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IEEE international conference on Future Internet of things and Cloud Workshops (FiCloudW)

作者： Gennady Krivulya Inna Skarga-Bandurova Zakhar Tatarchenko Olena Seredina Maryna Shcherbakova Eugene Shcherbakov Design Automation Department Kharkiv National University of Radio Electronics Kharkiv Ukraine Computer Science and Engineering Department V. Dahl East Ukrainian National University Severodonetsk Ukraine International Cooperation Department V. Dahl East Ukrainian National University Severodonetsk Ukraine

ISBN: (数字)9781728144115

ISBN: (纸本)9781728144122

An overview of the fault detection strategies, faults and failures related to Wireless Sensor Network (WSN) levels is provided. the recent research contributions to functional diagnostics of WSN were summarized. An adaptive neuro-fuzzy inference system ANFIS for intelligence diagnostics of WSN is proposed. the solution of the task of functional diagnostics is realized by the expert system with a knowledge base in the form of a neuron-fuzzy network. Neural-fuzzy network has been applied to the sensor nodes. Employing proposed techniques in WSN showed that ANFIS algorithm enables to improve the efficiency and accuracy of sensor node diagnosis.

关键词： wireless sensor network WSN failure detection diagnostic parameters neural network ANFIS fault tolerance Wireless sensor networks WSN gene Defect detection Fault tolerance Neural network Expert System Knowledge Bases

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Multiple-signal Synchronous Change-point Detection by Piecewise Linear Regression with Group Lasso Constraints

Multiple-signal Synchronous Change-point Detection by Piecew...

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international conference on Industrial Engineering and Applications (ICIEA)

作者： Lining Yang Yanting Li Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9781728167855

ISBN: (纸本)9781728167862

this paper studies the synchronous multiple change-point detection problem involving multiple signals. the original signals are fitted by a piecewise linear regression with Group Lasso constraints to ensure the synchronism of the change points. then, first-order difference is used to determine the candidate set of change points for the resultant fitted curve, and then the Bayesian information criterion (BIC) is utilized to determine change points from the candidate set. Monte Carlo simulation-based experiments are used to compare the new method with three commonly-used multi-signal synchronous change-point detection methods. the results show that the proposed method is superior in detecting both the number and the position of change points. the performance in real multiple vibration signals of cutting tools data further verifies the effectiveness of the method.

关键词： Synchronization Linear regression Bayes methods Dynamic programming Vibrations Cutting tools Industrial engineering

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Composite cis-acting epigenetic switches in eukaryotes:: lessons from Drosophila Fab-7 for the Igf2-H19 imprinted domain

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GENETICA 2003年第2期117卷 199-207页

作者： Brown, JP Singh, PB Cowell, IG Roslin Inst Edinburgh Nucl Programming Lab Div Gene Express & Dev Roslin EH25 9PS Midlothian Scotland

One of the central problems of eukaryotic gene regulation is to understand the mechanism(s) by which the activity of enhancer elements is circumscribed such that they only act upon their cognate promoter sequences. Studies on the bithorax gene complex (BX-C) in Drosophila have highlighted the potential problem of enhancer promiscuity and detailed molecular and genetic analyses are now providing insight into how this gene complex resolves the problem through the activity of boundary/silencer elements that can block the communication between enhancers and promoters. Analysis of the mouse Igf2-H19 imprinted locus also suggests a role for boundary/silencer elements, but in this case these elements are invoked to account for the preferential expression of Igf2 and H19 from the paternally and maternally inherited chromosomes respectively despite the presence of functional downstream enhancers. We discuss recent work that has illuminated both of these systems and consider what parallels exist between them.

关键词： boundary epigenetics parental imprinting Polycomb-group silencer

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Inverse Design Based on Time Reversal Differentiation of FDTD

Inverse Design Based on Time Reversal Differentiation of FDT...

