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Ivannikov ISPras Open Conference (ISPras)

作者： Bo Yang Qin Zhang Bingchen Liang Xin Liu Mengxiang Qu Kraposhin Matvey Erwan Bertevas College of Engineering Ocean University of China Qingdao China Ivannikov Institute for System Programming of the RAS Moscow Russia Keppel-NUS Corporate Laboratory National University of Singapore France

ISBN: (数字)9781665412919

ISBN: (纸本)9781665448215

In recent years, the research on deep-sea mining has become more and more popular, especially in the interaction between the harvesting system and seabed to estimate and minimize seabed disturbance. In this paper, an inclined plane is adopted to simplify the front of the nodule harvester, and a solver for simulating turbulent sediment transport and fluid-structure interaction is developed based on the drift-flux model in the OpenFOAM. The volume of fluid (VOF) algorithm is used to simulate the diffusion and sedimentation process of sediment in the water, and the kOmegaSST model is used to calculate the turbulent diffusion coefficient of the mixed solution. Two different dynamic mesh strategies, overset and arbitrarily coupled mesh interface (ACMI) methods, are used to simulate the movement of the tilting push plate. This paper compares the simulation results of two different strategies. The results show that under the same simulation accuracy, ACMI method is more reliable and efficient than overset method.

关键词： Solid modeling Simulation Numerical simulation Numerical models Sediments Reliability Optimization

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Sinkhorn Transformations for Single-Query Postprocessing in Text-Video Retrieval

arXiv

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arXiv 2023年

作者： Yakovlev, Konstantin Polyakov, Gregory Alimova, Ilseyar Podolskiy, Alexander Bout, Andrey Nikolenko, Sergey Piontkovskaya, Irina Huawei Noah’s Ark Lab Moscow Russia Ivannikov Institute for System Programming of the RAS Moscow Russia St. Petersburg Department the Steklov Institute of Mathematics St. Petersburg Russia

A recent trend in multimodal retrieval is related to postprocessing test set results via the dual-softmax loss (DSL). While this approach can bring significant improvements, it usually presumes that an entire matrix of test samples is available as DSL input. This work introduces a new postprocessing approach based on Sinkhorn transformations that outperforms DSL. Further, we propose a new postprocessing setting that does not require access to multiple test queries. We show that our approach can significantly improve the results of state of the art models such as CLIP4Clip, BLIP, X-CLIP, and DRL, thus achieving a new state-of-the-art on several standard text-video retrieval datasets both with access to the entire test set and in the single-query setting. Copyright © 2023, The Authors. All rights reserved.

关键词： Information retrieval

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Universal mitigation of NBTI-induced aging by design randomization

Universal mitigation of NBTI-induced aging by design randomi...

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East-West Design & Test Symposium (EWDTS)

作者： Maksim Jenihhin Alexander Kamkin Zainalabedin Navabi Somayeh Sadeghi-Kohan Department of Computer Engineering Tallinn University of Technology ESTONIA Institute for System Programming of the Russian Academy of Sciences (ISP RAS) RUSSIA Department of Electrical and Computer Engineering University of Tehran IRAN

ISBN: (纸本)9781509006946

In this paper we propose to think out of the box and discuss an approach for universal mitigation of Negative Bias Temperature Instability (NBTI) induced aging untied from the limitations of its modelling. The cost-effective approach exploits a simple property of a randomized design, i.e., the equalized signal probability and switching activity at gate inputs. The techniques considered for structural design randomization involve both the hardware architecture and embedded software layers. Ultimately, the proposed approach aims at extending the reliable lifetime of nanoelectronic systems.

关键词： Negative bias temperature instability Thermal variables control Logic gates Delays Registers Aging Degradation

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Classification of Static Analyzer Warnings using Machine Learning Methods

Classification of Static Analyzer Warnings using Machine Lea...

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Ivannikov Memorial Workshop (IVMEM)

作者： U. V. Tsiazhkorob V. N. Ignatyev Ivannikov Institute for System Programming of the Russian Academy of Sciences (ISP RAS) Moscow Russian Federation Moscow Institute of Physics and Technology Moscow Russian Federation Lomonosov Moscow State University Moscow Russian Federation

ISBN: (数字)9798331504663

ISBN: (纸本)9798331504670

The paper is devoted to the approach for static analyzer’s warnings classification using machine learning methods. Static analysis plays a crucial role in software development by identifying potential errors and vulnerabilities in source code. However, the huge amount of warnings generated by static analyzers often overwhelms developers, making it challenging to prioritize and address them effectively. This paper proposes a novel approach to automatically classify static analyzer warnings using machine learning techniques. It showed the result up to 92% accuracy on real-world projects. Our method uses a set of code metrics collected during the analysis process to generate features for training the classifier. In the paper it is explored various strategies for feature selection and model training, considering different types of warnings and analyzers. The effectiveness of the proposed approach in warning classification was experimentally demonstrated. The developed method will be used to automatically review the results generated by the industrial static analyzer.

