Helsinki Institute for Information Technology

About: Helsinki Institute for Information Technology is a facility organization based out in Espoo, Finland. It is known for research contribution in the topics: Population & Bayesian network. The organization has 630 authors who have published 1962 publications receiving 63426 citations.

Interaction in 4-second bursts: the fragmented nature of attentional resources in mobile HCI

Abstract: When on the move, cognitive resources are reserved partly for passively monitoring and reacting to contexts and events, and partly for actively constructing them. The Re-source Competition Framework (RCF), building on the Multiple Resources Theory, explains how psychosocial tasks typical of mobile situations compete for cognitive resources and then suggests that this leads to the depletion of resources for task interaction and eventually results in the breakdown of fluent interaction. RCF predictions were tested in a semi-naturalistic field study measuring attention during the performance of assigned Web search tasks on mobile phone while moving through nine varied but typical urban situations. Notably, we discovered up to eight-fold differentials between micro-level measurements of atten-tional resource fragmentation, for example from spans of over 16 seconds in a laboratory condition dropping to bursts of just a few seconds in difficult mobile situations. By cali-brating perceptual sampling, reducing resources from tasks of secondary importance, and resisting the impulse to switch tasks before finalization, participants compensated for the resource depletion. The findings are compared to previous studies in office contexts. The work is valuable in many areas of HCI dealing with mobility.

It's Mine, Don't Touch!: interactions at a large multi-touch display in a city centre

Abstract: We present data from detailed observations of CityWall, a large multi-touch display installed in a central location in Helsinki, Finland. During eight days of installation, 1199 persons interacted with the system in various social configurations. Videos of these encounters were examined qualitatively as well as quantitatively based on human coding of events. The data convey phenomena that arise uniquely in public use: crowding, massively parallel interaction, teamwork, games, negotiations of transitions and handovers, conflict management, gestures and overt remarks to co-present people, and "marking" the display for others. We analyze how public availability is achieved through social learning and negotiation, why interaction becomes performative and, finally, how the display restructures the public space. The multi-touch feature, gesture-based interaction, and the physical display size contributed differentially to these uses. Our findings on the social organization of the use of public displays can be useful for designing such systems for urban environments.

GANSpace: Discovering Interpretable GAN Controls

Abstract: This paper describes a simple technique to analyze Generative Adversarial Networks (GANs) and create interpretable controls for image synthesis, such as change of viewpoint, aging, lighting, and time of day. We identify important latent directions based on Principal Components Analysis (PCA) applied either in latent space or feature space. Then, we show that a large number of interpretable controls can be defined by layer-wise perturbation along the principal directions. Moreover, we show that BigGAN can be controlled with layer-wise inputs in a StyleGAN-like manner. We show results on different GANs trained on various datasets, and demonstrate good qualitative matches to edit directions found through earlier supervised approaches.

Theory and Practice of Bloom Filters for Distributed Systems

Abstract: Many network solutions and overlay networks utilize probabilistic techniques to reduce information processing and networking costs. This survey article presents a number of frequently used and useful probabilistic techniques. Bloom filters and their variants are of prime importance, and they are heavily used in various distributed systems. This has been reflected in recent research and many new algorithms have been proposed for distributed systems that are either directly or indirectly based on Bloom filters. In this survey, we give an overview of the basic and advanced techniques, reviewing over 20 variants and discussing their application in distributed systems, in particular for caching, peer-to-peer systems, routing and forwarding, and measurement data summarization.

SynergyFinder 2.0: visual analytics of multi-drug combination synergies.

Abstract: SynergyFinder (https://synergyfinder.fimm.fi) is a stand-alone web-application for interactive analysis and visualization of drug combination screening data. Since its first release in 2017, SynergyFinder has become a widely used web-tool both for the discovery of novel synergistic drug combinations in pre-clinical model systems (e.g. cell lines or primary patient-derived cells), and for better understanding of mechanisms of combination treatment efficacy or resistance. Here, we describe the latest version of SynergyFinder (release 2.0), which has extensively been upgraded through the addition of novel features supporting especially higher-order combination data analytics and exploratory visualization of multi-drug synergy patterns, along with automated outlier detection procedure, extended curve-fitting functionality and statistical analysis of replicate measurements. A number of additional improvements were also implemented based on the user requests, including new visualization and export options, updated user interface, as well as enhanced stability and performance of the web-tool. With these improvements, SynergyFinder 2.0 is expected to greatly extend its potential applications in various areas of multi-drug combinatorial screening and precision medicine.