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Abstract and Applied analysis 2020年第none期2020卷 1-8页

作者： Achik, Yamna Idmbarek, Asmaa Nafia, Hajar Agmour, Imane El Foutayeni, Youssef Analysis Modeling and Simulation Laboratory Hassan II University Morocco Unit for Mathematical and Computer Modeling of Complex Systems IRD France

The linear complementarity problem is receiving a lot of attention and has been studied extensively. Recently, El foutayeni et al. have contributed many works that aim to solve this mysterious problem. However, many results exist and give good approximations of the linear complementarity problem solutions. The major drawback of many existing methods resides in the fact that, for large systems, they require a large number of operations during each iteration;also, they consume large amounts of memory and computation time. This is the reason which drives us to create an algorithm with a finite number of steps to solve this kind of problem with a reduced number of iterations compared to existing methods. In addition, we consider a new class of matrices called the E-matrix. © 2020 Yamna Achik et al.

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History of the Basel internal-ratings-based (IRB) credit risk regulation

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Model Assisted Statistics and Applications 2020年第1期15卷 81-98页

作者： Penikas, Henry Department of Applied Economics International Centre of Decision Choice and Analysis National Research University Higher School of Economics Moscow Russian Federation Research and Forecasting Department Bank of Russia Moscow Russian Federation Laboratory of Mathematical Modeling of Complex Systems of the P.N. Lebedev Physical Institute Moscow Russian Federation

In December 2019 the Basel Committee has launched the consolidated Basel framework. The framework inherits the Basel II internal ratings-based (IRB) approach for the credit risk with mostly no changes. The absence of the material methodological changes is unexpected given the fact that the key shortcomings of the IRB approach stay unresolved. The paper objective is therefore to list its earlier discussed shortcomings and to address the new ones. Latter include the unbalanced treatment of PD and LGD parameters, as well as methodological inconsistency in expected and unexpected loss treatment. © 2020 - IOS Press and the authors. All rights reserved.

关键词： Basel Committee credit risk IRB regulation structural model

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Aircraft type classification in remote sensing images using deep learning 2

Aircraft type classification in remote sensing images using ...

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2nd IEEE International Conference on Electronics, Control, Optimization and Computer Science, ICECOCS 2020

作者： Youssef, Youssef Ben Merrouchi, Mohamed Abdelmounim, Elhassane Gadi, Taoufiq Interdisciplinary Laboratory of Applied Sciences National School of Applied Sciences Berrechid Morocco Lab Computing Imaging and Modeling of Complex Systems FST of Settat Hassan First University Settat Morocco Lab of Signal Analysis and Information Processing FST of Settat Hassan First University Settat Morocco

ISBN: (纸本)9781728169217

In aeronautic, redundancy of data is strongly desired to make optimal decisions. A large data source is available with the development of the technology used in remote sensing images. Remote Sensing Image Classification (RSIC) is widely exploited in military and civil fields. To improve the performance of multi-label classification, we addressed the problem of RSIC based on the Convolutional Neural Network (CNN) for remote sensing images of aircraft types. Previous studies have used intensive preprocessing which limits the rate of classification. We improved the network structure to make it more accurate and to limit underfitting or overfitting problems. A recent public dataset called Multi-Type Aircraft Remote Sensing Images (MTARSI) is used in this work to validate our method. Extensive experiments prove the effectiveness of the proposed method in terms of accuracy. © 2020 IEEE.

关键词： Convolutional neural networks

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First principles investigations of the electronic and magnetic properties of RVO3 (R = Er, Ho, Y, Lu) vanadates

arXiv

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arXiv 2022年

作者： Jmal, Sohail Ait Balli, Sohail Ait Bouhani, Hamza Mounkachi, Omar AMEEC Team LERMA International University of Rabat Parc Technopolis Rocade de Rabat- Salé 11100 Morocco Complex Systems and Interactions Ecole Centrale Casablanca Morocco Laboratory of Condensed Matter and Interdisciplinary Sciences Department of Physics Faculty of Sciences Mohammed V University in Rabat PO Box 1014 Rabat Morocco Modeling Simulation & Data Analysis Program Mohammed VI Polytechnic University Ben Guerir43150 Morocco

