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检索条件"丛书名=Lecture Notes in Networks and Systems"

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Autoadaptive networks of Coherent Domains for "Intelligent" Quantum Computation and Quantum Information

Autoadaptive Networks of Coherent Domains for "Intelligent" ...

引用

Intelligent systems Conference (IntelliSys)

作者： Caligiuri, Luigi Maxmilian Fdn Phys Res Ctr FoPRC I-87100 Cosenza IT Italy

ISBN: (纸本)9783031477201;9783031477218

It has been shown that liquid water can be considered as two-phases system composed of a coherent phase, in which the molecules oscillate in tune with an electromagnetic field within macroscopic regions called "coherent domains" and non-coherent vapor-like fraction, including uncorrelated molecules. Furthermore, such domains, due to the coherent dynamics, are the pools of quasi-free electrons forming cold coherent vortices upon an energy intake from the outside. Such electrons, in turn, form a plasma that, under suitable conditions, can itself become coherent and oscillate in tune with electromagnetic fields trapped inside it. We will show in this paper that if two or more plasma contained in water coherent domains interact each other, they can adaptively self-adjust their own oscillations in order to synchronize so creating a network of coherent domains oscillating in tune. Depending on the system's parameters, different clusters of coherent domains, at different space-time scales, can appear. We finally show how this feature could be exploited and used to realize novel advanced quantum information and computational systems and quantum neural networks.

关键词： QED coherence in matter Water Quantum computation Synchronization Quantum information

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Adapting Russian Higher Education to Global Trends: The Growing Importance of Data Mining and English Language 13th

Adapting Russian Higher Education to Global Trends: The Grow...

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13th Computer Science Online Conference

作者： Tsilenko, Lyubov Petrovna Ashrafi, Arifa Mokhnachev, Victor Sergeevich Moscow Polytech Univ Moscow 107023 Russia

ISBN: (纸本)9783031702846;9783031702853

This research explores the major challenges to the Russian Higher Education system. The paper articulates how easily the future specialist could adjust to the international work market and address the challenges in the best way possible to further advancement and prosperity of Russia with quality training and advanced technologies. In attempting to make sense of these issues, the study contemplates a new scheme of educational content that aims to increase the use of data mining techniques related to prediction analysis and the English language's potential. By leveraging data mining, educators can gain valuable insights into student performance, learning outcomes, and educational patterns. This enables them to identify areas for improvement and tailor educational programs to meet the demands of the global job market. The proposed methodology also looked into ways to select the best data mining methods to predict future global trends related to educational qualifications. A Comparative study and analysis among Russian students from different universities has taken place to understand the effectiveness of the proposed methods to enhance goal-oriented professional competency.

关键词： Data Mining English Language Global Trend Regression Analysis Russian Higher Education Knowledge discovery from data Data Classification

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Machine Learning Modeling for Shape Parameter c in MQ-RBF Applied to Burgers' Equations

Machine Learning Modeling for Shape Parameter c in MQ-RBF Ap...

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International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Geridonmez, Bengisen Pekmen Kayabasi, Merve TED Univ Dept Math TR-06420 Ankara Turkiye

ISBN: (纸本)9783031700170;9783031700187

The main goal of this study is to model the shape parameter of multiquadric radial basis function (RBF) by using neural networks. The data for modeling is obtained from the numerical results. The one and the two dimensional Burgers' equations are numerically concerned by multiquadric radial basis function (RBF) in space derivatives and by the second order backward differentiation formula in time derivatives. In the chosen equations having analytical solution, dependence of shape parameter to the problem parameters and the number of grid points is taken into account. Then, the shape parameters in an interval are performed in different combination of independent parameters, and the shape parameter associated with the smallest relative error is saved with independent parameters. By means of the data obtained by this way, shape parameter as a function of independent variables is modeled by neural networks. This model enables one to determine the shape parameter without performing any numerical control repeatedly in the considered problem. This approach is firstly proposed for finding an appropriate shape parameter in a specific important physical problem.

关键词： multiquadric radial basis function shape parameter ,Burgers' equations neural networks

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A Fuzzy Approach to Macroeconomic Stability 1

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International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Georgescu, Irina Kinnunen, Jani Bucharest Univ Econ Bucharest Romania Abo Akad Univ Turku Finland

ISBN: (数字)9783031671951

ISBN: (纸本)9783031671944;9783031671951

In this paper, we evaluate the macroeconomic stability of Romania from 2012 to 2023 by means of a fuzzy rule-based system (FRBS). The input variables are inflation rate (IR), unemployment rate (UR), GDP growth (GDPG) and net inflows of foreign direct investments (FDI), while the response variable is the macrostability. All variables are expressed from a scale from 1 to 5, while 1 represents extreme instability and 5 represents maximal stability. By means of this fuzzy rule-based system we reach the conclusion that in 2023 Romanias macroeconomic stability is evaluated at 1.5 on the scale from 1 to 5.

