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6th International Conference on Innovative Computing and Communication, ICICC 2023

作者： Caroline Mary, A. Senthil Kumar, A.V. Saleh, Omar S. Research Scholar Department of Computer Science Hindusthan College of Arts and Science Coimbatore India Assistant Professor Department of Applied Mathematics and Computational Sciences PSGCollege of Technology Coimbatore India Professor and Director Department of MCA Hindusthan College of Arts and Science Coimbatore India Ministry of Higher Education and Scientific Research Baghdad Iraq

ISBN: (纸本)9789819940707

Underwater communications are playing a major role in recent times as underwater happenings have gained interest. Especially in scenarios based on natural calamities like tsunamis, pollution detection, and surveillance, underwater communications are indispensable. Parameters like battery life span and capabilities of sensor nodes play a vital role in the underwater environment. QoS has to be taken care of in underwater communication. Congestion avoidance helps in using energy efficiently in underwater communication. Simulation results prove that this algorithm overcomes the drawback of a normal backpressure-based, static priority algorithm where packet loss, delay, the energy of nodes, and routing overhead are reduced overall, and packet delivery ratio and throughput are increased in special cases of real-time important packets. As underwater nodes are battery-operated, it is essential to have energy-efficient scheduling algorithm. The proposed algorithm solves the drawback of the backpressure algorithm by having energy-efficient queue length stabilizer (QLS) technique, where the backlog is adjusted such that no queues are affected and the energy consumption is less. And real-time packets are treated effectively such that real-time applications can be supported using this scheduling algorithm. The novelty of the proposed method is congestion control methodology with active priority and energy efficiency for an underwater network for effective scheduling of packets where queue backlog size is also adjusted virtually based on energy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Scheduling algorithms

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Multitask Classification of Antimicrobial Peptides for Simultaneous Assessment of Antimicrobial Property and Structural Fold

Multitask Classification of Antimicrobial Peptides for Simul...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Michaela Areti Zervou Effrosyni Doutsi Yannis Pantazis Panagiotis Tsakalides Department of Computer Science University of Crete Heraklion Greece Institute of Computer Science-FORTH Heraklion Greece Institute of Applied and Computational Mathematics-FORTH Heraklion Greece

Antimicrobial peptides (AMPs) play a significant role in guiding drug design, advancing targeted therapies, and cancer treatment research. The function of peptides is highly associated with their three-dimensional structure. AMPs particularly favor alpha-helical structures, or alpha-folds, due to their ability to disrupt the protective layers that surround cells effectively and their structural stability. Existing classifiers mainly identify AMPs but overlook their structural fold which can provide valuable insights into their function. To address this limitation, we introduce an innovative multitask classifier that recognizes AMPs and predicts their alphahelical folds simultaneously. Our approach employs k-mers and Transformer networks for efficient, accurate multitask classification. Results on the datasets indicate comparable performance compared to single-task methods in half the time and complexity.

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Optimizing Blocked-Davidson Method based on Adaptive Algorithm using the New Sunway Supercomputer 2

Optimizing Blocked-Davidson Method based on Adaptive Algorit...

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2022 2nd Conference on High Performance Computing and Communication Engineering, HPCCE 2022

作者： Yang, Chaochao Liu, Anjun Liu, Weifeng Hou, Jie Guo, Meng Shandong Computer Science Center Qilu University of Technology China Jinan Key Laboratory of High Performance Industrial Software China Institute of Applied Physics and Computational Mathematics China Jinan Institute of Supercomputing Technology China

ISBN: (纸本)9781510663374

The Davidson method is a traditional large-scale iterative diagonalization method in computational quantum chemistry. The Blocked-Davidson method is a classical version of the Davidson method, which is an important part of VASP software, occupying 22.9% of the calculation time. When VASP is transplanted to the new Sunway supercomputer, it is incompatible with the many-core heterogeneous environment of Sunway processor. The Blocked-Davidson method does not use slave-core accelerators. This paper designs collaborative computing, double buffer, store variables in slave-core LDM, LDM Level 2 Access, and segmented transmission methods of Blocked-Davidson method based on Sunway many-core architecture. The test results showed that the function in the Blocked-Davidson method accelerated 30.65 times with a single core group in the silica test case. However, negative optimization of the Blocked-Davidson method happens in some test cases such as ZrTiAlVSiN5 and Hg50. Therefore, an adaptive algorithm of automatic selection of less time-consuming optimization paths is designed to solve the negative optimization. The maximum acceleration is 23.6 times compared with not using the adaptive algorithm. © 2023 SPIE.

关键词： Supercomputers

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Combination of Fuzzy Sets and Rough Sets for Machine Learning Purposes (Tutorial – Extended Abstract)

Combination of Fuzzy Sets and Rough Sets for Machine Learnin...

