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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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Evolution of software in automated production systems: challenges and research directions

Evolution of software in automated production systems: chall...

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Software Engineering-Konferenz, SE 2016 - Software Engineering Conference, SE 2016

作者： Vogel-Heuser, Birgit Fay, Alexander Schaefer, Ina Tichy, Matthias Institute of Automation and Information Systems Technische Universität München Boltzmannstr. 15 Garching near Munich85748 Germany Institute of Automation Technology Helmut Schmidt University Holstenhofweg 85 Hamburg22043 Germany Institute of Software Engineering and Automotive Informatics Technische Universität Braunschweig Mühlenpfordtstr. 23 Braunschweig38106 Germany Institute of Software Engineering and Programming Languages Universität Ulm Ulm89069 Germany

ISBN: (纸本)9783885796466

Coping with evolution in automated production systems implies cross-disciplinary challenges along the system's life-cycle for variant-rich systems of high complexity. We provide an interdisciplinary survey on challenges and research directions in the evolution of automated production systems. After an initial discussion about the nature of automated production systems and their specific development process, we sketch in this extended abstract the challenges associated with evolution in the different development phases and a couple of cross-cutting areas.

关键词： Life cycle

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Leveraging Applications of Formal Methods, Verification, and Validation 1

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丛书名： Communications in Computer and Information Science

1000年

作者： Reiner Hähnle Jens Knoop Tiziana Margaria Dietmar Schreiner Bernhard Steffen

ISBN: (数字)9783642347818

ISBN: (纸本)9783642347801

This volume contains a selection of revised papers that were presented at the Software Aspects of Robotic systems, SARS 2011 Workshop and the Machine Learning for System Construction, MLSC 2011 Workshop, held during October 17-18 in Vienna, Austria, under the auspices of the International Symposium Series on Leveraging Applications of Formal Methods, Verification, and Validation, ISoLA. The topics covered by the papers of the SARS and the MLSC workshop demonstrate the breadth and the richness of the respective fields of the two workshops stretching from robot programming to languages and compilation techniques, to real-time and fault tolerance, to dependability, software architectures, computer vision, cognitive robotics, multi-robot-coordination, and simulation to bio-inspired algorithms, and from machine learning for anomaly detection, to model construction in software product lines to classification of web service interfaces. In addition the SARS workshop hosted a special session on the recently launched KOROS project on collaborating robot systems that is borne by a consortium of researchers of the faculties of architecture and planning, computer science, electrical engineering and information technology, and mechanical and industrial engineering at the Vienna University of Technology. The four papers devoted to this session highlight important research directions pursued in this interdisciplinary research project.

关键词： Artificial Intelligence Data Mining and Knowledge Discovery Software Engineering Computation by Abstract Devices Information Storage and Retrieval Pattern Recognition

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Method of Detection of Intrusions Based on Stacking Meta-Algorithm

Method of Detection of Intrusions Based on Stacking Meta-Alg...

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Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Svitlana Gavrylenko Vladislav Zozulia Nataliia Khatsko 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: (数字)9798350384499

ISBN: (纸本)9798350384505

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.

关键词： Training Support vector machines Computational modeling Stacking Training data Intrusion detection Predictive models Nearest neighbor methods Data models Random forests

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

arXiv

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arXiv 2024年

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

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 "failures" 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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Methods for Improving the Quality of Classification on Imbalanced Data

Methods for Improving the Quality of Classification on Imbal...

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Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Svitlana Gavrylenko Zozulia Vladislav Nataliia Khatsko 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

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.

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Classified emotion as implicit recommendation system feedback

Classified emotion as implicit recommendation system feedbac...

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Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Andrii Kuliahin Heorhii Kuchuk 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

the paper proposes the use of 3D convolutional neural network for recognizing user emotions on videos in a recommender system. The data approach aims to use the recognized emotion as important implicit feedback and improve the recommendation result. This is expected to significantly improve the performance of the recommender system.

