Notifications are a core feature of mobile phones. They inform users about a variety of events. Users may take immediate action or ignore them depending on the importance of a notification as well as their current context. The nature of notifications is manifold, applications use them both sparsely and frequently. In this paper we present the first large-scale analysis of mobile notifications with a focus on users' subjective perceptions. We derive a holistic picture of notifications on mobile phones by collecting close to 200 million notifications from more than 40,000 users. Using a data-driven approach, we break down what users like and dislike about notifications. Our results reveal differences in importance of notifications and how users value notifications from messaging apps as well as notifications that include information about people and events. Based on these results we derive a number of findings about the nature of notifications and guidelines to effectively use them.

Social media are massive marketplaces where ideas and news compete for our attention [1]. Previous studies have shown that quality is not a necessary condition for online virality [2] and that knowledge about peer choices can distort the relationship between quality and popularity [3]. However, these results do not explain the viral spread of low-quality information, such as the digital misinformation that threatens our democracy [4]. We investigate quality discrimination in a stylized model of online social network, where individual agents prefer quality information, but have behavioral limitations in managing a heavy flow of information. We measure the relationship between the quality of an idea and its likelihood to become prevalent at the system level. We find that both information overload and limited attention contribute to a degradation in the market's discriminative power. A good tradeoff between discriminative power and diversity of information is possible according to the model. However, calibration with empirical data characterizing information load and finite attention in real social media reveals a weak correlation between quality and popularity of information. In these realistic conditions, the model predicts that high-quality information has little advantage over low-quality information. * These two authors contributed equally to this work

The present study develops a stiffness reduction based model to characterize fatigue damage in unidirectional 0° and 90° plies and (0°/90°) laminates of fiber-reinforced polymer (FRP) composites. The proposed damage model has been developed, based on (i) cracking mechanism and damage progress in matrix (Region I), matrix-fiber interface (Region II) and fiber (Region III) and (ii) corresponding stiffness reduction of unidirectional composite laminates as the number of cycles progresses. Fatigue damage of (0/90)°composite systems was obtained by integrating damage values and occurred in composite plies of 0 and 90° under fatigue cycles. The predicted fatigue damage results based on the proposed damage model were found to be in good agreement for both unidirectional and (0/90) FRP composites, as they were compared with experimental data for these materials, tested at various cyclic stress levels, stress ratios, and off-axis angles reported in the literature.

Falling hardware prices and ever more displays being connected to the Internet will lead to large public display networks, potentially forming a novel communication medium. We envision that such networks are not restricted to display owners and advertisers anymore, but allow also passersby (e.g., customers) to exchange content, similar to traditional public notice areas, such as bulletin boards. In this context it is crucial to understand emerging practices and provide easy and straight forward interaction techniques to be used for creating and exchanging content. In this paper, we present Digifieds, a digital public notice area we built to investigate and compare possible interaction techniques. Based on a lab study we show that using direct touch at the display as well as using the mobile phone as a complementing interaction technology are most suitable. Direct touch at the display closely resembles the interaction known from classic bulletin boards and provides the highest usability. Mobile phones preserve the users' privacy as they exchange (sensitive) data with the display and at the same time allow content to be created on-thego or to be retrieved.

The present study develops a stiffness reduction-based model to characterize fatigue damage in unidirectional 0˚and θ°plies and (0/θ) laminates of fiber-reinforced polymer (FRP) composites. The proposed damage model was constructed based on (i) cracking mechanism and damage progress in matrix (Region I), matrix-fiber interface (Region II) and fiber (Region III) and (ii) corresponding stiffness reduction of unidirectional composite laminates as the number of cycles progresses. The proposed model enabled damage assessment of FRP (0/θ) composite laminates by integrating the fatigue damage values of 0˚and θ°plies. A weighting factor η was introduced to partition the efficiency of load carrying plies of 0°and θ°in the (0/θ) composite lamina. The fatigue damage curves of unidirectional FRP composite samples with off-axis angles of 0˚, 30˚, 45˚, and 90˚and composite laminate systems of (0˚/30˚), (0˚/45˚) and (0˚/90˚) predicted based on the proposed damage model were found in good agreement with experimental data reported at various cyclic stress levels and stress ratios in the literature.

a) Aluminum (b) Glass (c) MDF (d) Tile Figure 1: We explored the thermal reflectivity of different surfaces for interaction with projected surfaces. The thermal reflectivity allows to sense users that perform in-air gestures inside and outside the thermal camera's direct field-of-view. Four of the eight surfaces we analyzed and which can be found in normal office environments are presented above. ABSTRACTThermal cameras have recently drawn the attention of HCI researchers as a new sensory system enabling novel interactive systems. They are robust to illumination changes and make it easy to separate human bodies from the image background. Far-infrared radiation, however, has another characteristic that distinguishes thermal cameras from their RGB or depth counterparts, namely thermal reflection. Common surfaces reflect thermal radiation differently than visual light and can be perfect thermal mirrors. In this paper, we show that through thermal reflection, thermal cameras can sense the space beyond their direct field-of-view. A thermal camera can sense areas besides and even behind its field-of-view through thermal reflection. We investigate how thermal reflection can increase the interaction space of projected surfaces using camera-projection systems. We moreover discuss the reflection characteristics of common surfaces in our vicinity in both the visual and thermal radiation bands. Using a proof-of-concept prototype, we demonstrate the increased interaction space for hand-held camera-projection system. Furthermore, we depict a number of promising application examples that can benefit from the thermal reflection characteristics of surfaces.

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People spend a significant amount of time in their cars (US: 86 minutes/day, Europe: 43 minutes/day) while commuting, shopping, or traveling. Hence, the variety of entertainment in the car increases, and many vehicles are already equipped with displays, allowing for watching news, videos, accessing the Internet, or playing games. At the same time, the urbanization caused a massive increase of traffic volume, which led to people spending an ever-increasing amount of their time in front of red traffic lights. An observation of the prevailing forms of entertainment in the car reveals that content such as text, videos, or games are often a mere adaptation of content produced for television, public displays, PCs, or mobile phones and do not adapt to the situation in the car. In this paper we report on a web survey assessing which forms of entertainment and which types of content are considered to be useful for in-car entertainment by drivers. We then introduce an algorithm, which is capable of learning standing times in front of traffic lights based on GPS information only. This, on one hand, allows for providing content of appropriate length, on the other hand, for directing the attention of the driver back to-wards the street at the right time. Finally, we present a prototype implementation and a qualitative evaluation.