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International Computer Music Conference, ICMC 2006

作者： Zad, Damon Daylamani Araabi, Babak N. Lucas, Caru Department of Information Systems and Computing Brunel University United Kingdom Dept. of Electrical and Computer Engineering Control and Intelligent Processing Center of Excellence University of Tehran Iran

Artificial music composition is one of the ever rising problems of computer science. Genetic Algorithm has been one of the most useful means in our hands to solve optimization problems. By use of precise assumptions and adequate fitness function it is possible to change the music composing into an optimization problem. This paper proposes a new genetic algorithm for composing music. Considering entropy of the notes distribution as a factor of fitness function and developing mutation and crossover functions based on harmonic rules and trying to keep the melodies intact during these processes would result in a musical piece pleasant to human ears and interesting for human mind. This algorithm does not have the constraints of the previous algorithms. Restraining mutation and crossover functions with a goal of producing melodies based on acceptable melodies composed by humans, this algorithm is not bound to any genre, instrument or melody. The experimental results of this approach show that it is near to the human composing and the results produced from it are more acceptable than the ones produced by its predecessors.

关键词： Genetic algorithms

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A family of experiments to validate measures for UML activity diagrams of ETL processes in data warehouses

A family of experiments to validate measures for UML activit...

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作者： Muñoz, Lilia Mazón, Jose-Norberto Trujillo, Juan Lucentia Research Group Department of Information Systems Control Evaluation and Computing Resources Technological University of Panama P.O. Box #0819-07289 Panama Lucentia Research Group Department of Software and Computing Systems University of Alicante San Vicente del Raspeig 03080 Spain

In data warehousing, Extract, Transform, and Load (ETL) processes are in charge of extracting the data from the data sources that will be contained in the data warehouse. Their design and maintenance is thus a cornerstone in any data warehouse development project. Due to their relevance, the quality of these processes should be formally assessed early in the development in order to avoid populating the data warehouse with incorrect data. To this end, this paper presents a set of measures with which to evaluate the structural complexity of ETL process models at the conceptual level. This study is, moreover, accompanied by the application of formal frameworks and a family of experiments whose aim is to theoretical and empirically validate the proposed measures, respectively. Our experiments show that the use of these measures can aid designers to predict the effort associated with the maintenance tasks of ETL processes and to make ETL process models more usable. Our work is based on Unified Modeling Language (UML) activity diagrams for modeling ETL processes, and on the Framework for the Modeling and Evaluation of Software Processes (FMESP) framework for the definition and validation of the measures. © 2010 Elsevier B.V. All rights reserved.

关键词： Data warehouses

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Nonlinear Stochastic systems with Network-Induced Phenomena 1

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1000年

作者： Jun Hu Zidong Wang Huijun Gao

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Sustainability and Time Complexity Estimation of Cryptographic Algorithms Main Operations on Elliptic Curves 11

Sustainability and Time Complexity Estimation of Cryptograph...

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11th International Conference on Advanced Computer information Technologies, ACIT 2021

作者： Yakymenko, Igor Kasianchuk, Mykhailo Yatskiv, Vasyl Shevchuk, Ruslan Koval, Vasyl Yatskiv, Solomiya West Ukrainian National University Department of Cyber Security Ternopil Ukraine West Ukrainian National University Department of Computer Science Ternopil Ukraine West Ukrainian National University Department of Information and Computing Systems and Control Ternopil Ukraine

This paper presents the time complexity estimates for the methods of points exponentiation, which are basic for encrypting information flows in computer systems. As a result of numerical experiments, it is determined that the method of doubling-addition-subtraction has the lowest complexity. Mathematical models for determining the execution time of each considered algorithm for points exponentiation on elliptic curves were developed, which allowed to conduct in-depth analysis of their performance and resistance to special attacks, in particular timing analysis attack. The dependences of the cryptographic operations execution time on the key length and the sustainability of each method on the Hamming weight are investigated. It is proved that under certain conditions the highest sustainability of the system is achieved by the doubling-addition-subtraction algorithm. This allows to justify the choice of algorithm and its parameters for the implementation of cryptographic information security, which is resistant to special attacks. © 2021 IEEE.

关键词： Security of data

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Fuzzy controller of Pathological Conditions Diagnosis based on Analysis of Cytological Images 8

Fuzzy Controller of Pathological Conditions Diagnosis based ...

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8th International Conference Advanced Computer information Technologies, ACIT 2018

作者： Dubchak, Lesia Verbovyy, Serhiy Verbova, Olena Vasylkiv, Nadiia Department of Computer Engineering Ternopil National Economic University Ternopil 8 Chekhova str. Ukraine Department of Information and Computing Systems and Control Ternopil National Economic University 11 Lvivska str. Ternopil Ukraine

In this article authors proposed the fuzzy controller for the correct diagnosis of the breast pathological states. This mean can be used in medical practice by the cytologist as an additional way of diagnosis confirmi... 详细信息

ISBN: (纸本)9789666544899

关键词： Diagnosis

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Sensor attack correction for linear systems with known inputs

Sensor attack correction for linear systems with known input...

