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Modeling and Simulation of Processes in a Factory of the Future

Grznár, Patrik ; Gregor, Milan ; Krajčovič, Martin ; [et al.]

MDPI AG ; 2020

In: Applied Sciences Vol. 10, No. 13 ( 2020-06-29), p. 4503-

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In: Applied Sciences, MDPI AG, Vol. 10, No. 13 ( 2020-06-29), p. 4503-

Abstract: Current trends in manufacturing, which are based on customisation and gradually customised production, are becoming the main initiator for the development of new manufacturing approaches. New manufacturing approaches are counted as the application of new behavioural management patterns that calculate the retained competencies of decision-making by the individual members of the system agent; the production becomes decentralised. The interaction of the members of such a system creates emergent behaviour, where the result cannot be accurately determined by ordinary methods and simulation must be applied. Modelling and simulation will, therefore, be an integral part of the planning and control of the processes of factories of the future. The purpose of the article is to describe the use of modelling and simulation processes in factories of the future. The first part of the article describes new manufacturing concepts that will be used in factories of the future, with a description of modelling and simulation routing in the frame of Industry 4.0. The next section describes how simulation is used for the control of manufacturing processes in factories of the future. The included subsection describes the implementation of this suggested pattern in the laboratory of ZIMS (Zilina Intelligent Manufacturing System), with an example of a metamodeling application and the results obtained.

Type of Medium: Online Resource

ISSN: 2076-3417

URL: Article

DOI: 10.3390/app10134503

Language: English

Publisher: MDPI AG

Publication Date: 2020

detail.hit.zdb_id: 2704225-X

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2

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Levels of Automation in Urban Design Through Arti ficial Intelligence: A Framework to Characterize Automation Approaches

Koenig, Reinhard ; Bielik, Martin ; Dennemark, Martin ; [et al.]

Alexandrine Press ; 2020

In: Built Environment Vol. 46, No. 4 ( 2020-12-01), p. 599-619

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In: Built Environment, Alexandrine Press, Vol. 46, No. 4 ( 2020-12-01), p. 599-619

Abstract: One of the most important consequences of digitalization and the progress of artificial intelligence is automation in all areas of life. In this paper we investigate the automation of urban design. Based on four levels of automation, we provide a conceptual framework for the classification and comparison of various urban design automation approaches and consider the scope of their applicability and the division of tasks between humans and computers. The proposed framework is applied in two demonstration projects. Finally, we discuss the technical needs and possibilities for increasing urban design automation, as well as the implications these are expected to have for the profession of urban designers and architects.

Type of Medium: Online Resource

ISSN: 0263-7960

URL: Article

DOI: 10.2148/benv.46.4.599

Language: English

Publisher: Alexandrine Press

Publication Date: 2020

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3

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Gut Microbiota and Serum Metabolites in Individuals with Class III Obesity Without Type 2 Diabetes Mellitus: Pilot Analysis

Kubáňová, Libuša ; Bielik, Viktor ; Hric, Ivan ; [et al.]

Mary Ann Liebert Inc ; 2023

In: Metabolic Syndrome and Related Disorders Vol. 21, No. 5 ( 2023-06-01), p. 243-253

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In: Metabolic Syndrome and Related Disorders, Mary Ann Liebert Inc, Vol. 21, No. 5 ( 2023-06-01), p. 243-253

Type of Medium: Online Resource

ISSN: 1540-4196 , 1557-8518

URL: Article

DOI: 10.1089/met.2022.0071

Language: English

Publisher: Mary Ann Liebert Inc

Publication Date: 2023

detail.hit.zdb_id: 2110505-4

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4

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Examining Trade-Offs between Social, Psychological, and Energy Potential of Urban Form

Bielik, Martin ; Schneider, Sven ; Kuliga, Saskia ; [et al.]

