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作者： Wang, Jie Zhong, Weijun Zhang, Jun Department of Management Sciences and Engineering Southeast University Nanjing 210096 China Laboratory for High Performance Scientific Computing and Computer Simulation Department of Computer Sciences University of Kentucky Lexington KY 4056 United States

ISBN: (纸本)0769527027

The challenge in preserving data privacy is how to protect attribute values without jeopardizing the similarity between data objects under analysis. In this paper, we further our previous work on applying matrix techniques to protect privacy and present a novel algebraic technique based on iterative methods for non-negative-valued data distortion. As an unsupervised learning method for uncovering latent features in high-dimensional data, a low rank nonnegative matrix factorization (NNMF) is used to preserve natural data non-negativity and avoid subtractive basis vector and encoding interactions present in techniques such as principal component analysis. It is the first in privacy preserving data mining in our paper that combining non-negative matrix decomposition with distortion processing. Two iterative methods to solve bound-constrained optimization problem in NMF are compared by experiments on Wisconsin Breast Cancer Dataset. The overall performance of NMF on distortion level and data utility is compared to our previously-proposed SVD-based distortion strategies and other existing popular data perturbation methods. Data utility is examined by cross validation of a binary classification using the support vector machine. Our experimental results on data mining benchmark datasets indicate that, in comparison with standard data distortion techniques, the proposed NMF-based method are very efficient in balancing data privacy and data utility, and it affords a feasible solution with a good promise on high-accuracy privacy preserving data mining. © 2006 IEEE.

关键词： Non-negative matrix factorization

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Evaluating price limits and stock market volatility

Evaluating price limits and stock market volatility

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2008 International Conference on e-Learning, e-Business, Enterprise Information Systems, and e-Government, EEE 2008

作者： Elgohary, Rania Elshrkawy, Mohamed A. Helmy, Yehya M.K. Elwahab, Mohamed S.A. Information Systems Ain Shams University Faculty of computer and Information Sciences Cairo Egypt Information Systems Helwan University Faculty of computer and Information Sciences Cairo Egypt Scientific Computing Ain Shams University Faculty of computer and Information sciences Cairo Egypt

ISBN: (纸本)1601320639

This paper empirically examines the current symmetric price limit mechanism imposed on the Egyptian Stock Exchange. Price limits are usually instituted to control the volatility of daily stock price movements through establishing price constraints and providing time for rational reassessment of investment decisions during times of panic trading. This study asserts that such limits prove the opposite and can have three delirious consequences: (1) they can be the source of higher volatility on subsequent trading days, (2) they can delay full incorporation of information into prices, or they can (3) interfere with trading activities of investors. We examine the relationship between price limits and stock market volatility. We find when price limits are made more (less) restrictive stock market volatility is usually not lower (higher). We investigate that when price limits are hit, and then there is uncertainty with regard to the equilibrium price, which, in turn, may then actually increase stock market volatility. Therefore, restrictive price limits may in fact actually cause high volatility levels. This finding contradicts conventional wisdom and the view of most regulators.

关键词： Investments

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Learning algorithm of kohonen network with selection phase

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WSEAS Transactions on computers 2012年第11期11卷 387-396页

作者： Ettaouil, Mohamed Abdelatifi, Essafi Belhabib, Fatima El Moutaouakil, Karim UFR: Scientific Computing and Computer Sciences Engineering Sciences Modelling and Scientific Computing Laboratory University Sidi Mohamed Ben Abdelah Fez Morocco

The learning algorithm of kohonen network realized away from any notion of class. So, the labelling phase is necessary to find the class associated to data. Generally, the size of the topological map is randomly chosen. Such choice effect the performance of the Kohonen algorithm. Consequently, the labelling phase becomes difficult to realize. To overcome this problem, we add to learning Kohonen algorithm a phase called selection stage. This phase is based on a function called selection function;to construct, we use a sub-set of the data set. In addition, we divided the topological map on two parts: The first contains the used neurons;while the second one is formed by the unused ones. It should be noted that the size of the first and the second parts are modified by the use of the selection function. To compare our method with the classical one, some experiments results are performed.