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作者： Tang, Zhanghan Kuijper, Margreta Chong, Michelle Mareels, Iven Leckie, Christopher School of Electrical and Electronic Engineering University of Melbourne Australia Department of Automatic Control KTH Royal Institute of Technology Sweden IBM Research Australia Australia School of Computing and Information Systems University of Melbourne Australia

We address the problem of attack detection and attack correction for multi-input multi-output discrete-time linear time-invariant systems under sensor attacks. More specifically, we consider the situation that a system with known input is corrupted by additive adversarial attack signals on some of the system's outputs. In this paper, we use system representation in a behavioural approach, which allows for natural and compact statements regarding linear system security. We extend our earlier results for systems with zero inputs to systems with non-zero inputs. We assume that these non-zero inputs are known. © 2018

关键词： Error correction

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Improved Prediction of Metamaterial Antenna Bandwidth Using Adaptive Optimization of LSTM

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Computers, Materials & Continua 2022年第10期73卷 865-881页

作者： Doaa Sami Khafaga Amel Ali Alhussan El-Sayed M.El-kenawy Abdelhameed Ibrahim Said H.Abd Elkhalik Shady Y.El-Mashad Abdelaziz A.Abdelhamid Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Systems Engineering Faculty of Engineering at ShoubraBenha UniversityEgypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia

The design of an antenna requires a careful selection of its parameters to retain the desired ***,this task is time-consuming when the traditional approaches are employed,which represents a significant *** the other hand,machine learning presents an effective solution to this challenge through a set of regression models that can robustly assist antenna designers to find out the best set of design parameters to achieve the intended *** this paper,we propose a novel approach for accurately predicting the bandwidth of metamaterial *** proposed approach is based on employing the recently emerged guided whale optimization algorithm using adaptive particle swarm optimization to optimize the parameters of the long-short-term memory(LSTM)deep *** optimized network is used to retrieve the metamaterial bandwidth given a set of *** addition,the superiority of the proposed approach is examined in terms of a comparison with the traditional multilayer perceptron(ML),Knearest neighbors(K-NN),and the basic LSTM in terms of several evaluation criteria such as root mean square error(RMSE),mean absolute error(MAE),and mean bias error(MBE).Experimental results show that the proposed approach could achieve RMSE of(0.003018),MAE of(0.001871),and MBE of(0.000205).These values are better than those of the other competing models.

关键词： Metamaterial antenna long short term memory(LSTM) guided whale optimization algorithm(Guided WOA) adaptive dynamic particle swarm algorithm(AD-PSO)

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Image Contour Analysis in Local Coordinates

Image Contour Analysis in Local Coordinates

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IEEE International Workshop on Intelligent Data Acquisition and Advanced computing systems: Technology and Applications

作者： O.M. Berezsky K.M. Berezska O.P. Adamiv Department of Information Computing Systems and Control Ternopil National Economic University Ternopil Ukraine

The article is devoted to the analysis of an image contour, the algorithms of contours characteristic points determination and algorithms of contours approximation in local coordinates on the example of tumours cells ... 详细信息

关键词： Image analysis Image segmentation Tumors Biomedical imaging Medical diagnostic imaging Approximation algorithms Image recognition Image processing Conferences Data acquisition

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An Intelligent Method for Recognizing Real and Generated Ukrainian-Language Voices

An Intelligent Method for Recognizing Real and Generated Ukr...

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Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Khrystyna Lipianina-Honcharenko Dmytro Lendiuk Adam Ivaniush Gena Boguta Mariana Soia Khrystyna Yurkiv Department for Information-Computing Systems and Control West Ukrainian National University Ternopil Ukraine

ISBN: (数字)9798350384499

ISBN: (纸本)9798350384505

The modern development of speech synthesis technologies and convolutional neural networks (CNN) creates new opportunities and challenges in the field of voice recognition. One of the key tasks is to ensure the security and authenticity of audio information, especially in the context of information warfare and disinformation campaigns. In this context, the ability to recognize and identify generated voices becomes particularly important. This study aims to develop an intelligent method for recognizing real and generated Ukrainian-language voices using convolutional neural networks. The proposed method is based on the careful collection and preparation of data, the development and training of a CNN model, and its validation on test samples. Special attention is paid to ensuring the balance of the dataset, which is crucial for preventing model bias and improving its ability to generalize to unknown data. The model shows high performance in detecting real and generated voices, making this approach useful for local applications, particularly in Ukraine.

关键词： Training Accuracy Video on demand Speech recognition Mathematical models Data models Convolutional neural networks Web sites Speech synthesis Fake news

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Reliability improvement and reliability assessment for distributed hardware-software multi-agent systems

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WSEAS Transactions on Computers 2014年 13卷 670-690页

作者： Igumnov, Alexei V. Saradgishvili, Sergey E. Information and Control Systems Department Institute of Computing and Control Saint-Petersburg State Polytechnical University 29 Polytechnicheskaya Street Saint-Petersburg Russia

The problem of reliability of new object of distributed hardware software (DHS) multi-agent system (MAS) is considered. DHS MAS is determined as a system that is based on agent technologies and consists of both agents and hardware components required for execution of agents and for interaction of agents with an environment. Reliability improvement, fault-recovery and several reliability assessment approaches for DHS MAS are presented. The reliability improvement methodology is built upon replication of unique functional components and redundancy of universal components. The fault-recovery methodology defines a set of fault-recovery procedures required for restoration of consistent system configuration after failures of its components. Methodology for operability function formation was developed to enable utilization of logical-and- probabilistic methods for reliability assessment. Another approach for reliability assessment is based on Markovian model and system state graph and was developed to overcome limitations of logical-andprobabilistic methods that are suitable only for systems with hot standby. The state graph based approach allows reliability assessment for DHS MAS with cold standby and different operating modes of system components. The state graph based approach is also applicable for a case when probability of failure of one of components depends on states of other components. New failure model for determination of failure rates of system components in accordance with system state is introduced. computing experiments described in the article have validated developed methodologies.

关键词： Multi agent systems

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