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A Hybrid Solution for Secure Privacy-Preserving Cloud Storage & Information Retrieval

Human-centric computing and Information Sciences 2023年 13卷

作者： Kumar, Ankit Aljrees, Turki Hsieh, Sun-Yuan Singh, Kamred Udham Singh, Teekam Raja, Linesh Samriya, Jitendra Kumar Mundotiya, Rajesh Kumar Department of Computer Engineering & Applications GLA University UP Mathura India College of Computer Science and Engineering University of Hafr Al-Batin Eastern Province Saudi Arabia Department of Computer Science and Information Engineering Institute of Medical Information Institute of Manufacturing Information and Systems Center for Innovative FinTech Business Models and International Center for the Scientific Development of Shrimp Aquaculture National Cheng Kung University Tainan Taiwan School of Computing Graphic Era Hill University Dehradun India Department of Computer Science and Information Engineering National Cheng Kung University Tainan Taiwan Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun India Department of Computer Application Manipal University Jaipur Jaipur India Department of Computer Science and Engineering National Institute of Technology Delhi Delhi India School of Computer Science University of Petroleum and Energy Studies Dehradun India

Cloud storage is an emerging archetype used by businesses for data storage. Clients require easy access to data in the cloud, which helps clients with limited computing power move their high-value, high-risk principle jobs to the cloud. The primary concern of this study is towards flawless verifying, checking data bundles, and determining modules to carry out the project. As discussed at several research platforms, each client is concerned about data storage and retrieval. Data security is critical in cloud computing, and thus monitoring has evolved into a vigilance that abstracts the monitoring process. Request made by clients for security planning is always computationally exclusive. As a result, each customer is concerned as to their verified condition. This paper will highlight a secure cloud communication method for client data to address the afore-mentioned issues. Synchronization creates secret hare keys, combined with a model-encrypted data packet sent to the cloud. These secure data are then sent over a public network, subject to monitoring to avert data leakage to an unauthorized party. They lack the cohesion to outsource data storage to the cloud deliberately. As an outcome of this model's distribution, the perception of authorized data owners would be changed regarding cloud storage up to 97.6%, addressing the trust issues between data owners and cloud ace affiliations © 2023, Human-centric computing and Information *** Rights Reserved.

关键词： Cryptography

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Crystalline phase discriminating neutron tomography using advanced reconstruction methods

arXiv

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arXiv 2021年

作者： Ametova, Evelina Burca, Genoveva Chilingaryan, Suren Fardell, Gemma Jørgensen, Jakob S. Papoutsellis, Evangelos Pasca, Edoardo Warr, Ryan Turner, Martin Lionheart, William R.B. Withers, Philip J. Henry Royce Institute Department of Materials The University of Manchester M13 9PL United Kingdom Laboratory for Application of Synchrotron Radiation Karlsruhe Institute of Technology Germany ISIS Pulsed Neutron and Muon Source STFC UKRI Rutherford Appleton Laboratory United Kingdom Department of Mathematics The University of Manchester M13 9PL United Kingdom Institute for Data Processing and Electronics Karlsruhe Institute of Technology Germany Scientific Computing Department STFC UKRI Rutherford Appleton Laboratory United Kingdom Department of Applied Mathematics and Computer Science Technical University of Denmark Denmark Research IT Services The University of Manchester M13 9PL United Kingdom

Time-of-flight neutron imaging offers complementary attenuation contrast to X-ray computed tomography (CT), coupled with the ability to extract additional information from the variation in attenuation as a function of neutron energy (time of flight) at every point (voxel) in the image. In particular Bragg edge positions provide crystallographic information and therefore enable the identification of crystalline phases directly. Here we demonstrate Bragg edge tomography with high spatial and spectral resolution. We propose a new iterative tomographic reconstruction method with a tailored regularisation term to achieve high quality reconstruction from low-count data, where conventional filtered back-projection (FBP) fails. The regularisation acts in a separated mode for spatial and spectral dimensions and favours characteristic piece-wise constant and piecewise smooth behaviour in the respective dimensions. The proposed method is compared against FBP and a state-of-the-art regulariser for multi-channel tomography on a multi-material phantom. The proposed new regulariser which accommodates specific image properties outperforms both conventional and state-of-the-art methods and therefore facilitates Bragg edge fitting at the voxel level. The proposed method requires significantly shorter exposure to retrieve features of interest. This in turn facilitates more efficient usage of expensive neutron beamline time and enables the full utilisation of state-of-the-art high resolution detectors. © 2021, CC BY.

关键词： Iterative methods

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A Smart Forecasting System of Computational Cost of DFT calculations using Machine Learning and Cheminformatics

A Smart Forecasting System of Computational Cost of DFT calc...

