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arXiv 2023年

作者： Morel, Victor Santos, Cristiana Fredholm, Viktor Thunberg, Adam Chalmers University of Technology Göteborg Sweden Utrecht University Utrecht Netherlands Chalmers University of Technology Department of Computer Science and Engineering Göteborg Sweden

Cookie paywalls allow visitors of a website to access its content only after they make a choice between paying a fee or accept tracking. European Data Protection Authorities (DPAs) recently issued guidelines and decisions on paywalls lawfulness, but it is yet unknown whether websites comply with them. We study in this paper the prevalence of cookie paywalls on the top one million websites using an automatic crawler. We identify 431 cookie paywalls, all using the Transparency and Consent Framework (TCF). We then analyse the data these paywalls communicate through the TCF, and in particular, the legal grounds and the purposes used to collect personal data. We observe that cookie paywalls extensively rely on legitimate interest legal basis systematically conflated with consent. We also observe a lack of correlation between the presence of paywalls and legal decisions or guidelines by DPAs. © 2023, CC BY.

关键词： Websites

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Delegating Responsibilities to Intelligent Autonomous Systems: Challenges and Benefits

arXiv

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arXiv 2024年

作者： Dodig-Crnkovic, Gordana Basti, Gianfranco Holstein, Tobias Division of Computer Science and Software Engineering Mälardalen University Västerås Sweden Department of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden Pontifical Lateran University Vatican City Italy

MSC Codes K. Computing Milieux K.4 computerS AND SOCIETY K.4.1 Public Policy Issues. EthicsAs AI systems increasingly operate with autonomy and adaptability, the traditional boundaries of moral responsibility in techno-social systems are being challenged. This paper explores the evolving discourse on the delegation of responsibilities to intelligent autonomous agents and the ethical implications of such practices. Synthesizing recent developments in AI ethics, including concepts of distributed responsibility and ethical AI by design, the paper proposes a functionalist perspective as a framework. This perspective views moral responsibility not as an individual trait but as a role within a socio-technical system, distributed among human and artificial agents. As an example of 'AI ethical by design,' we present Basti and Vitiello's implementation. They suggest that AI can act as artificial moral agents by learning ethical guidelines and using Deontic Higher-Order Logic to assess decisions ethically. Motivated by the possible speed and scale beyond human supervision and ethical implications, the paper argues for 'AI ethical by design', while acknowledging the distributed, shared, and dynamic nature of responsibility. This functionalist approach offers a practical framework for navigating the complexities of AI ethics in a rapidly evolving technological landscape. © 2024, CC BY-NC-ND.

关键词： Public policy

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Fenics: A Modular Framework for Security Evaluation in Decentralized Federated Learning 25

Fenics: A Modular Framework for Security Evaluation in Decen...

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Proceedings of the 19th ACM International Conference on Distributed and Event-based Systems

作者： Shubham Saha Sifat Nawrin Nova Romaric Duvignau Carla Fabiana Chiasserini Department of Computer Science and Engineering Chalmers University of Technology Göteborg Västra Götaland Sweden Department of Computer Science and Engineering Chalmers University of Technology Göteborg Västra Götaland Sweden and Department of Electronics and Telecommunications Politecnico di Torino Turin Metropolitan City of Turin Italy

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Depth Perspective-Aware Multiple Object Tracking

SSRN

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SSRN 2023年

作者： Quach, Kha Gia Le, Huu Nguyen, Pha Duong, Chi Nhan Bui, Tien Dai Luu, Khoa Computer Science and Software Engineering Department Concordia University MontrealQC Canada Department of Electrical Engineering Chalmers University of Technology Sweden Computer Science and Computer Engineering University of Arkansas United States

This paper aims to tackle Multiple Object Tracking (MOT), an important problem in computer vision but remains challenging due to many practical issues, especially occlusions. Indeed, we propose a new real-time Depth Perspectiveaware Multiple Object Tracking (DP-MOT) approach1 to tackle the occlusion problem in MOT. A simple yet efficient Subject-Ordered Depth Estimation (SODE) is first proposed to automatically order the depth positions of detected subjects in a 2D scene in an unsupervised manner. Using the output from SODE, a new Active pseudo-3D Kalman filter, a simple but e↵ective extension of Kalman filter with dynamic control variables, is then proposed to dynamically update the movement of objects. In addition, a new high-order association approach is presented in the data association step to incorporate first-order and second-order relationships between the detected objects. The proposed approach consistently achieves state-of-the-art performance compared to recent MOT methods on standard MOT benchmarks. © 2023, The Authors. All rights reserved.

