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作者： Kalinov, Alexey Lastovetsky, Alexey Robert, Yves Institue for System Programming Russain Academy of Sciences B. Kommunisticheskaya 25 109004 Moscow Russia Department of Computer Science University College Dublin Belfield Dublin 4 Ireland LIP Ecole Normale Supérieure de Lyon Laboratoire LIP F-69364 Lyon Cedex 07 France

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Searching by Code: a New SearchBySnippet Dataset and SnippeR Retrieval Model for Searching by Code Snippets

arXiv

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arXiv 2023年

作者： Sedykh, Ivan Abulkhanov, Dmitry Sorokin, Nikita Nikolenko, Sergey Malykh, Valentin Huawei Noah's Ark lab Russia St. Petersburg Department of the Steklov Institute of Mathematics Russia Ivannikov Institute for System Programming Russia

Code search is an important and well-studied task, but it usually means searching for code by a text query. We argue that using a code snippet (and possibly an error traceback) as a query while looking for bugfixing instructions and code samples is a natural use case not covered by prior art. Moreover, existing datasets use code comments rather than full-text descriptions as text, making them unsuitable for this use case. We present a new SearchBySnippet dataset implementing the search-by-code use case based on StackOverflow data;we show that on SearchBySnippet, existing architectures fall short of a simple BM25 baseline even after fine-tuning. We present a new single encoder model SnippeR that outperforms several strong baselines on SearchBySnippet with a result of 0.451 Recall@10;we propose the SearchBySnippet dataset and SnippeR as a new important benchmark for code search evaluation. Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

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Towards safe data flow processing by integration of design by contract in deterministic UML activities

Towards safe data flow processing by integration of design b...

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XXII International Symposium on Information, Communication and Automation Technologies, ICAT

作者： Zamira Daw Marcus Vetter Josef Boercsoek Institute of Embedded Systems Hochschule Mannheim-University of Applied Sciences Mannheim Germany Department of Computer Architecture and System Programming University of Kassel Kassel Germany

Data flow processing is a common task of embedded systems which is usually modeled as a pipeline. Errors in a block of this pipeline can be propagated through it thus leading to unexpected and erroneous behaviors. For safety related applications, this pipeline has to be able to identify and react to failures. The DMOSES model-driven development method uses deterministic UML activities to describe and implement data flow processing. This method ensures deterministic behavior of concurrent processing. Design by Contract defines formal, precise and verifiable interfaces for software components. We propose a development method for safe data flow processing based on the integration of this concept in deterministic UML activities. This integration allows the identification of errors by detection of contracts violation. This paper presents an extension of the DMOSES tool for contracts verification at the model level and their monitoring at runtime.

关键词： Unified modeling language Contracts Monitoring Embedded systems Object oriented modeling Safety Pins

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Pulse DRFM Jamming Formation and Its Mathematical Simulation

Pulse DRFM Jamming Formation and Its Mathematical Simulation

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Ukrainian Microwave Week (UkrMW), IEEE

作者： Viacheslav P. Riabukha Andrii V. Semeniaka Yevhen A. Katiushyn Dmytro V. Atamanskiy department of system analysis modeling and programming Limited liability company “Radionix” Kyiv Ukraine Ivan Kozhedub Kharkiv National Air Force University Kharkiv Ukraine

The paper describes the principles for formation of a simulated pulse DRFM jamming in response to a sounding linear frequency modulated (LFM) pulse, the technique and results of mathematical (simulation) modeling of s... 详细信息

ISBN: (纸本)9798350331530

关键词： Target tracking Frequency modulation Chirp modulation Radar Radar tracking Microwave theory and techniques Mathematical models

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Lemma Functions for Frama-C: C Programs as Proofs

Lemma Functions for Frama-C: C Programs as Proofs

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Ivannikov ISPRAS Open Conference (ISPRAS)

作者： Grigoriy Volkov Mikhail Mandrykin Denis Efremov Faculty of Computer Science Higher School of Economics Moscow Russia Software Engineering Department Ivannikov Institute for System Programming of the Russian Academy of Sciences Moscow Russia

ISBN: (纸本)9781728112763;9781728112756

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, and evaluation on a set of string-manipulating functions from the Linux kernel. We illustrate the benefits our approach can bring concerning the effort required to prove lemmas, compared to the approach based on interactive provers such as Coq. Current limitations of the method and its implementation are discussed.

关键词： Tools Manuals Contracts Linux Kernel Economics

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The Knowledge Management system Development for Smart Education

The Knowledge Management System Development for Smart Educat...

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IEEE Conference on Quality Management, Transport and Information Security, Information Technologies (IT&MQ&IS)

作者： Natalia V. Dneprovskaya Inessa V. Shevtsova Department of Information System Management and Programming Plekhanov Russian University of Economics Moscow Russia School of Public Administration Lomonosov Moscow State University Moscow Russia

ISBN: (纸本)9781538667583

This paper is devoted to solving a problem of improving the content of education and instructional materials used. The digital technologies are developing so fast that the engineering aspects of application and scientific investigations start blurring the aspects associated with the methodology and content of smart learning. The need for development of digital economy places severe requirements not only upon know-how, but also upon the content of smart learning, i.e., the content of educational courses shall be a reflection of professional activity. The techniques and methods of knowledge management can provide for a desired rate and quality of development of educational materials. This paper describes a knowledge management system which employs intelligent database, network and co-authorship instruments to insure the compliance of the content being developed with the requirements of digital economy and fills out the smart learning with a qualitative content.