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2019中国化学会第十五届全国计算（机）化学学术会议

作者：马硕 Yingjin Ma Baohua Zhang Yingqi Tian Zhong Jin 中科院计算机网络信息中心 Department of High Performance Computing Technology and Application Development Computer Network Information Center Chinese Academy of Sciences Center of Scientific Computing Applications & Research Chinese Academy of Sciences School of Computer Science and Technology University of Chinese Academy of Sciences

The Density-functional theory(DFT) should be the most popular approach that used in computational physics or computational chemistry community. Normally, the computational time is unknown until the calculation is done. And as such, researchers can hardly arrange their schedules rationally. Additionally, for calculations that are carried out with computing clusters, unreasonable schedules would greatly increase the time and energy cost. Herein, we introduced a smart forecasting system based on three machine learning models, which are RF with FNNs(random forest with feedforward neural networks), Bi-LSTM with attention mechanism[1,2,3] and MPNN[4](message passing neural networks). The three models can accept the molecular information, calculating scheme(the combination of basis set and functional etc.) and machine configuration information as inputs, and then can predict the proposed computational cost. Comparing to the actual computational time, the average relative error is generally less than 20%, and it follows the normal distribution[5].

关键词： density-functional theory machine learning neural networks cheminformatics

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Multi-reference Epstein-Nesbet perturbation theory with density matrix renormalization group reference wavefunction

arXiv

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arXiv 2019年

作者： Song, Yinxuan Cheng, Yifan Ma, Yingjin Ma, Haibo School of Chemistry and Chemical Engineering Nanjing University Nanjing210023 China Department of High Performance Computing Technology and Application Development Computer Network Information Center Chinese Academy of Sciences Beijing100190 China Center of Scientific Computing Applications & Research Chinese Academy of Sciences Beijing100190 China

The accurate electronic structure calculation for strongly correlated chemical systems requires an adequate description for both static and dynamic electron correlation, and is a persistent challenge for quantum chemistry. In order to account for static and dynamic electron correlations accurately and efficiently, in this work we propose a new method by integrating the density matrix renormalization group (DMRG) method and multi-reference second-order Epstein-Nesbet perturbation theory (ENPT2) with a selected configuration interaction (SCI) approximation. Compared to previous DMRG-based dynamic correlation methods, the DMRG-ENPT2 method extends the range of applicability, allowing us to efficiently calculate systems with very large active spaces beyond 30 orbitals. We demonstrate this by performing calculations on H2S with an active space of (16e, 15o), hexacene with an active space of (26e, 26o) and trinuclear Manganese cluster with an active space of (47e, 43o). Copyright © 2019, The Authors. All rights reserved.

关键词： Quantum chemistry

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Externally-contracted multi-reference configuration interaction method using a DMRG reference wave function

arXiv

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arXiv 2018年

作者： Luo, Zhen Ma, Yingjin Wang, Xicun Ma, Haibo School of Chemistry and Chemical Engineering Nanjing University Nanjing210023 China Department of High Performance Computing Technology and Application Development Computer Network Information Center Chinese Academy of Sciences Beijing100190 China Center of Scientific Computing Applications & Research Chinese Academy of Sciences Beijing100190 China Nanjing Foreign Language School Nanjing210008 China

The recent development of the density matrix renormalization group (DMRG) method in multireference quantum chemistry makes it practical to evaluate static correlation in a large active space, while dynamic correlation provides a critical correction to the DMRG reference for strong-correlated systems and is usually obtained using multi-reference perturbation (MRPT) or configuration interaction (MRCI) methods with internal contraction (ic) approximation. These methods can use active space scalable to relatively larger size references than has previously been possible. However, they are still hardly applicable to systems with active space larger than 30 orbitals and/or large basis set because of high computation and storage costs of high-order reduced density matrices (RDMs) and the crucial dependence of the MRCI Hamiltonian dimension on the number of virtual orbitals. In this work, we propose a new effective implementation of DMRG-MRCI, in which we use re-constructed CASCI-type configurations from DMRG wave function via the entropy-driving genetic algorithm (EDGA) [Luo et. al., J. Chem. Theory Comput., 2017, 13, 4699-4710.], and integrate it with MRCI by an external contraction (ec) scheme. This bypasses the bottleneck of computing high-order RDMs in traditional DMRG dynamic correlation methods with ic approximation and the number of MRCI configurations is not dependent on the number of virtual orbitals. Therefore, DMRG-ec-MRCI method is promising for dealing with larger active space than 30 orbitals and large basis sets. We demonstrate the capability of our DMRG-ec-MRCI method in several benchmark applications, including the evaluation of potential energy curve of Cr2, single-triplet gaps of higher n-acene molecules and the energy of Eu-BTBP(NO3)3 complex. Copyright © 2018, The Authors. All rights reserved.

关键词： Quantum chemistry

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Multipath Transmission Model and Its Route Selection Policy Considering Packet Re-sequencing Buffers Availability

Multipath Transmission Model and Its Route Selection Policy ...

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International Conference on Advanced Information Networking and applications Workshops (AINAW)

作者： Yuta Yoshinaga Masayoshi Shimamura Katsuyoshi Iida Department of Communications and Computer Engineering Tokyo Institute of Technology Tokyo Japan Network Application Engineering Laboratories Ltd. Fukuoka Japan Global Scientific Information and Computing Center Tokyo Institute of Technology Tokyo Japan

ISBN: (纸本)9781479917761

Multipath transmission in intermediate nodes is a promising approach to support high bandwidth applications. To prevent out-of-order packet deliveries, packet re-sequencing nodes must be deployed. In this paper, we propose a multipath transmission model that incorporates packet re-sequencing buffers and the Random with Availability Check policy. After mathematically analyzing the model, we show numerical comparisons between the Random with Availability Check and Random policies.

