![]() ; ; et al in ACM Transactions on Software Engineering and Methodology (in press) ![]() Ma, Wei ![]() ![]() in ACM Transactions on Software Engineering and Methodology (in press) Detailed reference viewed: 67 (4 UL)![]() Titcheu Chekam, Thierry ![]() ![]() ![]() in ACM Transactions on Software Engineering and Methodology (in press) Detailed reference viewed: 76 (7 UL)![]() Mouline, Ludovic ![]() ![]() ![]() in INTERNATIONAL CONFERENCE ON SMART GRID COMMUNICATIONS, 11-13 November 2020 (2020, November) Smart grids allow operators to monitor the grid continuously, detect occurring incidents, and trigger corrective actions. To perform that, they require a deep understanding of the effective situation ... [more ▼] Smart grids allow operators to monitor the grid continuously, detect occurring incidents, and trigger corrective actions. To perform that, they require a deep understanding of the effective situation within the grid. However, some parameters of the grid may not be known with absolute confidence. Reasoning over the grid despite uncertainty needs the consideration of all possible states. In this paper, we propose an approach to enumerate only valid potential grid states. Thereby, we allow discarding invalid assumptions that poison the results of a given computation procedure. We validate our approach based on a real-world topology from the power grid in Luxembourg. We show that the estimation of cable load is negatively affected by invalid fuse state combinations, in terms of computation time and accuracy. [less ▲] Detailed reference viewed: 68 (10 UL)![]() ; ; Cordy, Maxime ![]() in SOFTWARE PRODUCT LINE CONFERENCE (2020, October) Detailed reference viewed: 11 (0 UL)![]() Antoniadis, Nikolaos ![]() ![]() in Communications in Computer and Information Science (2020, February 15) Cable overloading is one of the most critical disturbances that may occur in smart grids, as it can cause damage to the distribution power lines. Therefore, the circuits are protected by fuses so that ... [more ▼] Cable overloading is one of the most critical disturbances that may occur in smart grids, as it can cause damage to the distribution power lines. Therefore, the circuits are protected by fuses so that, the overload could trip the fuse, opening the circuit, and stopping the flow and heating. However, sustained overloads, even if they are below the safety limits, could also damage the wires. To prevent overload, smart grid operators can switch the fuses on or off to protect the circuits, or remotely curtail the over-producing/over-consuming users. Nevertheless, making the most appropriate decision is a daunting decision-making task, notably due to contractual and technical obligations. In this paper, we define and formulate the overloading prevention problem as a Multiobjective Mixed Integer Quadratically Constrained Program. We also suggest a solution method using a combinatorial optimization approach with a state-of-the-art exact solver. We evaluate this approach for this real-world problem together with Creos Luxembourg S.A., the leading grid operator in Luxembourg, and show that our method can suggest optimal countermeasures to operators facing potential overloading incidents. [less ▲] Detailed reference viewed: 256 (34 UL)![]() Garg, Aayush ![]() ![]() ![]() E-print/Working paper (2020) Detailed reference viewed: 6 (3 UL)![]() Ghamizi, Salah ![]() ![]() ![]() in International Conference on Software Engineering (ICSE) (2020) Detailed reference viewed: 35 (2 UL)![]() Ghamizi, Salah ![]() ![]() ![]() Scientific Conference (2020) We propose adversarial embedding, a new steganography and watermarking technique that embeds secret information within images. The key idea of our method is to use deep neural networks for image ... [more ▼] We propose adversarial embedding, a new steganography and watermarking technique that embeds secret information within images. The key idea of our method is to use deep neural networks for image classification and adversarial attacks to embed secret information within images. Thus, we use the attacks to embed an encoding of the message within images and the related deep neural network outputs to extract it. The key properties of adversarial attacks (invisible perturbations, nontransferability, resilience to