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46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)

作者： Abulkhanov, Dmitry Sorokin, Nikita Nikolenko, Sergey Malykh, Valentin Huawei Noahs Ark Lab Moscow Russia RAS Ivannikov Inst Syst Programming Moscow Russia RAS Steklov Inst Math St Petersburg Dept St Petersburg Russia

ISBN: (纸本)9781450394086

Data collection and mining is a crucial bottleneck for cross-lingual information retrieval (CLIR). While previous works used machine translation and iterative training, we present a novel approach to cross-lingual pretraining called LAPCA (language-agnostic pretraining with cross-lingual alignment). We train the LAPCA-LM model based on XLM-RoBERTa and LAPCA that significantly improves cross-lingual knowledge transfer for question answering and sentence retrieval on, e.g., XOR-TyDi and Mr. TyDi datasets, and in the zero-shot cross-lingual scenario performs on par with supervised methods, outperforming many of them on MKQA.

关键词： cross-lingual IR multilingual IR Transformer-based architectures

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Probabilistic Approach for Minimizing Checking Sequences for Non-deterministic FSMs 1

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35th IFIP WG 6.1 International Conference on Testing Software and systems (ICTSS)

作者： Kushik, Natalia Yevtushenko, Nina Lopez, Jorge Inst Polytechn Paris SAMOVAR Telecom Sud Paris Palaiseau France Russian Acad Sci Ivannikov Inst Syst Programming Moscow Russia Airbus Issy Les Moulineaux France

ISBN: (数字)9783031432408

ISBN: (纸本)9783031432392;9783031432408

The paper is devoted to model based testing against probabilistic FSMs. Differently from our prior work in 2021, we consider checking sequences and possibilities of test suite minimization through reducing the length of the resulting checking sequence. Given a level of certainty P, we define a P-probably checking sequence under a white box testing assumption and discuss how a suffix of an input sequence can be omitted, such that the resulting sub-sequence is P-probably checking. The specification and possible implementations are non-initialized, i.e., the assumption of 'no reset' is supported.

关键词： Model Based Testing Non-deterministic Finite State Machines Checking sequence Probabilistic Approach

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Evaluation of Free and Open Source Tools for Automated Software Composition Analysis 23

Evaluation of Free and Open Source Tools for Automated Softw...

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7th ACM Computer Science in Cars Symposium (CSCS)

作者： Bottner, Laura Hermann, Artur Eppler, Jeremias Thuem, Thomas Kargl, Frank Mercedes Benz Tech Innovat GmbH Ulm Germany Ulm Univ Inst Distributed Syst Ulm Germany Ulm Univ Inst Software Engn & Programming Languages Ulm Germany

ISBN: (纸本)9798400704543

Vulnerable or malicious third-party components introduce vulnerabilities into the software supply chain. Software Composition Analysis (SCA) is a method to identify direct and transitive dependencies in software projects and assess their security risks and vulnerabilities. In this paper, we investigate two open source SCA tools, Eclipse Steady (ES) and OWASP Dependency Check (ODC), with respect to vulnerability detection in Java projects. Both tools use different vulnerability detection methods. ES implements a code-centric and ODC a metadata-based approach. Our study reveals that both tools suffer from false positives. Furthermore, we discover that the success of the vulnerability detection depends on the underlying vulnerability database. Especially ES suffered from false negatives because of the insufficient vulnerability information in the database. While code-centric and metadata-based approaches offer significant potential, they also come with their respective downsides. We propose a hybrid approach assuming that combining both detection methods will lead to less false negatives and false positives.

关键词： Software Composition Analysis Vulnerable Dependency Identification Software Supply Chain Security Secure Software Development Life Cycle

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A novel multi-objective optimization approach to guarantee quality of service and energy efficiency in a heterogeneous bus fleet system

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ENGINEERING OPTIMIZATION 2023年第6期55卷 981-997页

作者： Pena, David Tchernykh, Andrei Dorronsoro, Bernabe Ruiz, Patricia Univ Cadiz Dept Comp Sci Cadiz Spain CICESE Res Ctr Dept Comp Sci Ensenada Baja California Mexico South Ural State Univ Chelyabinsk Russia RAS Ivannikov Inst Syst Programming Moscow Russia

An efficient public transport system is essential for sustainable city development, as it directly affects people's welfare. This article addresses the urban public transport timetabling problem with multi-objective evolutionary algorithms, considering multiple vehicle types and respecting the public transport restrictions of local authorities. The conflicting objectives are the minimization of fuel consumption and unsatisfied user demand, which are essential to make transit buses an attractive alternative for users, thus promoting environmentally friendly mobility. The problem was solved with two well-known metaheuristics, namely the non-dominated sorting genetic algorithm-II (NSGA-II) and cellular genetic algorithm for multi-objective optimization (MOCell), and their performance was compared using several metrics. Their parameters were tuned with a thorough study, and several evolutionary operators designed for the problem were considered. The outcomes suggest that a solution using various types of buses can produce diverse dispatching strategies, reducing pollutant emissions and maintaining tolerable ridership losses.