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IEEE international conference on Electronic Information and Communication Technology (ICEICT)

作者： Yihao Li Heng Zhong Ke Xu Ming Fang School of Electronic and Infomnation Engineering Anhui University Hefei China

ISBN: (数字)9798350384437

ISBN: (纸本)9798350384444

In this paper, a gradient calculation method based on the direct differential (DD) of the finite-difference time-domain (FDTD) algorithm is presented. Based on the DD FDTD, we introduce the technical process for inverse design problems, including optimization parameters and objective functions. Compared with the adjoint variable method (AVM) and the automatic differentiation (AD), this method has the lowest computational cost. Meanwhile, we can define objective functions in both frequency- and time-domain, which makes the proposed method more flexible for broadband inverse design problems. We apply the proposed inverse design approach to design a terahertz wavelength division multiplexer (WDM).

关键词： Time-frequency analysis Wavelength division multiplexing Linear programming Prediction algorithms Mathematical models Information and communication technology Time-domain analysis

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MSoln-PSO: Searching for Multiple Solutions and Numerically Verifying the Riemann Hypothesis

MSoln-PSO: Searching for Multiple Solutions and Numerically ...

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Advanced Algorithms and Control Engineering (ICAACE), international conference on

作者： Enlong Shang School of Mathematics and Statistics Wuhan University Wuhan China

ISBN: (数字)9798350361445

ISBN: (纸本)9798350361452

We introduce MSoln-PSO, a modified Particle Swarm Optimization algorithm aimed at overcoming limitations in finding singular optimal points. By adapting the social component to steer towards the closest leading particle, it discovers multiple optimal points simultaneously, utilizing high-fitness particles as leads or past-iteration particles that fit the criteria. Applying MSoln-PSO to the zeros of the zeta function within the [0, 500] imaginary interval yields all 269 zeros, showcasing its robustness in multi-solution searches. Remarkably, all solutions have a real part of 1/2, verifying the Riemann hypothesis numerically. Furthermore, MSoln-PSO's versatility extends to finding points where the objective function meets any given conditions. Particulary,it can also efficiently identifies points where the function value falls below a defined threshold, showcasing its strong capability in various fields.

关键词： Control engineering Linear programming Search problems Robustness Particle swarm optimization

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the Optimization of Hyperparameter Based on Mathematics for Gradient Descent Algorithm

The Optimization of Hyperparameter Based on Mathematics for ...

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international conference on Circuit, Power and Computing Technologies (ICCPCT)

作者： Abel C. H. Chen Information & Communications Security Laboratory Chunghwa Telecom Laboratories Taoyuan Taiwan

ISBN: (数字)9798350372816

ISBN: (纸本)9798350372823

Gradient descent algorithms are widely considered the primary choice for optimizing deep learning models. However, they often require adjusting various hyperparameters, like the learning rate, among others. these hyperparameters significantly impact both the speed of convergence and the accuracy of the solution. thus, this study introduces an analytical framework that uses mathematical models to assess the mean error of each objective function concerning gradient descent algorithms. Additionally, this framework aims to identify the most effective hyperparameter values by minimizing the mean error. By analyzing optimization models, generalized principles have been established for setting hyperparameter values. Empirical results demonstrate that our proposed method achieves superior convergence efficiency and reduced errors compared to existing approaches.

关键词： Deep learning Computers Accuracy Optimization models Computational modeling Linear programming Integrated circuit modeling

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A New Mathematical Model to Minimize Penalty Costs for a Single Machine with an Overtime Constraint

A New Mathematical Model to Minimize Penalty Costs for a Sin...

