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6th International Conference on Inventive Computation Technologies (ICICT)

作者： Arulmurugan, A. Waris, Saiyed Faiayaz Bhagyalakshmi, N. Vignans Fdn Sci Technol & Res Deemed Univ Dept Comp Sci & Engn Guntur 522213 Andhra Pradesh India

ISBN: (纸本)9781728185019

A wireless network is one of the emerging domains in the field of Computer Science. This domain solves the issue of the cost of laying cables in colleges and organizations. It makes help of radio waves to connect laptops, Smartphones to the Internet. One of the sub-areas of the cellular network is Wireless Sensor Network. As the name suggests wireless sensor network makes use of the sensor. These sensors are used to detect some phenomena and based on the phenomena information will be gathered. Clustering is a process by which sensor nodes in WSN are grouped based on some criteria. In general, each and every cluster will have a Cluster head that is selected based on election algorithms. This paper gives a detailed survey of the list of important CH selection algorithms that are available for selecting a group head in a group and it tries to focus more upon analyzing the drawbacks faced in the literature. This is going to be effective enough in creating a suitable cluster head selection mechanism for enhancing the lifetime of the network.

关键词： Wireless Sensor Networks Clustering Cluster head selection algorithm

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Reduce Training Error of Extreme Learning Machine by Selecting Appropriate Hidden Layer Output Matrix

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Journal of Systems Science and Systems Engineering 2021年第5期30卷 552-571页

作者： Yang Lv Bang Li Jinghu Yu Yiming Ding School of Science Wuhan University of TechnologyWuhan 430070China Center for Mathematical Sciences Wuhan University of TechnologyWuhan 430070China

Extreme learning machine(ELM)is a feedforward neural network with a single layer of hidden nodes,where the weight and the bias connecting input to hidden nodes are randomly *** output weight between hidden nodes and outputs are learned by a linear *** is interesting to ask whether the training error of ELM is significantly affected by the hidden layer output matrix H,because a positive answer will enable us obtain smaller training error from better *** single hidden layer feedforward neural network(SLFN)with one input neuron,there is significant difference between the training errors of different *** find there is a reliable strong negative rank correlation between the training errors and some singular values of the Moore-Penrose generalized inverse of *** on the rank correlation,a selection algorithm is proposed to choose robust appropriate H to achieve smaller training error among numerous *** experiments are carried out to validate the selection algorithm,including tests on real data *** results show that it achieves better performance in validity,speed and robustness.

关键词： ELM SLFNs training error Moore-Penrose generalized inverse selection algorithm

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Stall Model Identification of a Cessna Citation II from Flight Test Data Using Orthogonal Model Structure selection

Stall Model Identification of a Cessna Citation II from Flig...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech Forum)

作者： van Ingen, Joost B. de Visser, Coen C. Pool, Daan M. Delft Univ Technol Fac Aerosp Engn Control & Simulat Sect POB 5058 NL-2600 GB Delft Netherlands

ISBN: (数字)9781624106095

ISBN: (纸本)9781624106095

Since 2019, a key element of simulator-based training of airline pilots is stall training. A major and still largely open research question is which level of model fidelity is required for effective training. As part of an effort to answer this question, a model of the quasi-steady stall dynamics of a Cessna Citation II aircraft is identified from flight test data that was specifically collected for this research at an altitude of 5,500 m. To ensure any reductions in elevator and aileron effectiveness during stall were also explicitly measured, the test pilots used additional quasi-random flight test inputs. The considered stall model structure is based on Kirchoff's theory of flowseparation. During identification, the nonlinear and linear parameters of the model are estimated in separate, recursively executed, steps. This separation enables the application of a semi-objective model structure selection method using multivariate orthogonal functions for the aerodynamic coefficients included in the model. This approach shows that stall-related effects should be included in the model equations for lift, drag, and pitch moment. Overall, it is found that the model parameters were consistently estimated from the flight test data and that the model accurately describes the aircraft's stall dynamics in the considered flight condition. The developed methodology is concluded to be well-suited for the direct identification of stall models from flight test data.

关键词： Cessna Citation II Flight Test Instrumentation Control Surfaces Aerodynamic Force Coefficients Flow Separation Test Pilots Lift Coefficient Flight Data selection algorithm Flight Envelope

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Feature selection, Clustering, and Prototype Placement for Turbulence Data Sets

Feature Selection, Clustering, and Prototype Placement for T...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech Forum)

作者： Barone, Matthew Ray, Jaideep Domino, Stefan Sandia Natl Labs Aerosci Dept Albuquerque NM 87185 USA Sandia Natl Labs Extreme Scale Data Sci & Analyt Dept Albuquerque NM 87185 USA Sandia Natl Labs Computat Thermal & Fluid Mech Dept Albuquerque NM 87185 USA