关键词： Public transport sustainable cities greenhouse gas emission multi-objective optimization evolutionary algorithms

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Advanced Computer-Aided Optimization of Quartz Resonator-Based Sensors 19

Advanced Computer-Aided Optimization of Quartz Resonator-Bas...

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IEEE 19th International Conference on the Perspective Technologies and Methods in MEMS Design (MEMSTECH)

作者： Savchenko, Volodymyr Mnushka, Oksana Sokulskyi, Oleg Natl Tech Univ Kharkiv Polytech Inst Comp Engn & Programming Dept Kharkiv Ukraine Natl Tech Univ Ukraine Igor Sikorsky Kyiv Informat Syst & Technol Dept Kiev Ukraine

ISBN: (纸本)9798350378634;9798350378627

In this study, we present an improved approach to optimizing the parameters of sensor sensing elements using quartz resonators with an interelectrode gap. We combine graphical and analytical methods to solve the multi-criteria optimization problem. The work focuses on the modes of operation of a quartz resonator equipped with an interelectrode gap in sensors with a frequency output, determining a set of optimal parameters and representing them as surfaces in a particular optimization parameter space. The presented results reveal specific areas on the surface of the objective function where optimization of design and technological parameters is possible, taking into account technological influences and features of the sensor design, including the initial value of the interelectrode gap. By using an improved mathematical model for the oscillations of a quartz resonator with an electrode gap, this study achieves results with an accuracy of (8.11)% higher than previous studies, demonstrating the effectiveness of the proposed method in improving the design and functionality of piezoelectric sensors for advanced applications.

关键词： sensor quartz resonator unit

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Deep Learning Applications for Intrusion Detection in Network Traffic

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programming AND COMPUTER SOFTWARE 2024年第7期50卷 493-510页

作者： Getman, A. I. Rybolovlev, D. A. Nikolskaya, A. G. Russian Acad Sci Ivannikov Inst Syst Programming Moscow 109004 Russia Moscow Inst Phys & Technol Natl Res Univ Dolgoprudnyi 141701 Moscow Oblast Russia HSE Univ Ul Myasnitskaya 20 Moscow 101978 Russia Lomonosov Moscow State Univ Moscow 119991 Russia Orel State Univ Oryol 302026 Russia

This paper discusses the problems of applying deep learning methods for intrusion detection in network traffic. The results of analyzing the relevant studies and reviews of deep learning applications for intrusion detection are presented. The most popular deep learning methods are discussed and compared. A classification system of deep learning methods for intrusion detection is proposed. The current trends and challenges of applying deep learning methods for intrusion detection in network traffic are identified. To assess the applicability of deep learning methods for intrusion detection, the CNN-BiLSTM neural network is synthesized. The synthesized network is compared with the previously developed model based on the random forest classifier. The deep learning method makes it possible to simplify the feature engineering stage, with the values of quality metrics for the random forest and CNN-BiLSTM models being close. This confirms the high prospects for application of deep learning methods to intrusion detection.

关键词： information security intrusion detection system intrusion detection machine learning deep learning neural network convolutional neural network random forest network traffic computer attack

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Europeans and Americans of European origin show differences between their biological pathways related to the major histocompatibility complex

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SCIENTIFIC REPORTS 2024年第1期14卷 1-10页

作者： Vaulin, Andrey Karpulevich, Evgeny Kasianov, Artem Morozova, Irina Nanyang Technol Univ Nanyang Singapore Ivannikov Inst Syst Programming Russian Acad Sci I Informat Syst Dept Moscow Russia Inst Globally Distributed Open Res & Educ IGDORE Moscow India Univ Porto CIBIO Ctr Invest Biodiversidade & Recursos Genet InBIO Lab Associado Vairao Portugal CIBIO BIOPOLIS Program Genom Biodivers & Land Planning Vairao Portugal

In this study, we analysed biological pathway diversity among Europeans and Northern Americans of European origin, the groups of people that share a common genetic ancestry but live in different geographic regions. We used a novel complex approach for analysing genomic data: we studied the total effects of multiple weak selection signals, accumulated from independent SNPs within a pathway. We found significant differences between immunity-related biological pathways from the two groups. All identified pathways included genes belonging to the major histocompatibility complex (MHC) system, which plays an important role in adaptive immune responses. We suggest that the ways of evolution were different for the MHC-I and MHC-II gene groups at least in Europeans and Americans of European origin. We hypothesise that the observed variability between the two populations was triggered by selection pressures due to the different pathogen landscapes and pathogen loads on the two continents. Our findings can be important for epidemic prevention and control, as well as for analysing processes related to allergies, organ transplantation, and autoimmune diseases.

