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8th IEEE International Conference on Problems of Infocommunications, Science and Technology, PIC S and T 2021

作者： Bakhareva, Nadezhda Tarasov, Veniamin Povolzhskiy State University of Telecommunications And Informatics Department of Informatics And Computer Engineering Software And Management In Technical Systems Department Samara Russia

ISBN: (纸本)9781665406826

The purpose of this work is to compare two forms of the Erlang distribution law: ordinary and normalized. The ordinary Erlang distribution is a special case of a more general gamma distribution and its mathematical expectation depends on the order of the distribution k. For a normalized distribution, the mathematical expectation will not depend on the order of the distribution k;this is the meaning of the normalization operation. Consequently, these two forms of the Erlang distribution law will differ in their numerical characteristics. The paper considers the problem of how these two forms of the distribution law are applied in the theory of queuing and how they affect the main characteristic of queuing systems (QS)-the average delay of claims arriving for service in the system. The rest of the QS characteristics are derivatives of the average delay. For this, three different QSs are considered, including the Erlang distribution law. The method of spectral decomposition of the solution of the Lindley integral equation was used as a mathematical apparatus for studying the QS. For the practical application of the results obtained, the method of moments of the theory of probability was used. Basically, queueing systems G/G/1 with general distribution laws are in demand for modeling data transmission systems for various purposes, including computer and telecommunication networks. This is especially true since for G/G/1 systems there is no solution for the average latency in the final form for the general case. Therefore, such systems are investigated using examples with particular distribution laws. © 2021 IEEE.

关键词： Laplace transforms

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An Exact Formula for the Hazardous Event Frequency

An Exact Formula for the Hazardous Event Frequency

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Annual Symposium on Reliability and Maintainability (RAMS)

作者： Armin Zimmermann Andreas Hildebrandt Department of Computer Science and Automation Systems and Software Engineering Group Technische Universität Ilmenau Ilmenau Germany Pepperl+Fuchs SE Mannheim Germany

The remaining risk of safety-instrumented systems is an important non-functional requirement that is regulated by international standards. Several ways towards computing the safety as a function of its relevant design parameters have been studied in the literature. However, the standard approach only covers two special cases of high or low demand, which simplify the treatment by either ignoring the effects of demand rate or test interval on the safety. More detailed treatments in the literature derive Markov models, which can be numerically analyzed, or approximate solutions using Taylor series expansions etc. This paper introduces closed-form exact formulas for the average probability of failure on demand (PFD) and the resulting hazardous event frequency (HEF, or accident rate), taking into account demand rate and test interval. It integrates all cases of low, high and medium demand in one formula. The derivation is based on an analysis of the cyclostationary semi-Markov stochastic process of the safety-integrated system and its symbolic transient analysis over the test interval.

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Super-Resolution Based ROI Enhancement Approaches for Palmprint Recognition

Super-Resolution Based ROI Enhancement Approaches for Palmpr...

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International Artificial Intelligence and Data Processing Symposium (IDAP)

作者： Hüseyin Furkan Macan Özkan Bіngöl Salih Türk Murat Ekіncі Department of Management Information Systems Gumushane University Gümüşhane Turkey Department of Software Engineering Gumushane University Gümüşhane Turkey Department of Computer Engineering Karadeniz Technical University Trabzon Turkey

ISBN: (数字)9798331531492

ISBN: (纸本)9798331531508

The sizes of regions of interest (ROI) obtained from images captured by cameras in palmprint recognition may vary depending on the camera specifications and the position of the hand. The regions of interest that recognition systems can use are typically rescaled through interpolation techniques and then defined as inputs to the system. In such cases, there may be some loss of biometric data. This study aims to enhance the quality of the palmprint ROI images, which are critical for palmprint recognition systems. To achieve this, various super-resolution techniques were employed to reconstruct low-resolution ROI images to the target sizes while preserving the distinctiveness of their biometric features. This approach is designed to optimize recognition accuracy and improve data reliability in palmprint recognition processes.

关键词： Interpolation Image recognition Accuracy Palmprint recognition Superresolution Cameras Reliability engineering Data processing Artificial intelligence Image reconstruction

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Simulation-Based Study on False Alarms in Intrusion Detection systems for Organizations Facing Dual Phishing and Dos Attacks

Simulation-Based Study on False Alarms in Intrusion Detectio...