关键词： fuzzy rule-based system macroeconomic stability economic growth defuzzification

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An Optimized Diagnostic Precision Using Genetic Algorithm in Breast Cancer 8th

An Optimized Diagnostic Precision Using Genetic Algorithm in...

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Arivubrakan, P. Kujani, T. Deekshitha, Kandrathi Vel Tech Rangarajan Dr Sagunthala R&D Inst Sci & Chennai 600062 India

ISBN: (纸本)9789819713288;9789819713295

The machine learning-based optimization is the most popular research nowadays which provides the best solution among set of all possible solutions. Breast cancer stands as frequent noticed cancer and a primary reason for demise of women on a global scale. The analysis delves into the efficacy of genetic algorithms (GAs) for feature selection, presenting compelling results from our proposed model. Comprehensive evaluations utilizing various GA-based classifiers including the Random Forest, Logistic, K-nearest neighbors, Linear SVM, Gradient Boosting, Radial SVM, AdaBoost, and Decision Tree classifier were performed to assess their effectiveness in feature selection for breast cancer diagnosis. The experimental outcomes highlight a substantial improvement in the classifier's accuracy score following feature selection. Notably, this enhancement extends to both specificity and sensitivity, affirming the potential of our methodology to significantly elevate the accuracy of breast cancer diagnosis. The accuracy of the Random Forest classifier is 97.2%, which is the finest precision obtained by the GA-based classifier. This research paper contributes valuable insights into the application of genetic algorithms for feature selection and their impact on refining diagnostic outcomes in breast cancer.

关键词： Accuracy Genetic algorithm Classifiers Optimization

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A Community Security Operations Centre (ComSOC) Model for SMMEs in Developing Countries

A Community Security Operations Centre (ComSOC) Model for SM...

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Computing Conference

作者： Ntingi, Nombeko du Toit, Jaco von Solms, Sebastiaan Univ Johannesburg Johannesburg South Africa

ISBN: (纸本)9783031622793;9783031622779;9783031622762

Cybercriminals may target small, medium, and micro enterprises (SMMEs) as entry points to large enterprises through violations of third-party supply chain rules. Due to a lack of financial and human resources, SMMEs are often compelled to outsource their cybersecurity needs to third-party cybersecurity service providers. To mitigate cyber-attacks or eliminate the possibility of being the weakest link in the value chain, SMMEs need to collaborate and share resources. Our central contention is that SMMEs in developing countries lack resources, such as financial and human capital, to implement emerging or advanced cybersecurity solutions. This paper explores the Community Security Operations Centre (ComSOC) model for SMMEs in developing countries. The ComSOC model is our proposed cybersecurity solution for SMMEs in developing countries. This model seeks to adapt or tailor-make the SOCservices according to the specific needs of the SMMEs that intend to utilise advanced SOC services but lack the necessary resources to do so. Therefore, this paper's primary objective and outcome are to conceptualise the ComSOC model for SMMEs in developing countries. This model will serve as a guideline for SMMEs in developing countries to implement emerging or advanced cybersecurity solutions adapted to their specific needs, allowing SMMEs who could not otherwise afford to utilise the large enterprise SOC services. The sharing of resources will enable the SMMEs to implement these SOC services while minimising the cost of implementation.

关键词： Community SOC SMMEs Sharing of resources Homogeneous

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Track Learning Agent Using Multi-objective Reinforcement Learning 1

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4th Congress on Intelligent systems (CIS)

作者： Shah, Rushabh Ruparel, Vidhi Prabhu, Mukul D'mello, Lynette Dwarkadas J Sanghvi Coll Engn Mumbai Maharashtra India

ISBN: (数字)9789819990375

ISBN: (纸本)9789819990368;9789819990375

Reinforcement learning (RL) enables agents to make decisions through interactions with their environment and feedback in the form of rewards or penalties. The distinction between single-objective reinforcement learning (SORL) and multi-objective reinforcement learning (MORL) is established, emphasizing the latter's ability to optimize multiple conflicting objectives simultaneously. The study explores various algorithms and approaches within the MORL framework, focusing on track navigation optimization. Key components of the implementation are detailed, including states, actions, rewards, and tracks used for training. The proposed algorithm, Pareto Q-learning, is highlighted as a powerful approach to simultaneously optimize multiple objectives. The architecture and methodology of the learning agent are presented, outlining the training process and the impact of hyper-parameters. Results from experimentation are discussed, revealing the agent's learning curve, crash avoidance, and successful achievement of multiple objectives. The study underlines the significance of MORL in enabling agents to manage complex decision-making scenarios, leading to more robust and optimal policies. The paper concludes by emphasizing the practical implications of the MORL approach in navigating challenging tracks with conflicting goals, such as minimizing steps, maximizing rewards, and avoiding collisions.