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Federated Conference on computer science and Information Systems (FedCSIS)

作者： Chris Cornelis Henri Bollaert Department of Applied Mathematics Computational Web Intelligence Computer Science and Statistics Ghent University Belgium

Noting the highly complementary characteristics of fuzzy sets and rough sets, Dubois and Prade [7] proposed the first working definition of a fuzzy rough set, and thus paved the way for a flourishing hybrid theory wit...

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Biologically-Informed Shallow Classification Learning Integrating Pathway Knowledge

Biologically-Informed Shallow Classification Learning Integr...

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17th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2024

作者： Voigt, Julius Saralajew, Sascha Kaden, Marika Bohnsack, Katrin Sophie Reuss, Lynn Villmann, Thomas Saxon Institute for Computational Intelligence and Machine Learning University of Applied Sciences Mittweida Mittweida Germany NEC Laboratories Europe GmbH Heidelberg Germany Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence University of Groningen Groningen Netherlands

We propose a biologically-informed shallow neural network as an alternative to the common knowledge-integrating deep neural network architecture used in bio-medical classification learning. In particular, we focus on the Generalized Matrix Learning Vector Quantization (GMLVQ) model as a robust and interpretable shallow neural classifier based on class-dependent prototype learning and accompanying matrix adaptation for suitable data mapping. To incorporate the biological knowledge, we adjust the matrix structure in GMLVQ according to the pathway knowledge for the given problem. During model training both the mapping matrix and the class prototypes are optimized. Since GMLVQ is fully interpretable by design, the interpretation of the model is straightforward, taking explicit account of pathway knowledge. Furthermore, the robustness of the model is guaranteed by the implicit separation margin optimization realized by means of the stochastic gradient descent learning. We demonstrate the performance and the interpretability of the shallow network by reconsideration of a cancer research dataset, which was already investigated using a biologically-informed deep neural network. © 2024 by SCITEPRESS–science and Technology Publications, Lda.

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A Combined VTS/Lazard Quantifier Elimination Method 6

A Combined VTS/Lazard Quantifier Elimination Method

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6th Satisfiability Checking and Symbolic Computation-Square Workshop, SC-Square 2021

作者： Davenport, James H. Tonks, Zak P. Uncu, Ali K. University of Bath Faculty of Science Department of Computer Science Bath United Kingdom Johann Radon Institute for Computational and Applied Mathematics Austrian Academy of Science Altenbergerstraße 69 LinzA-4040 Austria

Many nonlinear optimisation problems involving systems of multivariate polynomial constraints can be expressed as Quantifier Elimination problems. In this regard, the need to eliminate quantifiers presents itself in many real problems such as in economics, mechanics, and motion planning. We focus on using Cylindrical Algebraic Decomposition and Virtual Term Substitution simultaneously. In this paper, we introduce the state-of-the-art theory behind an implementation of these methods produced in collaboration with Maplesoft. © 2021 Copyright for this paper by its authors.

关键词： Motion planning

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Enhancing the Swanepoel method: precise envelope detection of thin-film transmission spectra

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Optics Express 2025年第6期33卷 13376-13400页

作者： Ballester, Manuel Marquez, Almudena P. Lopez-Tapia, Santiago Fernandez, Susana Bass, John Minkov, Dorian Wuersch, Christoph Willomitzer, Florian Marquez, Emilio Katsaggelos, Aggelos K. Computer Science Department Northwestern University EvanstonIL60208 United States Department of Mathematics Faculty of Science University of Cadiz Puerto Real11510 Spain Department of Electrical and Computer Engineering Northwestern University EvanstonIL60208 United States CIEMAT Avenida Complutense 40 Madrid28040 Spain Wyant College of Optical Sciences University of Arizona TucsonAZ85721 United States Sofia1000 Bulgaria Institute for Computational Engineering ICE OST Eastern Switzerland University of Applied Sciences Switzerland Department of Condensed-matter Physics Faculty of Science University of Cadiz Puerto Real11510 Spain

The Swanepoel method is a widely used optical technique for characterizing thin films through normal-incidence transmission measurements. A critical step in this approach involves extracting the upper and lower envelopes of the measured oscillatory spectrum. By analyzing the transmission spectrum and its corresponding envelopes, the Swanepoel procedure enables precise determination of the film refractive index and extinction coefficient. However, even minor inaccuracies in envelope construction can propagate significant errors into the final characterization results. To address this challenge, we present what we believe to be a novel physics-informed optimization algorithm for envelope detection. Our mathematical model reformulates the envelope detection problem as a global optimization task that enforces the physical properties of the Swanepoel envelopes. Extensive validation on fifty randomly generated transmission spectra demonstrates unprecedented accuracy: the method achieves root-mean-square errors (RMSE) below 0.10% for the upper envelope and 0.06% for the lower envelope (more than doubling the accuracy of current state-of-the-art approaches). Furthermore, the proposed model has been assessed with two experimental transmission spectra, demonstrating its robustness and accuracy with real noisy data. We have developed an open-source Python software package (see text below). This software includes not only our innovative envelope construction algorithm but also additional envelope drawing algorithms for comparison and an efficient implementation of the Swanepoel method, enabling complete optical characterization of thin films. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Mean square error

