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Working IEEE/IFIP Conference on Software architecture

作者： Stephen John Warnett Uwe Zdun Research Group Software Architecture Faculty of Computer Science University of Vienna Vienna Austria UniVie Doctoral School Computer Science DoCS Faculty of Computer Science University of Vienna Vienna Austria

ISBN: (数字)9798331520908

ISBN: (纸本)9798331520915

In the domain of Industry 4.0 Cyber-Physical Production Systems (CPPSs), Reinforcement Learning (RL) has gained momentum as an effective strategy for training intelligent agents in digital twins. Whilst the practice of Machine Learning Operations (MLOps) has become established as a holistic approach to automating workflows in supervised and unsupervised Machine Learning (ML), the extent to which MLOps practices are applicable to RL, particularly due to major differences between ML and RL concerning model deployment and model training, are not currently well-understood. The literature on RLOps as a paradigm is scarce. We tackle this open question by conducting an exploratory, qualitative, deductive-inductive industry case study on a CPPS, performing content analysis of CPPS artefacts, such as architectural schematics and source code, and understanding their relation to 22 known Architectural Design Decisions and 86 associated decision options through classification into four distinct emergent categories. Our findings help bridge the gap between MLOps and RLOps architectures, contributing novel insights into understanding the application of MLOps to RL and providing practical insights and inspiration for further research.

关键词： Training Industries Production systems Content management Software architecture Source coding Reinforcement learning Fourth Industrial Revolution Digital twins Intelligent agents

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Constrained Planarity in Practice Engineering the Synchronized Planarity Algorithm

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Journal of Graph Algorithms and Applications 2025年第1期29卷 91-123页

作者： Fink, Simon D. Rutter, Ignaz Technische Universität Wien Algorithms and Complexity Group Austria University of Passau Faculty of Computer Science and Mathematics Germany

In the constrained planarity setting, we ask whether a graph admits a planar drawing that additionally satisfies a given set of constraints. These constraints are often derived from very natural problems;prominent examples are Level Planarity, where vertices have to lie on given horizontal lines indicating a hierarchy, and Clustered Planarity, where we in addition to the graph itself draw the boundaries of clusters which recursively group the vertices in a crossing-free manner. Despite receiving significant amount of attention and substantial theoretical progress on these problems, only very few of the found solutions have been put into practice and evaluated experimentally. In this paper, we describe our implementation of the recent quadratic-time algorithm by Bläsius et al. [8] for solving the problem Synchronized Planarity, which can be seen as a common generalization of several constrained planarity problems, including the aforementioned ones. Our experimental evaluation on an existing benchmark set shows that even our baseline implementation outperforms all competitors by at least an order of magnitude. We systematically investigate the degrees of freedom in the implementation of the Synchronized Planarity algorithm for larger instances and propose several modifications that further improve the performance. Altogether, this allows us to solve instances with up to 100 vertices in milliseconds and instances with up to 100 000 vertices within a few minutes. © 2025, Brown University. All rights reserved.

关键词： Drawing (graphics)

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Numerical Computation of SEIR Model for the Zika Virus Spreading

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computers, Materials & Continua 2023年第4期75卷 2155-2170页

作者： Suthep Suantai Zulqurnain Sabir Muhammad Asif Zahoor Raja Watcharaporn Cholamjiak Data Science Research Center Department of MathematicsFaculty of ScienceChiang Mai UniversityChiang Mai50200Thailand Research Group in Mathematics and Applied Mathematics Faculty of ScienceChiang Mai UniversityChiang Mai50200Thailand Department of Mathematics and Statistics Hazara UniversityMansehraPakistan Department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon Future Technology Research Center National Yunlin University of Science and Technology123 University RoadSection 3DouliouYunlinspan64002Taiwan School of Science University of PhayaoPhayao 56000Thailand

The purpose of this study is to present the numerical performancesand interpretations of the SEIR nonlinear system based on the Zika virusspreading by using the stochastic neural networks based intelligent computingsolver. The epidemic form of the nonlinear system represents the four dynamicsof the patients, susceptible patients S(y), exposed patients hospitalized inhospital E(y), infected patients I(y), and recovered patients R(y), i.e., SEIRmodel. The computing numerical outcomes and performances of the systemare examined by using the artificial neural networks (ANNs) and the scaledconjugate gradient (SCG) for the training of the networks, i.e., *** correctness of the ANNs-SCG scheme is observed by comparing theproposed and reference solutions for three cases of the SEIR model to solvethe nonlinear system based on the Zika virus spreading dynamics throughthe knacks of ANNs-SCG procedure based on exhaustive *** outcomes of the ANNs-SCG algorithm are found consistently in goodagreement with standard numerical solutions with negligible errors. Moreover,the procedure’s constancy, dependability, and exactness are perceived by usingthe values of state transitions, error histogram measures, correlation, andregression analysis.