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Algorithmic Support for Building a Distributed IoT System in a Cloud Service

Algorithmic Support for Building a Distributed IoT System in...

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Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Mykola Zamkovyi Svitlana Gavrylenko Kyrylo Khatsko Nataliia Khatsko dept. Information Systems and Technologies National Technical University «Kharkiv Polytechnic Institute» Kharkiv Ukraine Department of Computer Engineering and Programming National Technical University “Kharkiv Polytechnic Institute” Kharkiv Ukraine

The Internet of Things (IoT) today already connects billions of different IoT devices with the Internet. With the advent of new services and services, new challenges arise: how to make a cloud service publicly available, and reliable, how and where to store data. The article considers an example of the implementation of an IoT application with cloud components, considers the implementation of connecting IoT components to a cloud provider, and presents the IoT architecture. The focus is on the architecture and implementation of data exchange protocols, the implementation of protocols? for data collection and management of remote system components Given the large amount of data transmitted by IoT devices to the cloud, data compression and interaction with cloud services is a very relevant topic. Therefore, the article also offers recommendations for managing the traffic of IoT devices. The purpose of this article is to provide a description and algorithm for connecting IoT devices to the cloud, to bring together disparate information, and make it open and understandable to beginners and academic researchers.

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Traffic Modeling for the Industrial Internet of NanoThings 4

Traffic Modeling for the Industrial Internet of NanoThings

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

作者： Kuchuk, Nina Kovalenko, Andriy Ruban, Igor Shyshatskyi, Andrii Zakovorotnyi, Oleksandr Sheviakov, Iurii 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 Civil AviationI nstitute Ivan Kozhedub Kharkiv National Air Force University Kharkiv Ukraine

ISBN: (纸本)9798350395532

Industrial Internet of NanoThings (IIoNT) traffic model proposed. The model is based on the developed algorithm for Dynamic Data Composition Control. The application of the algorithm made it possible to reduce the total amount of transmitted information from the end nodes of IIoNT. The model made it possible to determine the parameters of aggregation traffic of IIoNT cluster gateway. With the calculated parameters, the value of the aggregated package is maximized. The main limitation is not exceeding the value of the boundary delay for the transmission of sensor readings. The model also allows you to dynamically determine the required amount of the gateway buffer memory. © 2023 IEEE.

关键词： Internet of things

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A Bidirectional LSTM for Estimating Dynamic Human Velocities from a Single IMU

A Bidirectional LSTM for Estimating Dynamic Human Velocities...

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International Conference on Indoor Positioning and Indoor Navigation (IPIN)

作者： Tobias Feigl Sebastian Kram Philipp Woller Ramiz H. Siddiqui Michael Philippsen Christopher Mutschler Programming Systems Group Friedrich-Alexander University Erlangen-Nürnberg (FAU) Germany Precise Positioning and Analytics Department Fraunhofer Institute for Integrated Circuits IIS Numberg Germany

The main challenge in estimating human velocity from noisy Inertial Measurement Units (IMUs) are the errors that accumulate by integrating noisy accelerometer signals over a long time. Known approaches that work on step length estimation are optimized for a specific application, sensor position, and movement type, require an exhaustive (manual) parameter tuning, and can thus not be applied to other movement types or to a broader range of applications. Moreover, varying dynamics (as they are present for instance in sports applications) cause abrupt and unpredictable changes in step frequency or step length and hence result in erroneous velocity estimates. We use machine learning (ML) and deep learning (DL) to estimate a human's velocity. Our approach is robust to varying motion states and orientation changes in dynamic situations. On data from a single un-calibrated IMU, our novel recurrent model not only outperforms the state-of-the-art on instantaneous velocity (≤0.10 m/s) and on traveled distance (≤29 m/km). It can also generalize to different and varying rates of motion and provides accurate and precise velocity estimates.

关键词： Microsoft Windows Estimation Acceleration Legged locomotion Feature extraction Pipelines Foot

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