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international conference on Industrial Engineering and Applications (ICIEA)

作者： Watchara Songserm Teeradej Wuttipornpun Rajamangala University of Technology Phra Nakhon Bangkok Thailand King Mongkut's University of Technology North Bangkok Bangkok Thailand

ISBN: (数字)9781728167855

ISBN: (纸本)9781728167862

the problem studied in this paper was to schedule jobs in a single machine production system with an overtime constraint. A new mathematical model is now proposed to minimize the total penalty cost, which is described as tardiness, overtime, earliness, and the idle time costs. the proposed math model is capable of improving some impractical overtime concepts, as reported in the literature. the proposed model was evaluated by using a set of hypothetical data that was generated from a new instance generator for scheduling problems named IGSP. Since the proposed math model is classified as NP-hard, the optimal solutions can be determined only for the problem of `up-to-20-jobs' within 120 minutes. Hence, for a large-scale problem, a satisfactory metaheuristic is required, in order to determine a near-optimal solution, within a short computational time.

关键词： Mathematical model Job shop scheduling Modeling Linear programming Industrial engineering Processor scheduling

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Comparison of Modern Customizable Code Visualization Tools

Comparison of Modern Customizable Code Visualization Tools

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Software and System Engineering (ICoSSE), international conference on

作者： Attila Gyén Norbert Pataki Department of Programming Languages and Compilers Eötvös Loránd University Budapest Hungary

ISBN: (数字)9798350386592

ISBN: (纸本)9798350386608

abstract-Nowadays, visualization is one of the most important things an integrated development environment or any smart code editor needs to have. there are several different options when it comes to the visualization. It plays a crucial role in software development and has several important benefits, like understanding the code structure, debugging, or troubleshooting. Code visualization enhances developer productivity, facilitates collaboration, and contributes to the maintainability and scalability of software projects. It is an essential aspect of modern software development practices. In this paper, we focus on one of the most widely used code editors - Visual Studio Code - and on a core component that drives the Visual Studio Code called Monaco Editor, mainly on how they can visualize different sections of a code and their complexity when it comes to visualization. Source code visualization refers to representing code visually to enhance understanding, analysis, and communication of software systems.

关键词： Productivity Visualization Codes Source coding Scalability Systems engineering and theory Software systems

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Parameter Space Reduction Based L2-norm Noise Constrained Estimation for Image Restoration

Parameter Space Reduction Based L2-norm Noise Constrained Es...

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international conference on Informative and Cybernetics for Computational Social Systems (ICCSS)

作者： Yu Guan Min Gan Guang-Yong Chen The College of Mathematics and Computer Science Fuzhou University Fujian China The College of Computer Science and Technology Qingdao University Qingdao China The Faculty of Science and Technology University of Macau Macau China

ISBN: (数字)9781728162461

ISBN: (纸本)9781665419352

In this paper, the image restoration is formulated as an l 2 -norm noise constrained estimation problem. Realizing that the constrained optimization problem is a separable nonlinear least squares problem, we eliminate a part of the parameters from the objective function using the idea of variable projection algorithms. then, the gradient projection method is used to optimize the reduced parameter space problem. the numerical experiments on image restoration illustrate that the proposed methodology accelerates the convergence rate significantly.

关键词： Digital images Estimation Linear programming Image restoration Projection algorithms Optimization Convergence

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An Improved BP Neural Network Anomaly Detection Method

An Improved BP Neural Network Anomaly Detection Method

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international conference on Information Systems and Computer Aided Education (ICISCAE)

作者： Long Zhang School of Information Engineering Xi'an Eurasia University Xi'an Shaanxi China

ISBN: (数字)9798350350760

ISBN: (纸本)9798350350777

the difficulty that the classical anomaly detection system based on BP neural network is that the convergence speed is too slow and the objective function falls into the local minimum problem. the established network genetic traffic detection model has low detection efficiency and accuracy. this article improves through a hybrid encoding method, while optimizing and modifying parameters such as crossover operator, mutation operator, crossover probability, and mutation probability. Based on this, this article proposes an genetically optimized BP neural network model by analyzing the structure of traditional neural network anomaly detection models. the research results show that the proposed algorithm overcomes the problem of slow training speed in traditional neural network anomaly detection and has better detection performance than traditional algorithms.

关键词： Training Analytical models Neural networks Intrusion detection Linear programming Genetics Feature extraction Encoding Anomaly detection Information systems

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