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2020 IEEE International Conference on Problems of Infocommunications Science and Technology, PIC S and T 2020

作者： Bakhareva, Nadezhda Tarasov, Veniamin Povolzhskiy State University of Telecommunications and Informatics Dept. of Info. and Computer Engineering and Software and Management in Technical Systems Department Samara Russia

ISBN: (纸本)9781728191775

The objective of this work is to the output the solution in closed form for the average waiting time in a queue for queueing systems with shifted Erlangian and exponential input distributions and comparative analysis of their results with the results for conventional systems. As is known from queuing theory, the average waiting time for requirements in a queue is the main characteristic of a queuing system. To solve this problem, we used the classical method of spectral decomposition of the solution of Lindley integral equation, which allows one to obtain a solution for average the waiting time for systems under consideration in a closed form. The method of spectral decomposition of the solution of Lindley integral equation plays an important role in the theory of systems G/G/1. For the practical application of the results obtained, the well-known method of moments of probability theory is used. The introduction of the time shift parameter in the laws of input flow distribution and service time for the systems under consideration turns them into systems with a delay with a shorter waiting time. This is because the time shift operation reduces the coefficient of variation in the intervals between the receipts of the requirements and their service time, and as is known from queuing theory, the average wait time of requirements is related to these coefficients of variation by a quadratic dependence. The obtained results expand and supplement the well-known incomplete formula of the queuing theory for the average waiting time of requirements in the queue for G/G/1 systems. © 2020 IEEE.

关键词： Integral equations

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Modification of the Genetic Algorithm for Building and Reconfiguring Schedules of Order Completion in the Field of Service Provision 12

Modification of the Genetic Algorithm for Building and Recon...

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12th International Conference on Advanced Computer Information Technologies, ACIT 2022

作者： Hrybkov, Serhii Seidykh, Olga Vlasenko, Lidia Lytvynov, Valerii National University of Food Technologies Department of Information Systems Kyiv Ukraine National University of Food Technologies Department of Informatics Kyiv Ukraine National University of Trade and Economics Department of Software Engineering and Cyber Security Kyiv Ukraine Institute of Mathematical Machines and Systems Problems of Nasu Research Department № 220 'Intelligent Information-analytical System' Kyiv Ukraine

ISBN: (数字)9781665410502

ISBN: (纸本)9781665466479

The paper offers a solution to an important scientific and applied problem of scheduling to complete the orders for the provision of services aimed at maintenance and support of computer networks and equipment. This problem is relevant for companies providing such services. The main idea is to form an effective schedule for the completion of orders, as well as to enable its modification in the shortest time when getting orders. The paper also proposes an evaluation function that takes into account bonuses for the timely completion of orders and penalties for the late ones. A combination of a genetic algorithm with the methods of additional improvement on the basis of local optimization is offered. It allows reducing the time for the construction of effective alternative variants of decisions and their estimation. The use of the proposed approach to combining algorithms allows creating and reconfiguring the schedule for the completion of orders in the operational mode in a short time, and optimization makes it possible to reduce the completion of orders by up to 20%. Thus, the application of the proposed approaches will allow effective distribution of tasks among performers and give an economic effect by reducing the time to complete all orders. © 2022 IEEE.

关键词： Genetic algorithms

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Crowdsourced Requirements engineering Challenges and Solutions:A software Industry Perspective

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Computer systems Science & engineering 2021年第11期39卷 221-236页

作者： Huma Hayat Khan Muhammad Noman Malik Youseef Alotaibi Abdulmajeed Alsufyani Saleh Alghamdi Department of Software Engineering National University of Modern LanguagesIslamabadPakistan Department of Computer Science National University of Modern LanguagesIslamabadPakistan Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkahSaudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityPO Box 11099TaifSaudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaifSaudi Arabia