In this paper, we investigate the influence of the rare earth element (R) on the physical properties of RVO3 (R = Er, Ho, Y, Lu). For this purpose, a theoretical work is reported in this study using ab initio method with the intent of enhancing our knowledge of the electronic, and magnetic properties of RVO3 (R = Er, Ho, Y, Lu) compounds. The electronic properties of these materials show the presence of Jahn-Teller effect, with a band gap of approximately 0.58eV, 1.57eV, 1.12eV, 1.28eV, for ErVO3, HoVO3, YVO3, LuVO3, respectively. The magnetic contribution of Ho, Er, and V atoms in HoVO3, and ErVO3 compounds was disentangled using X-ray magnetic circular dichroism (XMCD). The magnetic anisotropies of RVO3 with (R = Er, Ho, Y, Lu) are studied and analyzed using spin orbit coupling. We noticed an easy axis of magnetization along the c-direction with strong magneto-crystalline anisotropy energies for the non-magnetic rare earth elements (R = Lu, Y)VO3. For the magnetic rare earth elements, the easy and hard magnetization direction were found to be along b-axis and c-axis, and a- axis and c-axis for HoVO3, and ErVO3, respectively. This means that instead of the standard magnetization demagnetization process, large thermal effects can be obtained by spinning their single crystals in constant magnetic fields. The exchange coupling between (Ho-V) is also found to be greater than the other exchange interactions in HoVO3. Accordingly, a large conventional magnetocaloric effect could be created in HoVO3, since the Ho Ising moments experience a metamagnetic transition. However, the magnetocaloric effect (MCE) is expected to be lower in ErVO3 due to the weak (Er-V) exchange coupling. © 2022, CC BY.

关键词： Holmium compounds

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The impact of PD-LGD correlation on bank capital adequacy in nongranular loan portfolio1

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Model Assisted Statistics and Applications 2019年第1期14卷 103-120页

作者： Ermolova, M.D. Penikas, H.I. International Laboratory of Decision Choice and Analysis Department of Applied Economics National Research University Higher School of Economics Moscow Russian Federation Laboratory of Mathematical Modeling of Complex Systems P.N. Lebedev Physical Institute Moscow Russian Federation

The Central Banks discuss bank recapitalization arrangements. Markup to capital is needed because the current Basel approach is insensitive to some risks. As the Basel Committee moves from comprehensive risk modelling towards a revised, simplified, standardised approach, where one-two triggers measure risk, banking regulators increase demand for a capital addon to meet unaccounted risks. The paper suggests the add-on estimates for the joint effect of the concentration and PD-LGD correlation risks leaving other unaccounted ones out-of-scope. The previous studies estimated add-ons for each risk separately. We show their joint impact on capital can be higher up to 5.3 times than the sum of two taken apart. Then previous results do not provide sufficient capital for a bank. We obtain that Basel underestimates the joint risk in 1.9 times on average. We expect that our contribution will be useful at least but not last for specialised lending (e.g. real estate and project finance), where the joint effect of concentration and PD-LGD correlation risks is the most observable. © 2019 IOS Press and the authors. All rights reserved.

关键词： add-on Basel capital concentration PD-LGD correlation

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The efficiency of deep learning algorithms for detecting anatomical reference points on radiological images of the head profile

The efficiency of deep learning algorithms for detecting ana...

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Information Technology and Nanotechnology (ITNT), International Conference on

作者： Konstantin Dobratulin Andrey Gaidel Aleksandr Kapishnikov Anna Ivleva Irina Aupova Pavel Zelter Faculty of Informatics Samara National Research University Samara Russia Image Processing Systems Institute of RAS - Branch of the FSRC "Crystallography and Photonics" RAS Samara Russia SamSMU MOH Russia Samara Russia Laboratory of Analysis and Modeling of Complex Systems ICCS RAS Samara Russia FSBEI HE SamSMU MOH Russia Samara Russia

ISBN: (数字)9781728170411

ISBN: (纸本)9781728170428

In this article we investigate the efficiency of deep learning algorithms in solving the task of detecting anatomical reference points on radiological images of the head in lateral projection using a fully convolutional neural network and a fully convolutional neural network with an extended architecture for biomedical image segmentation - U-Net. A comparison is made for the results of detection anatomical reference points for each of the selected neural network architectures and their comparison with the results obtained when orthodontists detected anatomical reference points. Based on the obtained results, it was concluded that a U-Net neural network allows performing the detection of anatomical reference points more accurately than a fully convolutional neural network. The results of the detection of anatomical reference points by the U-Net neural network are closer to the average results of the detection of reference points by agroupoforthodontists.

