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检索条件"主题词=Software Algorithms"

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NORA and RODS the two Data Mining Technologies for National Security-A Review

NORA and RODS the two Data Mining Technologies for National ...

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Advance Computing and Innovative Technologies in Engineering (ICACITE), International Conference on

作者： Puneet Kaur Deepika Chaudhary Jaiteg Singh Chitkara University Institute of Engineering & Technology Chitkara University Punjab India

ISBN: (纸本)9781728177427

Although data mining and machine learning are among the popular technologies still very few people are aware of the impact which these technologies play in our daily lives. The role of data mining and machine learning is not only limited to discovering the hidden patterns or predicting a new algorithm or a model but these technologies also play a vital role when it comes to national security and surveillance systems. This paper is an attempt to present the role of data mining and machine learning in national security and disease surveillance. In this study, the two important software paradigms Non-Obvious Relationship Awareness (NORA) and Real-time Outbreak and Disease Surveillance (RODS) would be discussed. These systems can be used as a weapon against terrorism and anti-terrorism. The research outcome of this is to (a) Give the introduction of these two terms (b) Present a systematic literature review (c) Highlight the role of these paradigms in National Level Security and Surveillance.

关键词： Systematics Surveillance Weapons Government software algorithms Machine learning software

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SHA-3-LPHP: Hardware Acceleration of SHA-3 for Low-Power High-Performance Systems

SHA-3-LPHP: Hardware Acceleration of SHA-3 for Low-Power Hig...

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IEEE International Conference on software Reliability Engineering Workshops (ISSRE Wksp)

作者： Yuta Akiya Kyle Thomas Le Megan Luong Justin C Wilson Anas Salah Eddin Valerio Formicola Mohamed El-Hadedy California State Polytechnic University Pomona United-States Air Force Academy RecoIoT

ISBN: (纸本)9781665426046

In the last decade, the world transitioned from using Secure Hash Algorithm 1 (SHA-1) to Secure Hash Algorithm 2 (SHA-2) due to the flaws in SHA-1. However, SHA-2 still uses a similar internal structure with the same mathematical flaws as its predecessor. Safety in SHA-2 is attributed to the increased length of its output compared to SHA-1. Since then, a new hashing algorithm, SHA-3 has been introduced, which does not share the same flaws as its other family members. However, the transition to SHA-3 has not been complete due to lack of software and hardware support for SHA-3 as well as performance issues. The performance limitation, however, is only present in software implementations. In this paper, we propose a new implementation of SHA-3 based on FPGA hardware (SHA-3-LPHP), to be integrated in the architecture of low-power devices. SHA-3-LPHP achieves three orders magnitude improvement in execution time as compared to full software implementations, furthermore, requiring less energy, hence making it an excellent candidate for low-power and high-performance systems.

关键词： Performance evaluation Microprocessors System performance software algorithms software software reliability Safety

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Automated Synthetic Aperture Sonar Image Segmentation using Spatially Coherent Clustering

Automated Synthetic Aperture Sonar Image Segmentation using ...

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OCEANS

作者： Shannon-Morgan Steele Jillian Ejdrygiewicz Jeremy Dillon Kraken Robotic Systems Inc Dartmouth Canada

ISBN: (纸本)9781665427883

Seabed image segmentation is an important product for a variety of fields, including, habitat mapping, geological surveys, mine counter measures, and naval route planning. Developing a clustering algorithm that can both accurately segment high resolution imagery and generalize well over large areas is challenging. In this paper we will evaluate the performance of a new unsupervised image segmentation algorithm. The method utilizes imagery derived features (intensity and texture) to identify clusters (different seabed types) in feature space while also encouraging local homogeneity. In this paper we will demonstrate how our spatially coherent k-means clustering algorithm can efficiently and accurately segment Synthetic Aperture Sonar (SAS) images. Our experiments show that our spatially coherent clustering algorithm can increase segmentation accuracy up to 15 and 20 percent relative to OpenCV k-means and ArcGIS Pro ISO clustering, respectively.

关键词： Image segmentation software algorithms Spatial coherence Clustering algorithms Cost function Real-time systems Planning

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High Performance Uncertainty Quantification with Parallelized Multilevel Markov Chain Monte Carlo

High Performance Uncertainty Quantification with Parallelize...

