Information Behavior in the Mobile Environment: An Overview

As smartphones become ubiquitous, they increasingly influence the way in which students seek and use information. It is important to understand emerging information behavior as a result of wide spread use of smartphones. This paper provides an overview of information behavior in the mobile environment. Gender differences in mobile information seeking are discussed. People interact with mobile information in varied and unpredictable locations or while in transit. The mobility of information engagement is an important issue that human information theory should embrace

Grokking as Compression: A Nonlinear Complexity Perspective

We attribute grokking, the phenomenon where generalization is much delayed after memorization, to compression. To do so, we define linear mapping number (LMN) to measure network complexity, which is a generalized version of linear region number for ReLU networks. LMN can nicely characterize neural network compression before generalization. Although the $L_2$ norm has been a popular choice for characterizing model complexity, we argue in favor of LMN for a number of reasons: (1) LMN can be naturally interpreted as information/computation, while $L_2$ cannot. (2) In the compression phase, LMN has linear relations with test losses, while $L_2$ is correlated with test losses in a complicated nonlinear way. (3) LMN also reveals an intriguing phenomenon of the XOR network switching between two generalization solutions, while $L_2$ does not. Besides explaining grokking, we argue that LMN is a promising candidate as the neural network version of the Kolmogorov complexity since it explicitly considers local or conditioned linear computations aligned with the nature of modern artificial neural networks

Some Sufficient Conditions for Graphs to Be (g, f, n)-Critical Graphs

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Systematic Investigation of Integrating Small Wind Turbines into Power Supply for Hydrocarbon Production

In this paper, the technical and economic feasibility of integrating SWTs (Small Wind Turbines) into remote oil production sites are investigated. Compared to large turbines in onshore and offshore wind farms, SWTs are more suitable for individual power generations. A comprehensive approach based on wind energy assessment, wind power prediction, and economic analysis is then recommended, to evaluate how, where, and when small wind production recovery is achievable in oilfields. Firstly, wind resource in oilfields is critically assessed based on recorded meteorological data. Then, the wind power potential is numerically tested using specified wind turbines with density-corrected power curves. Later, estimations of annual costs and energy-saving are carried out before and after the installation of SWT via the LCOE (Levelized Cost of Electricity) and the EROI (Energy Return on Investment). The proposed methodology was tested against the Daqing oilfield, which is the largest onshore oilfield in China. The results suggested that over 80% of the original annual costs in oil production could be saved through the integrations between wind energy and oil production