5 Search Results for "Bartolini, Andrea"

Document
Short Paper
DOI: 10.4230/LIPIcs.CP.2025.41
Modeling and Solving a Composite Structure Design Problem with Constraint Programming (Short Paper)

Authors: Miguel Antoons, Augustin Delecluse, Samih Zein, and Pierre Schaus

Published in: LIPIcs, Volume 340, 31st International Conference on Principles and Practice of Constraint Programming (CP 2025)

Abstract
Composite structures are composed of plies (layers) of carbon fibers. For each ply, one must decide its orientation from the set of possible angles: -45°, 0°, 45°, and 90°. The stack of plies must follow strict constraints on the chosen orientations to achieve mechanical properties of the composite, such as sufficient buckling load. The design problem becomes more complex when determining the stack of plies for a complete surface material, that does not require the same number of plies in every region of the surface. Not only must the orientations be selected in each region, but it is also necessary to decide which plies are discontinued between adjacent regions. Thanks to its declarative nature, Constraint Programming (CP) offers an elegant modeling of the constraints, making it easy for designers to activate or deactivate them as needed. We propose a CP model, implemented in MiniZinc. The performance of this model on synthetic yet realistic instances when solved by different exact solvers, including Mixed Integer Programming (MIP) solvers, demonstrates the superiority of CP over MIP on our MiniZinc model, and over a commercial solution implemented by an industrial partner. It opens up the adoption of CP as an efficient building block of Computer-Aided Design tools for composite structures. By making the model and instances publicly available, we also hope to facilitate the inclusion of this problem in CP solver competitions and stimulate further research in this area.
Cite as

Miguel Antoons, Augustin Delecluse, Samih Zein, and Pierre Schaus. Modeling and Solving a Composite Structure Design Problem with Constraint Programming (Short Paper). In 31st International Conference on Principles and Practice of Constraint Programming (CP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 340, pp. 41:1-41:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{antoons_et_al:LIPIcs.CP.2025.41,
  author =	{Antoons, Miguel and Delecluse, Augustin and Zein, Samih and Schaus, Pierre},
  title =	{{Modeling and Solving a Composite Structure Design Problem with Constraint Programming}},
  booktitle =	{31st International Conference on Principles and Practice of Constraint Programming (CP 2025)},
  pages =	{41:1--41:9},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-380-5},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{340},
  editor =	{de la Banda, Maria Garcia},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2025.41},
  URN =		{urn:nbn:de:0030-drops-239022},
  doi =		{10.4230/LIPIcs.CP.2025.41},
  annote =	{Keywords: Constraint Programming, Composite Structures, Design Rules, MiniZinc}
}
Document
Vision
DOI: 10.4230/TGDK.1.1.9
Trust, Accountability, and Autonomy in Knowledge Graph-Based AI for Self-Determination

Authors: Luis-Daniel Ibáñez, John Domingue, Sabrina Kirrane, Oshani Seneviratne, Aisling Third, and Maria-Esther Vidal

Published in: TGDK, Volume 1, Issue 1 (2023): Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 1, Issue 1

Abstract
Knowledge Graphs (KGs) have emerged as fundamental platforms for powering intelligent decision-making and a wide range of Artificial Intelligence (AI) services across major corporations such as Google, Walmart, and AirBnb. KGs complement Machine Learning (ML) algorithms by providing data context and semantics, thereby enabling further inference and question-answering capabilities. The integration of KGs with neuronal learning (e.g., Large Language Models (LLMs)) is currently a topic of active research, commonly named neuro-symbolic AI. Despite the numerous benefits that can be accomplished with KG-based AI, its growing ubiquity within online services may result in the loss of self-determination for citizens as a fundamental societal issue. The more we rely on these technologies, which are often centralised, the less citizens will be able to determine their own destinies. To counter this threat, AI regulation, such as the European Union (EU) AI Act, is being proposed in certain regions. The regulation sets what technologists need to do, leading to questions concerning How the output of AI systems can be trusted? What is needed to ensure that the data fuelling and the inner workings of these artefacts are transparent? How can AI be made accountable for its decision-making? This paper conceptualises the foundational topics and research pillars to support KG-based AI for self-determination. Drawing upon this conceptual framework, challenges and opportunities for citizen self-determination are illustrated and analysed in a real-world scenario. As a result, we propose a research agenda aimed at accomplishing the recommended objectives.
Cite as