MDPI AG ; 2019

In: ISPRS International Journal of Geo-Information Vol. 8, No. 2 ( 2019-01-24), p. 52-

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In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 8, No. 2 ( 2019-01-24), p. 52-

Abstract: Urban planners are often challenged with the task of developing design solutions which must meet multiple, and often contradictory, criteria. In this paper, we investigated the trade-offs between social, psychological, and energy potential of the fundamental elements of urban form: the street network and the building massing. Since formal methods to evaluate urban form from the psychological and social point of view are not readily available, we developed a methodological framework to quantify these criteria as the first contribution in this paper. To evaluate the psychological potential, we conducted a three-tiered empirical study starting from real world environments and then abstracting them to virtual environments. In each context, the implicit (physiological) response and explicit (subjective) response of pedestrians were measured. To quantify the social potential, we developed a street network centrality-based measure of social accessibility. For the energy potential, we created an energy model to analyze the impact of pure geometric form on the energy demand of the building stock. The second contribution of this work is a method to identify distinct clusters of urban form and, for each, explore the trade-offs between the select design criteria. We applied this method to two case studies identifying nine types of urban form and their respective potential trade-offs, which are directly applicable for the assessment of strategic decisions regarding urban form during the early planning stages.

Type of Medium: Online Resource

ISSN: 2220-9964

URL: Article

DOI: 10.3390/ijgi8020052

Language: English

Publisher: MDPI AG

Publication Date: 2019

detail.hit.zdb_id: 2655790-3

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5

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Scalable race detection for Android applications

Bielik, Pavol ; Raychev, Veselin ; Vechev, Martin

Association for Computing Machinery (ACM) ; 2015

In: ACM SIGPLAN Notices Vol. 50, No. 10 ( 2015-12-18), p. 332-348

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In: ACM SIGPLAN Notices, Association for Computing Machinery (ACM), Vol. 50, No. 10 ( 2015-12-18), p. 332-348

Abstract: We present a complete end-to-end dynamic analysis system for finding data races in mobile Android applications. The capabilities of our system significantly exceed the state of the art: our system can analyze real-world application interactions in minutes rather than hours, finds errors inherently beyond the reach of existing approaches, while still (critically) reporting very few false positives. Our system is based on three key concepts: (i) a thorough happens-before model of Android-specific concurrency, (ii) a scalable analysis algorithm for efficiently building and querying the happens-before graph, and (iii) an effective set of domain-specific filters that reduce the number of reported data races by several orders of magnitude. We evaluated the usability and performance of our system on 354 real-world Android applications (e.g., Facebook). Our system analyzes a minute of end-user interaction with the application in about 24 seconds, while current approaches take hours to complete. Inspecting the results for 8 large open-source applications revealed 15 harmful bugs of diverse kinds. Some of the bugs we reported were confirmed and fixed by developers.

Type of Medium: Online Resource

ISSN: 0362-1340 , 1558-1160

URL: Article

DOI: 10.1145/2858965.2814303

Language: English

Publisher: Association for Computing Machinery (ACM)

Publication Date: 2015

detail.hit.zdb_id: 2079194-X

detail.hit.zdb_id: 282422-X

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6

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SDNRacer: concurrency analysis for software-defined networks

El-Hassany, Ahmed ; Miserez, Jeremie ; Bielik, Pavol ; [et al.]

Association for Computing Machinery (ACM) ; 2016

In: ACM SIGPLAN Notices Vol. 51, No. 6 ( 2016-08), p. 402-415

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In: ACM SIGPLAN Notices, Association for Computing Machinery (ACM), Vol. 51, No. 6 ( 2016-08), p. 402-415

Abstract: Concurrency violations are an important source of bugs in Software-Defined Networks (SDN), often leading to policy or invariant violations. Unfortunately, concurrency violations are also notoriously difficult to avoid, detect and debug. This paper presents a novel approach and a tool, SDNRacer, for detecting concurrency violations of SDNs. Our approach is enabled by three key ingredients: (i) a precise happens- before model for SDNs that captures when events can happen concurrently; (ii) a set of sound, domain-specific filters that reduce reported violations by orders of magnitude, and; (iii) a sound and complete dynamic analyzer, based on the above, that can ensure the network is free of harmful errors such as data races and per-packet incoherence. We evaluated SDNRacer on several real-world OpenFlow controllers, running both reactive and proactive applications in large networks. We show that SDNRacer is practically effective: it quickly pinpoints harmful concurrency violations without overwhelming the user with false positives.

