No Arabic abstract
Recently, a new web development technique for creating interactive web applications, dubbed AJAX, has emerged. In this new model, the single-page web interface is composed of individual components which can be updated/replaced independently. With the rise of AJAX web applications classical multi-page web applications are becoming legacy systems. If until a year ago, the concern revolved around migrating legacy systems to web-based settings, today we have a new challenge of migrating web applications to single-page AJAX applications. Gaining an understanding of the navigational model and user interface structure of the source application is the first step in the migration process. In this paper, we explore how reverse engineering techniques can help analyze classic web applications for this purpose. Our approach, using a schema-based clustering technique, extracts a navigational model of web applications, and identifies candidate user interface components to be migrated to a single-page AJAX interface. Additionally, results of a case study, conducted to evaluate our tool, are presented.
The frequency of a web search keyword generally reflects the degree of public interest in a particular subject matter. Search logs are therefore useful resources for trend analysis. However, access to search logs is typically restricted to search engine providers. In this paper, we investigate whether search frequency can be estimated from a different resource such as Wikipedia page views of open data. We found frequently searched keywords to have remarkably high correlations with Wikipedia page views. This suggests that Wikipedia page views can be an effective tool for determining popular global web search trends.
In this paper, we investigate the diversity aspect of paraphrase generation. Prior deep learning models employ either decoding methods or add random input noise for varying outputs. We propose a simple method Diverse Paraphrase Generation (D-PAGE), which extends neural machine translation (NMT) models to support the generation of diverse paraphrases with implicit rewriting patterns. Our experimental results on two real-world benchmark datasets demonstrate that our model generates at least one order of magnitude more diverse outputs than the baselines in terms of a new evaluation metric Jeffreys Divergence. We have also conducted extensive experiments to understand various properties of our model with a focus on diversity.
The increasing need to store large amounts of information with an ultra-dense, reliable, low power and low cost memory device is driving aggressive efforts to improve upon current perpendicular magnetic recording technology. However, the difficulties in fabricating small grain recording media while maintaining thermal stability and a high signal-to-noise ratio motivate development of alternative methods, such as the patterning of magnetic nano-islands and utilizing energy-assist for future applications. In addition, both from sensor and memory perspective three-dimensional spintronic devices are highly desirable to overcome the restrictions on the functionality in the planar structures. Here we demonstrate a three-dimensional magnetic-memory (magnetic page memory) based on thermally assisted and stray-field induced transfer of domains in a vertical stack of magnetic nanowires with perpendicular anisotropy. Using spin-torque induced domain shifting in such a device with periodic pinning sites provides additional degrees of freedom by allowing lateral information flow to realize truly three-dimensional integration.
In this letter, we use the exactly solvable Sachdev-Ye-Kitaev model to address the issue of entropy dynamics when an interacting quantum system is coupled to a non-Markovian environment. We find that at the initial stage, the entropy always increases linearly matching the Markovian result. When the system thermalizes with the environment at a sufficiently long time, if the environment temperature is low and the coupling between system and environment is weak, then the total thermal entropy is low and the entanglement between system and environment is also weak, which yields a small system entropy in the long-time steady state. This manifestation of non-Markovian effects of the environment forces the entropy to decrease in the later stage, which yields the Page curve for the entropy dynamics. We argue that this physical scenario revealed by the exact solution of the Sachdev-Ye-Kitaev model is universally applicable for general chaotic quantum many-body systems and can be verified experimentally in near future.
We study the black hole information problem within a semiclassically gravitating AdS$_d$ black hole coupled to and in equilibrium with a $d$-dimensional thermal conformal bath. We deform the bath state by a relevant scalar deformation, triggering a holographic RG flow whose trans-IR region deforms from a Schwarzschild geometry to a Kasner universe. The setup manifests two independent scales which control both the extent of coarse-graining and the entanglement dynamics when counting Hawking degrees of freedom in the bath. In tuning either, we find nontrivial changes to the Page time and Page curve. We consequently view the Page curve as a probe of the holographic RG flow, with a higher Page time manifesting as a result of increased coarse-graining of the bath degrees of freedom.