---
_id: '533'
author:
- first_name: Richard
  full_name: Borkowski, Richard
  last_name: Borkowski
citation:
  ama: Borkowski R. <i>Entwicklung eines Hybriden Planers zur verhaltensorientierten
    Selbstoptimierung</i>. Universität Paderborn; 2013.
  apa: Borkowski, R. (2013). <i>Entwicklung eines Hybriden Planers zur verhaltensorientierten
    Selbstoptimierung</i>. Universität Paderborn.
  bibtex: '@book{Borkowski_2013, title={Entwicklung eines Hybriden Planers zur verhaltensorientierten
    Selbstoptimierung}, publisher={Universität Paderborn}, author={Borkowski, Richard},
    year={2013} }'
  chicago: Borkowski, Richard. <i>Entwicklung eines Hybriden Planers zur verhaltensorientierten
    Selbstoptimierung</i>. Universität Paderborn, 2013.
  ieee: R. Borkowski, <i>Entwicklung eines Hybriden Planers zur verhaltensorientierten
    Selbstoptimierung</i>. Universität Paderborn, 2013.
  mla: Borkowski, Richard. <i>Entwicklung eines Hybriden Planers zur verhaltensorientierten
    Selbstoptimierung</i>. Universität Paderborn, 2013.
  short: R. Borkowski, Entwicklung eines Hybriden Planers zur verhaltensorientierten
    Selbstoptimierung, Universität Paderborn, 2013.
date_created: 2017-10-17T12:42:36Z
date_updated: 2022-01-06T07:01:49Z
language:
- iso: ger
project:
- _id: '1'
  name: SFB 901
- _id: '10'
  name: SFB 901 - Subprojekt B2
- _id: '3'
  name: SFB 901 - Project Area B
publisher: Universität Paderborn
status: public
title: Entwicklung eines Hybriden Planers zur verhaltensorientierten Selbstoptimierung
type: bachelorsthesis
user_id: '477'
year: '2013'
...
---
_id: '568'
abstract:
- lang: eng
  text: A major goal of the On-The-Fly Computing project is the automated composition
    of individual services based on services that are available in dynamic markets.
    Dependent on the granularity of a market, different alternatives that satisfy
    the requested functional requirements may emerge. In order to select the best
    solution, services are usually selected with respect to their quality in terms
    of inherent non-functional properties. In this paper, we describe our idea of
    how to model this service selection process as a Markov Decision Process, which
    we in turn intend to solve by means of Reinforcement Learning techniques in order
    to control the underlying service composition process. In addition, some initial
    issues with respect to our approach are addressed.
author:
- first_name: Alexander
  full_name: Jungmann, Alexander
  last_name: Jungmann
- first_name: Bernd
  full_name: Kleinjohann, Bernd
  last_name: Kleinjohann
citation:
  ama: 'Jungmann A, Kleinjohann B. Towards the Application of Reinforcement Learning
    Techniques for Quality-Based Service Selection in Automated Service Composition.
    In: <i>Proceedings of the 9th IEEE International Conference on Service Computing
    (SCC)</i>. ; 2012:701-702. doi:<a href="https://doi.org/10.1109/SCC.2012.76">10.1109/SCC.2012.76</a>'
  apa: Jungmann, A., &#38; Kleinjohann, B. (2012). Towards the Application of Reinforcement
    Learning Techniques for Quality-Based Service Selection in Automated Service Composition.
    In <i>Proceedings of the 9th IEEE International Conference on Service Computing
    (SCC)</i> (pp. 701–702). <a href="https://doi.org/10.1109/SCC.2012.76">https://doi.org/10.1109/SCC.2012.76</a>
  bibtex: '@inproceedings{Jungmann_Kleinjohann_2012, title={Towards the Application
    of Reinforcement Learning Techniques for Quality-Based Service Selection in Automated
    Service Composition}, DOI={<a href="https://doi.org/10.1109/SCC.2012.76">10.1109/SCC.2012.76</a>},
    booktitle={Proceedings of the 9th IEEE International Conference on Service Computing
    (SCC)}, author={Jungmann, Alexander and Kleinjohann, Bernd}, year={2012}, pages={701–702}
    }'
  chicago: Jungmann, Alexander, and Bernd Kleinjohann. “Towards the Application of
    Reinforcement Learning Techniques for Quality-Based Service Selection in Automated
    Service Composition.” In <i>Proceedings of the 9th IEEE International Conference
    on Service Computing (SCC)</i>, 701–2, 2012. <a href="https://doi.org/10.1109/SCC.2012.76">https://doi.org/10.1109/SCC.2012.76</a>.