关键词： Kalman filters

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Modeling and Security Verification of State-Based Smart Contracts

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IFAC-PapersOnLine 2022年第28期55卷 356-362页

作者： Sahar Mohajerani Wolfgang Ahrendt Martin Fabian Department of Electrical Engineering Department of Computer Science and Engineering Chalmers University of Technology Göteborg Sweden

Smart contracts are programs that are stored on a blockchain ledger with code immutable after deployment. Thus, verifying the correct behavior of smart contracts before deployment is vital. This paper demonstrates how a security vulnerability verification in a casino smart contract can be transformed to non-blocking verification. To this end, the contract is first modeled as interacting extended finite state machines (EFSM), with one EFSM for each function. Modeling the security vulnerability as a condition in the EFSM system, non-blocking verification reveals the system to be blocking. Investigating the counterexample produced by the verification shows that a transfer that is refused by its receiver may block the casino so that all remaining funds are forever locked into the contract, thus revealing a severe vulnerability. It is then demonstrated how the same technique can show the absence of this vulnerability, by verifying that the EFSM model of an improved casino contract is indeed non-blocking.

关键词： Extended finite state machine smart contract security verification nonblocking

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Low-Temperature (Cryogenic) Transport in Gate-All-Around (GAA) Silicon Nanowire Field-Effect Transistor

Low-Temperature (Cryogenic) Transport in Gate-All-Around (GA...

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IEEE Conference on Nanotechnology

作者： Amit Verma Reza Nekovei Daryoush Shiri Electrical Engineering & Computer Science at Texas A&M University-Kingsville Kingsville TX USA Quantum Technology Laboratory Chalmers University of Technology Gothenburg Sweden

ISBN: (数字)9798350386240

ISBN: (纸本)9798350386257

This work explores the temperature dependency of the performance of an ultra-thin silicon nanowire (SiNW) gate-all-around field-effect transistor (GAA-FET). The nanowire is assumed coaxially aligned with an ideal cylindrical gate-all-around device. The nanowire is [110] axially aligned with a diameter of 1.3 nm. Electron transport is modeled using Ensemble Monte Carlo (EMC) simulations coupled self-consistently with an electrostatic solver that solves Gauss Law in integral form. Electron scattering mechanisms include bulk silicon longitudinal acoustic and optical phonons. A wide range of temperatures is considered - from 4 K to 150 K to understand the effects of temperature on device performance under both steady-state and device switching conditions. The device is seen to work appropriately for the temperature range considered. The differences in device currents for different temperatures is attributed to the differences in the electron scattering rates for the various temperatures.

关键词： Performance evaluation Temperature distribution Optical switches Scattering Logic gates Silicon Steady-state

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Impact of Time-Varying Traffic Type on the Performance of Multilayer Networks

Impact of Time-Varying Traffic Type on the Performance of Mu...

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International Conference on Network and Service Management

作者： Aleksandra Knapińska Piotr Lechowicz Krzysztof Walkowiak Department of Systems and Computer Networks Wrocław University of Science and Technology Wrocław Poland Department of Electrical Engineering Chalmers University of Technology Gothenburg Sweden

ISBN: (数字)9783903176669

ISBN: (纸本)9798331505158

Traffic in backbone networks is characterized by strong seasonality, with clear patterns visible in various services and applications based on their usage throughout the day. Data-driven networks can learn these patterns to manage resources more efficiently as they become increasingly saturated. In this paper, we explore the benefits of traffic prediction and grooming across different traffic patterns. To achieve this, we simulate network operations using uniform sets of time-varying connection requests, where all demands in a simulation share the same traffic pattern related to a specific network-based service or application. Our goal is to thoroughly evaluate the robustness of the proposed techniques across diverse scenarios. The results will facilitate the design of future application-aware algorithms for the most efficient handling of each traffic pattern.

