Hci for emergencies

Klann, Markus; Malizia, Alessio; Chittaro, Luca; Cuevas, Ignacio Aedo; Levialdi, S.

doi:10.1145/1358628.1358963

Cited by 9 publications

(3 citation statements)

References 9 publications

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“…Network science, digital human modeling combined with user and experience-centered design in HCI offers significant advancement in developing digital interventions for global disease epidemics. For example, network science and computation could be integrated with the work in HCI for emergencies, which advocates with studying and understanding users and engaging users in the design process as well as evaluating designs in a realistic way could influence design and testing of new HCI design principles within the context of emergencies (Klann et al, 2008), designing context-aware HCI for collaborative emergency management (Flentge et al, 2008), developing digital technologies for supporting, and encouraging public participation of communications during crisis (Landgren and Nulden, 2007;Palen and Liu, 2007).…”

Section: Social Network Hci and Computation For Global Disease Epimentioning

confidence: 99%

Disaster Network Science: Research and Applications

Hossain

Feng

2016

Front. Commun.

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Section: Social Network Hci and Computation For Global Disease Epimentioning

confidence: 99%

Disaster Network Science: Research and Applications

Hossain

Feng

2016

Front. Commun.

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“…We design our approach from the simulation monitoring point of view. Its objective is to increase the situational awareness [5] of indoor emergency simulation. However, since the representation have to handle information from multiple perspectives.…”

Section: Introductionmentioning

confidence: 99%

Increasing Situational Awareness of Indoor Emergency Simulation Using Multilayered Ontology-Based Floor Plan Representation

Damrongrat

Kanai

Ikeda

2013

Human Interface and the Management of Information. Information and Interaction for Health, Safety, Mobility and Complex Environ

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Indoor emergency is a challenging research domain. It has to deal with dynamic situations, unexpected consequence of incidents, many entities involved such as human and building elements. Emergency simulation cannot avoid these various and dynamic information. This research proposes a multilayer of ontology-based floor plan representation in order to describe how the simulation goes with these complexities. Our approach uses ontology to model a floor plan into various perspectives e.g., AccessibilityPerspective, ControllingPerspective. Each perspective is used to support different purposes. For example, AccessibilityPerspective is used for way finding and navigation. These perspectives are represented by multilayer of graphs, one perspective per one graph. The research objective is to increase users' situational awareness in the indoor emergency simulation. The are two main advantages in this model. First is a capability to handle dynamic situations and consequences of emergency using ontology and inference rules. Second is the use of multilayered graphbased representation in describing the floor plan's situation in various perspectives and overcoming information overload. With these advantages, users can notice how the simulation goes, what and where have been changed in a glance.

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“…Due to the fact that emergencies are usually complicated by difficult physical situations, special attention has to be given to the design of information technology for emergencies [24]. A key issue of any such information system is the acquisition of textual information.…”

Section: Introductionmentioning

confidence: 99%

On Using Entropy for Enhancing Handwriting Preprocessing

Holzinger

Stocker

Peischl³

et al. 2012

Entropy

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Abstract:Handwriting is an important modality for Human-Computer Interaction. For medical professionals, handwriting is (still) the preferred natural method of documentation. Handwriting recognition has long been a primary research area in Computer Science. With the tremendous ubiquity of smartphones, along with the renaissance of the stylus, handwriting recognition has become a new impetus. However, recognition rates are still not 100% perfect, and researchers still are constantly improving handwriting algorithms. In this paper we evaluate the performance of entropy based slant-and skew-correction, and compare the results to other methods. We selected 3700 words of 23 writers out of the Unipen-ICROW-03 benchmark set, which we annotated with their associated error angles by hand. Our results show that the entropy-based slant correction method outperforms a window based approach with an average precision of ±6.02• for the entropy-based method, compared with the ±7.85• for the alternative. On the other hand, the entropy-based skew correction yields a lower average precision of ±2.86• , compared with the average precision of ±2.13• for the alternative LSM based approach.

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Hci for emergencies

Cited by 9 publications

References 9 publications

Disaster Network Science: Research and Applications

Disaster Network Science: Research and Applications

Increasing Situational Awareness of Indoor Emergency Simulation Using Multilayered Ontology-Based Floor Plan Representation

On Using Entropy for Enhancing Handwriting Preprocessing

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