  ieee: A. Jungmann and B. Kleinjohann, “Towards the Application of Reinforcement
    Learning Techniques for Quality-Based Service Selection in Automated Service Composition,”
    in <i>Proceedings of the 9th IEEE International Conference on Service Computing
    (SCC)</i>, 2012, pp. 701–702.
  mla: Jungmann, Alexander, and Bernd Kleinjohann. “Towards the Application of Reinforcement
    Learning Techniques for Quality-Based Service Selection in Automated Service Composition.”
    <i>Proceedings of the 9th IEEE International Conference on Service Computing (SCC)</i>,
    2012, pp. 701–02, doi:<a href="https://doi.org/10.1109/SCC.2012.76">10.1109/SCC.2012.76</a>.
  short: 'A. Jungmann, B. Kleinjohann, in: Proceedings of the 9th IEEE International
    Conference on Service Computing (SCC), 2012, pp. 701–702.'
date_created: 2017-10-17T12:42:43Z
date_updated: 2022-01-06T07:02:31Z
ddc:
- '040'
doi: 10.1109/SCC.2012.76
file:
- access_level: closed
  content_type: application/pdf
  creator: florida
  date_created: 2018-03-15T10:19:51Z
  date_updated: 2018-03-15T10:19:51Z
  file_id: '1274'
  file_name: 568-Towards_the_Application_of_Reinforcement_Learning_Techniques_for_Quality-Based_Service_Selection_in_Automated_Service_Composition.pdf
  file_size: 122607
  relation: main_file
  success: 1
file_date_updated: 2018-03-15T10:19:51Z
has_accepted_license: '1'
page: 701-702
project:
- _id: '1'
  name: SFB 901
- _id: '10'
  name: SFB 901 - Subprojekt B2
- _id: '3'
  name: SFB 901 - Project Area B
publication: Proceedings of the 9th IEEE International Conference on Service Computing
  (SCC)
status: public
title: Towards the Application of Reinforcement Learning Techniques for Quality-Based
  Service Selection in Automated Service Composition
type: conference
user_id: '15504'
year: '2012'
...
---
_id: '571'
abstract:
- lang: eng
  text: The paradigm shift from purchasing monolithic software solutions to a dynamic
    composition of individual solutions entails many new possibilities yet great challenges,
    too. In order to satisfy user requirements, complex services have to be automatically
    composed of elementary services. Multiple possibilities of composing a complex
    service inevitably emerge. The problem of selecting the most appropriate services
    has to be solved by comparing the different service candidates with respect to
    their quality in terms of inherent non-functional properties while simultaneously
    taking the user requirements into account. We are aiming for an integrated service
    rating and ranking methodology in order to support the automation of the underlying
    decision-making process. The main contribution of this paper is a first decomposition
    of the quality-based service selection process, while emphasizing major issues
    and challenges, which we are addressing in the On-The-Fly Computing project.
author:
- first_name: Alexander
  full_name: Jungmann, Alexander
  last_name: Jungmann
- first_name: Bernd
  full_name: Kleinjohann, Bernd
  last_name: Kleinjohann
citation:
  ama: 'Jungmann A, Kleinjohann B. Towards an Integrated Service Rating and Ranking
    Methodology for Quality Based Service Selection in Automatic Service Composition.
