This origami paper pack contains 192 sheets of high-quality paper printed with 10 different traditional patterns. Japanese patterns are elegant, colorful and unique. Origami Paper in a Box takes exciting, abstract patterns and transforms them into origami folding paper. These paper packs make a great resource for all different kinds of folding, crafting and scrapbooking projects. The package includes folding sheets as well as a booklet with instructions so that folders can start right away. This origami paper pack includes: 192 sheets of high-quality origami paper Double-sided color Small size 6x6 inch squares Origami basics introduction Folding techniques Instructions for several easy origami projects

Astronomy and Astrophysics Abstracts, which has appeared in semi-annual volumes since 1969, is de voted to the recording, summarizing and indexing of astronomical publications throughout the world. It is prepared under the auspices of the International Astronomical Union (according to a resolution adopted at the 14th General Assembly in 1970). Astronomy and Astrophysics Abstracts aims to present a comprehensive documentation of literature in all fields of astronomy and astrophysics. Every effort will be made to ensure that the average time interval between the date of receipt of the original literature and publication of the abstracts will not exceed eight months. This time interval is near to that achieved by monthly abstracting journals, com pared to which our system of accumulating abstracts for about six months offers the advantage of greater convenience for the user. Volume 18 contains literature published in 1976 and received before March 1, 1977; some older liter ature which was received late and which is not recorded in earlier volumes is also included.

Unstructured text, as one of the most important data forms, plays a crucial role in data-driven decision making in domains ranging from social networking and information retrieval to scientific research and healthcare informatics. In many emerging applications, people's information need from text data is becoming multidimensional—they demand useful insights along multiple aspects from a text corpus. However, acquiring such multidimensional knowledge from massive text data remains a challenging task. This book presents data mining techniques that turn unstructured text data into multidimensional knowledge. We investigate two core questions. (1) How does one identify task-relevant text data with declarative queries in multiple dimensions? (2) How does one distill knowledge from text data in a multidimensional space? To address the above questions, we develop a text cube framework. First, we develop a cube construction module that organizes unstructured data into a cube structure, by discovering latent multidimensional and multi-granular structure from the unstructured text corpus and allocating documents into the structure. Second, we develop a cube exploitation module that models multiple dimensions in the cube space, thereby distilling from user-selected data multidimensional knowledge. Together, these two modules constitute an integrated pipeline: leveraging the cube structure, users can perform multidimensional, multigranular data selection with declarative queries; and with cube exploitation algorithms, users can extract multidimensional patterns from the selected data for decision making. The proposed framework has two distinctive advantages when turning text data into multidimensional knowledge: flexibility and label-efficiency. First, it enables acquiring multidimensional knowledge flexibly, as the cube structure allows users to easily identify task-relevant data along multiple dimensions at varied granularities and further distill multidimensional knowledge. Second, the algorithms for cube construction and exploitation require little supervision; this makes the framework appealing for many applications where labeled data are expensive to obtain.