关键词： Training Measurement Reviews Source coding Conferences Computer bugs Static analysis

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ADVERSARIAL ATTACKS AND DEFENSES IN FAULT DETECTION AND DIAGNOSIS: A COMPREHENSIVE BENCHMARK ON THE TENNESSEE EASTMAN PROCESS

arXiv

引用

arXiv 2024年

作者： Pozdnyakov, Vitaliy Kovalenko, Aleksandr Makarov, Ilya Drobyshevskiy, Mikhail Lukyanov, Kirill AIRI Moscow Russia ISP RAS Research Center for Trusted Artificial Intelligence Moscow Russia Ivannikov Institute for System Programming of the Russian Academy of Sciences Moscow Russia Moscow Russia

Integrating machine learning into Automated Control systems (ACS) enhances decision-making in industrial process management. One of the limitations to the widespread adoption of these technologies in industry is the vulnerability of neural networks to adversarial attacks. This study explores the threats in deploying deep learning models for Fault Detection and Diagnosis (FDD) in ACS using the Tennessee Eastman Process dataset. By evaluating three neural networks with different architectures, we subject them to six types of adversarial attacks and explore five different defense methods. Our results highlight the strong vulnerability of models to adversarial samples and the varying effectiveness of defense strategies. We also propose a new defense strategy based on combining adversarial training and data quantization. This research contributes several insights into securing machine learning within ACS, ensuring robust FDD in industrial processes. © 2024, CC BY-NC-ND.

关键词： Decision making

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On the Problem of Choosing the Optimal Parameters for the Wind Farm in the Arctic Town of Tiksi 20th

On the Problem of Choosing the Optimal Parameters for the Wi...

引用

20th International Conference on Mathematical Modeling and Supercomputer Technologies, MMST 2020

作者： Strijhak, Sergei V. Gergel, Victor P. Ivanov, Aleksandr V. Gadal, Sebastien Zh. Ivannikov Institute for System Programming of the RAS Moscow109004 Russia Moscow Aviation Institute Moscow125993 Russia Lobachevsky State University of Nizhny Novgorod Nizhnij Novgorod603950 Russia Aix-Marseille Univ CNRS ESPACE UMR 7300 Univ Nice Sophia Antipolis Avignon Univ Aix-en-Provence13545 France North-Eastern Federal University Yakutsk Sakha Yakutia67000 Russia

ISBN: (纸本)9783030787585

The paper considers the problem of choosing the optimal parameters for the operation of 3 horizontal wind turbines of the wind farm in the town Tiksi, in the Sakha Republic. The open-source WRF-ARW and FLORIS packages are used to calculate the physical parameters in the wind farm. During the calculation, the values of wind velocity, temperature, pressure fields, and the value of the generated power of wind power plants were obtained. The optimization problem is formulated, the objective function is defined, and 2 variable parameters are selected, namely, yaw angle and angle of attack. The calculations were carried out on the computing cluster of ISP ras. © 2021, Springer Nature Switzerland AG.

关键词： Angle of attack

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Enhancing Cloud Security through Efficient Polynomial Approximations for Homomorphic Evaluation of Neural Network Activation Functions

Enhancing Cloud Security through Efficient Polynomial Approx...

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Cluster, Cloud and Internet Computing Workshops (CCGridW), IEEE/ACM International Symposium on

作者： Bernardo Pulido-Gaytan Andrei Tchemykh Mikhail Babenko Jorge M. Cortés-Mendoza Horacio González-Vélez Arutyun Avetisyan CICESE Researeh Center Ensenada Baja California Mexico Institute for System Programming RAS Moscow Russia North-Caucasus Federal University Stavropol Russia National College of Ireland Dublin Ireland

