Video classification problem has been studied many years. The success of Convolutional Neural Networks (CNN) in image recognition tasks gives a powerful incentive for researchers to create more advanced video classifi...
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The paper presents a test program generator for functional verification of RISC-V microprocessors. The generator is implemented on the base of MicroTESK framework and consists of formal specifications of RISC-V ISA an...
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ISBN:
(纸本)9781538692516
The paper presents a test program generator for functional verification of RISC-V microprocessors. The generator is implemented on the base of MicroTESK framework and consists of formal specifications of RISC-V ISA and ISA-independent core. The specifications describe instructions' syntax and semantics and can be easily modified to support more instructions (including custom extensions). The core implements techniques of instruction sequences composition and test data generation. Test programs are generated from test templates, describing the programs' structural and behavioral properties; among generation techniques, random, combinatorial, and constraint-based ones are supported.
In this paper, we propose a new approach to the construction of computationally secure secret sharing scheme based on the simultaneous use of the Residue Number system (RNS), as the symmetric encryption, and the perfe...
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ISBN:
(纸本)9781538678800
In this paper, we propose a new approach to the construction of computationally secure secret sharing scheme based on the simultaneous use of the Residue Number system (RNS), as the symmetric encryption, and the perfect Asmuth-Bloom secret sharing scheme. We combine the useful features of Redundant RNS to design space efficient secret sharing scheme with enough level of security and to control of data integrity. This combination provides verifiability and achieves a high speed of data processing.
This paper describes the development of an auto-active verification technique in the Frama-C framework. We outline the lemma functions method and present the corresponding ACSL extension, its implementation in Frama-C...
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This paper presents results from the development and evaluation of a deductive verification benchmark consisting of 26 unmodified Linux kernel library functions implementing conventional memory and string operations. ...
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Submerged jets at different Reynolds numbers (Re) with random perturbations added to the inlet velocity profile are simulated numerically by solving the Navier–Stokes equations. The effects of Re on flow behavior and...
Submerged jets at different Reynolds numbers (Re) with random perturbations added to the inlet velocity profile are simulated numerically by solving the Navier–Stokes equations. The effects of Re on flow behavior and the length of laminar jet region are studied. A natural gas jet flow emitting form the sea bottom is also simulated using the URANS and VOF methods, and forces acting on an object placed within the multiphase jet are evaluated.
Over the years, ATLAS has developed a large number of monitoring and accounting tools for distributed computing applications. In advance of the increased experiment data rates and monitoring data volumes foreseen for ...
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We address dynamic elasticity issues of VM provisioning in a heterogeneous distributed computing environment that integrates resources of a data center. We consider the scenario when the center includes dedicated reso...
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ISBN:
(纸本)9781538678800
We address dynamic elasticity issues of VM provisioning in a heterogeneous distributed computing environment that integrates resources of a data center. We consider the scenario when the center includes dedicated resources (private cloud) for providing virtualized service and non-dedicated resources for Grid-computing. Existing platforms for the resource virtualization does not support management of such an infrastructure. We propose an approach to a job management based on the dynamic elasticity of virtual machines provisioning using resources of both types. We develop the multi¬agent job scheduler for dedicated resources and hypervisor shell to launch virtual machines through queues of resource management systems in non-dedicated resources. The scheduler provides a dynamic elasticity of virtual machine provisioning. Advantages of the offered approach to the resource virtualization are demonstrated by an example of a job flow management for a scalable application to solve the complicated practical problem. It is related to the energy security of Vietnam. Provided experiments show that using the developed tools together with the platform for the resource virtualization enables agents to significantly speed up the problem-solving process.
This paper is devoted to morphological tagging task for Russian. There are multiple corpora created for the task during the years of research. Unfortunately, these corpora often have incompatible annotation guidelines...
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This paper is devoted to morphological tagging task for Russian. There are multiple corpora created for the task during the years of research. Unfortunately, these corpora often have incompatible annotation guidelines and tag sets. This makes it difficult to utilize more than one corpus for training machine learning methods. Several attempts to manually unify guidelines and tag sets took place in the past. The most recent one was MorphoRuEval-2017 evaluation where organizers decided to unify annotations of four corpora. In this paper we propose a morphological tagging method which is able to be trained on any set of corpora with arbitrary guidelines and tag sets without any manual mapping provided. The method is based on transfer learning technique successfully applied in multilingual and cross-domain research. Firstly we establish a couple of solid neural network-based morphological tagging baselines. They both employ bidirectional LSTM networks but utilize different word embeddings. Comparative study on multiple corpora shows that fasttext model clearly outperforms word2vec one. Further we extend these baselines with transfer learning application. We prove transfer learning-based method effectiveness by performing two series of experiments. In the first series we exploit three wellknown corpora with incompatible tag sets: RNC, SynTagRus (original and Universal Dependencies versions). In the second series we utilize four corpora from MorphoRuEval-2017 evaluation with tag sets preliminary unified by organizers. In both cases transfer learning application improves performance of the method while training on more corpora. In the second case it even surpasses traditional joint training.
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