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Iraqi Journal for Computer Science and Mathematics 2024年第3期5卷 441-472页

作者： Abotaleb, Mostafa Department of System Programming South Ural State University Chelyabinsk454080 Russia

This study introduces an advanced algorithm based on the Generalized Least Deviation Method (GLDM) tailored for the univariate time series analysis of COVID-19 data. At the core of this approach is the optimization of a loss function, strategically designed to enhance the accuracy of the model’s predictions. The algorithm leverages second-order terms, crucial for capturing the complexities inherent in time series data. Our findings reveal that by optimizing the loss function and effectively utilizing second-order model dynamics, there is a marked improvement in the predictive performance. This advancement leads to a robust and practical forecasting tool, significantly enhancing the accuracy and reliability of univariate time series forecasts in the context of monitoring COVID-19 trends. © 2024 College of Education, Al-Iraqia University. All rights reserved.

关键词： Prediction models

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Implementation of Safety-Related Intrusion Detection for an Industrial Robotic Arm

Implementation of Safety-Related Intrusion Detection for an ...

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2025 International Conference on Control, Automation, and Instrumentation, IC2AI 2025

作者： Haydar, Georgio Abou Telawi, Samer Borcsok, Josef Architecture and System Programming University of Kassel Department of Computer Kassel Germany

ISBN: (纸本)9798331529604

Ensuring the safety of human workers collaborating with industrial robots is paramount. This research work presents a novel approach by developing a safety-related intruder detection system for the operational zones of industrial robots, following the IEC 61508 standard and adopting the related redundant architecture. The hardware integrates light curtains and radar sensors in a dual-layer configuration, while the software utilizes a safety system-on-chip to implement real-time diagnostics and fault tolerance. Protecting employees and ensuring a smooth and safe work environment are significant concerns for all companies. As a result, numerous standards and regulations have been established to provide safe collaboration between humans and machines. However, despite these measures, accidents continue to occur, resulting in varying degrees of injuries. The proposed system is depicted through a comprehensive schematic, emphasizing the integration of safety measures within the robotic environment. The detailed prototype demonstrates practical application, show-casing the system's ability to detect intrusions, initiate emergency responses, and transition to fail-safe states during component failures. This research work advances safety protocols in human-robot collaboration within industrial settings, fostering a safe working environment through a well-defined safety framework. © 2025 IEEE.

关键词： Industrial robots

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Model Based Development Methodology in Compliance with ISO 26262 for Safe Automotive ECU

Model Based Development Methodology in Compliance with ISO 2...

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2023 IEEE International Conference on Electrical, Computer and Energy Technologies, ICECET 2023

作者： Hafiz, Muhammad Ikram University of Kassel Department of Computer Architecture and System Programming Kassel Germany

ISBN: (纸本)9798350327816

This work presents a practical approach of designing a functionally safe ECU for automotive application by implementing the Model Based Development (MBD) methodology. Functional safety (FuSa) in automotive can be achieved by strictly following the processes of electrical and electronic systems development as given in the ISO 26262. The scope of FuSa encompasses the risks emerging from systematic failures and random hardware failures. One approach to mitigate these failures is the Model Based Development (MBD) on which the ISO 26262 provides guidance. This approach enables to model an ECU and accelerates an IP creation by automatic RTL code generation for rapid prototyping on an FPGA level. In this work the MBD is implemented in accordance to the ISO 26262 to design and test a hardware model of an embedded ECU. The embedded Design under Test (DUT) is simulated and its output verified in Matlab/Simulink. Upon successful results, the RTL codes of the DUT are generated for a target FPGA. The RTL codes are simulated and the functionality of the DUT is verified at the FPGA level. © 2023 IEEE.

