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检索条件"机构=Dept. Information Systems and Computer Modeling"

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Seasonal-Trend Time Series Decomposition on Graphics Processing Units

Seasonal-Trend Time Series Decomposition on Graphics Process...

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2023 IEEE International Conference on Big Data, BigData 2023

作者： Serykh, Dmitry Oehmcke, Stefan Oancea, Cosmin Masiliunas, Dainius Verbesselt, Jan Cheng, Yan Horion, Stephanie Gieseke, Fabian Hinnerskov, Nikolaj University of Copenhagen Dept. of Computer Science Denmark Wageningen University Dept. of Information Systems Netherlands University of Copenhagen Dept. of Geosciences and Natural Resource Management Denmark University of Mūnster Dept. of Information Systems Germany

ISBN: (纸本)9798350324457

In many domains, large amounts of time series data are being collected and analyzed in a semi-automatic manner. A prominent approach is the seasonal and trend decomposition using locally estimated scatterplot smoothing (STL) technique, which has been applied extensively in the past. However, STL quickly becomes computationally very expensive when applied to large data sets. In this work, we propose the first parallel implementation for the STL decomposition approach, which is tailored to the specific needs of graphics processing units (GPU). Our experimental evaluation on two global-scale case studies in temperature and vegetation trend analysis exhibits at least three-to-four orders of magnitude speed-up, demonstrating the effectiveness of the overall approach and the immense potential of the implementation in spatio-temporal data analyses. The source code is publicly available at https://***/diku-dk/hastl. An artifact that allows the experimental results to be reproduced is available at https://***/sharelink/hOUrqJJ FfA. © 2023 IEEE.

关键词： Climate Change Parallel Implementation Remote Sensing Time Series Data Trend Analysis

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A Variable Step-Size Hybrid Adaptive Nonlinear Filter for Solar Radiation Prediction 10

A Variable Step-Size Hybrid Adaptive Nonlinear Filter for So...

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10th International Conference on systems and Informatics, ICSAI 2024

作者： Xiao, Y. Ma, L. Khorasani, K. Prefectural University of Hiroshima Dept. of Management & Information Systems Hiroshima734-8558 Japan Concordia University Dept. of Electrical & Computer Engineering Montreal Canada

ISBN: (纸本)9798331510138

In this paper, a new hybrid adaptive nonlinear filter (HANF) scheme with variable step sizes (VSS) is proposed for solar radiation prediction. Our methodology consists of a Volterra filter and a functional link artificial neural network (FLANN) filter. The Volterra filter with the first- and second-order kernels is included, that is capable of expressing both linearity and nonlinearity. The FLANN filter can handle the nonlinearity that may be expressed by higher-order exponential terms that the Volterra filter with a limited number of kernels is unable to deal with. The VSSs are introduced in the two filters to allow the HANF to enjoy desirable tracking capability such that the time-varying nonlinearity underlying the nonlinear phenomena can be detected and tracked. The proposed VSS-HANF is applied to a real hourly solar radiation time sequence to confirm its improved prediction performance as compared to its counterpart with fixed step sizes. © 2024 IEEE.

关键词： Adaptive filters

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VascularVision: Mixed Reality Based Teaching and Learning Environment for Cardiovascular Conditions 6

VascularVision: Mixed Reality Based Teaching and Learning En...

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6th International Conference on Advancements in Computing, ICAC 2024

作者： Nissanka, Hashith Wijayasundara, Sajini Rajarathne, Jude Vidanagamage, Sahan Arachchi, Didula Thanaweera Abeygunawardhana, Pradeep K. W. Sri Lanka Insitute of Information Technology Dept. Information Technology Kandy Sri Lanka Sri Lanka Insitute of Information Technology Dept. Information Technology Colombo Sri Lanka Sri Lanka Insitute of Information Technology Dept. Information Technology Malabe Sri Lanka Sri Lanka Insitute of Information Technology Dept. Computer Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9798331517878

