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Author |
Carlos Monsalve; Alain April; Alain Abran |
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Title |
BPM and requirements elicitation at multiple levels of abstraction: A review |
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Conference Article |
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2011 |
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IADIS International Conference on Information Systems 2011 |
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237-242 |
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Business process modeling, levels of abstraction, requirements elicitation, requirements modeling, review |
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Business process models can be useful for requirements elicitation, among other things. Software development depends on the quality of the requirements elicitation activities, and so adequately modeling business processes (BPs) is critical. A key factor in achieving this is the active participation of all the stakeholders in the development of a shared vision of BPs.
Unfortunately, organizations often find themselves left with inconsistent BPs that do not cover all the stakeholders’ needs
and constraints. However, consolidation of the various stakeholder requirements may be facilitated through the use of multiple levels of abstraction (MLA). This article contributes to the research into MLA use in business process modeling (BPM) for software requirements by reviewing the theoretical foundations of MLA and their use in various BP-oriented approaches. |
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CIDIS-FIEC, Escuela Superior Politécnica del Litoral (ESPOL) Km. 30.5 vía Perimetral, |
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cidis @ cidis @ |
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15 |
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Author |
Carlos Monsalve; Alain April; Alain Abran |
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Title |
Requirements Elicitation Using BPM Notations: Focusing on the Strategic Level Representation |
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Conference Article |
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Year |
2011 |
Publication |
10th WSEAS international conference on Applied computer and applied computational science |
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235-241 |
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Business process modeling, levels of abstraction, requirements elicitation, case study, action research |
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Business process models (BPM) can be useful for requirements elicitation, among other uses. Since the active participation of all stakeholders is a key factor for successful requirements engineering, it is important that BPM be shared by all stakeholders. Unfortunately, organizations may end up with inconsistent BPM not covering all stakeholders’ needs and constraints. The use of multiple levels of abstraction (MLA), such as at the strategic, tactical and operational levels, is often used in various process-oriented initiatives to facilitate the consolidation of various stakeholders’ needs and constraints. This article surveys the use of MLA in recent BPM research publications and reports on a BPM action-research case study conducted in a Canadian organization, with the aim of exploring the usefulness of the strategic level. |
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CIDIS – Electrical and Computer Engineering Department Escuela Superior Politécnica del Litoral Km. 30.5 vía Perimetral |
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1100 rue Notre-Dame Ouest, Montréal, Québec H3C 1K3 CANADA |
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English |
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English |
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cidis @ cidis @ |
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16 |
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Roberto Jacome Galarza; Miguel-Andrés Realpe-Robalino; Chamba-Eras LuisAntonio; Viñán-Ludeña MarlonSantiago and Sinche-Freire Javier-Francisco |
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Title |
Computer vision for image understanding. A comprehensive review |
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Conference Article |
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2019 |
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International Conference on Advances in Emerging Trends and Technologies (ICAETT 2019); Quito, Ecuador |
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248-259 |
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Computer Vision has its own Turing test: Can a machine describe the contents of an image or a video in the way a human being would do? In this paper, the progress of Deep Learning for image recognition is analyzed in order to know the answer to this question. In recent years, Deep Learning has increased considerably the precision rate of many tasks related to computer vision. Many datasets of labeled images are now available online, which leads to pre-trained models for many computer vision applications. In this work, we gather information of the latest techniques to perform image understanding and description. As a conclusion we obtained that the combination of Natural Language Processing (using Recurrent Neural Networks and Long Short-Term Memory) plus Image Understanding (using Convolutional Neural Networks) could bring new types of powerful and useful applications in which the computer will be able to answer questions about the content of images and videos. In order to build datasets of labeled images, we need a lot of work and most of the datasets are built using crowd work. These new applications have the potential to increase the human machine interaction to new levels of usability and user’s satisfaction. |
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gtsi @ user @ |
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97 |
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Author |
Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla |
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Title |
Colorizing Infrared Images through a Triplet Condictional DCGAN Architecture |
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Conference Article |
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Year |
2017 |
Publication |
19th International Conference on Image Analysis and Processing. |
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287-297 |
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no |
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gtsi @ user @ |
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66 |
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Byron Lima; Ricardo Cajo; Victor Huilcapi; Wilton Agila |