关键词： Availability Throughput Capacity planning Mathematical model Numerical models Bandwidth Sequential analysis

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EMD strategy for activation detection in functional MRI of the human brain

EMD strategy for activation detection in functional MRI of t...

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2010 International Conference on computer application and System Modeling, ICCASM 2010

作者： Zheng, Tianxiang Yang, Lihua Jiang, Tianzi Department of Tourism Management Shenzhen Tourism College Jinan University Shenzhen China Department of Scientific Computing and Computer Application School of Mathematics and Computational Science Sun Yat-sen University Guangzhou China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781424472369

This article investigates how the Empirical Mode Decomposition (EMD) algorithm, a newly-developed and effective technique in the fields of signal processing and time-frequency analysis, is introduced and applied to activation detection in task-related functional Magnetic Resonance Imaging (fMRI) of the human brain. The method is illustrated using fMRI data simulated under one paradigm as well as one real dataset, and its performance is compared to those of a leading model based (General Linear Model - GLM) and a leading data-driven (Region Growing Method - RGM) approach. It is concluded that the proposed method achieves much better performance than the computationally inefficient RGM and is slightly more sensitive than GLM. Experimental results support its efficiency and sensitivity, which indicates that it is to become a viable alternative to the fMRI analysis. © 2010 IEEE.

关键词： Empirical mode decomposition

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EMD Strategy for Activation Detection in Functional MRI of the Human Brain

EMD Strategy for Activation Detection in Functional MRI of t...

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The 2010 International Conference on computer application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

作者： Tianxiang Zheng Lihua Yangt Tianzi Jiang Department of Tourism Management Shenzhen Tourism College Jinan University Shenzhen China Department of Scientific Computing and Computer Application School of Mathematics and Computational National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Bei

This article investigates how the Empirical Mode Decomposition (EMD) algorithm, a newly-developed and effective technique in the fields of signal processing and time-frequency analysis, is introduced and applied to activation detection in task-related functional Magnetic Resonance Imaging (fMRI) of the human brain. The method is illustrated using fMRI data simulated under one paradigm as well as one real dataset, and its performance is compared to those of a leading model based (General Linear Model ? GLM) and a leading data-driven (Region Growing Method ? RGM) approach. It is concluded that the proposed method achieves much better performance than the computationally inefficient RGM and is slightly more sensitive than GLM. Experimental results support its efficiency and sensitivity, which indicates that it is to become a viable alternative to the fMRI analysis.

关键词： functional magnetic resonance imaging empirical mode decomposition blood oxygen level dependent region growing general linear model

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Automatic Digest Generation by Extracting Important Scenes from the Content of Presentations

Automatic Digest Generation by Extracting Important Scenes f...

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International Workshop on Database and Expert Systems applications

作者： Hieu Hanh Le Thitiporn Lertrusdachakul Tetsutaro Watanabe Haruo Yokota Department of Computer Science Tokyo Institute of Technology Japan Department of Computer Science Graduate School of Information and Engineering Tokyo Institute of Technology Japan Application Lab Ricoh Company Ltd Application Laboratory Software R&D Group Ricoh Company Limited Japan Department of Computer Science Tokyo Institute of Technology Global Scientific Information and Computing Center Tokyo Institute of Technology

Recently, combining a video recording of a presentation along with the digital slides used in it has become popular in e-learning and presentation of archives. For users of the archives, it is useful to preview a digest of such content to grasp the atmosphere and/or an outline of the presentation. This paper proposes a method of automatic digest generation by extracting important scenes from the presentation content. The extracted scenes are chosen based on several factors such as frequency and specificity of words, scene duration and order. Finally, the effectiveness of the proposed methods are evaluated by comparing with testers' answer sets for actual lectures.

关键词： Data mining Speech Proposals Electronic learning Arrays Video recording Software

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M-band wavelets application to palmprint recognition based on texture features

M-band wavelets application to palmprint recognition based o...

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2004 International Conference on Image Processing, ICIP 2004

作者： Dai, Qingyun Bi, Ning Huang, Daren Zhang, Dvaid Li, Feng Department of Scientific Computing and Computer Application Sun Yat-Sen University Guangzhou 510275 China Faculty of Information Engineering Guangdong University of Technology Guangzhou 510643 China Department of Computing Hong Kong Polytechnic University Kowloon Hong Kong

In this paper, a new texture feature set based on M-band wavelet analysis is proposed for online Palmprint identification. First, the central part of a palm was decomposed by M-band wavelets transformation, then, 1-norm energy was extracted out as our features, at last, the candidate was found by matching process. The presented experimental results demonstrate the validity of our approach. © 2004 IEEE.

关键词： Feature extraction

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