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11th International Conference on Geographic Information science - Part II, GIscience 2021

作者： Acharyya, Ankush Jallu, Ramesh K. Löffler, Maarten Meijer, Gert G.T. Saumell, Maria Silveira, Rodrigo I. Staals, Frank Czech Academy of Sciences Institute of Computer Science Prague Czech Republic Deptartment of Information and Computing Sciences Utrecht University Netherlands Academy of ICT and Creative Technologies NHL Stenden University of Applied Sciences Netherlands Department of Theoretical Computer Science Faculty of Information Technology Czech Technical University in Prague Czech Republic Department of Mathematics Universitat Politècnica de Catalunya Barcelona Spain Department of Information and Computing Sciences Utrecht University Netherlands

ISBN: (纸本)9783959772082

An important task in terrain analysis is computing viewsheds. A viewshed is the union of all the parts of the terrain that are visible from a given viewpoint or set of viewpoints. The complexity of a viewshed can vary significantly depending on the terrain topography and the viewpoint position. In this work we study a new topographic attribute, the prickliness, that measures the number of local maxima in a terrain from all possible angles of view. We show that the prickliness effectively captures the potential of terrains to have high complexity viewsheds. We present near-optimal algorithms to compute it for TIN terrains, and efficient approximate algorithms for raster DEMs. We validate the usefulness of the prickliness attribute with experiments in a large set of real terrains. © Ankush Acharyya, Ramesh K. Jallu, Maarten Löffler, Gert G.T. Meijer, Maria Saumell, Rodrigo I. Silveira, and Frank Staals;licensed under Creative Commons License CC-BY 4.0

关键词： Landforms

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BOUNDS ON THE SIZE OF THE CONVEX HULL OF PLANAR BROWNIAN MOTION AND RELATED INVERSE PROCESSES

arXiv

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arXiv 2023年

作者： Cygan, Wojciech Panzo, Hugo Šebek, Stjepan University of Wroclaw Faculty of Mathematics and Computer Science Institute of Mathematics pl. Grunwaldzki 2 Wroclaw50–384 Poland Technische Universität Dresden Faculty of Mathematics Institute of Mathematical Stochastics Zellescher Weg 25 Dresden01069 Germany Department of Mathematics and Statistics Saint Louis University St. Louis United States Department of Applied Mathematics Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia

MSC Codes 60D05, 60J65 (Primary) 52A10 (Secondary)We establish bounds on expected values of various geometric quantities that describe the size of the convex hull spanned by a path of the standard planar Brownian motion. Expected values of the perimeter and the area of the Brownian convex hull are known explicitly, and satisfactory bounds on the expected value of its diameter can be found in the literature as well. In this work we investigate circumradius and inradius of the Brownian convex hull and obtain lower and upper bounds on their expected values. Our other goal is to find bounds on the related inverse processes (that correspond to the perimeter, area, diameter, circumradius and inradius of the convex hull) which provide us with some information on the speed of growth of the size of the Brownian convex hull. Copyright © 2023, The Authors. All rights reserved.

关键词： Brownian movement

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FRACTAL ANALYSIS OF HYPERBOLIC SADDLES WITH APPLICATIONS

arXiv

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arXiv 2023年

作者： Crnković, Vlatko Huzak, Renato Resman, Maja University of Zagreb Faculty of Electrical Engineering and Computing Department of Applied Mathematics Hasselt University Campus Diepenbeek Unska 3 10000 Zagreb Croatia Agoralaan Gebouw D Diepenbeek3590 Belgium Hasselt University Campus Diepenbeek Agoralaan Gebouw D Diepenbeek3590 Belgium University of Zagreb Faculty of Science Department of Mathematics Horvatovac 102a Zagreb10000 Croatia

In this paper we express the Minkowski dimension of spiral trajectories near hyperbolic saddles and semi-hyperbolic singularities in terms of the Minkowski dimension of intersections of such spirals with transversals near these singularities. We apply these results to hyperbolic saddle-loops and hyperbolic 2-cycles to obtain upper bounds on the cyclicity of such limit periodic *** Codes 37C10, 28A75, 37C27, 37C29 © 2023, CC BY.