关键词： Measurement Network topology Traffic control Nonhomogeneous media Prediction algorithms Robustness Topology Optimization

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Neural Field Movement Primitives for Joint Modelling of Scenes and Motions

Neural Field Movement Primitives for Joint Modelling of Scen...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Ahmet Tekden Marc Peter Deisenroth Yasemin Bekiroglu Electrical Engineering Chalmers University of Technology Sweden Computer Science University College London U.K.

This paper presents a novel Learning from Demonstration (LfD) method that uses neural fields to learn new skills efficiently and accurately. It achieves this by utilizing a shared embedding to learn both scene and motion representations in a generative way. Our method smoothly maps each expert demonstration to a scene-motion embedding and learns to model them without requiring hand-crafted task parameters or large datasets. It achieves data efficiency by enforcing scene and motion generation to be smooth with respect to changes in the embedding space. At inference time, our method can retrieve scene-motion embeddings using test time optimization, and generate precise motion trajectories for novel scenes. The proposed method is versatile and can employ images, 3D shapes, and any other scene representations that can be modeled using neural fields. Additionally, it can generate both end-effector positions and joint angle-based trajectories. Our method is evaluated on tasks that require accurate motion trajectory generation, where the underlying task parametrization is based on object positions and geometric scene changes. Experimental results demonstrate that the proposed method outperforms the baseline approaches and generalizes to novel scenes. Furthermore, in real-world experiments, we show that our method can successfully model multi-valued trajectories, it is robust to the distractor objects introduced at inference time, and it can generate 6D motions.

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Precise Asymptotic Analysis of Deep Random Feature Models

arXiv

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arXiv 2023年

作者： Bosch, David Panahi, Ashkan Hassibi, Babak Department of Data Science and AI Computer Science and Engineering Chalmers University of Technology Sweden Department of Electrical Engineering California Institute of Technology United States

We provide exact asymptotic expressions for the performance of regression by an L−layer deep random feature (RF) model, where the input is mapped through multiple random embedding and non-linear activation functions. For this purpose, we establish two key steps: First, we prove a novel universality result for RF models and deterministic data, by which we demonstrate that a deep random feature model is equivalent to a deep linear Gaussian model that matches it in the first and second moments, at each layer. Second, we make use of the convex Gaussian Min-Max theorem multiple times to obtain the exact behavior of deep RF models. We further characterize the variation of the eigendistribution in different layers of the equivalent Gaussian model, demonstrating that depth has a tangible effect on model performance despite the fact that only the last layer of the model is being trained. Copyright © 2023, The Authors. All rights reserved.

关键词： Asymptotic analysis

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Scenario-based trajectory generation and density estimation towards risk analysis of autonomous vehicles

TechRxiv

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TechRxiv 2023年

作者： Johansson, Edvin Sönnergaard, Matilda Selpi Rahrovani, Sadegh Basimfar, Parsia Department of Computer Science and Engineering Chalmers University of Technology Sweden Autonomous Drive Department VolvoCars Sweden

A large amount of testing is needed to determine when autonomous vehicles are sufficiently safe. To achieve this goal, test cases should be representative of real-world driving but also designed to provide sufficient coverage of both frequent and rare events. This is a crucial step in finding potential high-consequence events, failure borders of the Autonomous Driving (AD) function and accurate estimation of the corresponding residual risks. In this paper, we propose a new method to adapt generative models to generate vehicle trajectories that are representative of the ones collected from the real world. The method uses Non-Uniform Rational B-Splines (NURBS) combined with normalizing flows to build a statistical scenario model. The method allows us to estimate a joint probability density that can be used to evaluate the likelihood of different trajectory occurrences. We demonstrate the method for statistical modeling on the cut-in traffic scenario and we give an example of how the estimated joint probability distribution can be used to assess the risk (trajectory occurrence probability and criticality) for different test cases. The results can be used for accelerated testing purposes, where the aim is to sample the rare tests more frequently, but can also be used to calculate the failure probability of AD functions. © 2023, CC BY.

关键词： Autonomous vehicles

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