Fetishizing Food in Digital Age: #foodporn Around the World

International AAAI Conference on Web and Social Media (ICWSM), 2016International AAAI Conference on Web and Social Media (ICWSM), 2016What food is so good as to be considered pornographic? Worldwide, the popular #foodporn hashtag has been used to share appetizing pictures of peoples' favorite culinary experiences. But social scientists ask whether #foodporn promotes an unhealthy relationship with food, as pornography would contribute to an unrealistic view of sexuality. In this study, we examine nearly 10 million Instagram posts by 1.7 million users worldwide. An overwhelming (and uniform across the nations) obsession with chocolate and cake shows the domination of sugary dessert over local cuisines. Yet, we find encouraging traits in the association of emotion and health-related topics with #foodporn, suggesting food can serve as motivation for a healthy lifestyle. Social approval also favors the healthy posts, with users posting with healthy hashtags having an average of 1,000 more followers than those with unhealthy ones. Finally, we perform a demographic analysis which shows nation-wide trends of behavior, such as a strong relationship (r=0.51) between the GDP per capita and the attention to healthiness of their favorite food. Our results expose a new facet of food "pornography", revealing potential avenues for utilizing this precarious notion for promoting healthy lifestyles

Beyond Node Degree: Evaluating AS Topology Models

This is the accepted version of 'Beyond Node Degree: Evaluating AS Topology Models', archived originally at arXiv:0807.2023v1 [cs.NI] 13 July 2008.Many models have been proposed to generate Internet Autonomous System (AS) topologies, most of which make structural assumptions about the AS graph. In this paper we compare AS topology generation models with several observed AS topologies. In contrast to most previous works, we avoid making assumptions about which topological properties are important to characterize the AS topology. Our analysis shows that, although matching degree-based properties, the existing AS topology generation models fail to capture the complexity of the local interconnection structure between ASs. Furthermore, we use BGP data from multiple vantage points to show that additional measurement locations significantly affect local structure properties, such as clustering and node centrality. Degree-based properties, however, are not notably affected by additional measurements locations. These observations are particularly valid in the core. The shortcomings of AS topology generation models stems from an underestimation of the complexity of the connectivity in the core caused by inappropriate use of BGP data

The category {\bf Rel}({\bf Nom})

The category ${\rm Rel}(\mathcal{C})$ may be formed for any category $\mathcal{C}$ with finite limits using the same objects as $\mathcal{C}$ but whose morphisms from $X$ to $Y$ are binary relations in $\mathcal{C}$, that is, subobjects of $X\times Y$. In this paper, concerning the topos ${\bf Nom}$, we study the category ${\bf Rel}({\bf Nom})$. In this category, we define and investigate certain morphisms, such as deterministic morphisms. Then, stochastic mappings between nominal sets are defined by exploiting the underlying relation of functions between nominal sets. This allows one to reinterpret concepts and earlier results in terms of morphisms

PRISM: Privacy Preserving Healthcare Internet of Things Security Management

Consumer healthcare Internet of Things (IoT) devices are gaining popularity in our homes and hospitals. These devices provide continuous monitoring at a low cost and can be used to augment high-precision medical equipment. However, major challenges remain in applying pre-Trained global models for anomaly detection on smart health monitoring, for a diverse set of individuals that they provide care for. In this paper, we propose PRISM, an edge-based system for experimenting with in-home smart healthcare devices. We develop a rigorous methodology that relies on automated IoT experimentation. We use a rich real-world dataset from in-home patient monitoring from 44 households of People Living With Dementia (PLWD) over two years. Our results indicate that anomalies can be identified with accuracy up to 99% and mean training times as low as 0.88 seconds. While all models achieve high accuracy when trained on the same patient, their accuracy degrades when evaluated on different patients

Anatomy of the Third-Party Web Tracking Ecosystem

The presence of third-party tracking on websites has become customary. However, our understanding of the third-party ecosystem is still very rudimentary. We examine third-party trackers from a geographical perspective, observing the third-party tracking ecosystem from 29 countries across the globe. When examining the data by region (North America, South America, Europe, East Asia, Middle East, and Oceania), we observe significant geographical variation between regions and countries within regions. We find trackers that focus on specific regions and countries, and some that are hosted in countries outside their expected target tracking domain. Given the differences in regulatory regimes between jurisdictions, we believe this analysis sheds light on the geographical properties of this ecosystem and on the problems that these may pose to our ability to track and manage the different data silos that now store personal data about us all

Relationship between flash points of some binary base oils and their constituent oils

Miscellaneous binary blends containing solvent neutral-150 (SN-150), solvent neutral-500 (SN-500), Bright Stock-150 (BS-150), polyalphaolephin-6 (PAO-6), PAO-100, a processed low sulfur waxy material, and polyisobutene-600 (PIB-600) were prepared and their corresponding flash point (FP) were measured. By using the measured FP data, the plots of FP vs. weight percentage of minor component were drawn and the equations due to each plot were derived. Except PIB-600 containing mixtures, linear relation between FP of blends and weight percentage of constituents has been observed. Also the obtained data indicate that except PIB-600 containing blends the FP of such mixtures can be calculated from the summation of "FP × weight ratio" of each component. In the case of PIB-600 containing blends, nonlinear and decreasing, nonlinear and increasing were observed as well as constant trends of FP vs. weight percentage of minor component. The observations have been interpreted based on the composition, molecular weight, and interactions of the constituents of the base oils. KEY WORDS: Flash point, Binary lubricants, Tribotests, Mineral oils, Synthetic oils, Semisynthetic oils Bull. Chem. Soc. Ethiop. 2015, 29(2), 229-237DOI: http://dx.doi.org/10.4314/bcse.v29i2.