关键词： FPGA Functional Safety HDL code generation ISO 26262 Model Based Development systematic failures

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Static Analysis Methods for Memory Leak Detection: A Survey

Static Analysis Methods for Memory Leak Detection: A Survey

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2022 Ivannikov Memorial Workshop, IVMEM 2022

作者： Aslanyan, Hayk Gevorgyan, Zhora Mkoyan, Ruslan Movsisyan, Hovhannes Sahakyan, Vardan Sargsyan, Sevak Russian-Armenian University System Programming Department Yerevan Armenia

ISBN: (数字)9781665492973

ISBN: (纸本)9781665492973

Memory leaks are still one of the common bugs in programs written in languages without garbage collectors. There is a list of methods to detect such bugs. One of the approaches is to use static analysis. This paper discusses static analysis methods for memory leak detection. Mainly those methods use two stages. First, they use different types of graphs to find memory leaks faster but with less precision. Then, for the detected cases they use path-sensitive analysis to increase precision. Additionally, we tested available tools on Juliet test suite. We chose false positive rate (FPR) and false negative rate (FNR) as metrics. On average SMOKE and Clang static analysis tools show the best FPR and FNR. © 2022 IEEE.

关键词： Smoke

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A Comprehensive Review on Cybersecurity Issues and Their Mitigation Measures in FinTech

Iraqi Journal for Computer Science and Mathematics

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Iraqi Journal for Computer Science and Mathematics 2024年第3期5卷 45-91页

作者： Ali, Guma Mijwil, Maad M. Buruga, Bosco Apparatus Abotaleb, Mostafa Muni University Arua00256 Uganda Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of Library and Information Services Muni University Arua00256 Uganda Department of System Programming South Ural State University Chelyabinsk Russia

The fourth industrial revolution has seen the evolution and wide adoption of game-changing and disruptive innovation "financial technologies (FinTech)" around the globe. However, the security of FinTech systems and networks remains critical. This paper comprehensively reviews the evolving landscape of cybersecurity issues within the FinTech sector and explores effective mitigation measures. Four independent researchers reviewed relevant literature from IEEE Xplore Digital Library, ScienceDirect, Taylor & Francis, Emerald Insight, Springer, SAGE, Wiley Online Library, Hindawi, MDPI, ACM Digital Library, IGI Global, and Google Scholar. The research paper begins by examining the history and evolution of FinTech, drivers for the growth of FinTech, segments of the FinTech industry, FinTech ecosystem, FinTech business model, and FinTech application. Subsequently, it then delves into an analysis of the most pressing cybersecurity issues confronting FinTech firms, such as privacy concerns, data breaches, malware attacks, hacking, insider threats, identity theft, social engineering attacks, distributed denial-of-service attacks, and others. In response to these cybersecurity issues, the paper evaluates various mitigation strategies and best practices adopted by FinTech firms and regulatory bodies globally. These measures include technological solutions such as authentication and access control mechanisms, cryptography, big data analytics, intrusion detection/prevention systems, regular data backup, artificial intelligence and machine learning, cloud computing technologies, blockchain technologies, and fraud detection and prevention systems. The paper also emphasizes the importance of FinTech regulatory sandboxes, regulatory compliance, basic security training, continuous monitoring of threats, zero-trust policy, robust cybersecurity culture, regular testing, and stringent security policies to strengthen the FinTech ecosystem's cyber resilience. Based on empirical research, i

关键词： Denial-of-service attack

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Hyper-parameter Tuning for Long Short-Term Memory (LSTM) Algorithm to Forecast a Disease Spreading 8

Hyper-parameter Tuning for Long Short-Term Memory (LSTM) Alg...

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8th International Conference on Information Technology and Nanotechnology, ITNT 2022

作者： Makarovskikh, Tatiana Abotaleb, Mostafa South Ural State University System Programming Department Chelyabinsk Russia