software crowdsourcing(SW CS)is an evolving software development paradigm,in which crowds of people are asked to solve various problems through an open call(with the encouragement of prizes for the top solutions).Because of its dynamic nature,SW CS has been progressively accepted and adopted in the software ***,issues pertinent to the understanding of requirements among crowds of people and requirements engineers are yet to be clarified and *** the requirements are not clear to the development team,it has a significant effect on the quality of the software *** study aims to identify the potential challenges faced by requirements engineers when conducting the SW–CS based requirements engineering(RE)***,solutions to overcome these challenges are also *** data analysis is performed on the interview data collected from software industry ***,20 SW–CS based RE challenges and their subsequent proposed solutions are devised,which are further grouped under seven *** study is beneficial for academicians,researchers and practitioners by providing detailed SW–CS based RE challenges and subsequent solutions that could eventually guide them to understand and effectively implement RE in SW CS.

关键词： software crowdsourced requirements engineering software industry software development survey challenges

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Loss Functions in Deep Learning: A Comprehensive Review

arXiv

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arXiv 2025年

作者： Elharrouss, Omar Mahmood, Yasir Bechqito, Yassine Serhani, Mohamed Adel Badidi, Elarbi Riffi, Jamal Tairi, Hamid Department of Computer Science and Software Engineering College of Information Technology United Arab Emirates University United Arab Emirates Department of Information Systems College of Computing and Informatics University of Sharjah Sharjah United Arab Emirates Department of Informatics Faculty of Sciences Dhar El Mahraz Sidi Mohamed Ben Abdellah University Fez Morocco

Loss functions are at the heart of deep learning, shaping how models learn and perform across diverse tasks. They are used to quantify the difference between predicted outputs and ground truth labels, guiding the optimization process to minimize errors. Selecting the right loss function is critical, as it directly impacts model convergence, generalization, and overall performance across various applications, from computer vision to time series forecasting. This paper presents a comprehensive review of loss functions, covering fundamental metrics like Mean Squared Error and Cross-Entropy to advanced functions such as Adversarial and Diffusion losses. We explore their mathematical foundations, impact on model training, and strategic selection for various applications, including computer vision (Discriminative and generative), tabular data prediction, and time series forecasting. For each of these categories, we discuss the most used loss functions in the recent advancements of deep learning techniques. Also, this review explore the historical evolution, computational efficiency, and ongoing challenges in loss function design, underlining the need for more adaptive and robust solutions. Emphasis is placed on complex scenarios involving multi-modal data, class imbalances, and real-world constraints. Finally, we identify key future directions, advocating for loss functions that enhance interpretability, scalability, and generalization, leading to more effective and resilient deep learning models. © 2025, CC BY.

关键词： Deep learning

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Memory and Schema in Human-Generative Artificial Intelligence Interactions

Memory and Schema in Human-Generative Artificial Intelligenc...

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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： Dimitrios P. Panagoulias Persephone Papatheodosiou Anastasios Bonakis Dimitrios Dikeos Maria Virvou George A. Tsihrintzis Department of Informatics University of Piraeus Piraeus Greece Department of Psychiatry Sleep Research Unit National and Kapodistrian University of Athens Athens Greece Second Department of Neurology National and Kapodistrian University of Athens Athens Greece Department of Informatics Lab of Software Engineering University of Piraeus Piraeus Greece Department of Informatics Lab of Pattern Recognition and Machine Learning - Multimedia Systems University of Piraeus Piraeus Greece

ISBN: (数字)9798331527235

ISBN: (纸本)9798331527242

In this paper, we explore memory and Schema through the lens of mathematical representation. By defining themes related to cognitive processes, we propose a compression algorithm that measures and retains important information of previous (historic) user-Generative AI interaction. Time and memory are interconnected via a decay mechanism, where context gets more abstract as time passes. At the same time, memories with thematic resemblance can be structured into Schemas using set theory, based on rules influenced by a maturity threshold. This threshold is determined by factors such as criticality, emotional-user interaction, and mass, which is the measure of the summation of related memories. Our approach reconstructs memories into reusable parameters and formulates Schemas, offering a foundation for more personalized and cost-effective human-GAI interactions.