Luis-Daniel Ibáñez, John Domingue, Sabrina Kirrane, Oshani Seneviratne, Aisling Third, and Maria-Esther Vidal. Trust, Accountability, and Autonomy in Knowledge Graph-Based AI for Self-Determination. In Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 1, Issue 1, pp. 9:1-9:32, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{ibanez_et_al:TGDK.1.1.9,
  author =	{Ib\'{a}\~{n}ez, Luis-Daniel and Domingue, John and Kirrane, Sabrina and Seneviratne, Oshani and Third, Aisling and Vidal, Maria-Esther},
  title =	{{Trust, Accountability, and Autonomy in Knowledge Graph-Based AI for Self-Determination}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{9:1--9:32},
  ISSN =	{2942-7517},
  year =	{2023},
  volume =	{1},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.1.1.9},
  URN =		{urn:nbn:de:0030-drops-194839},
  doi =		{10.4230/TGDK.1.1.9},
  annote =	{Keywords: Trust, Accountability, Autonomy, AI, Knowledge Graphs}
}
Document
Invited Paper
DOI: 10.4230/OASIcs.PARMA-DITAM.2023.3
RUST-Encoded Stream Ciphers on a RISC-V Parallel Ultra-Low-Power Processor (Invited Paper)

Authors: Francesco Barchi, Giacomo Pasini, Emanuele Parisi, Giuseppe Tagliavini, Andrea Bartolini, and Andrea Acquaviva

Published in: OASIcs, Volume 107, 14th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 12th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2023)

Abstract
Nowadays, the development of security applications is a relevant topic in the Internet of Things (IoT) and cyber-physical systems (CPS) fields. Different embedded architectures have been adopted in these areas, but the RISC-V parallel ultra-low-power (PULP) architecture stands out as a particularly efficient system. However, it has never been proposed to enable cryptography. In the context of video stream security, stream ciphers enable an efficient solution to ensure data privacy, and the exploitation of the PULP multi-core accelerator cluster paves the way to an efficient implementation of these ciphers. In this paper, we exploit the capability of the PULP architecture coupled with the code safety provided by the RUST programming language to design and implement an efficient stream encryption algorithm. We present a wrapper system between the development libraries of a PULP platform enabling the secure execution of a verified RUST-written implementation of ChaCha20 and AES-CTR, targeting a microdrones based video surveillance system. Experimental tests have resulted in an encryption efficiency of ChaCha20 of 2.3 cycles per Byte (cB), placing the resulting implementation at the state-of-the-art, in direct competition with higher-class architectures like Apple M1 (2.0 cB).
Cite as

Francesco Barchi, Giacomo Pasini, Emanuele Parisi, Giuseppe Tagliavini, Andrea Bartolini, and Andrea Acquaviva. RUST-Encoded Stream Ciphers on a RISC-V Parallel Ultra-Low-Power Processor (Invited Paper). In 14th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 12th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2023). Open Access Series in Informatics (OASIcs), Volume 107, pp. 3:1-3:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{barchi_et_al:OASIcs.PARMA-DITAM.2023.3,
  author =	{Barchi, Francesco and Pasini, Giacomo and Parisi, Emanuele and Tagliavini, Giuseppe and Bartolini, Andrea and Acquaviva, Andrea},
  title =	{{RUST-Encoded Stream Ciphers on a RISC-V Parallel Ultra-Low-Power Processor}},
  booktitle =	{14th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 12th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2023)},
  pages =	{3:1--3:12},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-269-3},
  ISSN =	{2190-6807},
  year =	{2023},
  volume =	{107},
  editor =	{Bispo, Jo\~{a}o and Charles, Henri-Pierre and Cherubin, Stefano and Massari, Giuseppe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.PARMA-DITAM.2023.3},
  URN =		{urn:nbn:de:0030-drops-177232},
  doi =		{10.4230/OASIcs.PARMA-DITAM.2023.3},
  annote =	{Keywords: Parallel Low-Power Embedded Systems, Rust, RISC-V, Stream Cipher}
}
Document
DOI: 10.4230/OASIcs.Gabbrielli.11
Derivation of Constraints from Machine Learning Models and Applications to Security and Privacy

Authors: Moreno Falaschi, Catuscia Palamidessi, and Marco Romanelli

Published in: OASIcs, Volume 86, Recent Developments in the Design and Implementation of Programming Languages (2020)

