2018
Authors
Lima, B;
Publication
ESEC/FSE'18: PROCEEDINGS OF THE 2018 26TH ACM JOINT MEETING ON EUROPEAN SOFTWARE ENGINEERING CONFERENCE AND SYMPOSIUM ON THE FOUNDATIONS OF SOFTWARE ENGINEERING
Abstract
In a growing number of domains, the provisioning of end-to-end services to the users depends on the proper interoperation of multiple systems, forming a new distributed system, often subject to timing constraints. To ensure interoperability and integrity, it is important to conduct integration tests that verify the interactions with the environment and between the system components in key scenarios. To tackle test automation challenges, we propose algorithms for decentralized conformance checking and test input generation, and for checking and enforcing the conditions (local observability and controllability) that allow decentralized test execution.
2018
Authors
Nogueira, AR; Ferreira, CA; Gama, J;
Publication
INTELLIGENT DATA ANALYSIS
Abstract
The Acute Kidney Injury (AKI), is a disease that affects the kidneys and is characterized by the rapid deterioration of these organs, usually associated with a pre-existing critical illness. Being an acute disease, time is a key element in the prevention. By anticipating a patient's state transition, we are preventing future complications in his health, such as the development of a chronic disease or loss of an organ, in addition to decreasing the amount of money spent on the patient's care. The main goal of this paper is to address the problem of correctly predicting the illness path in various patients by studying different methodologies to predict this disease and propose new distinct approaches based on this idea of improving the performance of the classification. Through the comparison of five different approaches (Markov Chain Model ICU Specialists, Markov Chain Model Features, Markov Chain Model Conditional Features, Markov Chain Model and Random Forest), we came to the conclusion that the application of conditional probabilities to this problem produces a more accurate prediction, based on common inputs.
2018
Authors
Ancuti, C; Ancuti, CO; Timofte, R; Van Gool, L; Zhang, L; Yang, MH; Patel, VM; Zhang, H; Sindagi, VA; Zhao, RH; Ma, XP; Qin, Y; Jia, LM; Friedel, K; Ki, S; Sim, H; Choi, JS; Kim, SY; Seo, S; Kim, S; Kim, M; Mondal, R; Santra, S; Chanda, B; Liu, JL; Mei, KF; Li, JC; Luyao,; Fang, FM; Jiang, AW; Qu, XC; Liu, T; Wang, PF; Sun, B; Deng, JF; Zhao, YH; Hong, M; Huang, JY; Chen, YZ; Chen, ER; Yu, XL; Wu, TT; Genc, A; Engin, D; Ekenel, HK; Liu, WZ; Tong, T; Li, G; Gao, QQ; Li, Z; Tang, DF; Chen, YL; Huo, ZY; Alvarez Gila, A; Galdran, A; Bria, A; Vazquez Corral, J; Bertalmo, M; Demir, HS; Adil, OF; Phung, HX; Jin, X; Chen, JL; Shan, CW; Chen, ZB;
Publication
PROCEEDINGS 2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW)
Abstract
This paper reviews the first challenge on image dehazing (restoration of rich details in hazy image) with focus on proposed solutions and results. The challenge had 2 tracks. Track 1 employed the indoor images (using I-HAZE dataset), while Track 2 outdoor images (using O-HAZE dataset). The hazy images have been captured in presence of real haze, generated by professional haze machines. I-HAZE dataset contains 35 scenes that correspond to indoor domestic environments, with objects with different colors and specularities. O-HAZE contains 45 different outdoor scenes depicting the same visual content recorded in hazefree and hazy conditions, under the same illumination parameters. The dehazing process was learnable through provided pairs of haze-free and hazy train images. Each track had similar to 120 registered participants and 21 teams competed in the final testing phase. They gauge the state-of-the-art in image dehazing.
2018
Authors
Cachada, A; Pires, F; Barbosa, J; Leitao, P; Cala, A;
Publication
Proceedings - 2018 IEEE Industrial Cyber-Physical Systems, ICPS 2018
Abstract
The fourth industrial revolution, commonly known as Industry 4.0, germinated in Germany as an industrial program of the government to reinvigorate the manufacturing sector. Nowadays, this change in the industrial paradigm has reached a global scale and is proposing to transform the traditional factories into more competitive, efficient and productive industries. In order to accomplish this goal it is necessary to establish methodologies to migrate from the traditional systems to innovative systems, namely those applying the Cyber-Physical Production Systems (CPPS) concepts. This paper proposes a methodology based on the Petri nets formalism for the modelling, analysis, validation and simulation of the migration process during the design phase and the control and monitoring of such processes during the implementation phase. © 2018 IEEE.
2018
Authors
Santos, MM; Jorge, PAS; Coimbra, J; Vale, C; Caetano, M; Bastos, L; Iglesias, I; Guimaraes, L; Reis Henriques, MA; Teles, LO; Vieira, MN; Raimundo, J; Pinheiro, M; Nogueira, V; Pereira, R; Neuparth, T; Ribeiro, MC; Silva, E; Castro, LFC;
Publication
SCIENCE OF THE TOTAL ENVIRONMENT
Abstract
The growing economic interest in the exploitation of mineral resources on deep-ocean beds, including those in the vicinity of sensitive-rich habitats such as hydrothermal vents, raise amounting concern about the damage that such actions might originate to these poorly-know ecosystems, which represent millions of years of evolution and adaptations to extreme environmental conditions. It has been suggested that mining may cause a major impact on vent ecosystems and other deep-sea areas. Yet, the scale and the nature of such impacts are unknown at present. Hence, building upon currently available scientific information it is crucial to develop new cost-effective technologies embedded into rigorous operating frameworks. The forward-thinking provided here will assist in the development of new technologies and tools to address the major challenges associated with deep sea-mining; technologies for in situ and ex situ observation and data acquisition, biogeochemical processes, hazard assessment of deep-sea mining to marine organisms and development of modeling tools in support of risk assessment scenarios. These technological developments are vital to validate a responsible and sustainable exploitation of the deep-sea mineral resources, based on the precautionary principle.
2018
Authors
Novais, S; Ferreira, CIA; Ferreira, MS; Pinto, JL;
Publication
Optics InfoBase Conference Papers
Abstract
A reflective fiber optic sensor based on multimode interference for the measurement of glucose aqueous solutions is proposed. A maximum experimental resolution of 0.04 wt.% of glucose is achieved. © OSA 2018 © 2018 The Author(s)
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