tampering) offer guarantees regarding the confidentiality and the integrity of the hidden messages. We empirically evaluate adversarial embedding using more than 100 models and 1,000 messages. Our results confirm that our embedding passes unnoticed by both humans and steganalysis methods, while at the same time impedes illicit retrieval of the message (less than 13% recovery rate when the interceptor has some knowledge about our model), and is resilient to soft and (to some extent) aggressive image tampering (up to 100% recovery rate under jpeg compression). We further develop our method by proposing a new type of adversarial attack which improves the embedding density (amount of hidden information) of our method to up to 10 bits per pixel. [less ▲] Detailed reference viewed: 303 (33 UL)![]() Ghamizi, Salah ![]() ![]() ![]() Report (2020) The COVID-19 pandemic has created a public health emergency unprecedented in this century. The lack ofaccurate knowledge regarding the outcomes of the virus has made it challenging for policymakers to ... [more ▼] The COVID-19 pandemic has created a public health emergency unprecedented in this century. The lack ofaccurate knowledge regarding the outcomes of the virus has made it challenging for policymakers to decideon appropriate countermeasures to mitigate its impact on society, in particular the public health and the veryhealthcare system.While the mitigation strategies (including the lockdown) are getting lifted, understanding the current im-pacts of the outbreak remains challenging. This impedes any analysis and scheduling of measures requiredfor the different countries to recover from the pandemic without risking a new outbreak.Therefore, we propose a novel approach to build realistic data-driven pandemic simulation and forecastingmodels to support policymakers. Our models allow the investigation of mitigation/recovery measures andtheir impact. Thereby, they enable appropriate planning of those measures, with the aim to optimize theirsocietal benefits.Our approach relies on a combination of machine learning and classical epidemiological models, circum-venting the respective limitations of these techniques to allow a policy-making based on established knowl-edge, yet driven by factual data, and tailored to each country’s specific context. [less ▲] Detailed reference viewed: 164 (12 UL)![]() Cordy, Maxime ![]() in International Journal on Software Tools for Technology Transfer (2019), 21(6), 635-649 Detailed reference viewed: 28 (0 UL)![]() Cordy, Maxime ![]() in Proceedings of the 23rd International Systems and Software Product Line Conference, SPLC 2019, Volume A, Paris, France, September 9-13, 2019 (2019, September) Detailed reference viewed: 22 (0 UL)![]() ; Cordy, Maxime ![]() in Proceedings of the 1st ACM SIGSOFT International Workshop on Education through Advanced Software Engineering and Artificial Intelligence, EASEAI@ESEC/SIGSOFT FSE 2019, Tallinn, Estonia, August 26, 2019 (2019, August 26) Detailed reference viewed: 20 (0 UL)![]() Cordy, Maxime ![]() in Proceedings of the 7th International Workshop on Formal Methods in Software Engineering (2019, May) Detailed reference viewed: 28 (0 UL)![]() ; Cordy, Maxime ![]() in Proceedings of the 41st International Conference on Software Engineering, ICSE 2019, Montreal, QC, Canada, May 25-31, 2019 (2019, May) Detailed reference viewed: 31 (1 UL)![]() ; Cordy, Maxime ![]() in Proceedings of the 13th International Workshop on Variability Modelling of Software-Intensive Systems, VAMOS 2019, Leuven, Belgium, February 06-08, 2019 (2019, February) Detailed reference viewed: 17 (0 UL)![]() ; ; et al Book published by ACM (2019) Detailed reference viewed: 19 (2 UL)![]() ; ; et al in 12th IEEE Conference on Software Testing, Validation and Verification, ICST 2019, Xi'an, China, April 22-27, 2019 (2019) Detailed reference viewed: 72 (0 UL)![]() Cordy, Maxime ![]() in From Software Engineering to Formal Methods and Tools, and Back - Essays Dedicated to Stefania Gnesi on the Occasion of Her 65th Birthday (2019) Detailed reference viewed: 28 (2 UL)![]() Cordy, Maxime ![]() ![]() in ACM SIGSOFT International Symposium on Software Testing and Analysis (2019) Detailed reference viewed: 126 (6 UL) |
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