Abstract
This paper shows how we can combine the power of machine learning with the flexibility of constraints. More specifically, we show how machine learning models can be represented by first-order logic theories, and how to derive these theories. The advantage of this representation is that it can be augmented with additional formulae, representing constraints of some kind on the data domain. For instance, new knowledge, or potential attackers, or fairness desiderata. We consider various kinds of learning algorithms (neural networks, k-nearest-neighbours, decision trees, support vector machines) and for each of them we show how to infer the FOL formulae. Then we focus on one particular application domain, namely the field of security and privacy. The idea is to represent the potentialities and goals of the attacker as a set of constraints, then use a constraint solver (more precisely, a solver modulo theories) to verify the satisfiability. If a solution exists, then it means that an attack is possible, otherwise, the system is safe. We show various examples from different areas of security and privacy; specifically, we consider a side-channel attack on a password checker, a malware attack on smart health systems, and a model-inversion attack on a neural network.
Cite as

Moreno Falaschi, Catuscia Palamidessi, and Marco Romanelli. Derivation of Constraints from Machine Learning Models and Applications to Security and Privacy. In Recent Developments in the Design and Implementation of Programming Languages. Open Access Series in Informatics (OASIcs), Volume 86, pp. 11:1-11:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{falaschi_et_al:OASIcs.Gabbrielli.11,
  author =	{Falaschi, Moreno and Palamidessi, Catuscia and Romanelli, Marco},
  title =	{{Derivation of Constraints from Machine Learning Models and Applications to Security and Privacy}},
  booktitle =	{Recent Developments in the Design and Implementation of Programming Languages},
  pages =	{11:1--11:20},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-171-9},
  ISSN =	{2190-6807},
  year =	{2020},
  volume =	{86},
  editor =	{de Boer, Frank S. and Mauro, Jacopo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Gabbrielli.11},
  URN =		{urn:nbn:de:0030-drops-132338},
  doi =		{10.4230/OASIcs.Gabbrielli.11},
  annote =	{Keywords: Constraints, machine learning, privacy, security}
}
Document
DOI: 10.4230/LITES-v003-i001-a003
Modeling Power Consumption and Temperature in TLM Models

Authors: Matthieu Moy, Claude Helmstetter, Tayeb Bouhadiba, and Florence Maraninchi

Published in: LITES, Volume 3, Issue 1 (2016). Leibniz Transactions on Embedded Systems, Volume 3, Issue 1

Abstract
Many techniques and tools exist to estimate the power consumption and the temperature map of a chip. These tools help the hardware designers develop power efficient chips in the presence of temperature constraints. For this task, the application can be ignored or at least abstracted by some high level scenarios; at this stage, the actual embedded software is generally not available yet.However, after the hardware is defined, the embedded software can still have a significant influence on the power consumption; i.e., two implementations of the same application can consume more or less power. Moreover, the actual software power manager ensuring the temperature constraints, usually by acting dynamically on the voltage and frequency, must itself be validated. Validating such power management policy requires a model of both actuators and sensors, hence a closed-loop simulation of the functional model with a non-functional one.In this paper, we present and compare several tools to simulate the power and thermal behavior of a chip together with its functionality. We explore several levels of abstraction and study the impact on the precision of the analysis.
Cite as

Matthieu Moy, Claude Helmstetter, Tayeb Bouhadiba, and Florence Maraninchi. Modeling Power Consumption and Temperature in TLM Models. In LITES, Volume 3, Issue 1 (2016). Leibniz Transactions on Embedded Systems, Volume 3, Issue 1, pp. 03:1-03:29, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@Article{moy_et_al:LITES-v003-i001-a003,
  author =	{Moy, Matthieu and Helmstetter, Claude and Bouhadiba, Tayeb and Maraninchi, Florence},
  title =	{{Modeling Power Consumption and Temperature in TLM Models}},
  journal =	{Leibniz Transactions on Embedded Systems},
  pages =	{03:1--03:29},
  ISSN =	{2199-2002},
  year =	{2016},
  volume =	{3},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LITES-v003-i001-a003},
  URN =		{urn:nbn:de:0030-drops-192584},
  doi =		{10.4230/LITES-v003-i001-a003},
  annote =	{Keywords: Power consumption, Temperature control, Virtual prototype, SystemC, Transactional modeling}
}
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