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Supercomputing Conference

作者： Linus Seelinger Anne Reinarz Leonhard Rannabauer Michael Bader Peter Bastian Robert Scheichl Institute for Scientific Computing Heidelberg University Heidelberg Germany Department of Computer Science Durham University Durham United Kingdom Department of Informatics Technical University of Munich Garching Germany Institute for Applied Mathematics Heidelberg University Heidelberg Germany

ISBN: (数字)9781450384421

ISBN: (纸本)9781665483902

Numerical models of complex real-world phenomena often necessitate High Performance Computing (HPC). Uncertainties increase problem dimensionality further and pose even greater challenges. We present a parallelization strategy for multilevel Markov chain Monte Carlo, a state-of-the-art, algorithmically scalable Uncertainty Quantification (UQ) algorithm for Bayesian inverse problems, and a new software framework allowing for large-scale parallelism across forward model evaluations and the UQ algorithms themselves. The main scalability challenge presents itself in the form of strong data dependencies introduced by the MLMCMC method, prohibiting trivial parallelization. Our software is released as part of the modular and open-source MIT Uncertainty Quantification Library (MUQ), and can easily be coupled with arbitrary user codes. We demonstrate it using the Distributed and Unified Numerics Environment (DUNE) and the ExaHyPE Engine. The latter provides a realistic, large-scale tsunami model in which we identify the source of a tsunami from buoy-elevation data.

关键词： Uncertainty Monte Carlo methods Inverse problems Computational modeling High performance computing software algorithms Markov processes

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Area efficient VLSI architecture for reversible radix_2 FFT algorithm

Area efficient VLSI architecture for reversible radix_2 FFT ...

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Emerging Smart Computing and Informatics (ESCI), Conference on

作者： Syeda Farhat Sultana Basavarja Patil VTU Centre for PG Studies Kalaburagi India

ISBN: (数字)9781728185194

ISBN: (纸本)9781728185200

In this work, we propose a new way of implementing Fast Fourier transform multiplier. Previous approaches achieve FFTs with a unity gain using a complex multiplier or a non-unity gain factor. The IEEE 754 format is used for a floating-point number representation. This project proposes an effective float reconstruction scheme that showed greater delay and area implementation. A community of Karatsuba and Urdhva-Tiryagbhyam algorithms are used to implement a binary multiplier. The algorithms are implemented by Verilog (HDL) and are targeted to the Xilinx ISE simulator for FPGA Spartan-3E board. This decreases the FFT architecture and design computing resources.

关键词： Computational modeling software algorithms Computer architecture Very large scale integration software Delays Hardware design languages

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Petri net implementation in programmable logic controllers: methodology for development and validation

Petri net implementation in programmable logic controllers: ...

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International Symposium on Applied Machine Intelligence and Informatics (SAMI)

作者： Igor Azkarate Fernández Juan Carlos Mugarza Cortabarría Luka Eciolaza Echeverría Mondragon Unibertsitatea Arrasate-Mondragón Spain

ISBN: (数字)9781728180533

ISBN: (纸本)9781728180540

Lead times are key to good market positioning of providers of automated solutions based on a programmable logic controller (PLC). Testing control software against a digital twin (DT) of the process, any programming errors that may have incurred are detected before commissioning, which reduces project duration. This work raises the possibility of reducing that probability of error when programming discrete event dynamic systems (DEDS), by implementing a Petri net (PN) managing algorithm. A framework is presented which combines the use of this algorithm, by means of pre-incidence and post-incidence matrices and initial marking vector of a net, with code validation through emulation. A use case is brought forward in which the control program of a sequential process with parallel operations is implemented, with both virtual (VC) and real commissioning.

关键词： Heuristic algorithms Buffer storage software algorithms Petri nets Process control Programming software

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Recurrent Neural Networks algorithms and applications

Recurrent Neural Networks algorithms and applications

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Big Data & Artificial Intelligence & software Engineering (ICBASE), International Conference on

作者： Yuexing Chen Jiarun Li Rutgers Business School The State University of New Jersey New Brunswick New Jersey United Stated School of Beijing Institute of Petrochemical Technology Beijing China

ISBN: (纸本)9781665427104

Since recurrent neural networks (RNNs) were firstly proposed, it is widely used, and many extended RNNs algorithms have been developed, which achieve good results in many application fields. To report the latest research results of RNNs and help researchers quickly understand the latest progress of RNNs algorithm. In this research, we briefly introduce the basic principle of RNN, review more than 20 papers about RNNs and summarize the previous work. Then, we make qualitative and quantitative analyses on four representative algorithms (CNN-RNN, ResNet-110, ResNet-164, and ResNet-1001). Among them, the model of CNN-RNN obtains the best performance on the CIFAR-100 dataset with standard data augmentation. Finally, we discuss the future development trend of RNNs.