关键词： Learning algorithms

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Deepfake Detection Using EfficientNet and XceptionNet 11

Deepfake Detection Using EfficientNet and XceptionNet

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11th IEEE International Conference on Intelligent computing and Information Systems, ICICIS 2023

作者： Yasser, Basma Hani, Jumana El-Gayar, Salma Amgad, Omar Ahmed, Nourhan Ebied, Hala M. Amr, Habiba Salah, Mohamed Ain Shams University Software Engineering Faculty of Computer and Information Sciences Cairo Egypt Ain Shams University Faculty of Computer and Information Sciences Computer Science Department Cairo Egypt Ain Shams University Faculty of Computer and Information Sciences Scientific Computing Department Cairo Egypt

ISBN: (纸本)9798350322101

The increasing prevalence of manipulated media, particularly deepfake videos, poses significant challenges in distinguishing real from fake content. This paper addresses the issue of detecting deepfake videos using advanced CNN architectures such as EfficientNet-B4 and XceptionNet. The FF++ and Celeb-DF (v2) datasets are used to compare real and fake videos. The methodology involves preprocessing the Celeb- DF dataset by extracting frames and isolating faces, training the models, and evaluating their performance using log loss and Area Under the Curve (AUC) metrics. The study shows that both models are effective in accurately classifying real and fake videos and highlights the importance of continuously updating deepfake detection algorithms in response to evolving deepfake generation techniques. © 2023 IEEE.

关键词： Fake detection

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DieT Transformer model with PCA-ADE integration for advanced multi-class brain tumor classification

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Intelligence-Based Medicine 2025年 11卷 100192-100192页

作者： Amin, Mohammad Nahar, Khalid M.O. Gharaibeh, Hasan Nasayreh, Ahmad Alsalmanc, Neda'a Alomar, Alaa Malkawi, Majd Alqasem, Noor Smerat, Aseel Zitar, Raed Abu Nusier, Shawd Ezugwu, Absalom E. Abualigah, Laith Department of Information Technology and Computer Sciences Yarmouk University Irbid 211633 Jordan Faculty of Computer Studies Arab Open University P.O.Box 84901 Riyadh 11681 Saudi Arabia Department of Computer Science Faculty of Information Technology Jordan University of Science and Technology Irbid 22110 Jordan Department of Medicine Faculty of Medicine Jordan University of Science and Technology Irbid 22110 Jordan Department of Biomedical Systems and Informatics Engineering Hijjawi Faculty for Engineering Technology Yarmouk University Irbid 21163 Jordan Centre for Research Impact & Outcome Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura 140401 India Department of Biosciences Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai 602105 India Artificial Intelligence and Sensing Technologies (AIST) Research Center University of Tabuk Tabuk 71491 Saudi Arabia Faculty of Engineering and Computing Liwa College Abu Dhabi United Arab Emirates Department of Health and Clinical Outcomes Research Saint Louis University St. Louis MO United States Unit for Data Science and Computing North-West University 11 Hofman Street Potchefstroom 2520 South Africa Computer Science Department Al al-Bayt University Mafraq 25113 Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman 19328 Jordan

Early and accurate diagnosis of brain tumors is crucial to improving patient outcomes and optimizing treatment strategies. Long-term brain injury results from aberrant proliferation of either malignant or nonmalignant tissues in the brain. MRIs, or magnetic resonance imaging, are one of the most used approaches for detecting brain tumors. Professionals physically evaluate people after they have had MRI filtering, the process of enhancing MRI scans for radiologist interpretation, to establish if they have a brain tumor. Because different specialists use different frames to make judgments on the same MRI image, their analyses may yield contradictory results. Furthermore, simply detecting a tumor is insufficient. Inconsistent diagnoses can lead to delays in treatment, impacting survival rates and quality of care. It is also crucial to diagnose the patient's tumor so that treatment can begin as soon as possible. In this research, we investigate the multi-class classification of brain tumors utilizing a cutting-edge methodology that includes feature extraction from pictures using the DieT Transformer model, dimensionality reduction with PCA, and feature selection using the ADE algorithm. The proposed model, known in the publication as ADE_DieT, obtained an accuracy of 96.09 %. In addition, this article analyzes the performance of various pre-trained models, including MobileNetV3, NasNet, ResNet50, VGG16, VGG19, and DeiT. The proposed approach shortens the time required for manual diagnosis by clinicians by assisting in the rapid and accurate identification of brain tumors using MRI data. In oncology, this is important since it allows for early treatment. Integrating ADE_DieT into clinical workflows can support radiologists by reducing diagnosis time and enhancing diagnostic consistency. © 2024 The Authors

关键词： Brain tumor Medical image analysis MRI Vision Transformer

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Pseudo complementary measurement for traditional single-pixel cameras

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Chinese Physics B 2020年第11期29卷 315-322页