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Annual Modeling and Simulation Conference (ANNSIM)

作者： Jeongkeun Shin L. Richard Carley Kathleen M. Carley Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA United States Software and Societal Systems Department Carnegie Mellon University Pittsburgh PA United States

ISBN: (数字)9781713899310

ISBN: (纸本)9798350350562

Machine learning-based intrusion detection systems (IDS) have attracted considerable attention for their role in proactively identifying intrusion attempts and facilitating swift organizational response. While numerous researchers have conceptually discussed the potential negative impacts of high false alarms in machine learning-based IDS on organizations and have proposed various methods to reduce them, there is a shortage of studies that explore how these false alarms can exacerbate cyberattack damage in different organizational settings and in the face of various cyberattack campaigns. This paper introduces an agent-based modeling and simulation approach to assess false alarm consequences in machine learning-based IDS during dual Denial of Service (DoS) and phishing attacks. The IDS with distinct false positive rates, constructed using the KDD Cup 1999 dataset with diverse machine learning algorithms, were simulated to analyze how these varying false alarm rates affect the extent of damage caused by phishing and DoS attacks.

关键词： Machine learning algorithms Phishing Intrusion detection Organizations Agent-based modeling Cyberattack Faces

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Automated Classification of Medical Images Using Convolutional Neural Networks 15

Automated Classification of Medical Images Using Convolution...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Pillai, N. Muthuvairavan Manimala, S. Rongali, Aruna Sri Gugnani, Anchit Kumar, Senthil A. Sriramakrishnan, G.V. Computer Science and Business Systems R.M.D Engineering College Thiruvallur district Kavarapettai India Computer science and engineering University SJCE JSS Science and technology University Karnataka Mysore India Sr. Software Engineer Department Information Technology Emphasis/Information Technology Ph.D University The country University of The Cumberlands United States Physiotherapy Amity University Rajasthan Jaipur India Artificial Intelligent department Shri Vishnu Engineering College for Women AP Bhimavaram India Tamilnadu Chennai India

ISBN: (纸本)9798350370249

Medical imagery has been increasingly used in diagnosing and treating various diseases, leading to advances in healthcare. While humans usually lead the qualitative interpretation of visual features, Automated Classification of Medical Images Using Convolution Neural Networks (CNNs) has gained traction for accurate image classification. CNNs are a type of deep learning algorithm that attempts to mimic the structure of the human brain and are ideal for image classification due to their convolution layers that can detect patterns within the image. These convolution layers enable the networks to learn the characteristics of the data through a series of convolution and pooling operations. Additionally, they can rapidly identify relationships and patterns within the dataset and extract features from the input image, thus allowing a more accurate classification. With the increasing availability of medical imaging data, advancements in the field of ML/AI has enabled the use of CNNs for automated medical image classification, helping clinicians to diagnose diseases accurately with less time and effort. ©2024 IEEE.

关键词： Convolutional neural networks

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Image Classification Analysis to Identify the Tourism Potential Sukabumi on Instagram Using A Deep Learning Approach

Image Classification Analysis to Identify the Tourism Potent...

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International Conference on Informatics and Computing (ICIC)

作者： Falentino Sembiring Rieska Rahayu Ayuningsih Muhamad Muslih Muhammad Andy Maulana Gina Wahdayani Futri Mohd Zainuri Saringat Rachma Siva Ainunnisa Anggun Fergina Information Systems Nusa Putra University Sukabumi Indonesia Department of Software Engineering Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia

ISBN: (数字)9798331517601

ISBN: (纸本)9798331517618

This research focuses on image classification, grouping images based on shared characteristics. The study aims to identify the highest-potential category within various fields, from high to low potential. By understanding existing potential, researchers can inform targeted strategies for future development. The methodology combines Logistic Regression in Orange Data Mining to enhance classification accuracy. Hierarchical Clustering is used to analyze 7,777 image results. Findings reveal that Tourism (C3) has the most potential, followed by Culinary (C2) and Culture (C4), while Handcrafts (C1) exhibit the least potential. In conclusion, logistic regression successfully identifies influential aspects of Sukabumi through Instagram images, aiding potential development

关键词： Deep learning Logistic regression Accuracy Web sites Multimedia communication Data mining Cultural differences Informatics Image classification

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A Theoretical and Practical Framework for Evaluating Uncertainty Calibration in Object Detection

arXiv

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arXiv 2023年

作者： Conde, Pedro Lopes, Rui L. Premebida, Cristiano Institute os Systems and Robotics Department Of Electrical and Computer Engineering University of Coimbra Portugal Critical Software S.A. Portugal

The proliferation of Deep Neural Networks has resulted in machine learning systems becoming increasingly more present in various real-world applications. Consequently, there is a growing demand for highly reliable models in many domains, making the problem of uncertainty calibration pivotal when considering the future of deep learning. This is especially true when considering object detection systems, that are commonly present in safety-critical applications such as autonomous driving, robotics and medical diagnosis. For this reason, this work presents a novel theoretical and practical framework to evaluate object detection systems in the context of uncertainty calibration. This encompasses a new comprehensive formulation of this concept through distinct formal definitions, and also three novel evaluation metrics derived from such theoretical foundation. The robustness of the proposed uncertainty calibration metrics is shown through a series of representative experiments. Copyright © 2023, The Authors. All rights reserved.