ISBN: (数字)9781624106095

ISBN: (纸本)9781624106095

This paper explores unsupervised learning approaches for analysis and categorization of turbulent flow data. Single point statistics from several high-fidelity turbulent flow simulation data sets are classified using a Gaussian mixture model clustering algorithm. Candidate features are proposed, which include barycentric coordinates of the Reynolds stress anisotropy tensor, as well as scalar and angular invariants of the Reynolds stress and mean strain rate tensors. A feature selection algorithm is applied to the data in a sequential fashion, flow by flow, to identify a good feature set and an optimal number of clusters for each data set. The algorithm is first applied to Direct Numerical Simulation data for plane channel flow, and produces clusters that are consistent with turbulent flow theory and empirical results that divide the channel flow into a number of regions (viscous sub-layer, log layer, etc). Clusters are then identified for flow over a wavy-walled channel, flow over a bump in a channel, and flow past a square cylinder. Some clusters are closely identified with the anisotropy state of the turbulence, as indicated by the location within the barycentric map of the Reynolds stress tensor. Other clusters can be connected to physical phenomena, such as boundary layer separation and free shear layers. Exemplar points from the clusters, or prototypes, are then identified using a prototype selection method. These exemplars summarize the dataset by a factor of 10 to 1000. The clustering and prototype selection algorithms provide a foundation for physics-based, semi-automated classification of turbulent flow states and extraction of a subset of data points that can serve as the basis for the development of explainable machine-learned turbulence models.

关键词： Turbulence Turbulent Flow Reynolds Stress Gaussian Mixture Models Boundary Layer Separation Direct Numerical Simulation selection algorithm Strain Rate Tensor Turbulence Models

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Hybrid Discontinuous Galerkin/Finite Volume Method with Subcell Resolution for Shocked Flows

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AIAA JOURNAL 2021年第6期59卷 2027-2044页

作者： Jiang, Zhen-Hua Deng, Xi Xiao, Feng Yan, Chao Yu, Jian Lou, Shuai Beijing Univ Aeronaut & Astronaut Coll Aeronaut Sci & Engn Beijing 100191 Peoples R China Imperial Coll London Dept Aeronaut London SW7 2AZ England Tokyo Inst Technol Dept Mech Engn Meguro Ku 2-12-1 i6-29 Ookayama Tokyo 1528550 Japan

A hybrid discontinuous Galerkin (DG)/finite volume (FV) method under the multistage boundary variation diminishing (BVD) reconstruction paradigm is developed for shocked inviscid and viscous flows. The methodology uses high-order unlimited polynomials and the THINC (which stands for tangent of hyperbola for interface capturing) function as the candidate reconstruction functions to perform FV computation on embedded subcells. The reconstruction scheme on the FV subcells can be designed in a way to keep the resulting approach as compact as the underlying DG method. The reconstruction information based on the modified BVD selection algorithm has been applied as an indicating strategy so that no additional discontinuity indicator is required for the hybrid DG/FV computation. The designed approach has been investigated through the coupling with the explicit and implicit time discretization scheme for both inviscid and viscous flows. Numerical results demonstrate the high-fidelity characteristics of the method by using a much coarser grid to capture both the discontinuity and the smooth flow structure with high resolution.

关键词： Numerical Integration Hypersonic Flows Finite Volume Method selection algorithm Total Variation Diminishing Mach Reflection Mach Number Vortices Euler Equations Conductivity Coefficients

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A selection algorithm for firewall in distributed environment

A selection algorithm for firewall in distributed environmen...

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ICINS 2014 - 2014 International Conference on Information and Network Security

作者： Liangjia Fu Chunhe Xia Xiaochen Liu Jinghua Gao Software College Beihang University Beijing China Beijing Key Laboratory of Network Technology School of Computer Science and Engineering Beihang University China

ISBN: (纸本)9781510804289

In a distributed network, there are multiple routing paths between source node and destination node. In order to meet certain demands of network security, selecting required firewalls in multiple routing paths and deploying appropriate rules on them are indispensable steps. Thus, in this paper, we carry on a further research on it and propose permit and deny algorithms which serve to improve the performance of network security. Then, we give theoretical proof of our algorithms. Finally, we test the effectiveness of algorithms based on a network simulation platform named mininet. The analysis of time efficiency of our algorithms and previous algorithms, as well as the comparison between them prove the high efficiency of our algorithms.

关键词： deny firewall permit simple path Permit firewalls (computers) selection algorithm Multiple Routing Network security Trachinotus falcatus algorithms DENY time efficiency DISTRIBUTED NETWORKS

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Predicting the Protein Tertiary Structure by Hybrid Clonal selection algorithms on 3D Square Lattice

Predicting the Protein Tertiary Structure by Hybrid Clonal S...