作者： Qian Dong Xu-Ri Yao Xin Liu Bing Liu Guang-Jie Zhai State Key Laboratory of Computer Science Institute of SoftwareChinese Academy of SciencesBeijing 100190China Key Laboratory of Electronics and Information Technology for Space Systems National Space Science CenterChinese Academy of SciencesBeijing 100190China State Key Laboratory of Scientific and Engineering Computing Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China

A traditional single-pixel camera needs a large number of measurements to reconstruct the object with compressive sensing *** with the 1/0 matrices in classical measurement,the 1/-1 matrices in the complementary measurement has better property for reconstruction computation and returns better reconstruction ***,each row of the 1/-1 matrices needs two measurements with the traditional single-pixel camera which results into double measurements compared with the 1/0 *** this paper,we consider the pseudo complementary measurement which only takes the same amount of measurements with the row number of some properly designed 1/0 matrix to compute the total luminous flux of the objective and derives the measurement data of the corresponding 1/-1 matrix in a mathematical *** numerical simulation and experimental result show that the pseudo complementary measurement is an efficient tool for the traditional single-pixel camera imaging under low measurement rate,which can combine the advantages of the classical and complementary measurements and significantly improve the peak signal-to-noise ratio.

关键词： computational imaging single-pixel camera

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MAP-based Problem-Agnostic Diffusion Model for Inverse Problems

arXiv

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arXiv 2025年

作者： Tao, Pingping Liu, Haixia Su, Jing Yang, Xiaochen Tan, Hongchen Shandong University Library No. 180 West Culture Road Shandong Weihai264209 China School of Mathematics and Statistics Hubei Key Laboratory of Engineering Modeling and Scientific Computing Institute of Interdisciplinary Research for Mathematics and Applied Science Huazhong University of Science and Technology No. 1037 Luoyu road Hubei Wuhan430074 China Dapartment of Basic Sciences Dalian University of Science and Technology No. 999-26 Harbor Road Liaoning Dalian116052 China School of Computer Science and Technology Harbin Institute of Technology No. 2 West Culture Road Shandong Weihai264209 China Institute of Future Technology Dalian University of Technology No. 2 Lingong Road Liaoning Dalian116081 China

Diffusion models have indeed shown great promise in solving inverse problems in image processing. In this paper, we propose a novel, problem-agnostic diffusion model called the maximum a posteriori (MAP)-based guided term estimation method for inverse problems. To leverage unconditionally pretrained diffusion models to address conditional generation tasks, we divide the conditional score function into two terms according to Bayes’ rule: an unconditional score function (approximated by a pretrained score network) and a guided term, which is estimated using a novel MAP-based method that incorporates a Gaussian-type prior of natural images. This innovation allows us to better capture the intrinsic properties of the data, leading to improved performance. Numerical results demonstrate that our method preserves contents more effectively compared to state-of-the-art methods—for example, maintaining the structure of glasses in super-resolution tasks and producing more coherent results in the neighborhood of masked regions during inpainting. Our numerical implementation is available at https://***/liuhaixias1/ MAP-DIFFUSION-IP. Copyright © 2025, The Authors. All rights reserved.

关键词： Inverse problems

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A computational framework for Carreau nanomaterial induced by stretchy regime considering Brownian diffusion, viscous dissipation, ferromagnetism and thermophoresis

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Partial Differential Equations in Applied Mathematics 2025年 13卷

作者： Hussain, Iftikhar Khan, Waqar Azeem Tabrez, Muhammad Waqas, M. Ibrahim, Talib K. Saidani, Taoufik Kausar, M.S. Zamri, Nurnadiah Abdullaeva, Barno Garalleh, Hakim AL Department of Mathematics Mohi-ud-Din Islamic University Nerian Sharif Jammu and Kashmir Azad 12010 Pakistan School of Mathematics and Statistics Beijing Institute of Technology Beijing 100081 China NUTECH School of Applied Sciences and Humanities National University of Technology Islamabad 44000 Pakistan Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Besut Campus Terengganu Besut 22200 Malaysia Department of Computer Science and Mathematics Lebanese American University Beirut Lebanon Department of Petroleum Engineering College of Engineering Knowledge University Erbil 44001 Iraq Department of Petroleum Engineering Al-Kitab University Altun Kupri Iraq Center for Scientific Research and Entrepreneurship Northern Border University Arar 73213 Saudi Arabia Faculty of Informatics and Computing Universiti Sultan Zainal Abidin (Kampus Gong Badak) Terengganu Kuala Terengganu 21300 Malaysia Department of Mathematics and Information Technologies Vice-Rector for Scientific Affairs Tashkent State Pedagogical University Tashkent Uzbekistan Department of Mathematical Science College of Engineering University of Business and Technology Jeddah 21361 Saudi Arabia

