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Approbation of a Generalization of the Synergetic Design of Regulators for a Stochastic Base Immunology System 10

Approbation of a Generalization of the Synergetic Design of ...

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10th International Conference on Information Technology and Nanotechnology, ITNT 2024

作者： Kolesnikova, Svetlana Kustova, Ekaterina Institute Of Computational Systems And Programming St. Petersburg State University Of Aerospace Instrumentation St. Petersburg Russia

ISBN: (纸本)9798350372939

The results of application of the invariance condition as the basic principle of the synergetic control theory to a stochastic biomedical object - immunology, are presented. Using four-dimensional nonlinear base object with a delay, it is shown that the assumptions on the object controllability in the state space and the analytical description of the target invariant of the system are the sufficient conditions for an existence of a stochastic regulator minimizing the dispersion of the output variable in transferring a random controlled object to a target manifold of states. © 2024 IEEE.

关键词： Immunology

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METHOD OF DETECTION OF INTRUSIONS BASED ON STACKING META-ALGORITHM 5

METHOD OF DETECTION OF INTRUSIONS BASED ON STACKING META-ALG...

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5th IEEE KhPI Week on Advanced Technology, KhPIWeek 2024

作者： Gavrylenko, Svitlana Zozulia, Vladislav Khatsko, Nataliia Department of Computer Engineering and Programming National Technical University "Kharkiv Polytechnic Institute" Kharkiv Ukraine Department Information Systems and Technologies National Technical University «Kharkiv Polytechnic Institute» Kharkiv Ukraine

ISBN: (纸本)9798350384499

An analysis of modern computer network intrusion detection systems was carried out. The application of machine and deep learning methods for classification problems has been investigated. The UNSW-NB15 dataset, developed at the Australian Cyber Security Center's (ACCS) Cyber Range Laboratory, contains data on normal network operations and synthetic intrusions. Data pre-processing was performed, including class balancing using the SMOTEENN method and selection of informative features using the Recursive Feature Elimination method. The possibility of using the stacking meta-algorithm to detect intrusions into computer networks has been investigated. A new algorithm for generating packets of raw data is proposed, which generates two sets of training data: one for training basic models, the other for a meta-model. A study of the effectiveness of using Random Forest, ANN, K Nearest Neighbor methods and Support Vector Machine and Random Forest as a decision-making meta-model was conducted. The use of the stacking meta-algorithm with the proposed algorithm for forming packets of output data, as well as basic models and a meta-model, led to a significant improvement in the quality of the model. It was found that, on average, recall and f1 score increased by 55.6% and 37.4%, respectively, compared to raw data and other models. ©2024 IEEE.

关键词： Network intrusion

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WIP: An Engaging Undergraduate Intro to Model Checking in Software Engineering Using TLA+ 54

WIP: An Engaging Undergraduate Intro to Model Checking in So...

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54th IEEE Frontiers in Education Conference, FIE 2024

作者： Läufer, Konstantin Mertin, Gunda Thiruvathukal, George K. Loyola University Software and Systems Laboratory Department of Computer Science Chicago United States Institute for Software Engineering and Programming Languages University of Lübeck Germany

ISBN: (纸本)9798350351507

Background: In this Innovative Practice Work in Progress, we present our initial efforts to integrate formal methods, with a focus on model-checking specifications written in Temporal Logic of Actions (TLA+), into computer science education, targeting undergraduate juniors/seniors and graduate students. Many safety-critical systems and services crucially depend on correct and reliable behavior. Formal methods can play a key role in ensuring correct and safe system behavior, yet remain underutilized in educational and industry contexts. Aims: We aim to (1) qualitatively assess the state of formal methods in computer science programs, (2) construct level-appropriate examples that could be included midway into one's undergraduate studies, (3) demonstrate how to address successive 'failuresy' through progressively stringent safety and liveness requirements, and (4) establish an ongoing framework for assessing interest and relevance among students. Methods: We detail our pedagogical strategy for embedding TLA+ into an intermediate course on formal methods at our institution. After starting with a refresher on mathematical logic, students specify the rules of simple puzzles in TLA+ and use its included model checker (known as TLC) to find a solution. We gradually escalate to more complex, dynamic, event-driven systems, such as the control logic of a microwave oven, where students will study safety and liveness requirements. We subsequently discuss explicit concurrency, along with thread safety and deadlock avoidance, by modeling bounded counters and buffers. Results: Our initial findings suggest that through careful curricular design and choice of examples and tools, it is possible to inspire and cultivate a new generation of software engineers proficient in formal methods. Conclusions: Our initial efforts suggest that 84% of our students had a positive experience in our formal methods course. Our future plans include a longitudinal analysis within our own institution and

关键词： Students

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Analysis of Trade-Offs Between Accuracy And Speed of Real-Time Object Detectors for the Tasks of Explosive Ordnance Detection 5

Analysis of Trade-Offs Between Accuracy And Speed of Real-Ti...