关键词： SEIR nonlinear system Zika virus artificial neural networks scaled conjugate gradient statistical measures

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Evolutionary Explainable Rule Extraction from (Modal) Random Forests 26

Evolutionary Explainable Rule Extraction from (Modal) Random...

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26th European Conference on Artificial Intelligence, ECAI 2023

作者： Ghiotti, Michele Manzella, Federico Pagliarini, Giovanni Sciavicco, Guido Stan, Ionel Eduard Aclai Laboratory Department of Mathematics and Computer Science University of Ferrara Italy Department of Mathematical Physical and Computer Sciences University of Parma Italy Dbs Group Faculty of Engineering Free University of Bozen-Bolzano Italy

ISBN: (纸本)9781643684369

Symbolic learning is the subfield of machine learning concerned with learning predictive models with knowledge represented in logical form, such as decision tree and decision list models. Ensemble learning methods, such as random forests, are usually deployed to improve the performance of decision trees;unfortunately, interpreting tree ensembles is challenging. In order to deal with unstructured (e.g., temporal or spatial) data, moreover, decision trees and random forests have been recently generalized to the use of modal logics, which are harder to interpret than their propositional counterpart. Recently, a methodology for extracting simple rules from propositional random forests, based on a sequence of optimization steps, was proposed. In this work, we generalize this approach along two directions: from propositional to modal logic and from a sequence of optimization steps to a single multi-objective optimization problem. Even if confined to the temporal domain, our experimental results, based on open-source implementations and public data, show that our method is robust and able to extract small, accurate, and informative decision lists even for complex classification problems. © 2023 The Authors.

关键词： Decision trees

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Optimization in Sanger sequencing

arXiv

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arXiv 2024年

作者： Carpente, Luisa Cerdeira-Pena, Ana Lorenzo-Freire, Silvia Places, Ángeles S. Database Laboratory Department of Computer Science Faculty of Computer Science University of A Coruña Spain MODES Research Group Department of Mathematics Faculty of Computer Science University of A Coruña Spain

The main objective of this paper is to solve the optimization problem that is associated with the classification of DNA samples in PCR plates for Sanger sequencing. To achieve this goal, we design an integer linear programming model. Given that the real instances involve the classification of thousands of samples and the linear model can only be solved for small instances, the paper includes a heuristic to cope with bigger problems. The heuristic algorithm is based on the simulated annealing technique. This algorithm obtains satisfactory solutions to the problem in a short amount of time. It has been tested with real data and yields improved results compared to some commercial software typically used in (clinical) laboratories. Moreover, the algorithm has already been implemented in the laboratory and is being successfully used. © 2024, CC BY-NC-ND.

关键词： Simulated annealing

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Preface of the Symposium “Qualitative Properties of Solutions of Differential Equations”

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AIP Conference Proceedings 2022年第1期2425卷 1-4页

作者： Ruggieri, Marianna Scapellato, Andrea Faculty of Engineering and Architecture Kore University of Enna Enna Italy Department of Mathematics and Computer Science University of Catania Catania Italy

Marianna Ruggieri, Andrea Scapellato; Preface of the Symposium “Qualitative Properties of Solutions of Differential Equations”, AIP Conference Proceedings, Volu

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Supporting Architectural Decision Making on Training Strategies in Reinforcement Learning architectures

Supporting Architectural Decision Making on Training Strateg...

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Working IEEE/IFIP Conference on Software architecture

作者： Evangelos Ntentos Stephen John Warnett Uwe Zdun Faculty of Computer Science Research Group Software Architecture University of Vienna Vienna Austria

ISBN: (数字)9798350359169

ISBN: (纸本)9798350359176

In the dynamic landscape of artificial intelligence and machine learning, Reinforcement Learning (RL) has emerged as a powerful paradigm for training intelligent agents in sequential decision-making. As RL architectures progress in complexity, the need for informed decision-making regarding training strategies and related consequences on the software architecture becomes increasingly intricate. This work addresses this challenge by presenting the outcomes of a qualitative, in-depth study focused on best practices and patterns within training strategies for RL architectures, as articulated by practitioners. Leveraging a model-based qualitative research method, we introduce a formal architecture decision model to bridge the gap between scientific insights and practical implementation. We aim to enhance the understanding of practitioners' approaches in RL architecture. The paper analyzes 33 knowledge sources to discern established industrial practices, patterns, relationships, and decision drivers. Based on this knowledge, we introduce a formal Architectural Design Decision (ADD) model, encapsulating 6 decisions, 29 decision options, and 19 decision drivers, providing robust decision-making support for this critical facet of RL-based software architectures.

