Catching the Viewer\u27s Eye: Examining Exploration and Exploitation Strategies in the Live Streaming Market

Live streaming has become an important feature on social media platforms like Facebook and Instagram. More and more entrepreneurs (content creators) are competing in live streaming platforms like Twitch to maximize the attention they receive from consumers (viewers). In this competitive landscape, it is crucial for entrepreneurs to develop and provide new compelling content that can maximize the consumers’ attention and aid the discovery of their content. We adopt an exploration-exploitation framework and assess the four strategies these new entrepreneurs could use to attract viewership and position themselves on Twitch: exploration, exploitation, learning from viewers, and their neighbor streamers. We combined the natural language processing techniques with theory-driven measures to accomplish this. Using our proposed measures, we estimate the utility of consumers from these different strategies using the discrete choice demand model

Analysis of Transverse Mixing Using Natural Tracers Continuously Introduced from Tributaries

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchive

Taxonomy and Evaluations of Low-Power Listening Protocols for Machine-to-Machine Networks

Even though a lot of research has made significant contributions to advances in sensor networks, sensor network protocols, which have different characteristics according to the target application, might confuse machine-to-machine (M2M) network designers when they choose the protocol most suitable for their specific applications. Therefore, this paper provides a well-defined taxonomy of low-power listening protocols by examining in detail the existing low-power sensor network protocols and evaluation results. It will also be very useful for helping M2M designers understand specific features of low-power media access control protocols as they design new M2M networks

Near-Infrared Photometry of the Star Clusters in the Dwarf Irregular Galaxy IC 5152

We present JHK-band near-infrared photometry of star clusters in the dwarf irregular galaxy IC 5152. After excluding possible foreground stars, a number of candidate star clusters are identified in the near-infrared images of IC 5152, which include young populations. Especially, five young star clusters are identified in the (J-H, H-K) two color diagram and the total extinction values toward these clusters are estimated to be A_V =2 - 6 from the comparison with the theoretical values given by the Leitherer et al. (1999)'s theoretical star cluster model.Comment: Accepted by the Journal of the Korean Astronomical Society, 2006 December issue (Vol. 39, No. 4

Improving Neural Radiance Field using Near-Surface Sampling with Point Cloud Generation

Neural radiance field (NeRF) is an emerging view synthesis method that samples points in a three-dimensional (3D) space and estimates their existence and color probabilities. The disadvantage of NeRF is that it requires a long training time since it samples many 3D points. In addition, if one samples points from occluded regions or in the space where an object is unlikely to exist, the rendering quality of NeRF can be degraded. These issues can be solved by estimating the geometry of 3D scene. This paper proposes a near-surface sampling framework to improve the rendering quality of NeRF. To this end, the proposed method estimates the surface of a 3D object using depth images of the training set and sampling is performed around there only. To obtain depth information on a novel view, the paper proposes a 3D point cloud generation method and a simple refining method for projected depth from a point cloud. Experimental results show that the proposed near-surface sampling NeRF framework can significantly improve the rendering quality, compared to the original NeRF and a state-of-the-art depth-based NeRF method. In addition, one can significantly accelerate the training time of a NeRF model with the proposed near-surface sampling framework.Comment: 13 figures, 2 table

Low-Power Complementary Inverter Based on Graphene/Carbon-Nanotube and Graphene/MoS₂ Barristors

The recent report of a p-type graphene(Gr)/carbon-nanotube(CNT) barristor facilitates the application of graphene barristors in the fabrication of complementary logic devices. Here, a complementary inverter is presented that combines a p-type Gr/CNT barristor with a n-type Gr/MoS2 barristor, and its characteristics are reported. A sub-nW (~0.2 nW) low-power inverter is demonstrated with a moderate gain of 2.5 at an equivalent oxide thickness (EOT) of ~15 nm. Compared to inverters based on field-effect transistors, the sub-nW power consumption was achieved at a much larger EOT, which was attributed to the excellent switching characteristics of Gr barristors