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Title |
Modeling and comparative study of linear and nonlinear controllers for rotary inverted pendulum |
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Conference Article |
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2017 |
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Journal of Physics: Conference Series |
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783 |
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The rotary inverted pendulum (RIP) is a problem difficult to control, several studies have been conducted where different control techniques have been applied. Literature reports that, although problem is nonlinear, classical PID controllers presents appropriate performances when applied to the system. In this paper, a comparative study of the performances of linear and nonlinear PID structures is carried out. The control algorithms are evaluated in the RIP system, using indices of performance and power consumption, which allow the categorization of control strategies according to their performance. This article also presents the modeling system, which has been estimated some of the parameters involved in the RIP system, using computer-aided design tools (CAD) and experimental methods or techniques proposed by several authors attended. The results indicate a better performance of the nonlinear controller with an increase in the robustness and faster response than the linear controller |
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English |
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no |
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gtsi @ user @ |
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69 |
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Author |
Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla |
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Title |
Learning Image Vegetation Index through a Conditional Generative Adversarial Network |
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Conference Article |
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2017 |
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2nd IEEE Ecuador Tehcnnical Chapters Meeting (ETCM) |
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no |
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gtsi @ user @ |
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70 |
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Author |
Lukas Danev; Marten Hamann; Nicolas Fricke; Tobias Hollarek; Dennys Paillacho |
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Development of animated facial expression to express emotions in a robot: RobotIcon. |
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Conference Article |
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2017 |
Publication |
IEEE Ecuador Technical Chapter Meeting (ETCM) |
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2017-January |
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1-6 |
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no |
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gtsi @ user @ |
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71 |
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Author |
Xavier Soria; Angel D. Sappa; Arash Akbarinia |
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Title |
Multispectral Single-Sensor RGB-NIR Imaging: New Challenges an Oppotunities |
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Conference Article |
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2017 |
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The 7th International Conference on Image Processing Theory, Tools and Application |
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1-6 |
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gtsi @ user @ |
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72 |
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Author |
Milton Mendieta; F. Panchana; B. Andrade; B. Bayot; C. Vaca; Boris X. Vintimilla; Dennis G. Romero |
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Title |
Organ identification on shrimp histological images: A comparative study considering CNN and feature engineering. |
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Conference Article |
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2018 |
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IEEE Ecuador Technical Chapters Meeting ETCM 2018. Cuenca, Ecuador |
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1-6 |
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The identification of shrimp organs in biology using
histological images is a complex task. Shrimp histological images
poses a big challenge due to their texture and similarity among
classes. Image classification by using feature engineering and
convolutional neural networks (CNN) are suitable methods to
assist biologists when performing organ detection. This work
evaluates the Bag-of-Visual-Words (BOVW) and Pyramid-Bagof-
Words (PBOW) models for image classification leveraging big
data techniques; and transfer learning for the same classification
task by using a pre-trained CNN. A comparative analysis
of these two different techniques is performed, highlighting
the characteristics of both approaches on the shrimp organs
identification problem. |
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Call Number |
gtsi @ user @ |
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87 |
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Author |
Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla; Riad I. Hammoud |
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Title |
Deep Learning based Single Image Dehazing |
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Conference Article |
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2018 |
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14th IEEE Workshop on Perception Beyond the Visible Spectrum – In conjunction with CVPR 2018. Salt Lake City, Utah. USA |
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This paper proposes a novel approach to remove haze
degradations in RGB images using a stacked conditional
Generative Adversarial Network (GAN). It employs a triplet
of GAN to remove the haze on each color channel independently.
A multiple loss functions scheme, applied over a
conditional probabilistic model, is proposed. The proposed
GAN architecture learns to remove the haze, using as conditioned
entrance, the images with haze from which the clear
images will be obtained. Such formulation ensures a fast
model training convergence and a homogeneous model generalization.
Experiments showed that the proposed method
generates high-quality clear images. |
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gtsi @ user @ |
Serial |
83 |
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