关键词： Cognitive processes Set theory Artificial intelligence Compression algorithms Lenses

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Suggestion Mining from Opinionated Text of Big Social Media Data

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Computers, Materials & Continua 2021年第9期68卷 3323-3338页

作者： Youseef Alotaibi Muhammad Noman Malik Huma Hayat Khan Anab Batool Saif ul Islam Abdulmajeed Alsufyani Saleh Alghamdi Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversitySaudi Arabia Department of Computer Science Faculty of Engineering and Computer SciencesNational University of Modern LanguagesIslamabadPakistan Department of Software Engineering Faculty of Engineering and Computer SciencesNational University of Modern LanguagesIslamabadPakistan Department of Computer Sciences Institute of Space TechnologyIslamabadPakistan Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaifSaudi Arabia

:Social media data are rapidly increasing and constitute a source of user opinions and tips on a wide range of products and *** increasing availability of such big data on biased reviews and blogs creates challenges for customers and businesses in reviewing all content in their decision-making *** overcome this challenge,extracting suggestions from opinionated text is a possible *** this study,the characteristics of suggestions are analyzed and a suggestion mining extraction process is presented for classifying suggestive sentences from online customers’reviews.A classification using a word-embedding approach is used via the XGBoost *** two datasets used in this experiment relate to online hotel reviews and Microsoft Windows App Studio discussion reviews.F1,precision,recall,and accuracy scores are *** results demonstrated that the XGBoost classifier outperforms—with an accuracy of more than 80%.Moreover,the results revealed that suggestion keywords and phrases are the predominant features for suggestion ***,this study contributes to knowledge and practice by comparing feature extraction classifiers and identifying XGBoost as a better suggestion mining process for identifying online reviews.

关键词： Suggestion mining word embedding Naïve Bayes random forest XGBoost dataset

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Thrilling AI-A novel, signal-based digital biomarker for diagnosing canine heart diseases

Thrilling AI-A novel, signal-based digital biomarker for dia...

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作者： Bisgin, Pinar Strube, Tom Henze, Jasmin Ljungvall, Ingrid Häggström, Jens Wess, Gerhard Stadler, Julia Schummer, Christoph Meister, Sven Howar, Falk Maria Fraunhofer Institute for Software and Systems Engineering Emil-Figge-Str. 91 Dortmund44227 Germany Department of Clinical Sciences University of Agricultural Sciences Uppsala Sweden Clinic of Small Animal Medicine University of Munich Munich Germany Boehringer Ingelheim Animal Health Ingelheim am Rhein Germany Department of Health Informatics Witten/Herdecke University Witten Germany Department in Software Engineering Technical University of Dortmund Dortmund Germany

Auscultation methods enable non-invasive diagnosis of diseases, e.g. of the heart, based on heartbeat sounds. Regular, early examinations using machine learning techniques could help to detect diseases at an early stage to prevent serious health conditions and then provide optimal therapy through continuous monitoring. There is already a lot of work on human data using AI algorithms to detect patterns in signals or images. However, there is hardly no work on detecting heart murmurs with digital such as Myxomatous Mitral Valve Disease. In this paper, we present a canine auscultation project that aims to provide a tool to establish a baseline of classification parameters from audio signals that could be used to monitor canine health status by analyzing deviations from this baseline. In the future, data analysis could also lead to prediction and early detection of other diseases. © 2022 by Walter de Gruyter Berlin/Boston.

关键词： Pattern recognition

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A Distributed MAPE-K Framework for Self-Protective IoT Devices

A Distributed MAPE-K Framework for Self-Protective IoT Devic...