关键词： Deep learning Image segmentation Head Neural networks Convolutional neural networks Task analysis Biomedical imaging

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Aircraft Type Classification in Remote Sensing Images using Deep Learning

Aircraft Type Classification in Remote Sensing Images using ...

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International Conference on Electronics, Control, Optimization and Computer Science (ICECOCS)

作者： Youssef Ben Youssef Mohamed Merrouchi Elhassane Abdelmounim Taoufiq Gadi Interdisciplinary Laboratory of Applied Sciences National School of Applied Sciences Berrechid Morocco Lab computing imaging and modeling of complex systems FST of Settat Hassan first University Settat Morocco Lab of Signal Analysis and Information Processing FST of Settat Hassan first University Settat Morocco

ISBN: (数字)9781728169217

ISBN: (纸本)9781728169224

关键词： Aircraft Training Remote sensing Convolution Feature extraction Testing Task analysis

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The efficiency of deep learning algorithms for detecting anatomical reference points on radiological images of the head profile

arXiv

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arXiv 2020年

作者： Dobratulin, Konstantin Gaidel, Andrey Aupova, Irina Ivleva, Anna Kapishnikov, Aleksandr Zelter, Pavel Faculty of Informatics Samara National Research University Samara Russia Video Mining Laboratory IPSI RAS Brach of the FSRC"Crystallography and Photonics" RAS Samara Russia Department of Pediatric Dentistry FSBEI HE SamSMU MOH Russia Samara Russia Laboratory of analysis and modeling of complex systems Institute for the Control of Complex Systems of Russian Academy of Sciences Samara Russia Department of Radiation Diagnostics and Radiation Therapy FSBEI HE SamSMU MOH Russia Samara Russia X-ray Department FSBEI HE SamSMU MOH Russia Samara Russia

关键词： Convolutional neural networks

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Preventing Black Hole Attack in Wireless Sensor Network Using HMM

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Procedia Computer Science 2019年 148卷 552-561页

作者： Hanane Kalkha Hassan Satori Khalid Satori Laboratory Computer Science Image processing and Numerical Analysis Faculty of Sciences Dhar MahrazSidi Mohammed Ben Abbdallah University Fez Morocco Artificial Intelligence Complex Systems and modeling Department of Mathematics and Computer Science Faculty Polydisciplinary of Nador Mohammed Premier University 300 Selouane 62700 Nador Morocco

Secure routing is a difficult task because of the limited nature of wireless sensor network resources. This paper provides a Hidden Markov Model solution to identify malicious nodes in wireless sensor networks through prevention of black hole attack. Our proposed approach based on a new routing algorithm which analyses shortest path in order to avoid malicious node path. Our results demonstrate the success and the efficiency of our proposed routing algorithm.

关键词： WSN HMM Black Hole Malicious Shortest path

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Whole heart modeling — Spatiotemporal dynamics of electrical wave conduction and propagation

Whole heart modeling — Spatiotemporal dynamics of electrica...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Hui Yang Yun Chen Fabio M. Leonelli Complex Systems Monitoring Modeling and Analysis Laboratory The Pennsylvania State University University Park PA

Cardiac electrical activities are varying in both space and time. Human heart consists of a fractal network of muscle cells, Purkinje fibers, arteries and veins. Whole-heart modeling of electrical wave conduction and propagation involves a greater level of complexity. Our previous work developed a computer model of the anatomically realistic heart and simulated the electrical conduction with the use of cellular automata. However, simplistic assumptions and rules limit its ability to provide an accurate approximation of real-world dynamics on the complex heart surface, due to sensitive dependence of nonlinear dynamical systems on initial conditions. In this paper, we propose new reaction-diffusion methods and pattern recognition tools to simulate and model spatiotemporal dynamics of electrical wave conduction and propagation on the complex heart surface, which include (i) whole heart model; (ii) 2D isometric graphing of 3D heart geometry; (iii) reaction-diffusion modeling of electrical waves in 2D graph, and (iv) spatiotemporal pattern recognition. Experimental results show that the proposed numerical solution has strong potentials to model the space-time dynamics of electrical wave conduction in the whole heart, thereby achieving a better understanding of disease-altered cardiac mechanisms.

关键词： Heart Computational modeling Spatiotemporal phenomena Geometry Solid modeling Numerical models Three-dimensional displays

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