In recent decade, the research in nanotechnology brought the idea of nanofluids which are highly conducting materials. Some important applications of nanofluids are justified in pharmaceutical industry, coolants in vehicles engine, preparation process of various medicines for treatment of fatal diseases like cancer, aircraft industry, latest heat exchangers etc. The ferro particles are special class of nanomaterial which attract variety of interest from the researchers. The objective of current research is to perform the investigation for heat and mass transfer subject to Carreau nanofluid to observe the enhancement of heat transmission phenomena. The induction of magnetic dipole has been observed for thermal transport phenomenon. The flow is causing by stretched surface. A simplified system is obtained by utilizing the dimensionless variables. Physical interpretation of results have been presented. Result showed that temperature profile in presence of ferrofluid fluid boosts up with escalation in thermophoresis parameter, while opposite behavior is noted for power law index. The concentration of ferrofluid showing declining behavior for Schmidt numbers and rises for thermophoresis parameter. © 2024

关键词： Carreau ferrofluid Heat and mass transfer Magnetic dipole Numerical solution

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A New Process and Framework for Direct Anonymous Attestation Based on Symmetric Bilinear Maps

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Wuhan University Journal of Natural sciences 2011年第5期16卷 369-375页

作者： TAN Liang1,2, ZHOU Mingtian3 1. College of computer/Key Lab of Visualization in scientific computing and Virtual Reality of Sichuan, Sichuan Normal University, Chengdu 610066, Sichuan, China 2. Institute of computing Technology, Chinese Academy of sciences, Beijing 100190, China 3. School of computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610054, Sichuan, China College of Computer/Key Lab of Visualization in Scientific Computing and Virtual Reality of Sichuan Sichuan Normal University Chengdu Sichuan China Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu Sichuan China

For the problem of the original direct anonymous attestation （DAA） scheme＇s complexity and great time consumption, a new DAA scheme based on symmetric bilinear pairings is presented, which gives a practical solution to ECC-based TPM in protecting the privacy of the TPM. The scheme still includes five procedures or algorithms： Setup, Join, Sign, Verify and Rogue tagging, but gets rid of zero-knowledge proof and takes on a new process and framework, of which the main operations are addition, scalar multiplication and bilinear maps on supersingular elliptic curve systems. Moreover, the scheme adequately utilizes the properties of bilinear maps as well as the signature and verification of the ecliptic curve system itself. Compared with other schemes, the new DAA scheme not only satis- fies the same properties, and shows better simplicity and high effi- ciency. This paper gives not only a detailed security proof of the proposed scheme, but also a careful performance analysis by comparing with the existing DAA schemes.

关键词： direct anonymous attestation bilinear map privacy authentication trusted computing platform trusted platform module

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Fast facial fitting based on mixture appearance model with 3D constraint

Fast facial fitting based on mixture appearance model with 3...

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Chinese Conference on Pattern Recognition

作者： Huang, Xiangsheng Gong, Lujin Wang, Xiaoyan Institute of Automation Chinese Academy of Sciences Beijing 100190 China State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing AMSS Beijing 100190 China College of Computer Science and Technology Zhejiang University of Technology Hangzhou 310023 China

ISBN: (纸本)9781424472109

Fast facial points fitting plays an important role in applications such as Human-computer Interaction, entertainment, surveillance, and is highly relevant to the techniques of facial expression analysis, face recognition, 3D face model generation, etc. Active Appearance Models (AAMs) are generative models commonly used to fit face. They are sensitive to illumination and expression changes because they use only raw intensity to build observation models. In this paper, a real time facial points fitting approach using mixture observation models is presented. Furthermore, the 3D modes are used to constrain the AAM so that it can only generate model instances that can also be generated with the 3D modes. Finally, we give a derivative process for fast energy minimization using the inverse compositional algorithm. A coarse-to-fine fitting strategy is used for realtime and robust facial points fitting. We apply this algorithm to facial expression cloning of 3D Avatar system. Experimental results demonstrate that fitting the AAM with mixture observation models and 3D constraint outperforms other classical algorithms. ©2010 IEEE.

关键词： Mixtures

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