Type of Medium: Online Resource

ISSN: 0362-1340 , 1558-1160

URL: Article

DOI: 10.1145/2980983.2908124

Language: English

Publisher: Association for Computing Machinery (ACM)

Publication Date: 2016

detail.hit.zdb_id: 2079194-X

detail.hit.zdb_id: 282422-X

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Probabilistic model for code with decision trees

Raychev, Veselin ; Bielik, Pavol ; Vechev, Martin

Association for Computing Machinery (ACM) ; 2016

In: ACM SIGPLAN Notices Vol. 51, No. 10 ( 2016-12-05), p. 731-747

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In: ACM SIGPLAN Notices, Association for Computing Machinery (ACM), Vol. 51, No. 10 ( 2016-12-05), p. 731-747

Abstract: In this paper we introduce a new approach for learning precise and general probabilistic models of code based on decision tree learning. Our approach directly benefits an emerging class of statistical programming tools which leverage probabilistic models of code learned over large codebases (e.g., GitHub) to make predictions about new programs (e.g., code completion, repair, etc). The key idea is to phrase the problem of learning a probabilistic model of code as learning a decision tree in a domain specific language over abstract syntax trees (called TGen). This allows us to condition the prediction of a program element on a dynamically computed context. Further, our problem formulation enables us to easily instantiate known decision tree learning algorithms such as ID3, but also to obtain new variants we refer to as ID3+ and E13, not previously explored and ones that outperform ID3 in prediction accuracy. Our approach is general and can be used to learn a probabilistic model of any programming language. We implemented our approach in a system called Deep3 and evaluated it for the challenging task of learning probabilistic models of JavaScript and Python. Our experimental results indicate that Deep3 predicts elements of JavaScript and Python code with precision above 82% and 69%, respectively. Further, Deep3 often significantly outperforms state-of-the-art approaches in overall prediction accuracy.

Type of Medium: Online Resource

ISSN: 0362-1340 , 1558-1160

URL: Article

DOI: 10.1145/3022671.2984041

Language: English

Publisher: Association for Computing Machinery (ACM)

Publication Date: 2016

detail.hit.zdb_id: 2079194-X

detail.hit.zdb_id: 282422-X

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Learning programs from noisy data

Raychev, Veselin ; Bielik, Pavol ; Vechev, Martin ; [et al.]

Association for Computing Machinery (ACM) ; 2016

In: ACM SIGPLAN Notices Vol. 51, No. 1 ( 2016-04-08), p. 761-774

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In: ACM SIGPLAN Notices, Association for Computing Machinery (ACM), Vol. 51, No. 1 ( 2016-04-08), p. 761-774

Abstract: We present a new approach for learning programs from noisy datasets. Our approach is based on two new concepts: a regularized program generator which produces a candidate program based on a small sample of the entire dataset while avoiding overfitting, and a dataset sampler which carefully samples the dataset by leveraging the candidate program's score on that dataset. The two components are connected in a continuous feedback-directed loop. We show how to apply this approach to two settings: one where the dataset has a bound on the noise, and another without a noise bound. The second setting leads to a new way of performing approximate empirical risk minimization on hypotheses classes formed by a discrete search space. We then present two new kinds of program synthesizers which target the two noise settings. First, we introduce a novel regularized bitstream synthesizer that successfully generates programs even in the presence of incorrect examples. We show that the synthesizer can detect errors in the examples while combating overfitting -- a major problem in existing synthesis techniques. We also show how the approach can be used in a setting where the dataset grows dynamically via new examples (e.g., provided by a human). Second, we present a novel technique for constructing statistical code completion systems. These are systems trained on massive datasets of open source programs, also known as ``Big Code''. The key idea is to introduce a domain specific language (DSL) over trees and to learn functions in that DSL directly from the dataset. These learned functions then condition the predictions made by the system. This is a flexible and powerful technique which generalizes several existing works as we no longer need to decide a priori on what the prediction should be conditioned (another benefit is that the learned functions are a natural mechanism for explaining the prediction). As a result, our code completion system surpasses the prediction capabilities of existing, hard-wired systems.