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Neural Cryptography with Fog Computing Network for Health Monitoring Using IoMT

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computer Systems science & Engineering 2023年第1期44卷 945-959页

作者： G.Ravikumar K.Venkatachalam Mohammed A.AlZain Mehedi Masud Mohamed Abouhawwash Department of Computer Science and Engineering Coimbatore Institute of Engineering and TechnologyCoimbatore641109India Department of Applied Cybernetics Faculty of ScienceUniversity of Hradec Králové50003Hradec KrálovéCzech Republic Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA

Sleep apnea syndrome(SAS)is a breathing disorder while a person is *** traditional method for examining SAS is Polysomnography(PSG).The standard procedure of PSG requires complete overnight observation in a *** typically provides accurate results,but it is expensive and time ***,for people with Sleep apnea(SA),available beds and laboratories are ***,it may produce inaccurate ***,this paper proposes the Internet of Medical Things(IoMT)framework with a machine learning concept of fully connected neural network(FCNN)with k-near-est neighbor(k-NN)*** paper describes smart monitoring of a patient’s sleeping habit and diagnosis of SA using FCNN-KNN+average square error(ASE).For diagnosing SA,the Oxygen saturation(SpO2)sensor device is popularly used for monitoring the heart rate and blood oxygen *** diagnosis information is securely stored in the IoMT fog computing *** can care-fully monitor the SA patient remotely on the basis of sensor values,which are efficiently stored in the fog computing *** proposed technique takes less than 0.2 s with an accuracy of 95%,which is higher than existing models.

关键词： Sleep apnea polysomnography IOMT fog node security neural network KNN signature encryption sensor

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Directional anomaly detection

arXiv

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arXiv 2024年

作者： Lenz, Oliver Urs van Leeuwen, Matthijs Leiden Institute of Advanced Computer Science Leiden University Netherlands Research Group for Computational Web Intelligence Department of Applied Mathematics Computer Science and Statistics Ghent University Belgium

Semi-supervised anomaly detection is based on the principle that potential anomalies are those records that look different from normal training data. However, in some cases we are specifically interested in anomalies that correspond to high attribute values (or low, but not both). We present two asymmetrical distance measures that take this directionality into account: ramp distance and signed distance. Through experiments on synthetic and real-life datasets we show that ramp distance performs as well or better than the absolute distance traditionally used in anomaly detection. While signed distance also performs well on synthetic data, it performs substantially poorer on real-life datasets. We argue that this reflects the fact that in practice, good scores on some attributes should not be allowed to compensate for bad scores on others. © 2024, CC BY-NC-ND.

关键词： k-nearest neighbors

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Isolated calmness of perturbation mappings in generalized nonlinear programming and local superlinear convergence of Newton-type methods

arXiv

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arXiv 2024年

作者： Benko, Matúš Mehlitz, Patrick Johann Radon Institute for Computational and Applied Mathematics Linz4040 Austria Philipps-Universität Marburg Department of Mathematics and Computer Science Marburg35032 Germany

In this paper, we characterize Lipschitzian properties of different multiplier-free and multiplier-dependent perturbation mappings associated with the stationarity system of a so-called generalized nonlinear program popularized by Rockafellar. Special emphasis is put on the investigation of the isolated calmness property at and around a point. The latter is decisive for the locally fast convergence of the so-called semismooth* Newton-type method by Gfrerer and Outrata. Our central result is the characterization of the isolated calmness at a point of a multiplier-free perturbation mapping via a combination of an explicit condition and a rather mild assumption, automatically satisfied e.g. for standard nonlinear programs. Isolated calmness around a point is characterized analogously by a combination of two stronger conditions. These findings are then related to so-called criticality of Lagrange multipliers, as introduced by Izmailov and extended to generalized nonlinear programming by Mordukhovich and Sarabi. We derive a new sufficient condition (a characterization for some problem classes) of nonexistence of critical multipliers, which has been also used in the literature as an assumption to guarantee local fast convergence of Newton-, SQP-, or multiplier-penalty-type methods. The obtained insights about critical multipliers seem to complement the vast literature on the *** Codes 49J52, 49J53, 90C30 © 2024, CC BY-NC-SA.

关键词： Nonlinear simulations

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