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5th IEEE KhPI Week on Advanced Technology, KhPIWeek 2024

作者： Mishchuk, Vadym Podorozhniak, Andrii Department of Computer Systems Networks and Cybersecurity National Aerospace University "Kharkiv Aviation Institute" Kharkiv Ukraine Department of Computer Engineering and Programming National Technical University "Kharkiv Polytechnic Institute" Kharkiv Ukraine

ISBN: (纸本)9798350384499

This paper investigates the performance trade-offs between accuracy and inference time in real-time object detection models, particularly for detecting landmines and unexploded ordnance (UXO). Using subsets from the COCO validation dataset, the models' performance is evaluated across various input resolutions. Object detection has seen substantial advancements over the past few decades, propelled by deep learning and enhanced computational resources. However, the balance between accuracy and inference time differs among models and configurations, requiring detailed evaluation to identify the optimal solution for specific applications like landmine and UXO detection. This balance is critical for autonomous robotic systems, where swift and accurate decision-making is imperative. ©2024 IEEE.

关键词： Landmine detection

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Predicting the Performance of ATL Model Transformations 23

Predicting the Performance of ATL Model Transformations

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14th Annual ACM/SPEC International Conference on Performance Engineering, ICPE 2023

作者： Groner, Raffaela Bellmann, Peter Höppner, Stefan Thiam, Patrick Schwenker, Friedhelm Tichy, Matthias Institute of Software Engineering and Programming Languages Ulm University Ulm Germany Institute of Neural Information Processing Ulm University Ulm Germany Institute of Medical Systems Biology Ulm University Ulm Germany

ISBN: (纸本)9798400700682

Model transformation languages are special-purpose languages, which are designed to define transformations as comfortably as possible, i.e., often in a declarative way. Typically, developers create their transformations based on small input models which systematically cover the language of the input models. This makes it difficult for the developers to estimate how the transformations would perform for a large and diverse set of input models. Hence, developers would benefit from an approach for predicting the performance of model transformations based on just abstract characteristics of input models. Regression approaches based on machine learning lend themselves well to such predictions. However, it is currently unknown, whether and which regression approach is suitable in this context as well as how a model should be abstractly characterized for this purpose. We conducted several experiments to analyze how well different machine learning methods predict the execution time of model transformations defined in the Atlas Transformation Language (ATL) transformations for distinct sets of model characteristics. As possible methods, we have investigated linear regression, random forests and support vector regression using a radial basis function kernel. The results of our experiments show that support vector regression is the best choice in terms of usability and prediction accuracy for the model transformation modules covered in our experiments and is thus suited for a prediction approach. In addition, simple model characterizations based only on the number of model elements, the number of references, and the number of attributes are a suitable way to easily describe a model and to achieve decent prediction accuracy. © 2023 Owner/Author.

关键词： Forecasting

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METHODS FOR IMPROVING THE QUALITY OF CLASSIFICATION ON IMBALANCED DATA 4

METHODS FOR IMPROVING THE QUALITY OF CLASSIFICATION ON IMBAL...

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4th IEEE KhPI Week on Advanced Technology, KhPI Week 2023

作者： Gavrylenko, Svitlana Vladislav, Zozulia Khatsko, Nataliia Department of Computer Engineering and Programming National Technical University "Kharkiv Polytechnic Institute" Kharkiv Ukraine Department of Information Systems and Technologies National Technical University «Kharkiv Polytechnic Institute» Kharkiv Ukraine

ISBN: (纸本)9798350395532

The subject of the study is methods of balancing raw data. The purpose of the article is to improve the quality of intrusion detection in computer networks by using class balancing methods. Task: to investigate methods of balancing classes and to develop a classification method on imbalanced data to increase the level of network security. The methods used are: methods of artificial intelligence, machine learning. The following results were obtained: Class balancing methods based on Undersampling, Oversampling and their combinations were studied. The following methods were chosen for further research: SMOTEENN, SVMSMOTE, BorderlineSMOTE, ADASYN, SMOTE, KMeansSMOTE. The UNSW-NB 15 set was used as the source data, which contains information about the normal functioning of the network and during intrusions. A decision tree based on the CART (Classification And Regression Tree) algorithm was used as the basic classifier. According to the research results, it was found that the use of the SMOTEENN method provides an opportunity to improve the quality of detection of intrusions in the functioning of the network. Conclusions. The scientific novelty of the obtained results lies in the complex use of data balancing methods and the method of data classification based on decision trees to detect intrusions into computer networks, which made it possible to reduce the number of Type II errors. © 2023 IEEE.

关键词： Classification (of information)

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Formalization of Data Exchange Between the systems of Monitoring and Control over an Anaerobic Bioreactor 4

Formalization of Data Exchange Between the Systems of Monito...