关键词： Training Software architecture Decision making computer architecture Reinforcement learning Planning Complexity theory

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On the Understandability of Machine Learning Practices in Deep Learning and Reinforcement Learning Based Systems

SSRN

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SSRN 2024年

作者： Ntentos, Evangelos Warnett, Stephen John Zdun, Uwe Faculty of Computer Science Research Group Software Architecture University of Vienna Vienna Austria UniVie Doctoral School Computer Science DoCS Faculty of Computer Science University of Vienna Vienna Austria

Machine learning (ML) utilizes diverse algorithms for predictive analytics. Deep Learning (DL) employs neural networks for intricate problem-solving, while Reinforcement Learning (RL) tackles sequential decision-making challenges. Best practices like transfer learning and checkpoints address issues with vast datasets and generalization to new *** ML systems solely from source code is difficult, particularly for novice developers. Our study hypothesizes that incorporating ML system diagrams detailing workflows and practices can improve comprehension in system design tasks. We anticipate this enhancement will positively impact correctness and duration of tasks, revealing varying participant *** findings suggest integrating semi-formal ML system diagrams alongside source code enhances task correctness in DL sub-tasks. However, differences in performance between participants who received only source code and those with diagrams were less pronounced in RL sub-tasks. This implies varied efficacy across learning settings, highlighting the need for deliberate diagram usage based on practitioners' goals. © 2024, The Authors. All rights reserved.

关键词： Predictive analytics

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API Rate Limit Adoption -- A pattern collection 23

API Rate Limit Adoption -- A pattern collection

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Proceedings of the 28th European Conference on Pattern Languages of Programs

作者： Souhaila Serbout Amine El Malki Cesare Pautasso Uwe Zdun Software Institute Università della Svizzera italiana Switzerland Faculty of Computer Science Software Architecture Research Group and UniVie Doctoral School Computer Science DoCS University of Vienna Austria Faculty of Computer Science Software Architecture Research Group University of Vienna Austria

ISBN: (纸本)9798400700408

The API Rate Limit pattern controls the rate at which clients make API requests by counting the number of requests in a specified time interval and reacting against abusive clients, in order to protect the limited resources of the API from exhaustion and denial of service attacks. This practice helps service providers to prevent abuse and ensure fair resource allocation, maintain system stability, monitor and control service availability, protect against DDoS attacks In this research paper, we have identified patterns covering the API Rate Limit pattern adoption starting from its documentation to its implementation. Our objective is to elucidate the trade-offs associated with different identified patterns and offer guidance to developers in making informed decisions when choosing the most suitable Rate Limit method, scope, and granularity for their service. By providing a comprehensive overview of how to adopt the Rate Limit pattern, this paper aims to enhance the understanding of how APIs can be designed to facilitate high scalability, security, reliability, and service availability. Furthermore, we present each pattern along with known uses observed in real-world APIs and technologies.

关键词： Application Programming Interfaces Pattern Language Rate Limit

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An enhanced scheme for mutual authentication for healthcare services

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Digital Communications and Networks 2022年第2期8卷 150-161页

作者： Salman Shamshad Muhammad Faizan Ayub Khalid Mahmood Saru Kumari Shehzad Ashraf Chaudhry Chien-Ming Chen Department of Computer Science COMSATS University IslamabadSahiwal Campus57000Pakistan Department of Mathematics Ch.Charan Singh UniversityMeerutUttar Pradesh250004India Department of Computer Engineering Faculty of Engineering and ArchitectureIstanbul Gelisim UniversityIstanbulTurkey College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao266590China Riphah School of Computing&Innovation(RSCI) Riphah International UniversityLahore CampusLahore 55150Pakistan Department of Mathematics University of Padua35131 PaduaItaly

With the advent of state-of-art technologies,the Telecare Medicine Information System(TMIS)now offers fast and convenient healthcare services to patients at their ***,this architecture engenders new risks and challenges to patients'and the server's confidentiality,integrity and *** order to avoid any resource abuse and malicious attack,employing an authentication scheme is widely considered as the most effective approach for the TMIS to verify the legitimacy of patients and the ***,several authentication protocols have been proposed to this *** recently,Chaudhry et *** that there are vulnerabilities of impersonation attacks in Islam et al.'s ***,they introduced an improved protocol to mitigate those security ***,Qiu et *** that these schemes are vulnerable to the man-in-the-middle,impersonation and offline password guessing ***,they introduced an improved scheme based on the fuzzy verifier techniques,which overcome all the security flaws of Chaudhry et al.'s ***,there are still some security flaws in Qiu et al.'s *** this article,we prove that Qiu et al.'s protocol has an incorrect notion of perfect user anonymity and is vulnerable to user impersonation ***,we introduce an improved protocol for authentication,which reduces all the security flaws of Qiu et al.'s *** also make a comparison of our protocol with related protocols,which shows that our introduced protocol is more secure and efficient than previous protocols.

关键词： Authentication protocol Security protocol Anonymous protocol Impersonation attack TMIS

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