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A Systematic review of Multi-Mode Fiber based on Dimensional Code in Optical-CDMA 3

A Systematic review of Multi-Mode Fiber based on Dimensional...

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3rd International Conference on applied and Practical sciences, ICAPS 2021

作者： Ghazi, Alaan Aljunid, S.A. Idrus, Syed Zulkarnain Syed Rashidi, C.B.M. Al-Dawoodi, Aras Mahmood, Baban A. Fareed, Alaa Zaenal, Mohammed U. Qasim, Nameer Hashim Rafeeq, Ranjdr M. Faculty of Applied and Human Sciences University Malaysia Perlis Malaysia School of Computer and Communication Engineering University Malaysia Perlis Malaysia Computer Science Department College of Computer Science and Information Technology Kirkuk University Kirkuk Iraq Computer Technical Engineering Al-Qalam University College Iraq School of Computing University Utara Malaysia Malaysia

This paper deals with optical code division multiple access (optical-CDMA) and provides a general analysis of multi-mode fiber (MMF). The purpose of this work is to classify the works in the literature that are related to Optical-CDMA based on MMF and to find the limitation of the researches done in this field. Several challenges that occur in the medium such as multiple-access interference (MAI), pulse dispersion (PD) and nonlinearity in optical fibers deteriorate system performances and become a major performance-limiting factor. © Published under licence by IOP Publishing Ltd.

关键词： Multiple access interference

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A Two-Party Combined Cryptographic Scheme and Its Application

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Chinese Journal of Electronics 2023年第4期21卷 687-691页

作者： Shengbao WANG Qi XIE Qiang TANG Peng ZENG Wei CHEN School of Information Science and Engineering Hangzhou Normal University Hangzhou China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China New Star Institute of Applied Technology Hefei China Faculty of EWI University of Twente The Netherlands Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China

In this paper, we extend Haber and Pinkas' notion of combined (cryptographic) scheme to the two-party setting, which is shown to be a useful tool in some real-world application which we name the “2-boss problem”. In a two-party combined scheme, a single public key associated with two independent private keys and one escrow decryption key is provided. Any ciphertext encrypted under the public key can be simultaneously decrypted by the three keys. Meanwhile, the two private keys can also be used as signing keys to achieve non-repudiation service. We provide formal security definitions for two-party combined schemes, and present a simple and efficient scheme. Our construction is derived from bilinear pairings, and the security is based on the Bilinear Diffie-Hellman (BDH) assumption.

关键词： Public key Switches Non-repudiation

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Multi-Source Fusion-Based Model with Customized Loss Function for Stock Selection

SSRN

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SSRN 2022年

作者： Snášel, Václav Velasquez Silva, Juan Domingo Pant, Millie Georgiou, Dimitrios Kong, Lingping Faculty of Electrical Engineering and Computer Science VŠB-TU Ostrava Czech Republic Departament of Industrial Engineering University of Chile Santiago Chile Chile Department of Applied Mathematics and Scientific Computing Indian Institute of Technology Uttarakhand Roorkee247667 India Faculty of Electrical Engineering and Computer Science National Technical University of Athens Greece

Selecting outstanding tech stocks for investment is challenging for any market investor. This challenge comes from the complexity caused by the dynamic and volatile nature of public policies and macroeconomic factors. Moreover, this task appears complex as an investor needs to decide from a diverse set of stocks, where performance ranking can conflict with another for different criteria, e.g., the contradiction between pure returns and risk performance. The paper proposes a novel model for stock evaluation and selection problems based on multi-source data fusion and decision-level fusion by multi-criteria decision-making (MCDM) techniques. The narrow criteria performance of a single source usually restricts a candidate's overall evaluation, especially on stock selection. Therefore, the proposed multi-source acquisition is promising to enhance reliability with reasonable data fusion, Furthermore, proper raw data processing and information integration by data fusion techniques are essential to obtain more accurate and concise data for decision-making support. Most important, the proposed multi-MCDM decision-fusion procedure can enhance the strength of a model to overcome the weakness of a single-performed model. Besides, we propose a customized loss function that improves the accuracy of time-series data prediction and increases the data's credibility. Meanwhile, the experiment shows that the proposed method reduces the prediction log error by 28\% in a best case on the experimental real-situation data and decreases the time-series data matching cost by 20\% between the prediction and observation. Finally, we conducted the real-world stock data selection by the proposed fusion-based model. The proposed model locates five potential preferred stocks, and the results are practical and effective, which are further justified through a detailed ablation study. Meanwhile, the time-series forecasting data got a lower error prediction than the baseline loss. © 2022, The Author