关键词： Recurrent neural networks Statistical analysis software algorithms Diversity reception Prediction algorithms Market research Data models

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Optimization and Operation of Stand-alone Hybrid PV/Biomass/Hydroelectric Pumped Storage Energy System in Iraq

Optimization and Operation of Stand-alone Hybrid PV/Biomass/...

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IEEE NW Russia Young Researchers in Electrical and Electronic Engineering Conference (EIConRusNW)

作者： Ahmed S. Al-akayshee Oleg N. Kuznetsov Hamdy M. Sultan Jabir ibn Hayyan Medical University Al Najaf Iraq National Research University "MPEI" Moscow Russia Minia University Minia Egypt

ISBN: (数字)9781665404761

ISBN: (纸本)9781665446426

Isolated load is considered a popular case and especially in the remote or rural areas in which diesel generators are used to cover the demand with special care of their environmental impact. This paper introduces an off-grid hybrid system (PV/Biomass/Hydroelectric Pumped Storage) as a study case in Iraq which is considered a clean, inexhaustible, and reliable energy system to achieve the sustainable and development targets. In this work, Atom Search Optimization (ASO) algorithm has been utilized to determine the optimal configuration of the hybrid system. The optimal sizing is determined from the economic point of view that achieving minimum Net Present Cost (NPC) for the whole system by using a real-time load demand information and meteorological data of a certain location in Iraq.

关键词： Power supplies software algorithms software Real-time systems software reliability Optimization Matlab

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An Anatomization for Classification Skin Lesion Using Custom CNN Framework

An Anatomization for Classification Skin Lesion Using Custom...

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Industrial Electronics Research and Applications (ICIERA), International Conference on

作者： Shubham Gupta Acropolis Institute of Technology and Research Indore India

ISBN: (纸本)9781665435437

A skin lesion is a growth or appearance anomaly in the dermis that is different from the rest of the body. A tiny scratch or something more serious like skin cancer might be completely unnoticeable. The use of deep learning (DL) architectures for image categorization in several fields, including dermatology, has shown impressive results. The expectations produced by DL for applications like image-based diagnostics have necessitated that non-experts become acquainted with algorithms’ working principles. Obtaining hands-on experience using these tools through a simplified however realistic method, in our opinion, may significantly aid in their intuitive comprehension. Even students without a strong mathematical background may understand concepts like convolution by seeing the outcomes of DL algorithms’ operations on dermatological images. Furthermore, the ability to fine-tune hyperparameters & even computer code expands the reach of basic intuitive understanding of these methods without having complex computational & theoretical skills. It is now feasible because of recent technology advancements that have lowered technical & technological obstacles associated with usage of these tools, creation them available to a larger population. So, we present a custom CNN for training a CNN on a dataset that contains skin lesions images linked by distinct skin cancer groups. Activity is open-source & doesn't need any additional software to be installed to use it. Additionally, we describe the algorithm and its functions in detail, starting with the creation of the basic computer code building blocks and leading the reader through the execution of real-world examples, comprising visualization & assessment of results. We get a training accuracy of 100 percent & a validation accuracy of 98.32 percent using this method.

关键词： Training Solid modeling Transfer learning software algorithms Sociology Lesions Statistics

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Information Transmission Protection Using Linguistic Steganography With Arithmetic Encoding And Decoding Approach

Information Transmission Protection Using Linguistic Stegano...

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IEEE International Conference on Advanced Trends in Information Theory (ATIT)

作者： Maksym Ivasenko Olha Suprun Oleh Suprun Taras Shevchenko National University of Kyiv Kyiv Ukraine National Academy of the Security Service of Ukraine Kyiv Ukraine

ISBN: (纸本)9781665406673

Security of Internet of Things and Internet space in general is one of the main areas of research in the field of information technology today and steganography - one of the best methods of message encryption and transmission. Steganography algorithms are used to hide data in cover media, such as text, images, videos, etc., as cover media and change the structure and features of a text message so that it is not identified by human eyes and machines. However, the use of text media as accompanying text is relatively difficult compared to other methods of information coverage due to the lack of available redundant information in the text data. At the same time, text data is being transmitted the fastest and most frequently, so it is ideal for quickly transmitting short important messagesю In this research, an overview of existing approaches to textual steganography and our approaches to steganography methods are presented. New approaches to text steganography, which easily hide the text-coverage and also take less time to encrypt, are presented. A new method of steganography is shown and tested; a software implementation of this method is created. The advantages of using a new method of steganography are substantiated. It is confirmed that this algorithm is faster when working with large amounts of data, comparing to existing algorithms. At the same time, it allows to choose different parameters and settings, increasing its protective potential.

关键词： Steganography Heuristic algorithms software algorithms Media Market research software Encryption

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