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Tyrone Rodríguez, Adriana Guilindro, Paolo Piedrahita & Miguel Realpe |
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Title |
Towards Birds Conservation in Dry Forest Ecosystems through Audio Recognition via Deep Learning |
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2024 |
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In 9th International Congress on Information and Communication Technology ICICT 2024 |
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cidis @ cidis @ |
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239 |
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Patricia Suarez, Angel D. Sappa |
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Title |
A Generative Model for Guided Thermal Image Super-Resolution |
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2024 |
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In 19th International Conference on Computer Vision Theory and Applications VISAPP 2024 |
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cidis @ cidis @ |
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240 |
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Henry Velesaca Lara, Patricia Suarez, Darío Carpio & Angel Sappa |
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Title |
Fruit Grading based on Deep Learning and Active Vision System |
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2024 |
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Accepted in CIIA – II International Conference of Applied Industrial Engineering |
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cidis @ cidis @ |
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241 |
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Henry Velesaca Lara, Juan Antonio Holgado & José Miguel Gutiérrez |
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Title |
Optimizing Smart Factory Operations: A Methodological Approach to Industrial System Implementation based on OPC-UA |
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2024 |
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Accepted in CIIA – II International Conference of Applied Industrial Engineering |
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cidis @ cidis @ |
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242 |
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Patricia Suarez, Angel Sappa |
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Title |
Depth-Conditioned Thermal-like Image Generation |
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Conference Article |
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2024 |
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Accepted in 14th International Conference on Pattern Recognition Systems (ICPRS) |
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no |
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cidis @ cidis @ |
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243 |
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Omar Coello, Moisés Coronel, Darío Carpio, Boris X. Vintimilla & Luis Chuquimarca |
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Title |
Enhancing Apple’s Defect Classification: Insights from Visible Spectrum and Narrow Spectral Band Imaging |
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2024 |
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Accepted in 14th International Conference on Pattern Recognition Systems (ICPRS) |
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no |
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cidis @ cidis @ |
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244 |
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Author |
Luis Chuquimarca, Boris X. Vintimilla & Sergio Velastin |
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Title |
Classifying Healthy and Defective Fruits with a Siamese Architecture and CNN Models |
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Conference Article |
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2024 |
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Accepted in 14th International Conference on Pattern Recognition Systems (ICPRS) |
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no |
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cidis @ cidis @ |
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245 |
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Mónica Villavicencio; Alain Abran |
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Title |
Facts and Perceptions Regarding Software Measurement in Education and in Practice: Preliminary Results |
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2011 |
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Journal of Software Engineering and Application |
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pp. 227-234 |
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Software measurement, education, software engineering |
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Abstract |
How is software measurement addressed in undergraduate and graduate programs in universities? Do organizations consider that the graduating students they hire have an adequate knowledge of software measurement? To answer these and related questions, a survey was administered to participants who attended the IWSM-MENSURA 2010 conference in Stuttgart, Germany. Forty-seven of the 69 conference participants (including software development practitioners, software measurement consultants, university professors, and graduate students) took part in the survey. The results indicate that software measurement topics are: A) covered mostly at the graduate level and not at the undergraduate level, and B) not mandatory. Graduate students and professors consider that, of the measurement topics covered in university curricula, specific topics, such as measures for the requirements phase, and measurement techniques and tools, receive more attention in the academic context. A common observation of the practitioners who participated in the survey was that students hired as new employees bring limited software measurement-related knowledge to their organizations. Discussion of the findings and directions for future research are presented. |
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2 CIDIS-FIEC, Escuela Superior Politécnica del Litoral (ESPOL), Guayaquil, Ecuador |
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English |
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cidis @ cidis @ |
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17 |
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Author |
Carlos Monsalve; Alain April and Alain Abran |
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Title |
Measuring software functional size from business process models |
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2011 |
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International Journal of Software Engineering and Knowledge Engineering |
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Vol. 21 |
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pp. 311–338 |
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Abstract |
ISO 14143-1 specifies that a functional size measurement (FSM) method must provide measurement procedures to quantify the functional user requirements (FURs) of software. Such quantitative information, functional size, is typically used, for instance, in software estimation. One of the international standards for FSM is the COSMIC FSM method — ISO 19761 — which was designed to be applied both to the business application (BA) software domain and to the real-time software domain. A recurrent problem in FSM is the availability and quality of the inputs required for measurement purposes; that is, well documented FURs. Business process (BP) models, as they are commonly used to gather requirements from the early stages of a project, could be a valuable source of information for FSM. In a previous article, the feasibility of such an approach for the BA domain was analyzed using the Qualigram BP modeling notation. This paper complements that work by: (1) analyzing the use of BPMN for FSM in the BA domain; (2) presenting notation-independent guidelines for the BA domain; and (3) analyzing the possibility of using BP models to perform FSM in the real-time domain. The measurement results obtained from BP models are compared with those of previous FSM case studies. |
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cidis @ cidis @ |
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19 |
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Author |
Cristina L. Abad; Yi Lu; Roy H. Campbell |
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Title |
DARE: Adaptive Data Replication for Efficient Cluster Scheduling |
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2011 |
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IEEE International Conference on Cluster Computing, 2011 |
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159 - 168 |
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MapReduce, replication, scheduling, locality |
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Placing data as close as possible to computation is a common practice of data intensive systems, commonly referred to as the data locality problem. By analyzing existing production systems, we confirm the benefit of data locality and find that data have different popularity and varying correlation of accesses. We propose DARE, a distributed adaptive data replication algorithm that aids the scheduler to achieve better data locality. DARE solves two problems, how many replicas to allocate for each file and where to place them, using probabilistic sampling and a competitive aging algorithm independently at each node. It takes advantage of existing remote data accesses in the system and incurs no extra network usage. Using two mixed workload traces from Facebook, we show that DARE improves data locality by more than 7 times with the FIFO scheduler in Hadoop and achieves more than 85% data locality for the FAIR scheduler with delay scheduling. Turnaround time and job slowdown are reduced by 19% and 25%, respectively. |
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yes |
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cidis @ cidis @ |
Serial |
21 |
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