关键词： Data fusion

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Deep and handcrafted feature supported diabetic retinopathy detection: A study

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Procedia Computer science 2023年 218卷 2675-2683页

作者： Seifedine Kadry Rubén González Crespo Enrique Herrera-Viedma Sujatha Krishnamoorthy Venkatesan Rajinikanth Faculty of Applied Computing and Technology Noroff University College Kristiansand 94612 Norway Computer Science Department School of Engineering and Technology Universidad Internacional de La Rioja 26006 Andalusian Spain Research Institute in Data Science and Computational Intelligence University of Granada Granada Spain Zhejiang Bioinformatics International Science and Technology Cooperation Center Wenzhou-Kean University Zhejiang Province China Wenzhou Municipal Key Lab of Applied Biomedical and Biopharmaceutical Informatics Wenzhou-Kean University Zhejiang Province China Department of Electronics and Instrumentation Engineering St. Joseph's College of Engineering OMR Chennai 600119 Tamil Nadu India

The eye is the prime sensory organ in physiology, and the abnormality in the eye severely influences the vision system. Therefore, eye irregularity is commonly assessed using imaging schemes, and Fundus Retinal Image (FRI) supported eye screening is one of the ophthalmological practices. This work proposed a Deep-Learning Procedure (DLP) to recognize Diabetic Retinopathy (DR) in FI. The proposed work presents the experimental work with different DLP methods found in the literature. This work is executed with two modes; (i) DR detection using conventional deep-features and (ii) DR discovery using deep ensemble features. To demonstrate this work, 1800 fundus images (900 regular and 900 DR class) are considered for the assessment, and the advantage of proposed plan is confirmed using various performance metrics. The experimental outcome of this study confirms that the AlexNet-based detection provides a better detection (>96%), and the deep ensemble features of AlexNet, VGG16, and ResNet18 provide a detection accuracy of >98% on the chosen FRI database.

关键词： Eye abnormality Diabetic retinopathy Fundus imaging Deep-Learning Classification

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Automatic detection of lung nodule in CT scan slices using CNN segmentation schemes: A study

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Procedia Computer science 2023年 218卷 2786-2794页

作者： Seifedine Kadry Enrique Herrera-Viedma Rubén González Crespo Sujatha Krishnamoorthy Venkatesan Rajinikanth Faculty of Applied Computing and Technology Noroff University College Kristiansand 94612 Norway Research Institute in Data Science and Computational Intelligence University of Granada Granada Andalusian Spain Computer Science Department School of Engineering and Technology Universidad Internacional de La Rioja 26006 Spain Zhejiang Bioinformatics International Science and Technology Cooperation Center Wenzhou-Kean University Zhejiang Province China Wenzhou Municipal Key Lab of Applied Biomedical and Biopharmaceutical Informatics Wenzhou-Kean University Zhejiang Province China Department of Electronics and Instrumentation Engineering St. Joseph's College of Engineering OMR Chennai 600119 Tamil Nadu India

The lung is one of the prime respiratory organs in human physiology, and its abnormality will severely disrupt the respiratory system. Lung Nodule (LN) is one of the abnormalities, and early screening and treatment are necessary to reduce its harshness. The proposed work aims to implement the Convolutional-Neural-Network (CNN) segmentation methodology to extract the LN in various lung CT slices, such as axial, coronal, and sagittal planes. This work consists of the following phases; (i) Image collection and pre-processing, (ii) Ground-truth generation, (iii) CNN-supported segmentation, and (iv) Performance evaluation and validation. In this work, the merit of pre-trained CNN segmentation schemes is verified using (i) One-fold training and (ii) Two-fold training methods. The test images for this study are collected from The Cancer Imaging Archive (TCIA) database. The experimental investigation is executed using Python®, and the outcome of this study confirms that the VGG-SegNet helps to get better values of Jaccard (>88%), Dice (>93%), and Accuracy (>96%) compared to other CNN methods.