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International Conference on Modern Problems of Radio Engineering, Telecommunications and Computer Science

作者： Iryna Fefelova Andrey Fefelov Mariia Voronenko Alexander Kornelyuk Anatoliy Sachenko Eduard Ryzhkov Volodymyr Lytvynenko Department Informatics and Computer Science Kherson National Technical University Kherson Ukraine Department of Design Kherson National Technical University Kherson Ukraine Department of Protein Engineering and Bioinformatics Institute of Molecular Biology and Genetics Kyiv Ukraine Reseach Institute for Intelligent Computer Systems Ternopil National Economic University Ternopil Ukraine Department of economic and information security Dnipro State University of Internal Affairs Dnipro Ukraine

ISBN: (数字)9781728155661

ISBN: (纸本)9781728155678

The article considers the task of predicting the tertiary structure of a protein based on its primary sequence. The task of protein folding is solved by searching for conformation with minimal energy, if you look in terms of optimization problem. The work describes the use of a hybrid artificial immune system. In our work we try to combine clonal selection algorithms with differential and trigonometric differential evolution algorithms. We use special coding and decoding methods for individual individuals. The affinity function reduces the number of solutions with self-intersections (incorrect conformations) in the developed hybrid algorithms. We chose the hydrophobic-polar Dill model on a three-dimensional square lattice to test our algorithms. The study shows the advantages of the developed algorithms in comparison with other existing methods using experimental studies of test sequences.

关键词： artificial immune systems biology computing evolutionary computation molecular biophysics optimisation proteins artificial immune systems biology computing evolutionary algorithm molecular biology selection algorithm algorithms Tertiary Protein Structure Clonal selection Proteins

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Validation of an algorithm to Identify Epidermal Necrolysis on a Medico-Administrative Database

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JOURNAL OF INVESTIGATIVE DERMATOLOGY 2024年第3期144卷 708-710.e7页

作者： Bettuzzi, Thomas Hoisnard, Lea Beytout, Quentin Ingen-Housz-Oro, Saskia Sbidian, Emilie Henri Mondor Hosp AP HP Dept Dermatol Creteil France Paris Est Creteil Univ UPEC Epidemiol Dermatol & Evaluat Therapeut EpiDermE Creteil France Henri Mondor Hosp AP HP Tox Bullous Dermatoses & Severe Drug React Referen TOXIBUL Creteil France Henri Mondor Hosp AP HP Univ Hosp Federat FHU TRUE InnovaT theRapy immUne Creteil France Henri Mondor Hosp INSERM Clin Invest Ctr 1430 Creteil France

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Bulk Recycling: Density Separation Models for Mixed Plastic Waste

Bulk Recycling: Density Separation Models for Mixed Plastic ...

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作者： St. Hilaire, Megan Lee University of Rhode Island

学位级别：M.S., Master of Science/Master of Surgery

Microplastic pollution is now everywhere, from the highest elevation of Mount Everest to the deepest dives of the Mariana Trench. The use of synthetic polymers has contributed to the transformation of our modern world. Nonetheless, the growing presence of plastics in the natural environment constitutes a sense of urgency to develop sustainable solutions to address the global plastic pollution crisis. Approximately 80 percent of all the plastics ever produced have been discarded. Our relationship with plastic needs rethinking. Achieving a circular economy requires a holistic approach to redesign the systems that make, use and reuse plastics. Evaluating the life cycle of plastic products is key to effective advancements in the collection, separation and sorting systems of mixed plastic waste streams. This thesis critically reviews bulk recycling methods used in industry. Recycling provides significant opportunities for recovering material resources through mechanical and/or chemical processes, which in return reduces petrochemical usage, greenhouse gas emissions, and the quantity of waste requiring disposal. Yet, recovering the resource value of mixed plastic waste streams presents critical challenges in materials identification and recycling process design. Bulk recycling models consider the selection of the best sequence for isolating target materials from a mixed material stream. This thesis models the separation of single and multiple target materials using density separation techniques to minimize the total processing volume and cost. Furthermore, a selection algorithm is implemented to calculate the processing costs of each pass, determine the minimum cost of separation, and present the optimal separation sequence.

关键词： Circular economy Density separation Plastic waste Process optimization Recycling selection algorithm

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Novel Network selection algorithm Based on Fuzzy Inference

Novel Network Selection Algorithm Based on Fuzzy Inference

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8th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI)

作者： Todinca, Doru Cernazanu-Glavan, Cosmin Univ Politehn Timisoara Dept Comp Timisoara Romania

ISBN: (纸本)9781467364003;9781467363976

In the heterogeneous mobile networks of the future, the mobile users, equipped with multi-mode terminals, will be able to select the radio network that suits best the needs of the mobile user and of the applications running on the mobile terminal. In this work we propose a novel network selection algorithm based on fuzzy inference. Our algorithm permits a prioritization of the users by using different fuzzy rules for each class of users. We investigate by simulation the efficiency of our algorithm and compare its results with an existing network selection algorithm, called consumer surplus.

关键词： selection algorithm Consumers Fuzzy inference Fuzzy logic mobile networking mobile terminal mobile communication Network

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