Developments in Augmented Reality (AR) and Virtual Reality (VR) have the potential to revolutionize medical education, especially in the areas of Coronary Angiography and Cardiac Auscultation. By giving medical and nursing students realistic, interactive experiences, the suggested VR and AR settings seek to modernize medical education by addressing the issues regarding the lack of real-world practice. Interactive 3D models, such as a realistic virtual body, rotatable heart models, ECG recordings, and real-life heart sounds, are available in the VR Cardiac Auscultation Environment. With the use of these components, students can practice diagnosing diseases including bradycardia, tachycardia, and cardiac murmurs in a dynamic and risk-free setting, improving their diagnostic skills. Similar to this, the AR Cardiac Auscultation Application combines interactive quizzes, machine learning for diagnostic verification, and real-time ECG scans to provide a powerful tool for teaching students how to recognize and understand various heart diseases and noises, this also can be a verification tool for junior doctors. By giving students firsthand experience with intricate medical procedures, virtual reality and augmented reality platforms offer a compelling and realistic approach to medical education. According to the research, these instruments can greatly enhance diagnostic proficiency, which will ultimately result in better educational outcomes and more qualified healthcare workers. © 2024 IEEE.

关键词： Students

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Method and Algorithm of Successive Approximation Analog-to-Digital Conversion of information in Management systems 14

Method and Algorithm of Successive Approximation Analog-to-D...

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14th International Conference on Advanced computer information Technologies, ACIT 2024

作者： Petryshyn, Lubomyr Petryshyn, Mykhailo Agh University of Krakow Dept. of Enterprise Management Krakow Poland Precarpathian National University Dept. of Computer Science and Information Systems Ivano-Frankivsk Ukraine

ISBN: (纸本)9798350350036

modeling methods and algorithms for analog-to-digital conversion of information in control systems are significant components in the development and design of devices for analog signals digitizing. This process involves several steps, including sampling, quantization, and encoding, to convert continuous signals into a digital format that can be easily manipulated and analyzed by digital *** quest to enhance the speed of converters is driven by the ever-increasing demand for rapid and efficient data processing. The research into additive successive approximation methods has yielded a novel approach: bitwise balancing. This innovative method, supported by a robust mathematical model, promises to revolutionize analog-to-digital conversion by significantly reducing the conversion time. The empirical analysis suggests that this reduction could range from 6 to 25 %, marking a substantial improvement over existing methods. This breakthrough shows not only the potential for faster data processing but also sets a new direction for the development of technical apparatuses designed for swift information form conversion. © 2024 IEEE.

关键词： additive method algorithm analog-to-digital conversion computational processes management information systems mathematical representations successive approximation

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Selfish Users in Listen-Before-Talk Co-existence of Cellular-Wi-Fi Networks: Counteraction Methods 21

Selfish Users in Listen-Before-Talk Co-existence of Cellular...

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21st International Symposium on modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2023

作者： Saibharath, S. Mishra, Sudeepta Arora, Gazal Sharma, Anamika Hota, Chittaranjan Dept. of Computer Science and Information systems BITS Pilani Hyderabad Campus India Dept. of Computer Science and Engineering IIT Ropar Punjab India

ISBN: (纸本)9783903176553

5G operates in the unlicensed spectrum to expand its capacity. This spectrum provides more uplink and downlink frequency bands in 5G to satisfy ultra-dense and scalability requirements. Wi-Fi is a prominent wireless technology that operates in unlicensed bands. Due to the proximity of cellular and Wi-Fi channels, utilization of both Wi-Fi and 5G New Radio (NR) can cause interference. The co-existence of 5G NR and Wi-Fi devices lacks the means of communication for negotiation and coordination among them. Listen-Before-Talk and Duty-cycling are standard Medium Access Control (MAC) mechanisms to enable co-existence. Due to a lack of coordination, network utilization becomes unfair with the existence of selfish devices. The selfish users could maximize throughput and affect other Wi-Fi and NR users. Here, we investigate the effects of selfish nodes on this Wi-Fi Co-existence with 5G. These nodes disobey exponential backoff to boost their channel acquisition. We study the effect of misbehavior through the Order Gain metric. Through standard CSMA/CA settings with overall channel occupancy of 99.75%, we demonstrate that selfish users profoundly impact fair co-existence. We study the side effects through throughput, channel sensing, and acquisition for various backoff window access patterns. Finally, we go through counteraction methods to overcome the selfish user impact. © 2023 IFIP.

关键词： Wi-Fi

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A Lightweight Edge-CNN-Transformer Model for Detecting Coordinated Cyber and Digital Twin Attacks in Cooperative Smart Farming

A Lightweight Edge-CNN-Transformer Model for Detecting Coord...