    In: <i>Proceedings of the 4th International Conferences on Advanced Service Computing
    (SERVICE COMPUTATION)</i>. ; 2012:43-47.'
  apa: Jungmann, A., &#38; Kleinjohann, B. (2012). Towards an Integrated Service Rating
    and Ranking Methodology for Quality Based Service Selection in Automatic Service
    Composition. In <i>Proceedings of the 4th International Conferences on Advanced
    Service Computing (SERVICE COMPUTATION)</i> (pp. 43–47).
  bibtex: '@inproceedings{Jungmann_Kleinjohann_2012, title={Towards an Integrated
    Service Rating and Ranking Methodology for Quality Based Service Selection in
    Automatic Service Composition}, booktitle={Proceedings of the 4th International
    Conferences on Advanced Service Computing (SERVICE COMPUTATION)}, author={Jungmann,
    Alexander and Kleinjohann, Bernd}, year={2012}, pages={43–47} }'
  chicago: Jungmann, Alexander, and Bernd Kleinjohann. “Towards an Integrated Service
    Rating and Ranking Methodology for Quality Based Service Selection in Automatic
    Service Composition.” In <i>Proceedings of the 4th International Conferences on
    Advanced Service Computing (SERVICE COMPUTATION)</i>, 43–47, 2012.
  ieee: A. Jungmann and B. Kleinjohann, “Towards an Integrated Service Rating and
    Ranking Methodology for Quality Based Service Selection in Automatic Service Composition,”
    in <i>Proceedings of the 4th International Conferences on Advanced Service Computing
    (SERVICE COMPUTATION)</i>, 2012, pp. 43–47.
  mla: Jungmann, Alexander, and Bernd Kleinjohann. “Towards an Integrated Service
    Rating and Ranking Methodology for Quality Based Service Selection in Automatic
    Service Composition.” <i>Proceedings of the 4th International Conferences on Advanced
    Service Computing (SERVICE COMPUTATION)</i>, 2012, pp. 43–47.
  short: 'A. Jungmann, B. Kleinjohann, in: Proceedings of the 4th International Conferences
    on Advanced Service Computing (SERVICE COMPUTATION), 2012, pp. 43–47.'
date_created: 2017-10-17T12:42:43Z
date_updated: 2022-01-06T07:02:37Z
ddc:
- '040'
file:
- access_level: closed
  content_type: application/pdf
  creator: florida
  date_created: 2018-03-15T09:39:02Z
  date_updated: 2018-03-15T09:39:02Z
  file_id: '1271'
  file_name: 571-Towards_an_Integrated_Service_Rating_and_Ranking_Methodology__for_Quality_Based_Service_Selection_in_Automatic_Service_Composition.pdf
  file_size: 103343
  relation: main_file
  success: 1
file_date_updated: 2018-03-15T09:39:02Z
has_accepted_license: '1'
page: 43-47
project:
- _id: '1'
  name: SFB 901
- _id: '10'
  name: SFB 901 - Subproject B2
- _id: '3'
  name: SFB 901 - Project Area B
publication: Proceedings of the 4th International Conferences on Advanced Service
  Computing (SERVICE COMPUTATION)
status: public
title: Towards an Integrated Service Rating and Ranking Methodology for Quality Based
  Service Selection in Automatic Service Composition
type: conference
user_id: '15504'
year: '2012'
...
---
_id: '617'
abstract:
- lang: eng
  text: In this paper, a color based feature extraction and classification approach
    for image processing in embedded systems in presented. The algorithms and data
    structures developed for this approach pay particular attention to reduce memory
    consumption and computation power of the entire image processing, since embedded
    systems usually impose strong restrictions regarding those resources. The feature
    extraction is realized in terms of an image segmentation algorithm. The criteria
    of homogeneity for merging pixels and regions is provided by the color classification
    mechanism, which incorporates appropriate methods for defining, representing and
    accessing subspaces in the working color space. By doing so, pixels and regions
    with color values that belong to the same color class can be merged. Furthermore,
    pixels with redundant color values that do not belong to any pre-defined color
    class can be completely discarded in order to minimize computational effort. Subsequently,
    the extracted regions are converted to a more convenient feature representation
    in terms of statistical moments up to and including second order. For evaluation,
    the whole image processing approach is applied to a mobile representative of embedded
    systems within the scope of a simple real-world scenario.
