investigation of the theoretical limits of using the Turing Machine formal model of computation in detecting viruses. Cohen gave a simple but realistic, formal, definition of the characteristic actions of a computer virus as a Turing Machine that replicates itself and proved that detecting this behaviour, in general. is an undecidable problem. In this paper, we complement Cohen's approach by providing a simple generalization of his definition of a computer virus so as to model any type of malware behaviour and showing that the malware/nonmalware classification problem is, again, undecidable. Most importantly, beyond Cohen's work, our work provides a generic theoretical framework for studying anti-malware applications and identifying, at an early stage, before their deployment, several of their inherent vulnerabilities which may lead to the construction of zero-day exploits and malware strains with stealth properties. To this end, we show that for any given formal system, which can be seen as an anti-malware formal model, there are infinitely many, effectively constructible, programs for which no proof can be produced by the formal system that they are either malware or non-malware programs. Moreover, infinitely many of these programs are, indeed, malware programs which evade the detection powers of the given formal system. © 2024, The Authors. All rights reserved.

关键词： Turing machines

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First steps towards modeling the interaction of cardiovascular agents and smooth muscle activation in arterial walls

First steps towards modeling the interaction of cardiovascul...

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92nd Annual Meeting of the International Association of applied Mathematics and Mechanics, GAMM 2022

作者： Nurani Ramesh, S. Uhlmann, K. Saßmannshausen, L. Rheinbach, O. Klawonn, A. Heinlein, A. Balzani, D. Civil and Environmental Engineering Ruhr University Bochum Universitätsstraße 150 Bochum44801 Germany University of Cologne Department of Mathematics and Computer Science Cologne Germany Technische Universität Bergakademie Freiberg Department of Mathematics and Informatics Freiberg Germany Delft Institute of Applied Mathematics Delft University of Technology Mekelweg 4 Delft2628 CD Netherlands

Numerical simulation of the response of healthy and pathological arteries to cardiovascular agents can provide valuable information to the physician in the treatment of diseases such as hypertension, atherosclerosis, and the Marfan syndrome. Here, we provide a first step towards a computational framework to model the effects of antihypertensive agents on the mechanical response of arterial walls. A material model is developed by extending an existing formulation for wall tissue to incorporate the effects of calcium-ion channel blockers. The resulting coupled deformation-diffusion problem is then solved using the finite element method. Simulation results with drug activity show that, indeed, an increased lumen diameter due to reduced contraction is obtained. Additionally, a decrease in the rate of arterial contraction is observed, which is also consistent with expected behavior. Finally, we compare results for an implicit or explicit treatment of the the deformation-diffusion coupling, and we observe that both coupling schemes yield comparable results for a wide range of time step sizes. © 2023 The Authors. Proceedings in applied Mathematics & Mechanics published by Wiley-VCH GmbH.

关键词： Diseases

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AI Based Prediction for Heart Disease: A Comparative Analysis and an Improved Machine Learning Approach

AI Based Prediction for Heart Disease: A Comparative Analysi...

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Artificial Intelligence technology (ACAIT), Asian Conference on

作者： Jay Raval Jai Prakash Verma Sardar N. M. Islam Rachna Jain Narina Thakur Computer Science Engineering Department Institute of Technology Nirma University Ahmedabad India Applied Informatics Research Victoria University Melbourne Australia Department of Computer Science and Engineering Bhagwan Parshuram Institute of Technology Delhi India

Heart disease problems are growing day by day in the world. Many factors are responsible for increasing the chance of heart attack and any other disease. Many countries have a low level of cardiovascular competence in predicting heart disease-related issues. Finding the best accurate machine learning classifiers for various diagnostic uses by data mining and machine learning techniques aids in predicting whether or not the heart disease-related issue will occur. To predict heart disease, a number of supervised machine-learning algorithms are used and their effectiveness are evaluated. With the exceptionof MLP and KNN, all applied algorithms had their estimated feature significance scores for each feature. This helps to find the main factors affecting heart disease and the accuracy of the model, which helps to get the best prediction. At the end of the research the support vector machine gives us 87.91 % highest testing accuracy compare with all applied machine learning algorithm.

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