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2024 IEEE International Conference on Big Data, BigData 2024

作者： Praharaj, Lopamudra Gupta, Deepti Gupta, Maanak Tennessee Tech University Dept. of Computer Science CookevilleTN38505 United States Texas A&m University - Central Texas Dept. of Computer Information Systems TX United States

ISBN: (纸本)9798350362480

The agriculture sector is increasingly adopting innovative technologies to meet the growing food demands of the global population. To optimize resource utilization and minimize crop losses, farmers are joining cooperatives to share their data and resources among member farms. However, while farmers benefit from this data sharing and interconnection, it exposes them to cybersecurity threats and privacy concerns. A cyberattack on one farm can have widespread consequences, affecting the targeted farm as well as all member farms within a cooperative. For instance, a de-authentication attack prevents sensors from connecting to the network, obstructing the farming application from receiving real-time data. This disruption obstructs decision-making for all member farms that rely on this data from an attacked farm. Further, farmers have adopted digital twin (DT) technology that facilitates a virtual farm replica that encompasses vital aspects of farming, such as crop cultivation, soil composition and weather conditions. However, it's critical to acknowledge that attackers can target these digital twins (DTs), potentially disrupting real physical farm *** this research, we address existing gaps by proposing a novel and secure architecture for Cooperative Smart Farming (CSF). First, we highlight the role of edge-based DTs in enhancing the efficiency and resilience of agricultural operations. To validate this, we develop a test environment for CSF, implementing various cyberattacks on both the DTs and their physical counterparts using different attack vectors. We collect two smart farming network datasets to identify potential threats. After identifying these threats, we focus on preventing the transmission of malicious data from compromised farms to the central cloud server. To achieve this, we propose a CNN-Transformer-based network anomaly detection model, specifically designed for deployment at the edge. As a proof of concept, we implement this model and evaluate

关键词： Amazon Web Services (AWS) Attacks Azure Digital Twin CNN Cooperative Smart Farming (CSF) Digital Twin (DT) ML algorithms Security

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Signal Processing Techniques from Accelerometers on Railway Transport Based on the Wavelet Transform

Signal Processing Techniques from Accelerometers on Railway ...

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2024 Conference of Young Researchers in Electrical and Electronic Engineering, ElCon 2024

作者： Boronakhin, Alexander M. Bolshakova, Alexandra V. Klionskiy, Dmitry M. Larionov, Daniil Yu. Shalymov, Roman V. Saint Petersburg Electrotechnical University 'LETI' Faculty of Information Measurement and Biotechnical Systems Dept. of Laser Measurement and Navigational Systems Saint Petersburg Russia Saint Petersburg Electrotechnical University 'LETI' Dept. of Laser Measurement and Navigational Systems Saint Petersburg Russia Saint Petersburg Electrotechnical University 'LETI' Dept. of Information Systems Dept. of Software Engineering and Computer Applications Saint Petersburg Russia

ISBN: (纸本)9798350360646

Railway transport safety is directly connected with the condition of railway tracks and also the condition of railway wheels' surface. One of the main reasons for abnormal situations on railways are various defects such as irregularities of a railway track. Thus, we need to estimate the length of short and impulse irregularities. It is also important to carry out joint analysis of vibration acceleration signals recorded by accelerometers in order to study types and sizes of railway track irregularities. © 2024 IEEE.

关键词： continuous wavelet transform discrete wavelet transform irregularity of railway track vibration acceleration signal vibration movement wavelet scalogram

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An Overview of Cybersecurity Knowledge Graphs Mapped to the MITRE ATT&CK Framework Domains 20

An Overview of Cybersecurity Knowledge Graphs Mapped to the ...

