The Architectural Space and the Healing Bed: On the Dimension of Privacy in Hospital Architectures

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Online debates provide critical insights into public opinion and societal trends, yet the unstructured nature of these discussions presents significant challenges for analysis. In this paper, we present SAGESSE, a novel argumentation parsing pipeline tailo ...

The advancement of data-driven decision making has become a key priority in political agendas and private sector strategies. However, the growing demand for data and the opacity of data-driven systems raise concerns about the threats to individual privacy ...

Distributed constraint optimization (DCOP) is a framework in which multiple agents with private constraints (or preferences) cooperate to achieve a common goal optimally. DCOPs are applicable in several multi-agent coordination/allocation problems, such as ...

With the pervasive digitalization of modern life, we benefit from efficient access to information and services. Yet, this digitalization poses severe privacy challenges, especially for special-needs individuals. Beyond being a fundamental human right, priv ...

Despite the importance of learning analytics in digital education, there is limited support for researchers in education to generate, access, and share experimental data while complying with ethical and privacy legislation. We propose a set of related tool ...

Decentralized algorithms for stochastic optimization and learning rely on the diffusion of information through repeated local exchanges of intermediate estimates. Such structures are particularly appealing in situations where agents may be hesitant to shar ...

Graph Neural Networks (GNNs) have demonstrated superior performance in learning node representations for various graph inference tasks. However, learning over graph data can raise privacy concerns when nodes represent people or human-related variables that ...

Global pandemics call for large and diverse healthcare data to study various risk factors, treatment options, and disease progression patterns. Despite the enormous efforts of many large data consortium initiatives, scientific community still lacks a secur ...

The current trend towards personalized medicine creates an urgent need to share data among different hospitals and health institutions, which endangers the privacy of the data subjects if not done with the appropriate precautions. Conversely, the frequency ...

A significant number of pictures are posted to social media sites or exchanged through instant messaging and cloud-based sharing services. Most social media services offer a range of access control mechanisms to protect users privacy. As it is not in the b ...

By the end of 2013, the number of internet-connected mobile devices is expected to exceed that of humans. Omnipresent and context-aware, mobile devices enable people to communicate and exchange data anytime and almost anywhere. The myriad of ”digital footp ...

Equipped with state-of-the-art smartphones and mobile devices, today's highly interconnected urban population is increasingly dependent on these gadgets to organize and plan their daily lives. These applications often rely on current (or preferred) locatio ...

This paper presents a concrete and widespread example of situation where a user’s location privacy is unintentionally compromised by others, specifically the location-privacy threat that exists at access points (public hotspots, FON, home routers, etc.) th ...

As large-scale theft of data from corporate servers is becoming increasingly common, it becomes interesting to examine alternatives to the paradigm of centralizing sensitive data into large databases. Instead, one could use cryptography and distributed com ...

Wireless network operators increasingly deploy WiFi hotspots and low-power, low-range base stations in order to satisfy users' growing demands for context-aware services and performance. In addition to providing better service, such capillary infrastructur ...

We provide a formal model for identification schemes. Under this model, we give strong definitions for security and privacy. Our model captures the notion of a powerful adversary who can monitor all communications, trace tags within a limited period of tim ...

The biggest challenge for RFID technology is to provide benefits without threatening the privacy of consumers. Many solutions have been suggested but almost as many ways have been found to break them. An approach by Ohkubo, Suzuki and Kinoshita using an in ...

The Architectural Space and the Healing Bed: On the Dimension of Privacy in Hospital Architectures

Chattez avec Graph Search

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