ISBN: (数字)9798350377514

ISBN: (纸本)9798350377521

Current security cloud practices can successfully protect stored data and data in transit, but they do not keep the same protection during data processing. The data value extraction requires decryption, creating critical exposure points. As a result, privacy-preserving techniques are emerging as a crucial consideration in cloud computing. The homomorphic processing of machine learning models in the cloud represents a central challenge. The activation function is fundamental in constructing a privacy-preserving Neural Network (NN) with Homomorphic Encryption (HE). Standard activation functions require operations not supported by HE, so it is necessary to find cryptographically compatible replacement functions to operate over encrypted data. Multiple approaches address the limitation of function compatibility with polynomial approximation. These functions should exhibit a trade-off between complexity and accuracy, limiting the efficiency of conventional approximation techniques. The current literature on polynomial approximation of NN activation functions still lacks a thorough review. In this paper, we comprehensively review the standard activation functions of modern NN models and current polynomial approximation approaches. We highlight fundamental features to consider in the activation function and the approximation technique to operate over encrypted data.

关键词： Privacy Accuracy Reviews Computational modeling Artificial neural networks Data processing Polynomials Cryptography Standards Biological neural networks

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Deductive verification of unmodified linux kernel library functions

arXiv

引用

arXiv 2018年

作者： Efremov, Denis Mandrykin, Mikhail Khoroshilov, Alexey National Research University Higher School of Economics Moscow Russia Ivannikov Institute for System Programming RAS Moscow Russia Moscow Institute of Physics and Technology Moscow Russia Lomonosov Moscow State University Moscow Russia

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. The formal contract of the functions was extracted from their source code and was represented in the form of preconditions and postconditions. The correctness of 23 functions was completely proved using AstraVer toolset, although success for 11 functions was achieved using 2 new specification language constructs. Another 2 functions were proved after a minor modification of their source code, while the final one cannot be completely proved using the existing memory model. The benchmark can be used for the testing and evaluation of deductive verification tools and as a starting point for verifying other parts of the Linux kernel. Copyright © 2018, The Authors. All rights reserved.

关键词： Formal verification

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A Case Study of Valency Patterns for Motion Verbs in Vakh Khanty by Means of Lingvodoc

A Case Study of Valency Patterns for Motion Verbs in Vakh Kh...

引用

Ivannikov ISPras Open Conference (ISPras)

作者： Irina Novitskaya Victoria Vorobeva Department of Foreign Languages National Research Tomsk State University Tomsk Russian Federation Information Systems Department Ivannikov Institute for System Programming of the RAS TPU Moscow Tomsk Russian Federation

The article presents a study of the syntactic compatibility of verbs of motion in the Vakh dialect of the Khanty language. The study was conducted with the help of the tools of the platform for documentation of the Uralic languages Lingvodoc. The purpose of the article is to describe patterns of syntactic valency that Vakh Khanty verbs of motion have.

关键词： Documentation Syntactics

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Real-time analytics, hybrid transactional/analytical processing, in-memory data management, and non-volatile memory

Real-time analytics, hybrid transactional/analytical process...

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Ivannikov ISPras Open Conference (ISPras)

作者： Sergey D. Kuznetsov Pavel E. Velikhov Qiang Fu Ivannikov Institute for System Programming of the RAS Lomonosov Moscow State University Moscow Institute of Physics and Technology (State University) National Research University Higher School of Economics Moscow Russia Huawei Russian Research Institute Moscow Russia

ISBN: (数字)9781665412919

ISBN: (纸本)9781665448215

These days, real-time analytics is one of the most often used notions in the world of databases. Broadly, this term means very fast analytics over very fresh data. Usually the term comes together with other popular terms, hybrid transactional/analytical processing (HTAP) and in-memory data processing. The reason is that the simplest way to provide fresh operational data for analysis is to combine in one system both transactional and analytical processing. The most effective way to provide fast transactional and analytical processing is to store an entire database in memory. So on the one hand, these three terms are related but on the other hand, each of them has its own right to life. In this paper, we provide an overview of several in-memory data management systems that are not HTAP systems. Some of them are purely transactional, some are purely analytical, and some support real-time analytics. Then we overview nine in-memory HTAP DBMSs, some of which don't support real-time analytics. Existing real-time in-memory HTAP DBMSs have very diverse and interesting architectures although they use a number of common approaches: multiversion concurrency control, multicore parallelization, advanced query optimization, just in time compilation, etc. Additionally, we are interested whether these systems use non-volatile memory, and, if yes, in what manner. We conclude that an emergence of new generation of NVM will greatly stimulate its use in in-memory HTAP systems.

关键词： Nonvolatile memory Multicore processing Query processing Distributed databases Transforms Real-time systems Concurrency control

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