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SEAMS International Workshop on software engineering for Adaptive and Self-Managing systems, ICSE

作者： Michael Riegler Johannes Sametinger Michael Vierhauser LIT Secure and Correct Systems Lab Johannes Kepler University Linz Linz Austria Department of Business Informatics - Software Engineering Johannes Kepler University Linz Linz Austria

Internet of Things (IoT) devices have become ubiquitous in our everyday life, with security becoming an ever-growing issue as more and more cyber-attack incidents being reported, primarily due to deficiencies in existing security mechanisms. However, while, for example, cloud-based applications, or industrial automation systems of systems possess significant resources for monitoring health, and determining their status and correct behavior at runtime, IoT devices operate with limited hardware capabilities and under tight resource constraints, making monitoring, analysis, and response activities a challenging endeavor. Following the NIST Cybersecurity Framework, IoT devices need to identify, protect, detect, respond, and recover from cyber-attacks, unauthorized access, and other security threats. A common way to provide self-adaptation to changing conditions is the MAPE-K loop with four pivotal phases: Monitor, Analyze, Plan, and Execute. This paper presents DSec4IoT, a “Distributed MAPE-K Framework for Self-Protective IoT Devices”. Our framework leverages the idea of distributed MAPE-K patterns and establishes a model for managing and controlling Self-Protective IoT Devices. We evaluate our approach by simulating port scans and performing adaptation activities. Results have confirmed that DSec4IoT can be easily applied to detect and mitigate them.

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Trustworthy Model Elements as Basis for Seamless Bim Collaboration

SSRN

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SSRN 2024年

作者： Paskaleva, Galina Mazak-Huemer, Alexandra Huemer, Christian TU Wien Institute of Information Systems Engineering Favoritenstr. 9-11 ViennaA-1040 Austria Johannes Kepler University Linz Department of Business Informatics - Software Engineering Altenberger Strasse 69 Science Park 3 LinzA-4040 Austria

Current applications of BIM in the Architecture engineering and Construction (AEC) industry require multiple stakeholders to collaborate on the same digital model over multiple project phases, sharing the responsibility for the same model element. This requires trust, both between the stakeholders and between each stakeholder and the BIM technology. Lack of trust often manifests as poor collaboration, model duplications and break-down of model continuity. In this work, we present a method for the introduction of trust into the digital twin of a built structure by creating trustworthy model elements. The source of trust can be any technical or legal requirement. Such trusted model elements can offer a formal guarantee that the corresponding requirement has been fulfilled. Furthermore, this guarantee can be renewed automatically after each update by any project stakeholder. Finally, we introduce a standardized workflow for the maintenance and update of already established trusted elements in a digital twin. © 2024, The Authors. All rights reserved.

关键词： Architectural design

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Wheelchair Wheel Design with Transformable “Wheel-Leg” Configuration for Climbing Stairs and Various Surfaces

Wheelchair Wheel Design with Transformable “Wheel-Leg” Con...

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International Russian Smart Industry Conference (SmartIndustryCon)

作者： Islam Magomedov Timur Aygumov Anzor A. Kanametov Bissnes informatics Kadyrov Chechen state university Grozny Russia Department of software engineering computer technology and automated systems Dagestan State Technical University Dagestan Russia Department of Electronics and Digital Information Technologies Kabardino-Balkarian State University Nalchik Russia

ISBN: (数字)9798331511241

ISBN: (纸本)9798331511258

The dynamic and uneven terrain of our environment introduces complexity for locomotion vehicles to navigate easily across different settings. Wheelchairs belong to the category of vehicles that require locomotion across various uneven terrains, such as stairs and other partitions. Therefore, the aim of this work is to design a wheel that can travel through various environments without using complex mechanisms. This aim was achieved by creating a novel transformable wheel. This wheel can turn into a legged wheel without using a complex mechanism and, when unnecessary, transform back into a normal wheel. Several simulations were carried out to understand the design's capability to overcome obstacles. In this case, the stair was the obstacle, and the results illustrated that the wheel is capable of climbing stairs without serious issues. Different parameters, such as speed and force, were examined with various values. The results showed that the weight on the wheelchair plays a significant role in climbing. For instance, with lighter weight, the structure moves without major slipping. The roughness of the surface is also related to the wheelchair's ability to reach the top of the stairs. A finer depth of cuts on the surface of the stairs increases the chance of the legged wheel firmly gripping and moving up the stairs.

关键词： Shape Navigation Wheelchairs Wheels Rotors Transforms Stairs Surface roughness Rough surfaces Vehicle dynamics

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