Alternatives to Author-Centric Knowledge Organization

This article explores the differences between collaborative and collective authorship, focusing on the most obvious example of the latter, the Internet, and the challenges it poses for knowledge organization. An alternative to current author-centric knowledge systems is presented in the experimental Quanta system

A Review of Reinforcement Learning for Natural Language Processing, and Applications in Healthcare

Reinforcement learning (RL) has emerged as a powerful approach for tackling complex medical decision-making problems such as treatment planning, personalized medicine, and optimizing the scheduling of surgeries and appointments. It has gained significant attention in the field of Natural Language Processing (NLP) due to its ability to learn optimal strategies for tasks such as dialogue systems, machine translation, and question-answering. This paper presents a review of the RL techniques in NLP, highlighting key advancements, challenges, and applications in healthcare. The review begins by visualizing a roadmap of machine learning and its applications in healthcare. And then it explores the integration of RL with NLP tasks. We examined dialogue systems where RL enables the learning of conversational strategies, RL-based machine translation models, question-answering systems, text summarization, and information extraction. Additionally, ethical considerations and biases in RL-NLP systems are addressed

Interactive water streams with sphere scan conversion

Figure 1: Interactive water simulation of 2500 particles at 75 fps with surface extraction by sphere scan conversion on the CPU and rendering of shadow and environment maps on the GPU. Fluid simulations require efficient dynamics, surface extraction and rendering in order to achieve real time interaction. We present a novel technique for the surface extraction of stream-shaped fluid simulations represented as particles. Typical surface extraction methods for particles combine implicit function evaluation with the marching cubes algorithm. In our approach, we dynamically update vertex positions in pre-generated geometry to efficiently construct and render fluid surfaces. Cylinders are wrapped to water streams composed of particles, with simulation and polygonization on the CPU, and shadows and lighting on the GPU. While limited to stream-shaped fluids, our technique is significantly faster than marching cubes, scales well with resolution and number of particles and, unlike point-based rendering, produces true 3D polygonal surfaces. CR Categories: I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling—Curve, surface, solid, and objec

RoSE Research-oriented Social Environment: Bibliographical Knowledge as Social Knowledge

RoSE is a Web-based system that shapes humanities bibliographical resources into a social-computing model presenting the past and present as one living "social network." In the largest terms, it is an experiment in how the humanities can engage with today's expansive knowledge society from both inside and outside the "library," in the process connecting current social-networking practices to a full sense of the historical human record. Stocked with initial information gathered from knowledge bases, RoSE provides profile pages for persons and documents, other data, and visualizations showing the interrelated nature of knowledge. Uniquely, it allows users to add metadata on top of standard bibliographical data to facilitate a social-network-like sense of active relation to the objects of research. RoSE is in early prototype. We seek to improve several key areas so that we can make RoSE available as an "open beta" for humanities scholars and other digital humanities projects to explore