author:
- first_name: Alexander
  full_name: Jungmann, Alexander
  last_name: Jungmann
- first_name: Bernd
  full_name: Kleinjohann, Bernd
  last_name: Kleinjohann
- first_name: Elisabeth
  full_name: Kleinjohann, Elisabeth
  id: '15588'
  last_name: Kleinjohann
- first_name: Maarten
  full_name: Bieshaar, Maarten
  last_name: Bieshaar
citation:
  ama: 'Jungmann A, Kleinjohann B, Kleinjohann E, Bieshaar M. Efficient Color-Based
    Image Segmentation and Feature Classification for Image Processing in Embedded
    Systems. In: <i>Proceedings of the Fourth International Conference on Resource
    Intensive Applications and Services (INTENSIVE)</i>. ; 2012:22-29.'
  apa: Jungmann, A., Kleinjohann, B., Kleinjohann, E., &#38; Bieshaar, M. (2012).
    Efficient Color-Based Image Segmentation and Feature Classification for Image
    Processing in Embedded Systems. In <i>Proceedings of the Fourth International
    Conference on Resource Intensive Applications and Services (INTENSIVE)</i> (pp.
    22–29).
  bibtex: '@inproceedings{Jungmann_Kleinjohann_Kleinjohann_Bieshaar_2012, title={Efficient
    Color-Based Image Segmentation and Feature Classification for Image Processing
    in Embedded Systems}, booktitle={Proceedings of the Fourth International Conference
    on Resource Intensive Applications and Services (INTENSIVE)}, author={Jungmann,
    Alexander and Kleinjohann, Bernd and Kleinjohann, Elisabeth and Bieshaar, Maarten},
    year={2012}, pages={22–29} }'
  chicago: Jungmann, Alexander, Bernd Kleinjohann, Elisabeth Kleinjohann, and Maarten
    Bieshaar. “Efficient Color-Based Image Segmentation and Feature Classification
    for Image Processing in Embedded Systems.” In <i>Proceedings of the Fourth International
    Conference on Resource Intensive Applications and Services (INTENSIVE)</i>, 22–29,
    2012.
  ieee: A. Jungmann, B. Kleinjohann, E. Kleinjohann, and M. Bieshaar, “Efficient Color-Based
    Image Segmentation and Feature Classification for Image Processing in Embedded
    Systems,” in <i>Proceedings of the Fourth International Conference on Resource
    Intensive Applications and Services (INTENSIVE)</i>, 2012, pp. 22–29.
  mla: Jungmann, Alexander, et al. “Efficient Color-Based Image Segmentation and Feature
    Classification for Image Processing in Embedded Systems.” <i>Proceedings of the
    Fourth International Conference on Resource Intensive Applications and Services
    (INTENSIVE)</i>, 2012, pp. 22–29.
  short: 'A. Jungmann, B. Kleinjohann, E. Kleinjohann, M. Bieshaar, in: Proceedings
    of the Fourth International Conference on Resource Intensive Applications and
    Services (INTENSIVE), 2012, pp. 22–29.'
date_created: 2017-10-17T12:42:52Z
date_updated: 2022-01-06T07:02:55Z
ddc:
- '040'
file:
- access_level: closed
  content_type: application/pdf
  creator: florida
  date_created: 2018-03-15T06:47:50Z
  date_updated: 2018-03-15T06:47:50Z
  file_id: '1245'
  file_name: 617-INTENSIVE2012-Jungmann.pdf
  file_size: 2787964
  relation: main_file
  success: 1
file_date_updated: 2018-03-15T06:47:50Z
has_accepted_license: '1'
page: 22-29
project:
- _id: '1'
  name: SFB 901
- _id: '10'
  name: SFB 901 - Subprojekt B2
- _id: '3'
  name: SFB 901 - Project Area B
publication: Proceedings of the Fourth International Conference on Resource Intensive
  Applications and Services (INTENSIVE)
related_material:
  link:
  - relation: confirmation
    url: http://www.thinkmind.org/index.php?view=article&articleid=intensive_2012_1_50_30031
status: public
title: Efficient Color-Based Image Segmentation and Feature Classification for Image
  Processing in Embedded Systems
type: conference
user_id: '477'
year: '2012'
...