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20th IEEE International Conference on Intelligence and Security Informatics, ISI 2023

作者： Bolton, Joshua Elluri, Lavanya Joshi, Karuna Pande University of Maryland Baltimore County Dept. of Information Systems Baltimore United States Texas A&m University - Central Texas Dept. of Computer Information Systems Killeen United States

ISBN: (纸本)9798350337730

A large volume of cybersecurity-related data sets are generated daily from systems following disparate protocols and standards. It is humanly impossible for cybersecurity experts to manually sieve through these large data sets, with different schema and metadata, to determine potential attacks or issues. A myriad of applications and tool sets are offered to automate the analysis of large cyber data sets. Semantic Web's community has been studying the field of cybersecurity for over a decade and produced numerous knowledge graphs and frameworks. The Unified Cybersecurity Ontology (UCO) connected many of the leading knowledge representation frameworks, providing a holistic mapping of cyber data, beginning in 2016. MITRE ATT&CK is used by a wide variety of practitioners to understand how their current data and tooling prepare them to defend against both Advanced Persistent Threats (APTs) and less formal threat actors. The UCO and MITRE ATT&CK have provided researchers and practitioners, respectively, with tools to standardize data collection, correlation, and analysis. However, it is not apparent how current knowledge graphs and their applications in the cybersecurity domain utilize ATT&CK. In this paper, we present the results of our study on whether current cybersecurity knowledge graphs have mapped the main MITRE ATT&CK matrices. © 2023 IEEE.

关键词： Cybersecurity

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Queues Theory for the Task Flows Management of UAV Swarms 7

Queues Theory for the Task Flows Management of UAV Swarms

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7th IEEE International Conference on Actual Problems of Unmanned Aerial Vehicles Development, APUAVD 2024

作者： Petryshyn, Lubomyr Petryshyn, Mykhailo AGH University of Krakow Dept. of Enterprise Management Krakow Poland Precarpathian National University Dept. of Computer Science adh Information Systems Ivano-Frankivsk Ukraine

ISBN: (纸本)9798331534141

As modern combat experience shows, the use of individual or swarms of unmanned aerial vehicles is an effective tool for striking enemy targets. However, managing such parallelized strike resources is a challenging task that requires real-time information transfer, planning, and dynamic replanning of strike processes organization. Synchronization and control of strike or reconnaissance resources necessitate the development of mathematical support, algorithms, and automated control programs using adequate mathematical models and artificial intelligence. The relevance of these research results is due to the application of the mathematical apparatus of queueing theory, which allows with a high degree of reliability to describe and analyze service processes in systems of unmanned aerial vehicles and artificial intelligence as platforms for data transformation and control over enemy resources. The aim of the research is to analyze and substantiate the possibility of applying queueing theory, based on which the development of algorithmic and software tools for managing artificial intelligence is proposed. The goal was achieved through the implementation of methods for analyzing incoming task streams, classifying and prioritizing them, and planning and executing service tasks. The novelty of this work lies in the application of probabilistic mathematical models that enable the efficient servicing of incoming tasks in unmanned aerial vehicle systems. Another aspect is the use of artificial intelligence tools. The practical aspect involves the development of network software and control systems for unmanned aerial vehicles. This article presents the first part of the research;subsequent results will be presented in future papers in this series. © 2024 IEEE.

关键词： Queueing theory

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Architectures of UAV Service systems 7

Architectures of UAV Service Systems

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7th IEEE International Conference on Actual Problems of Unmanned Aerial Vehicles Development, APUAVD 2024

ISBN: (纸本)9798331534141

Modern technologies being applied in single-task and multi-task unmanned systems elevate tactical control, planning, and combat operations to a new qualitative level. The automated management of UAV swarms and hives in real-time demands significant computational power and effective algorithms for data transformation and combat task execution, which underscores the relevance of this research. The objective of this work is to develop and apply artificial intelligence mechanisms based on the mathematical apparatus of queue theory. The novelty of the research lies in the application of queue and probability theories, which adequately allows for the modelling and execution of UAV swarm tasks. The practical significance stems from the development of mathematical and algorithmic models, specialized software using artificial intelligence, and the architectures of multi-task UAV systems. In this part of the research, real and fictitious operations, external and internal task flows are defined. Additionally, a source for the incoming task stream, a queue as an aggregation of service requirements, and an input accumulator are introduced. This paper clearly explains the innovation, objectives, and practical implications of the research in developing AI-driven UAV service systems utilizing queue theory. The next task involved the analysis and classification of architectures for individual UAVs and UAV swarms. The architectures were grouped as single-channel, multi-channel, with priority servicing with segregated and shared accumulators, as well as with unreliable service components. © 2024 IEEE.

关键词： Queueing theory

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