关键词： Reinforcement learning Vector reward system Multi-objective reinforcement learning Pareto Q-learning

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Blockchain Adoption in Education with Enhancing Data Privacy 12th

Blockchain Adoption in Education with Enhancing Data Privacy

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12th World Conference on Information systems and Technologies (WorldCIST)

作者： Abdullah, Khadeejah Saleh, Kassem Manuel, Paul Kuwait Univ Kuwait Kuwait

ISBN: (纸本)9783031602207;9783031602214

Blockchain technology adoption has influenced several fields, including healthcare, financial, and supply chain systems. Lately, this technology has expanded its application in education because of its unique attributes, which are decentralization, immutability, consensus, and security. Despite the bright side of centralized credentialing and implementation, there are some challenges that need to be addressed. Thus, a comprehensive literature review of the reasons that blockchain adoption in education field is considered necessary and effective. To do so, we investigate and explore the benefits and gaps of decentralized credentialing systems that are utilized to securely issue, verify, and share digital credentials such as grades, degrees, diplomas, and certificates through simulation of blockchain and smart contract embedded logic. In this paper, we focus on two major themes: adoption of blockchain in education and enhancing the data privacy on blockchain through means of consensus algorithm. We express and analyze the results conducted as experimental simulations by stakeholders which are university administrations, professors, and students, when combining the two themes to propose a solution in terms of trust and adoption to enhance the privacy and security of student learning data and maintain individual privacy rights. we have discussed the methodology which is Design Science Research (DSR) and evaluated the results to emphasize on the significance of blockchain in education. We believe there is future work in enhancing the logic and validation of smart contract through means of hashing and cryptography.

关键词： Blockchain Smart Contract Consensus Hash Distributed Ledger Timestamp Immutability P2P

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Computing VUCA Way

Computing VUCA Way

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Computing Conference

作者： Fukuda, Shuichi Keio Univ Syst Design & Management Res Inst 3-9-33-3910KohanMinato Ku Tokyo 1080075 Japan

ISBN: (纸本)9783031622755;9783031622731;9783031622724

The word "VUCA" is getting wide attention. The real world comes to change everyminute today and we need to prepare ourselves for the inexperienced situations. Traditionally, our computing has been based on 0-1 basis digital computing. Datasets are required to be orthonormal and distance is interval-based. But today, information is composed of a wide variety of elements and thus the idea of VUCA emerged. But we have no other tool than our instinct to cope with such situation. Thus this proposes instinct support tool "Mahalanobis Distance-Pattern (MDP)". MahalanobisDistance is ordinal scale, so we can prioritize our decisions. In short, in the technology-driven Industrial Society, wewere treated as consumers, and we went deeper and deeper. But the Industrial Society is getting close to its end. And many issues emerged such as excessive use of energy, etc. We cannot sustain such society anymore. Interestingly enough, Self-Determination Theory '(SDT)' was published in the same year 1985 as VUCA. SDT demonstrates, we, humans, get the maximum happiness and the feeling of achievement when we do the job internally motivated and self-determined. We, humans, alone can think about the future and we would like to make our dreams come true. It is a challenge. Thus, MDP is proposed and the importance of simplifying technology is emphasized so that everybody can enjoy creating a world of "Self".

关键词： VUCA computing Analog Instinct support

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Comparative Lightweight Scheme for Individual Identification Through Hand-Vein Patterns 1

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Intelligent systems Conference (IntelliSys)

作者： Mejia-Herrera, Mateo Botero-Valencia, Juan S. Hernandez-Garcia, Ruber Inst Tecnol Metropolitano Fac Ingn Grp Sistemas Control & Robot Medellin Colombia Inst Univ Envigado Grp Invest Sistemas Informt Envigado Colombia Univ Catolica Maule Res Ctr Adv Studies Maule CIEAM Talca Chile

ISBN: (数字)9783031477218

ISBN: (纸本)9783031477201;9783031477218

Biometric characterization systems are generally used in safety-related applications because they allow the identification or verification of individuals based on human body traits. In recent years hand veins have become an attractive biometric trait due to their advantages compared with other classical biometric traits (i.e., fingerprints, iris, face). However, due to the number of possible architectures for feature extraction and individual identification, different combinations between such methods should be evaluated to give a baseline for further vein biometrics development. This work presents a comparative analysis for individual identification based on hand-vein biometrics, which combines four feature extraction techniques and three classic machine learning techniques using two main types of images. The results show the reliability of some combinations for hand-vein biometric identification achieving accuracy levels above 98% and an Equal Error Rate under 3.2%.

关键词： Hand-Veins Vein feature extraction Biometric systems Machine learning

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