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4th International Conference on Control systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2022

作者： Kolesnikova, Svetlana Fomenkova, Anastasia Institute of Computational Systems and Programming St. Petersburg State University of Aerospace Instrumentation St. Petersburg Russia

ISBN: (数字)9781665456593

ISBN: (纸本)9781665456593

A conceptual scheme for monitoring and control of the technical state of a complex system - an anaerobic bioreactor - is proposed. A mathematical apparatus and the heart of its algorithmic software are presented as a basis for the synthesis of a smart system of control over the technological processes at production facilities. Examples of the analytical synthesis of an adaptive control system for a nonlinear multidimensional object and an observer algorithm for unmeasurable variables are presented. © 2022 IEEE.

关键词： Adaptive control systems

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A Comparative Analysis of Multi-agent Simulation Platforms for Energy and Mobility Management 20th

A Comparative Analysis of Multi-agent Simulation Platforms ...

引用

Proceedings of the 20th European Conference on Multi-Agent systems, EUMAS 2023

作者： Ali, Aliyu Tanko Leucker, Martin Schuldei, Andreas Stellbrink, Leonard Sachenbacher, Martin Institute for Software Engineering and Programming Languages University of Lübeck Ratzeburger Allee 160 Lübeck Germany Institute for Multimedia and Interactive Systems University of Lübeck Ratzeburger Allee 160 Lübeck Germany

ISBN: (纸本)9783031432637

Effective energy and mobility management benefits from multi-agent simulations (MAS) to model complex interactions among various agent types. Selecting the optimal MAS platform to implement and simulate these interactions is vital for achieving accurate results, scalability to realistic problem sizes, and efficient computational performance. This paper investigates the energy and mobility domain and identifies key parameters such as the number and complexity of agents, parallel computing power, CPU requirements etc., for developing MAS in the context of this domain. It then presents a comprehensive evaluation of various MAS development platforms. Using a multi-level selection and elimination approach, we narrowed down our evaluation to two final candidates. We then implemented key aspects of our model in both platforms to compare them in terms of practical relevance. Our findings reveal that the *** platform outperforms the Mesa platform in terms of runtime performance, has a smaller memory footprint for large numbers of agents, and offers scalability, making it the most suitable choice for developing MAS for integrated energy and mobility models. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Scalability

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Predicting the Performance of ATL Model Transformations (extended abstract)

Predicting the Performance of ATL Model Transformations (ext...

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2024 Software Engineering, SE 2024

作者： Groner, Raffaela Bellmann, Peter Höppner, Stefan Thiam, Patrick Schwenker, Friedhelm Tichy, Matthias Ulm University Institute for Software Engineering and Programming Languages James-Franck-Ring UlmD-89069 Germany Ulm University Institute of Medical Systems Biology Albert-Einstein-Allee UlmD-89081 Germany Ulm University Institute of Medical Systems Biology Institute of Neural Information Processing Albert-Einstein-Allee UlmD-89081 Germany Ulm University Institute of Neural Information Processing James-Franck-Ring UlmD-89069 Germany

ISBN: (纸本)9783885797371

Model transformations are used in different areas of computer science. They are often used during the development of software but also at runtime, e.g., to update a digital twin. However, users of these languages still suffer from very limited tool support, especially in the context of performance engineering techniques, users are left to their own devices. In particular, performance prediction approaches for model transformations are unknown until now. To tackle this issue, we performed several experiments in which we used three different machine learning approaches to predict the performance of five transformations written in the Atlas Transformation Language (ATL) based on different characterizations of input models. In our experiments, we trained a random forest, a linear regression, and a support vector regression model with a radial basis functional kernel using real-world models. The results of our experiments show that we can achieve a mean absolute percentage error between 2.07% and 10.63% using support vector regression and a straightforward model characterization consisting of the number of model elements, the number of references, and the number of attributes. We also show a weakness of our approach which fails to predict the performance of transforming attributes with an arbitrary size, like string attributes. More details about our experiments can be found in our corresponding publication, which was accepted by the 2023 ACM/SPEC International Conference on Performance Engineering (ICPE) [Gr23]. © 2024 Gesellschaft fur Informatik (GI). All rights reserved.

关键词： Prediction models

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The method of dynamic routing in Self-healing Networks 5

The method of dynamic routing in Self-healing Networks

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5th IEEE KhPI Week on Advanced Technology, KhPIWeek 2024

作者： Anna, Shyman Kuchuk, Nina Kovalenko, Andriy Kashkevich, Svitlana Partyka, Stanislav Yankovskyi, Oleksandr Department of Computer Engineering and Programming National Technical University Kharkiv Polytechnic Institute" Kharkiv Ukraine Department of Electronic Computers Kharkiv National University of Radio Electronics Kharkiv Ukraine Department of Computerized Management Systems National Aviation University Kyiv Ukraine

ISBN: (纸本)9798350384499

The report proposes a dynamic routing method for Self-healing Networks (ShN). The method takes into account the specific features of ShN. During routing, the flow of service information is reduced. The search for the optimal route is carried out using a convolutional neural network. The method significantly outperforms existing methods when some network nodes fail. ©2024 IEEE.

关键词： Dynamic routing algorithms

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