Type of Medium: Online Resource

ISSN: 0362-1340 , 1558-1160

URL: Article

DOI: 10.1145/2914770.2837671

Language: English

Publisher: Association for Computing Machinery (ACM)

Publication Date: 2016

detail.hit.zdb_id: 2079194-X

detail.hit.zdb_id: 282422-X

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Gut Microbiome Suffers from Hematopoietic Stem Cell Transplantation in Childhood and Its Characteristics Are Positively Associated with Intra-Hospital Physical Exercise

Ugrayová, Simona ; Švec, Peter ; Hric, Ivan ; [et al.]

MDPI AG ; 2022

In: Biology Vol. 11, No. 5 ( 2022-05-21), p. 785-

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In: Biology, MDPI AG, Vol. 11, No. 5 ( 2022-05-21), p. 785-

Abstract: Gut microbiome impairment is a serious side effect of cancer treatment. The aim of this study was to identify the effects of hematopoietic stem cell transplantation (HSCT) treatment on gut microbiota composition in children with acute lymphoblastic leukemia (ALL). Fecal microbiotas were categorized using specific primers targeting the V1–V3 region of 16S rDNA in eligible pediatric ALL patients after HSCT (n = 16) and in healthy controls (Ctrl, n = 13). An intra-hospital exercise program was also organized for child patients during HSCT treatment. Significant differences in gut microbiota composition were observed between ALL HSCT and Ctrl with further negative effects. Plasma C-reactive protein correlated positively with the pathogenic bacteria Enterococcus spp. and negatively with beneficial bacteria Butyriccocus spp. or Akkermansia spp., respectively (rs = 0.511, p = 0.05; rs = −0.541, p = 0.04; rs = −0.738, p = 0.02). Bacterial alpha diversity correlated with the exercise training characteristics. Therefore, specific changes in the microbiota of children were associated with systemic inflammation or the ability to exercise physically during HSCT treatment.

Type of Medium: Online Resource

ISSN: 2079-7737

URL: Article

DOI: 10.3390/biology11050785

Language: English

Publisher: MDPI AG

Publication Date: 2022

detail.hit.zdb_id: 2661517-4

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Untersuchungen zur Plasma Metal Deposition (PMD) von 6061- und 7075-Aluminiumlegierungen für Anwendungen in der Luft- und Raumfahrt sowie in der Automobilindustrie

Wallis, Christopher ; Neubauer, Erich ; Kitzmantel, Michael ; [et al.]

Springer Science and Business Media LLC ; 2023

In: BHM Berg- und Hüttenmännische Monatshefte Vol. 168, No. 5 ( 2023-05), p. 209-218

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In: BHM Berg- und Hüttenmännische Monatshefte, Springer Science and Business Media LLC, Vol. 168, No. 5 ( 2023-05), p. 209-218

Type of Medium: Online Resource

ISSN: 0005-8912 , 1613-7531

URL: Article

DOI: 10.1007/s00501-023-01345-4

RVK:

TE 1000

Language: English

Publisher: Springer Science and Business Media LLC

Publication Date: 2023

detail.hit.zdb_id: 2376950-6

SSG: 19,1

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Kooperativer Bibliotheksverbund

Berlin Brandenburg