Sustainability and Ethicality are Peripheral to Students’ Software Design

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We study the privatization of distributed learning and optimization strategies. We focus on differential privacy schemes and study their effect on performance. We show that the popular additive random perturbation scheme degrades performance because it is ...

Humanitarian aid-distribution programs help bring physical goods to people in need. Traditional paper-based solutions to support aid distribution do not scale to large populations and are hard to secure. Existing digital solutions solve these issues, at th ...

Exploring a wide range of relevant design options from the outset is crucial for every sound conceptual design process. Optimization techniques are generally employed to generate well-performing structural design options. However, focusing only on performa ...

Smartphones present many interesting opportunities for survey research, particularly through the use of mobile data collection applications (apps). There is still much to learn, however, about how to integrate apps in general population surveys. Recent stu ...

Although encryption hides the content of communications from third parties, metadata, i.e., the information attached to the content (such as the size or timing of communication) can be a rich source of details and context. In this dissertation, we demonstr ...

Despite the importance of using artifacts during the design thinking process, there is a limited understanding of the influence of tangibles with lower perceptual richness on design thinking skills within educational settings. It is speculated that tangibl ...

Background: Increasingly, hospitals and research institutes are developing technical solutions for sharing patient data in a privacy preserving manner. Two of these technical solutions are homomorphic encryption and distributed ledger technology. Homomorph ...

The transition towards a human-centered indoor climate is beneficial from occupants’ thermal comfort and from an energy reduction perspective. However, achieving this goal requires the knowledge of the thermal state of individuals at the level of body part ...

Recommenders are central in many applications today. The most effective recommendation schemes, such as those based on collaborative filtering (CF), exploit similarities between user profiles to make recommendations, but potentially expose private data. Fe ...

Strategic information is valuable either by remaining private (for instance if it is sensitive) or, on the other hand, by being used publicly to increase some utility. These two objectives are antagonistic and leaking this information by taking full advant ...

Several optimization scenarios involve multiple agents that desire to protect the privacy of their preferences. There are distributed algorithms for constraint optimization that provide improved privacy protection through secure multiparty computation. How ...

Sustainability and Ethicality are Peripheral to Students’ Software Design

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Enforcing Privacy in Distributed Learning With Performance Guarantees

Not Yet Another Digital ID: Privacy-Preserving Humanitarian Aid Distribution

Computational Conceptual Design – Typological Exploration Of Spatial Truss Systems Through Optimization

Data Privacy Concerns as a Source of Resistance to Complete Mobile Data Collection Tasks Via a Smartphone App

Protecting privacy through metadata analysis

What Role Do Tangibles Play in Fostering Design Thinking Skills? An Exploratory Study

Health data privacy through homomorphic encryption and distributed ledger computing: an ethical-legal qualitative expert assessment study

Toward contactless human thermal monitoring: A framework for Machine Learning-based human thermo-physiology modeling augmented with computer vision

TEE-based decentralized recommender systems: The raw data sharing redemption

Utility/privacy trade-off as regularized optimal transport

Differentially Private Multi-Agent Constraint Optimization