关键词： Calibration

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ZigBee Network for AGV Communication in Industrial Environments

ZigBee Network for AGV Communication in Industrial Environme...

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International Conference on Data Science and Advanced Analytics (DSAA)

作者： Jarosław Flak Tomasz Skowron Rafał Cupek Marcin Fojcik Dariusz Caban Adam Domański Department of Distributed Systems and Informatic Devices Silesian University of Technology Gliwice Poland Department of Computer Science Electrical engineering Western Norway University of Applied Sciences Bergen Norway

Automated Guided Vehicles (AGVs) are a key component of many modern industrial systems. AGVs are supposed to communicate with each other in real time using wireless networks. In this article, the advantages and disadvantages of the ZigBee wireless network related to the control of AGVs are considered. We analyze the performance of the ZigBee network programmed with both C# and Python libraries to control ZigBee devices. The throughput and signal strength are presented and discussed depending on the transmission speed of the serial port, the payload size, and the presence and distance from the obstacles. The results of the experiments show the effective values of these parameters, the methods of using C# and Python, and the reliability of the throughput up to a certain point in network devices.

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A Communication-Induced Checkpointing Algorithm for Consistent-Transaction in distributed Database systems 1

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8th International Symposium on Security in Computing and Communications, SSCC 2020

作者： Mansouri, Houssem Pathan, Al-Sakib Khan Laboratory of Networks and Distributed Systems Computer Science Department Faculty of Sciences Ferhat Abbas Setif University 1 Setif Algeria Department of Computer Science and Engineering Independent University Dhaka Bangladesh

ISBN: (数字)9789811604225

ISBN: (纸本)9789811604218

For better protection of distributed systems, two well-known techniques are: checkpointing and rollback recovery. While failure protection is often considered a separate issue, it is crucial for establishing better secure distributed systems. This article is dedicated to the proposal of a new checkpointing algorithm for saving a consistent-transaction state in distributed databases ensuring that database management systems are able, after a failure, to recover the state of the database. The proposed communication-induced algorithm does not hamper the normal transaction processing and saves a global consistent-transaction state that records only the fully completed transactions. Analysis and experimental results of our proposal show that the proposed scheme saves a minimum number of forced checkpoints and has some performance gains compared to the alternative approaches. © 2021, Springer Nature Singapore Pte Ltd.

关键词： distributed database systems

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Quality of Service (QoS)-Driven Edge Computing and Smart Hospitals: A Vision, Architectural Elements, and Future Directions 1

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NIELIT's International Conference on Communication, Electronics and Digital Technology, NICE-DT 2023

作者： Buyya, Rajkumar Srirama, Satish N. Mahmud, Redowan Goudarzi, Mohammad Ismail, Leila Kostakos, Vassilis Lab School of Computing and Information Systems The University of Melbourne Melbourne Australia School of Computer and Information Sciences The University of Hyderabad Hyderabad India School of Electrical Engineering Computing and Mathematical Sciences Curtin University Perth Australia Lab Department of Computer Science and Software Engineering National Water and Energy Center United Arab Emirates University Abu Dhabi United Arab Emirates

ISBN: (数字)9789819916993

ISBN: (纸本)9789819916986

The Internet of Things (IoT) paradigm is drastically changing our world by making everyday objects an integral part of the Internet. This transformation is increasingly being adopted in the healthcare sector, where Smart Hospitals are now relying on IoT technologies to track staff, patients, devices, and equipment, both within a hospital and beyond. This paradigm opens the door to new innovations for creating novel types of interactions among objects, services, and people in smarter ways to enhance the quality of patient services and the efficient utilisation of resources. However, the realisation of real-time IoT applications in health care and, ultimately, the development of Smart Hospitals are constrained by their current Cloud-based computing environment. Edge computing emerged as a new computing model that harnesses Edge-based resources alongside Clouds for real-time IoT applications. It helps to capitalise on the potential economic impact of the IoT paradigm of $11 trillion per year, with a trillion IoT devices deployed by 2025 to sense, manage, and monitor the hospital systems in real time. This vision paper proposes new algorithms and software systems to tackle important challenges in Edge computing-enabled Smart Hospitals, including how to manage and execute diverse real-time IoT applications and how to meet their diverse and strict Quality of Service (QoS) requirements in hospital settings. The vision we outline can help tackle timely challenges that hospitals increasingly face. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Quality of service

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