ISBN: (数字)9781665485715

ISBN: (纸本)9781665485715

Artificial intelligence (AI), machine learning (ML), and deep learning (DL) are just a few of the technologies that can help healthcare organizations support real-time decision-making to control the spread of a pandemic. This study aims to investigate hyper-parameter tuning for Long Short-Term Memory (LSTM) to forecast SARSCoV2 daily infection cases in the Russian Federation by selecting the best loss function, activation function, number of epochs, number of neurons in a cell, and optimizer to minimize the error in addition to a good fit for the model on both the training and validation sets. In the meanwhile, we use LSTM, LSTMs (stacked LSTM), bidirectional LSTM, BILSTMs (stacked BILSTM), convolution neuron networks (Conv), ConvLSTMs and other forecasting models to forecast the daily SARSCoV2 infection cases one by one. We analyzed and compared the results obtained by these models. We discovered that BiLSTM can efficiently extract features from the data, which are the items from the previous day. With the extracted feature data, we used this model to forecast daily infection cases. We used BiLSTM to forecast SARSCoV2 spreading in the Russian Federation for one month. Hence, the Bidirectional LSTM can accurately predict daily SARSCoV2 infection cases in Russia, according to experiments. © 2022 IEEE.

关键词： Forecasting

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Searching by Code: a New SearchBySnippet Dataset and SnippeR Retrieval Model for Searching by Code Snippets 30

Searching by Code: a New SearchBySnippet Dataset and SnippeR...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

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

ISBN: (纸本)9782493814104

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. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Information retrieval

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A Method to Evaluate Binary Code Comparison Tools

A Method to Evaluate Binary Code Comparison Tools

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2021 Ivannikov Memorial Workshop, IVMEM 2021

作者： Arutunian, Mariam Hovhannisyan, Hripsime Vardanyan, Vahagn Sargsyan, Sevak Kurmangaleev, Shamil Aslanyan, Hayk Russian-Armenian University System programming department Yerevan Armenia Institute for System Programming Russian Academy of Sciences System programming department Moscow Russia

ISBN: (纸本)9781665423274

Binary code comparison tools are widely used to analyze vulnerabilities, search for malicious code, detect copyright violations, etc. The article discusses three tools - BCC, BinDiff, Diaphora. Those are based on static analysis of programs. The tools receive as input data two versions of the program in binary form and match their functions. The purpose of the article is to assess the quality of the tools. We developed a testing system to automatically determine the precision and recall of each instrument. F1 score on the developed testing system for BCC instrument is 85.6%, for BinDiff - 82.4%, for Diaphora - 64.7%. © 2021 IEEE.

关键词： Static analysis

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Development of a Safe Charging Infrastructure system: Requirements, Design, Verification and Validation 10th

Development of a Safe Charging Infrastructure System: Requ...

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10th International Conference on Smart Cities and Green ICT systems, SMARTGREENS 2021, and 7th International Conference on Vehicle Technology and Intelligent Transport systems, VEHITS 2021

作者： Kivelä, Tommi Sperling, Marvin Abdelawwad, Mohamed Drabesch, Malte Schwarz, Michael Börcsök, Josef Furmans, Kai Karlsruhe Germany Department of Computer Architecture and System Programming University of Kassel Kassel Germany

ISBN: (纸本)9783031170973

With the ongoing shift from fossil fuels towards electric mobility, there’s an increasing need for charging infrastructure for electric vehicles, both private and public. With this increasing role of charging infrastructure in day-to-day life, safety and security should be guaranteed for these systems. In this work we report on the development of an integrated electronic charging infrastructure system. The development was based on both current functional safety and charging infrastructure standards. The whole development process is presented, including requirements analysis, overall system design, safety hardware and software design, as well as the verification & validation of the safety system against the requirements set in the beginning. The presented work can be used as a basis and reference for the functional safety aspects when developing next generation charging infrastructure systems. © 2022, Springer Nature Switzerland AG.

关键词： systems analysis

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Implementation of Safety-Related Intrusion Detection for an Industrial Robotic Arm

Implementation of Safety-Related Intrusion Detection for an ...

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Control, Automation, and Instrumentation (IC2AI), International Conference on

作者： Georgio Abou Haydar Samer Telawi Josef Börcsök Department of Computer Architecture and System Programming University of Kassel Kassel Germany

ISBN: (数字)9798331529604

ISBN: (纸本)9798331529611

关键词： Service robots Intrusion detection Prototypes Human-robot interaction Industrial robots Manipulators Safety system-on-chip IEC Standards Standards

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