关键词： Training Knowledge management Electronic learning Organizations Task analysis Instruments

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Modelling the Decision Making Process on Legal Conducting the Surrogate Motherhood

Modelling the Decision Making Process on Legal Conducting th...

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IEEE International Conference on Dependable systems, Services and Technologies (DESSERT)

作者： Tetiana Hovorushchenko Alla Herts Yelyzaveta Hnatchuk Computer Engineering & System Programming Department Khmelnytskyi National University Khmelnytskyi Ukraine Civil Law and Legal Proceedings Department Ivan Franko National University of Lviv Lviv Ukraine

ISBN: (数字)9781728199573

ISBN: (纸本)9781728199580

Currently, there is a need in Ukraine for the design and development of multidisciplinary decision support systems (DSSs) for the medical and other related spheres - for example, the medical law sector, in particular, the DSS for the surrogacy's legal regulation field. This DSS will be able to protect doctors from potentially wrong decisions by taking into account all available information when making the decisions. For design such DSS, it's necessary to conduct the modelling of the decision-making process on surrogacy's legal conducting, that is the goal of this research. In this paper, there are the theoretical foundations of using the ontologies for the decision-making process on surrogacy's legal conducting, a model of base ontology with the necessary requirements and recommendations for conducting the surrogate motherhood, and ontology-based model of the decision-making process on surrogacy's legal conducting. The conducted modelling is a theoretical basis for the development of methods and design of DSS in the field of legal regulation of surrogate motherhood.

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Forecasting and modeling on average rainwater and vapor pressure in Chelyabinsk Russia using deep learning models

Forecasting and modeling on average rainwater and vapor pres...

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6th Smart Cities Symposium (SCS 2022)

作者： M. Abotaleb T. Makarovskikh A. Ali Subhi H. Alkattan A.O. Adebayo Department of System Programming South Ural State University Chelyabinsk Russia University of Diyala Diyala Iraq Information Communication and Technology Department Lagos State University Lagos Nigeria

Machine learning technique is full-fledged as a boosting sector to develop modeling and forecasting of complex time series observations in the present environment. This study made an attempt to inspect the future performance of rainfall data and vapor in Chelyabinsk by using a machine learning technique. The data series is divided into a training set (60%) and a test set (40%) for model developing a validation purpose. We further developed deep learning models such as, LSTM, BILSTM, GRU and compared on the basis of ME, RMSE, MAE, MPE, MAPE, ACF1 on the training data set. For testing data set, we compared these deep learning models based on RMSE. LSTM model acts as a superior machine learning model over BILSTM and GRU in this data series. Forecasting performance of these three models significantly at par. This finding may be significant to build a strong literature of the Chelyabinsk weather's forecast, which can be helpful for policy makers and researchers. Also, we strongly believe that, this work could be used as a literature adaptation of machine learning technique for complex time series over statistical models.

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Optimizing Machine Learning Algorithms to Enhance Blood Donation for Liver Patients: A Case Study 7

Optimizing Machine Learning Algorithms to Enhance Blood Dona...

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7th IET Smart Cities Symposium, SCS 2023

作者： Mijwil, Maad M. El-Kenawy, El-Sayed M. Bala, Indu Aljanabi, Mohammad Abotaleb, Mostafa Ibrahim, Abdelhameed Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt School of Electrical and Electronics Engineering Lovely Professional University Punjab India Department of Computer Aliraqia University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

ISBN: (纸本)9781839539831

Blood is vital for transporting oxygen, nutrients, and hormones to all body parts as it circulates through arteries and veins. It removes carbon dioxide, regulates body temperature, and maintains the body's immune system. Individuals constantly need blood and its derivatives to save their lives and improve their health through medical treatments and surgical operations. Liver diseases are one of the diseases that affects the health of individuals and requires blood to continue living. These diseases cause significant damage to people's health, and early diagnosis plays a crucial role in saving lives. In this paper, machine learning algorithms (support vector machine and random forest) are involved in detecting liver diseases and determining whether donors are suitable to donate blood from blood values. This paper is applied research that found that the performance measures of the random forest algorithm achieved excellent performance in identifying suitable people to donate blood. © The Institution of Engineering & Technology 2023.

关键词： Support vector machines

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Network-based safety-related vibration and position analysis for railway vehicles

Network-based safety-related vibration and position analysis...

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International Conference on Connected Vehicles and Expo (ICCVE)

作者： Samer Telawi Yusuf Sima Bashier Machmur Ali Hayek Josef Börcsök Udo Pinders Walter Schreiber Department of Computer Architecture and System Programming University of Kassel Kassel Germany Universitat Kassel Kassel Hessen DE Reuschling GmbH & Co KG Hattingen Germany

Nowadays, many considerable efforts are focused on the development of efficient and effective systems that increase the productivity of vehicles by controlling and manipulating the extraordinary states, such as sliding and spinning, during the operational time. Those states play a central role in the performance of the vehicles described as an interaction among different mechanical parts regarding their life-time, their wear and tear, as well as the maintenance costs. In addition, these states ultimately affect the safety of target system and its environment. Therefore, the necessity of avoiding, controlling, or manipulating these states to lower their effects into a tolerable level has become the major driver for conducting the current research work. In this paper, a prototype for safety-related platform for detecting and controlling railway vehicles states by means of vibration capture is presented. Additionally, test procedures in order to collect the vibration data related to each state are presented; these tests were performed under the supervision of an industrial partner. Moreover, the recognized initial patterns of the vibration signals related to the studied states are also introduced.

关键词： Safety Vehicles Acceleration Vibrations Computer architecture Sensor systems

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