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Satisfiability and Model Checking for One Parameterized Extension of Linear Temporal Logic

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AUTOMATIC CONTROL AND COMPUTER SCIENCES 2022年第7期56卷 649-660页

作者： Gnatenko, A. R. Zakharov, V. A. Natl Res Univ Higher Sch Econ HSE Moscow 101000 Russia Russian Acad Sci Ivannikov Inst Syst Programming Moscow 109004 Russia

Sequential reactive systems are computer programs or hardware devices which process the flows of input data or control signals and output the streams of instructions or responses. When designing such systems one needs formal specification languages capable of expressing the relationships between the input and output flows. Previously we introduced a family of such specification languages based on temporal logics LTL , CTL and CTL* combined with regular languages. A characteristic feature of these new extensions of conventional temporal logics is that temporal operators and basic predicates are parameterized by regular languages. In our early papers we estimated the expressive power of the new temporal logic Reg-LTL and introduced model checking algorithm for Reg-LTL , Reg-CTL , and Reg-CTL*. The main issue which still remains unclear is the complexity of decision problems for these logics. In this paper we give a complete solution to satisfiability checking and model checking problems for Reg-LTL and prove that both problems are Pspace-complete. The computational hardness of the problems under consideration is easily proved by reducing to them the intersection emptyness problem for the families of regular languages [16]. The main result of the paper is an algorithm for reducing the satisfiability checking Reg-LTL formulas to the emptiness problem for Buchi automata of relatively small size and a description of a technique that allows one to check the emptiness of the obtained automata within space polynomial of the size of input formulas.

关键词： temporal logics regular language transducer model checking satisfiability checking Buchi automata emptiness problem

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AADMIP: Adversarial Attacks and Defenses Modeling in Industrial Processes 33

AADMIP: Adversarial Attacks and Defenses Modeling in Industr...

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33rd International Joint Conference on Artificial Intelligence (IJCAI)

作者： Pozdnyakov, Vitaliy Kovalenko, Aleksandr Makarov, Ilya Drobyshevskiy, Mikhail Lukyanov, Kirill Russian Acad Sci Ivannikov Inst Syst Programming Moscow Russia Natl Res Univ Moscow Inst Phys & Technol Moscow Russia AIRI Moscow Russia ISP RAS Res Ctr Trusted Artificial Intelligence Moscow Russia

ISBN: (纸本)9781956792041

The development of the smart manufacturing trend includes the integration of Artificial Intelligence technologies into industrial processes. One example of such implementation is deep learning models that diagnose the current state of a technological process. Recent studies have demonstrated that small data perturbations, named adversarial attacks, can significantly affect the correct predictions of such models. This fact is critical in industrial systems, where AI-based decisions can be made to manage physical equipment. In this work, we present a system which can help to evaluate the robustness of technological process diagnosis models to adversarial attacks, as well as consider protection options. We briefly review the system's modules and describe useful applications. Our demo video is available at: http://***/3by9zcj5.

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Gradient-Free Algorithms for Solving Stochastic Saddle Optimization Problems with the Polyak-Lojasiewicz Condition

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programming AND COMPUTER SOFTWARE 2023年第6期49卷 535-547页

作者： Sadykov, S. I. Lobanov, A. V. Raigorodskii, A. M. Moscow Inst Phys & Technol Inst Per 9 Dolgoprudnyi 141701 Russia Russian Acad Sci Ivannikov Inst Syst Programming Trusted Artificial Intelligence Res Ctr Ul Solzhenitsyna 25 Moscow 109004 Russia Adyghe State Univ Caucasian Math Ctr Ul Pervomaiskaya 208 Maykop 385000 Russia

This paper focuses on solving a subclass of stochastic nonconvex-nonconcave black box optimization problems with a saddle point that satisfy the Polyak-Lojasiewicz (PL) condition. To solve this problem, we provide the first (to our best knowledge) gradient-free algorithm. The proposed approach is based on applying a gradient approximation (kernel approximation) to an oracle-biased stochastic gradient descent algorithm. We present theoretical estimates that guarantee its global linear rate of convergence to the desired accuracy. The theoretical results are checked on a model example by comparison with an algorithm using Gaussian approximation.

关键词： Stochastic systems

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