关键词： Lung nodule CT scan CNN segmentation VGG-SegNet Accuracy Detection

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Numerical solution of third-order Robin boundary value problems using diagonally multistep block method 28

Numerical solution of third-order Robin boundary value probl...

引用

28th Simposium Kebangsaan Sains Matematik, SKSM 2021

作者： Nasir, N.M. Majid, Z.A. Ismail, F. Bachok, N. Institute for Mathematical Research Universiti Putra Malaysia Serdang Selangor43400 Malaysia Department of Mathematics Faculty of Science Universiti Putra Malaysia UPM Serdang Selangor43400 Malaysia Centre for Mathematical Sciences College of Computing and Applied Sciences Universiti Malaysia Pahang Pahang Gambang26300 Malaysia

This numerical study exclusively focused on developing a diagonally multistep block method of order five (2DDM5) to get the approximate solution of the third-order Robin boundary value problems directly. The mathematical derivation of the developed 2DDM5 method is by approximating the integrand function with Lagrange interpolation polynomial. The proposed direct integrator scheme was applied to compute numerical solution at two-point concurrently. Shooting technique adapted with the Newtons divided difference interpolation method was implemented throughout the proposed algorithm. The theoretical characteristics of the developed method including the order, consistency, zero-stable and convergence are discussed. The method are tested on four Robin boundary value problems. The numerical results signify that the computational performances of the proposed method is competitive in terms of accuracy and efficiency than the existing method. © Published under licence by IOP Publishing Ltd.

关键词： Boundary value problems

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A PCA-based fuzzy tensor evaluation model for multiple-criteria group decision making

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applied Soft computing 2023年 132卷

作者： Singh, Meenu Pant, Millie Kong, Lingping Alijani, Zahra Snášel, Václav Department of Applied Mathematics and Scientific Computing Indian Institute of Technology Roorkee Uttarakhand247667 India Mehta Family School of Data Science and Artificial Intelligence Indian Institute of Technology Roorkee Uttarakhand247667 India Faculty of Electrical Engineering and Computer Science VŠB-TU Ostrava Czech Republic Institute for Research and Applications of Fuzzy Modeling University of Ostrava 30. dubna 22 701 03 Ostrava Czech Republic

Multiple-criteria group decision-making (MCGDM) problems mainly consist of multiple factors and multiple Decision Makers (DMs) or Users, for which dimension extension is necessary when considering all the entries of DMs together. Tensor, a generalized form of a matrix, displays a multi-way array item, which is the most suitable and practical way to represent high-dimensional data without losing any information. In this paper, we first reduce the dimension through Principal Component Analysis (PCA), which helps consider the most-informative criteria. Then, we reintroduced the tensor as a fuzzy-form tensor for the MCGDM problem because of user information uncertainty. We choose Interval-valued Neutrosophic Fuzzy numbers (IVNFNs) as the basis for the tensor form because of their ability to distinguish between truth, indeterminacy, and falsity in the data. Lastly, a Generalized Interval-valued Neutrosophic Fuzzy Weighted Geometric (GIVNFWG) operator is defined. Moreover, a generalized framework for fuzzy-form tensors for high-dimensional MCGDM problems is proposed. The feasibility and efficiency of this proposed process is illustrated for a real-world MCGDM problem of ranking the most efficient Third Party Reverse Logistics Partners (3PRLPs), i.e., recycled fiber-based paper mills for the packaging industry. The obtained results are according to the experts and are validated using sensitivity analysis. This analysis facilitates in assessing the impact on the overall ranking performance of 3PRLPs by considering various combinations of environment and technological sub-criteria. © 2022 Elsevier B.V.

关键词： Principal component analysis

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